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CHAPTER I

INTRODUCTION

1.1 Profile of The Software Industry

The Indian software industry has been a remarkable success story. The

software industry epitomizes all that market forces and liberalization can bring to a

rather insulated economy. Expanding market opportunities, exponential growth

prospects, access to the latest technology, increased income levels, better corporate

governance etc. have been some of the key benefits that this industry has witnessed

over the years. India continues to be a rather small player in the global IT landscape

with a share of around 20.0 percent in the global customized software market and less

than 1.0 percent in the products and packages market in the year 2000. However,

domestic majors have started to create a mark for themselves in the global software

industry, especially in the services segment. The success of the offshore model (a

model that facilitates the development/ execution of projects based in India and

transmitting the deliverables through high-speed data links etc.) has resulted in

software export revenues growing exponentially over the last decade. The growth has

been possible due to some competitive advantages that the country enjoys including a

huge manpower base that is highly skilled and relatively cheap when compared to

global standards, knowledge of the English language, proactive government policies,

improvement in the existing telecom infrastructure etc. The private training institutes

have been a major reason for this continuous supply of skilled manpower. Continuing

in the rich Indian tradition of imparting knowledge to the world, these institutes strive

to bridge the inadequacies in the conventional educational system by offering students

access to the latest technologies.

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1.1.1. Global Scenario of the Software Industry:

The global business environment is fast changing with technology permeating

the functioning of businesses to a great extent. Information technology has started to

affect all facets of business, be it customer relations or vendor management or

research or marketing etc. Some of the prominent trends that are influencing global

business today and will continue to do so in the future include,

1. Increasing E-enablement of businesses

2. Greater interaction between customers and marketing channels

(intermediaries)

3. Rapid convergence of the IT, telecommunication and entertainment medium

4. Proliferation of numerous mobile devices, resulting in a slow decline of the

PC

5. Greater cost cutting initiatives and de-risking of businesses resulting in a

proliferation in outsourcing activities

6. Application Service Providers (ASPs) revolutionizing the software industry by

changing the pricing dynamics.

7. The rapid generation of data and the rising importance of the same will propel

the growth in the storage segment.

1.1.2. India vs. Global Scenario

Globally, software product companies dominate the software landscape. In

case of the Indian market, it is the services-based companies that dominate the

scenario. A major reason for this is the high-risk profile of the product segment. This

segment typically involves huge research and development investments; enormous

marketing network and the chances of product success is rather limited. Consequently,

domestic software majors have preferred to tread the more cautious services route.

Similar to the Silicon Valley in the US, India has also seen its share of Software

Technology Parks (STPs) that offer high-speed data links, better infrastructure etc.

which has seen mushrooming of software companies in STPs. Despite such

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developments, IT spend, as a proportion of Gross Domestic Product (GDP), continues

to be low when compared to other global markets. However, one area where India

compares favourably to other developed markets is the declining level of piracy.

1.1.3. Software Industry Structure and Segmentation

The Indian software industry has been concentrated in a few major cities such as

Bangalore, Chennai, Hyderabad, Mumbai, and Delhi in the past. However, in recent

times, the proactive initiatives taken by various State Governments have resulted in

software companies setting up their development centres across the country. New

clusters in Pune, Noida, and Gurgaon etc. are growing at a rapid pace. The industry

can be broadly segmented into the products & packages segment, the services

segment and the training segment. The products and packages segment in turn can be

classified based on technology/ application into the application software category, the

system infrastructure software category and the application development software

category. The application software category has select product categories such as

financial accounting products, Enterprise Resource Planning (ERP) software, Anti-

Virus products and Multi-media Software. The software services segment can be

broadly classified based on the type of project contracts entered into by software

majors. These include the Time & Material (T&M) based contracts and the fixed

material price contracts. In case of the former kind of projects, the domestic company

executes either a part or the whole project. These types of projects are invariably of

lower value and don’t allow the Indian company any scope for pricing power.

However, the overseas company gains in terms of time and cost. In case of the latter

kind of projects, the onus of project management is shifted to the contracted.

Generally, overseas clients offer this kind of contract to Indian companies that have

gained a reputation in terms of project management skills. Margins in this kind of

contracts are typically higher when compared to the T&M type of contracts (around

25.0 percent-30.0 percent). The IT training segment can be broadly classified into 3

segments based on the end-user profile. These include the toddlers, the adolescents

and the adults. Toddlers are essentially people who have low or no knowledge of

computers and basically are interested in becoming computer literate and/or enhance

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their computer skills to include design & graphics, know about the Internet and

enhance their office productivity tools skills (MS-Word, MS-Excel etc.). The

adolescents’ category includes people who want to upgrade their computer skills, who

want to switch from an engineering background to the software industry and/or people

wanting to go abroad. The adults’ category primarily involves people in the software

industry wanting to keep themselves abreast of the changing technologies.

1.1.4. Current Scenario of the Information Technology Industry in

India

Global IT spending continued to persist in the year 2012 given the dire

economic situation in the US and Europe. Businesses across the globe started cutting

on discretionary IT budgets and this was particularly true for the Banking, Financial

Services and Insurance companies. Indian IT industry, however, managed to weather

the storm to some extent on the back of superior quality, cost and execution

efficiencies and between year 2008 and year 2012, the industry grew from Rs. 2,534

billion to Rs. 4639 billion, registering a CAGR of 16%.

India's IT industry can be divided into five main components, viz. Software

Products, IT services, Engineering and R&D services, ITES/BPO (IT-enabled

services/Business Process Outsourcing) and Hardware. Export revenues primarily on

project based IT Services continue to drive growth with IT Services accounting for

59% of total revenues followed by BPO and Engineering services at 22% and

Software Products at 19%. Multi-year annuity based outsourcing agreements are

expected to increase going forward. In terms of total export and domestic revenues,

Application Development and Maintenance (ADM)still continues to be the bread and

butter for Indian IT companies, contributing to roughly 60% of their total revenues.

Labour arbitrage has been the competitive edge of the Indian software sector

over the last few years. However, this seems to be threatened now by MNCs’ who are

replicating the Indian outsourcing model and setting up bases in the country. Going

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forward, the advantage of low employee costs could peter out and the sector could get

commoditised.

Increasing competition, pressure on billing rates and increasing commoditization of

lower-end ADM services are among the key reasons forcing the Indian software

industry to make a fast move up the software value chain by providing higher value-

added services like consulting, product development, R&D, mobile, cloud computing

and end-to-end turnkey solutions. With the Indian government emphasizing on better

technology enabled delivery mechanisms for a multitude of government projects like

e-passport, Unique Identification Scheme, etc., the domestic market connected with

software services looks equally promising. Domestic IT-ITES market increased

revenues from Rs. 886 billion in year 2008 to Rs. 1,475 billion in year 2012

registering a CAGR of 14%, with Software and Services contributing to 60% of

domestic revenue and Hardware contributing to the balance 40%.

1.1.5 Prospects of the Indian IT Industry

India is regarded as the premier destination for global IT and ITES

outsourcing, accounting for almost 55% of the global sourcing market in 2010,

according to the Ministry of Communications and Information Technology. The ITES

sector includes IT hardware, software and services. The Indian IT-BPO sector is

estimated to have aggregated revenues of USD 88.1 billion in 2010–2011, with the IT

software and services sector (excluding hardware) accounting for USD 76.2 billion of

revenues. During this period, direct employment is expected to have reached nearly

2.5 million, an addition of 240,000 employees, while indirect job creation is estimated

at 8.3 million. As a proportion of national GDP, the sector revenues have grown from

1.2% in 1997–1998 to an estimated 6.4% in 2010–2011. Its share of total Indian

exports (merchandise plus services) has increased from less than 4% in 1997–1998 to

26% in 2010–2011, as per the report of the working group on the IT sector for the

12th Five-Year Plan (2012–17).

As per NASSCOM, the Indian IT/ITES industry is expected to grow by 11-

14% in year 2013. NASSCOM has also envisaged the Indian IT/ITES industry to

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achieve a revenue target of USD 225 billion by 2020 for which the industry needs to

grow by 13% on a year to year basis in the next eight years.

NASSCOM further added that globally IT services spending are expected to

grow by 4.7% in 2013. Currently India accounts for less than 5% of the global

technology spending and this provides huge opportunities for the growth of the Indian

IT-BPO industry. However, Indian IT companies are expected to face competition

from emerging outsourcing destinations like Philippines, Poland, Hungary, Romania,

etc.

The main growth drivers of the IT and ITES industry are cost efficiencies,

utilization rates, diversification into new verticals, and shifting business and pricing

models. India is a preferred destination for companies that are seeking to offshore IT

and back-office functions. It also retains its low-cost advantage and is a financially

attractive location when viewed in combination with the business environment it

offers and the availability of skilled people. The country is also known across the

world for its successful export-led software industry.

Software and services exports (including ITES-BPO), excluding hardware

exports, were estimated at USD 59 billion in 2010–11, as per NASSCOM, India’s

premier association in the IT sector. Software and services exports constituted more

than half of the electronics and IT-ITES industry’s revenues in 2010–11.

As per the report of the task force set up by Ministry of Communications and

Information Technology (MoC&IT), the demand for electronics hardware in the

country is projected to increase from the USD 45 billion in 2009 to USD 400 billion

by 2020. The task force has been set up to suggest measures to stimulate the growth

of the IT-ITES and the electronics hardware manufacturing industry in India.

According to the executive summary report published by the Department of

Electronics and Information Technology, MoC&IT, the sector has grown to become

the biggest employment generator in the country; direct employment within the IT-

BPO sector was expected to be 2.5 million and indirect employment was estimated to

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be about 8.3 million in 2010–11. As per NASSCOM estimates, the workforce in the

Indian IT sector will touch 30 million by 2020.

Between April 2000 and March 2011, the computer software and hardware

sector received cumulative foreign direct investment (FDI) of USD 10,723 million,

according to the Department of Industrial Policy and Promotion (DIPP), which is part

of the Ministry of Commerce and Industry and which is responsible for formulating

the country’s FDI policy.

Emerging protectionist policies in the Developed World are also expected to

affect the Indian IT companies. Due to lower approval of H1 visa application by US

government for Indian IT professionals and rising visa cost, most Indian IT

companies are increasingly subcontracting onsite jobs to local employee in the US.

Indian IT companies are increasingly looking for global delivery model. They

are setting up development centres in Latin America, South East Asia and Eastern

European countries to take advantage of low cost and also cater to the local market.

ADM services, which used to provide major chunk of revenues to the

domestic IT players, are getting affected due to the falling billing rates. Hence, the

companies are now venturing into new high value services such as IT Consulting,

Product Development, and end-to-end turnkey solutions.

With backing of BPO services, Indian IT companies are able to straddle across

the entire value chain which is expected to make them more competitive as compared

to other outsourced destinations.

The integration of IT-BPO contracts is expected to become more common, as

clients look out for end-to-end service providers. Companies like Infosys, TCS,

Wipro, Mahindra Satyam, HCL Technologies and Mphasis, all of which are also into

BPO are expected to benefit from this trend.

Billing rates will remain stressed in the short term; companies are expected to

preserve their margins through effective cost containment. Lessons learnt during the

crisis can benefit in the long run.

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Rupee's depreciation against the US dollar and other major currencies is

expected to provide relief for Indian IT companies in the near term, offsetting the

pricing and demand pressures to some extent.

1.1.6 IT Policy and Promotion

IT and ITES has played a major role in the overall growth and development of

India. In the electronics and IT sector, 100% FDI is permitted under the automatic

route. The major fiscal incentives provided by the Government of India in this sector

have been for export-oriented units (EOU), software technology parks (STP) and

special economic zones (SEZ). These are detailed below:

Software Technology Parks (STPs) were set up as autonomous societies under

the Department of Electronics and Information Technology in 1991 to promote

software exports from the country. There are about 51 STP centres that have been set

up since the start of the programme. STPs enjoy a number of benefits that include

exemptions from service tax, excise duty and rebate for payment of Central sales tax.

The most important incentive available is 100% exemption from income tax of export

profits; the STPs have been instrumental in boosting India’s IT and ITES exports.

As per MoC&IT, exports by STP units crossed Rs. 2,044.40 billion in

2010–11. The state with the largest export contribution was Karnataka followed by

Maharashtra, Andhra Pradesh and Tamil Nadu. STPs have a pan-India presence,

including in the cities of Bangalore, Bhubaneswar, Chennai, Coimbatore, Hyderabad,

Gurgaon, Pune, Guwahati, Noida, Mumbai, Kochi, Kolkata, Kanpur, Lucknow,

Dehradun, Patna, Rourkela, Ranchi, Gandhinagar, Imphal, Shillong and Nashik,

among others.

The Special Economic Zones (SEZ) scheme was enacted by the Government

of India in 2005 with an objective of providing an internationally competitive and

hassle-free environment for exports. It provides drastic simplification of procedures

and a single-window clearance policy on matters relating to Central and state

governments. Under the scheme, the exemption from income tax is tapered down over

15 years from the date of commencement of manufacture. There is 100% exemption

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of export profits from income tax for the first five years, 50% for the next five years

and 50% for next five years subject to transfer of profits to special reserves.

According to the SEZ Approval Board of India, the maximum number of

SEZs has been approved for the IT-ITES sector. Overall for the IT, ITES, electronic

hardware and semiconductor sectors, the government has given formal approval to

354 SEZs and the number of notified SEZs in these sectors was 236 until 2010.

Information Technology Investment Regions (ITIRs) were notified in 2008 in

order to address the sector’s infrastructure needs. As per plans, these regions will be

endowed with excellent infrastructure that will allow companies to reap the benefits

of co-siting, networking and greater efficiency through use of common infrastructure

and support services.

R&D promotion is also being encouraged by the government; major highlights

include promoting start-ups that are focused on technology and innovation, and a

weighted deduction of 150% of expenditure incurred on in-house R&D under the

Income Tax Act. In addition to the existing scheme for funding R&D projects, the

Department has put in place the two key schemes — Support International Patent

Protection in Electronics & IT (SIP-EIT) and Multiplier Grants Scheme (MGS). The

Cabinet has approved the proposal to provide a special incentive package to promote

large-scale manufacturing in the electronic system design and manufacturing (ESDM)

sector which is called the Modified Special Incentive Package Scheme (M-SIPS). The

main features of M-SIPS are as follows:

The scheme provides subsidy for investments in capital expenditure — 20%

for investments in SEZs and 25% in non-SEZs. It also provides for reimbursement of

CVD/excise for capital equipment for non-SEZ units. For high technology and high

capital investment units, such as fabs, reimbursement of Central taxes and duties is

also provided. The incentives are available for investments made in a project within a

period of 10 years from the date of approval.

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The incentives are available for 29 category of ESDM products including

telecom, IT hardware, consumer electronics, medical electronics, automotive

electronics, solar photovoltaic, LEDs, LCDs, strategic electronics, avionics, industrial

electronics, nano-electronics, semiconductor chips and chip components, other

electronic components and EMS. Units across the value chain starting from raw

materials, including assembly, testing and packaging, and accessories of these

categories of products are included. The scheme also provides incentives for

relocation of units from abroad. The scheme is open for three years from notification.

Over and above these, the government has been taking steps to bring down the

total taxation level on electronics hardware. The general rate of excise duty

(CENVAT) has been reduced to 8% and Central Sales Tax (CST) has been reduced

from 3% to 2%. VAT on IT products is at 4%, as per MoC&IT. Further, under the

Technical Advisory Group for Unique Projects (TAGUP), the government is

developing IT infrastructure in five key areas, including:

New Pension System (NPS)

Goods and Services Tax (GST)

Setting up the National Taskforce on Information Technology and Software

Development with the objective of framing a long-term national IT policy for

the country

Enactment of the Information Technology Act, which provides a legal

framework to facilitate electronic commerce and electronic transactions

Setting up of more than 50 STPs for the promotion of software exports

According to the ministry, the salient features of the existing Foreign Trade

Policy applicable to the electronics hardware industry are:

Import of capital goods at 3% customs duty, subject to an export obligation

equivalent to eight times of duty saved on capital goods imported under the

EPCG scheme, to be fulfilled in eight years reckoned from authorization issue-

date. However, a 0% duty EPCG scheme allows import of capital goods at 0%

customs duty, subject to an export obligation equivalent to six times of duty

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saved on capital goods imported under EPCG scheme, to be fulfilled in six

years reckoned from authorization issue date.

SEZs are being set up to enable hassle-free manufacturing for export purposes.

Sales from domestic tariff areas (DTA) to SEZs are being treated as physical

exports. This entitles domestic suppliers to drawback/DEPB benefits, CST

exemption and service tax exemption. 100% income tax exemption on export

profits is available to SEZ units for five years, 50% for next five years and

50% of ploughed back profits for five years thereafter.

Major Players

Global companies such as Accenture, HP Enterprise Services, IBM and Cap

Gemini have a strong presence in India. These companies already have a large

number of India-based employees — Accenture (40,000+), IBM (130,000+), HP

Enterprise Services (15,000+) and Cap Gemini (26,000+); global players are aiming

to develop onshore service providers who can deliver seamless hybrid onshore-

offshore services at low costs.

Some of the top IT firms in India are TCS, Tech Mahindra Limited, Infosys

Technologies Limited, Patni Computer Systems Limited, Wipro Technologies

Limited, Oracle Financial (I-Flex Solutions Ltd), Mahindra Satyam Computer

Services Limited, Mphasis, HCL Technologies Limited and Larsen & Toubro

Infotech Limited.

Indian IT companies have, in recent years, started expanding their global

footprint through the global delivery model to seamlessly service their clients’ needs

worldwide. Industry analysts expect the top IT firms to grow between 23% and 27%

in 2012 on the basis of an increased number of discretionary projects, improved

pricing and robust business volumes.

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1.1.7. India – One of the Most Preferred Destinations for Software

Development Worldwide

The Indian IT Industry has grown at an exponential rate over the past 10 years

doing Rs.10000 crore of export, fetching for India valuable foreign exchange,

propping up the Indian Stock Market with its share prices reaching dizzying heights

before the scam, and employing over 2 lakh professionals with this number poised to

rise to around 20 lakh in another 3 years. India missed the Agrarian, Industrial and the

early Computer Revolutions but became a global player in the IT revolution because

of two main factors-opening up of the markets and India's cheap and vast manpower

with knowledge of English. Right from 1991, Indian companies grew at a mind-

boggling rate of attracting lucrative projects from companies all over the world,

especially the US. India exports software services to more than 60 countries, with two

thirds to the United States, including half of all Fortune 500.

Economic policy has undergone substantial revision driven by this sector, and

India began to open up. Foreign exchange reserves are high, markets greatly influence

policy, and a string of coalition governments have not deviated from economic

liberalization. Benefits are uneven as the very poor have been little affected. High

unemployment continues and huge bureaucracies still yield to corruption. While

problems remain India is an emerging economy fuelled by techno-savvy manpower

and a world class information technology industry.

Indian software industry quickly moved up the value chain from performing

low cost programming abroad to providing to providing comprehensive software

development services from India for overseas clients. An abundant pool of Indian

technical manpower due to early government investment in technical investment,

created a series of technical and management institutes that responded to a severe

shortage of technical manpower. English – speaking trainable and hungry for higher

wages, Indian firms sent staff to onsite client facilities in the United States. Software

Development commands extreme significance for new IT solutions and IT-enabled

services due to the rising global demand. Appropriate software development gives the

right amount of thrust to the web sites functionality and service quality. This task

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requires thousands of skilled professionals who put in hours of research,

experimentation, testing and trials. Apart from the rising demand, skilled manpower,

technology and infrastructure are essential for Software development and that makes

offshore outsourcing an indispensable requirement for the IT Industry. The developed

countries that desire to make rapid strides in the field of IT, finds it difficult to get the

right amount of manpower needed. On the other hand, developing countries,

especially Asian countries like India and China, have followed an IT policy that

resulted in the generation of enormously skilled manpower and a well-developed IT

infrastructure. This has led to a real boom in outsourcing industry with the destination

being India. India is one of the most preferred destinations for software development

worldwide. With its highly skilled and available human resources, use of latest

technologies and high–end infrastructure, India is capable of handling any type of

software development. The strong point of software development India industry is its

capacity to develop more rapidly the required software and provide innovative and

customized software development solutions. The 50% - 75% of the Fortune-500

companies have outsourced work to India and the Indian IT outsourcing industry is

growing by 25% - 30% on an average annually. Thus, India evidently has a

competitive edge and clear-cut advantages over other contending players

(destinations) in the Software Development Outsourcing business. Indian outsourcing

destinations like Bangalore, Chennai, Pune, Mumbai, Delhi and Kolkata are

developing with lots of investment in the infrastructure in terms of power, road and

communications. India also has the expertise of quality certified software firms and

outsourcing suppliers that not many countries can boast of. So as of now, India seems

to hold its position as the leader in outsourcing service market.

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1.1.8 Factors that make India a Potential Software Outsourcing

Destination:

Vast Manpower: With a population of 1 billion and ever expanding army of

highly skilled science and English graduates, India has unmatched potential in the

human resources department even exceeding China in this area.

Cost-effective services: Outsourcing to India helps the companies in saving

more than half of their operating costs without compromising on quality as India has a

large pool of educated, trained and technically skilled manpower unlike the west,

where technical talent is rare.

High-quality services: India uses the latest in software, technology and

infrastructure to provide global customers with high-quality outsourcing solutions.

India has also proved it has technical superiority over other countries that provide

outsourcing solutions. India has the largest English-speaking audience after the U.S.

which is computer literate as well.

State of the Art Communication Infrastructure: Indian companies offer

plenty of high-speed bandwidth via satellite connectivity, submarine cables and

optical fiber networks. Add to this the fact of countrywide mobile telecom coverage

and 24/7 flawless connectivity with vendors and clients 365 days of a year.

Time Zone Advantages: The time zone advantages between India and

countries in the U.S and U.K has proved to be another important factor why

companies outsource to India. Organizations who wish to provide their customer with

24x7x365 days customer support or helpdesk services outsource to India.

Rapid Economic Growth in India: Indian economy has been witnessing a

robust growth rate for many years now and the Indian growth story is largely due to

the services sector, which accounts for more than 50% of the GDP. This has

catapulted India in the position of world's second largest software exporter, a leading

IT superpower indeed.

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Stable Polity with Clear IT Policies: India has been witnessing new political

maturity with large but stable coalitions that have continued the market-friendly

reforms introduced in 1991. The IT and ITES sectors have been the biggest

beneficiary of these policies. The government is also trying to cut down the red

tapeism by introducing single window clearances for setting up IT projects and firms.

The Indian Parliament has enacted the Information Technology Bill, 2000 recognizing

electronic contracts, barring electronic crime, and e-filing of documents. India also

has a nodal association of the IT companies called NASSCOM to provide a blue print

of the needs and progress path of IT vendors and companies in India.

Attractive Tax and non-tax Incentives for IT Companies: The Central

Government has provided many tax and other incentives to boost investment in the IT

outsourcing industry in India. Some of the benefits accruing to IT firms are:

10 year tax holiday for companies involved in construction and/or

maintenance/operation of an infrastructure complex.

10 year tax holiday to firm that generate and/or distribute power.

5 year tax holiday to telecom firms providing internet and broadband services.

10 year tax holiday to IT firms setting up venture in notified IT parks and

Special Economic Zones (SEZ).

5 year tax holiday for IT and other firms setting up a project in backward

districts and states.

IT outsourcing and other firms also get tax incentives on exports as tax is

deducted on profit for exporters setting units on SEZ's, Electronic Processing

Zones (EPZ), Software Technology Parks (STP).

Attractive tax incentives are available on expenditure for research and

development including deduction of 150% on scientific research and 10-year

tax holiday for scientific and industrial research R&D companies.

Today, the MNCs have a greater focus on the Indian IT outsourcing and

software development market. While a large number of companies are

outsourcing their software development to Indian companies, others are

establishing a presence in India and participating actively in the software

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export arena. Thus, India is an ideal offshore destination for software

development, programming and IT outsourcing due to a number of factors

some of which are categorized above.

1.1.9 The Indian Software Industry-Current Trends, Challenges and

the Future

The Indian Software Industry is the uncrowned king in the outsourcing of

software services . They have shifted emphasis to off-shore projects since the on-site

software development has virtually come to a standstill. They have started to scout for

newer markets, improve on the per capita efficiency, concentrate on future

technologies, revamp their organizational and marketing structure.

The share of on site work has come down as most foreign companies prefer to

sustain as much of their own employees rather than outsiders. Companies in India

have now shifted gears doing off-shore development which is much cheaper. They

have started looking at the European and Japanese markets which have not yet been

affected by the slowdown. Other markets which they are tentatively eyeing are the

Australian, South American and Middle East markets. Most companies have decided

to tide over the problem of reduced profits by resorting to layoffs and cutting down

heavily on fresh recruitment. These are measures to bring down the numbers on the

bench which have been increasing for some time now. The focus on web centric

software development which used to be their prime revenue earner is a thing of the

past and these companies are concentrating now on the banking and the e-governance

sectors. Even the high flying companies are doing the low grade maintenance work

for their clients to create good relationships in the hope of getting a big project from

them sometime in the future.

Another challenge that Indian companies are facing is that most corporations

prefer to keep the most lucrative projects for their employees and leaving the crumbs

for the Indians to brush up.

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The Indian IT Industry( 109Billion $) is going through a massive shift in a move

taken by software companies where India's IT outsourcers are promoting "mini

CEOs" capable of running businesses on their own, while trimming down on the

hordes of entry-level computer coders they normally hire as they try to squeeze more

profits out of their staff.

The shift by Infosys Ltd and others is symptomatic of a maturing industry that

wants more revenue from its own intellectual property instead of providing only

labour-intensive, lower-margin information technology and back-office services.

For young graduates who see the $108 billion IT industry as a sure pathway to

modern India's growing middle class, the transformation is unsettling. The focus was

more on career earlier but now the value of a professional is judged by how quickly

he is able to adapt himself to the changing environment and do skilful learning.

1.2 Women in the Indian Software Industry

One of the significant changes witnessed in the labour markets in India in the last

decade has been the entry of women professionals. The percentages of females in

regular employment in urban India, increased from 25.8% in 1983 to 33.3% in 2000

and the labour force participation rates is projected to reach 361 per 1000 females in

the year 2026.(McNay, Unni, & Cassen, 2004). In the organised sector, women

workers constituted 18.4% as on March 31, 2003, of which about 49.68 lakh (4.96

million) women were employed in the public and private sectors (The Financial

Express, 2006). In fact, the largest numbers of women employees are in the IT/ITES

sector (Wakhlu, 2008). The phenomenon of Indian Women IT professionals’ is the

term used to describe the enormous rise of women in the IT/BPO industry (The Indian

programmer, 2000).Women accounted for 26.4% of the total India-based workforce

in the IT industry in 2007, up from 24% in 2005 and women comprise 25% of the

employee strength of the major Indian IT companies (Ali, 2006). Women’s

participation in the IT workforce is seen as a critical enabling factor for the continued

growth of the industry (The Economic Times, 2009).

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The characteristics of the software services industry in India and the nature of the

work pose some unique challenges for professionals in the industry. The challenges

are aggravated in the case of women professionals.

The software industry in India is characterised by a project-oriented organisation

and as the industry has matured, more complex and strategic projects have been

outsourced to India (Ethiraj, Kale, Krishnan, & Singh, 2005).

Software professionals are faced with an environment of uncertainty and instability

with consequent pressures to work longer hours (Scholarios & Marks, 2004). This

pressure is a result of two factors. First, the time differences with the West, US and

Europe, necessitate employees to work at night in India. Furthermore, the

concept of a 24-hour knowledge factory - the evolution of 24-7-365 help desk

support-requires software engineers to conduct team meetings and virtual work

sessions, where team members need to adopt temporal flexibility, a more fluid

approach to time-whether holding conference calls outside the traditional 8 to 6

workday or fast-tracking a software project in shifts (Teagarden, Meyer & Jones,

2008). Second is the project-based work with unpredictable workloads and the

requirement to deliver projects consistently within the stipulated time and without

critical bugs (Mathew, 2007), often involving extensive travel.

The project orientation of the industry with rapid technology changes that

make skills quickly obsolete requires software professionals to frequently re-skill.

Consequently, software professionals need to put in extra training and educational

hours to keep up with these changes (Armstrong, Riemenschneider, Allen & Reid,

2007).

Women who aspire to play a bigger role in technology need to maintain a

consistently high learning curve. With the constant innovation happening in this

arena, it is not enough to be a good worker in the IT industry; one must keep updating

technological skills. No other industry sees such significant changes in technology

from time to time (Ali, 2006).

19

The time required for professional development will have to come out of the

personal time of the employees. Long working hours, unpredictable workloads and

the constant pressure of updating skills all lead to work-life conflict of software

professionals. However, it must be recognised that in Indian society, where a

woman’s role in relation to herself, her family and society is being redefined, the new

and expanded role of women with a strong occupational identity is putting a lot of

pressure on women’s time and energy.

Indeed, balancing work and family and evading conflict between these two

roles was one of the commonly cited challenges of IT work in a study on women in IT

(Adya, 2008).

Thus well educated, highly skilled women software professionals in India

have entered a rapidly growing and very demanding sector in which they want to

pursue careers. The nature of the industry and the fact that women software

professionals are in the crucial phase in their lives, 23-38 years, where women are

drawn into marriage and motherhood, puts increasing pressure on maintaining a

balance instead of conflict between work and family. (Perrons, 2003; Rajalakshmi,

2003).

It is evident that the nature of the sector and the changing aspirations and roles

of women in Indian society create challenges for their work-family conflict, which

this study puts under further scrutiny. The present study was designed to explore,

document and analyse the factors that influence the work-family conflict of women

software professionals in India and also to understand the support they receive both in

their personal and professional lives.

20

1.3 Nature of the Software Industry and its Impact on the Work -

Life Conflict Study.

The software industry has contributed much to the confidence of women at

work place. Advances have been made with regards to gender equality and financial

independence of women in the software industry, considering the condition of women

workforce in other industries. Women constitute 37% of the workforce in Indian

software industry. Greater use of technology, exposure to modernity, lesser or

negligible reliance on physical strength to carry out the work are the distinguishing

factors which has made this possible, along with higher salaries compared to other

traditional industries.

There are contradictory role expectations from working women in the software

industry while she is at work and at home. The working women are expected to be

committed, dynamic, competitive, straight forward, non-sentimental and acting a

“business like” manner on the professional front and at home women are expected to

be sweet, soft, sensitive, adaptable, gentle, unassertive and domesticated (Misra1998).

An ideal working women tries to fulfil the duties of a faithful wife, a sacrificing

mother, obedient and respectful daughter in-law and an efficient and highly placed

career woman. These contradictory expectations cause the most confusion, tension

and create many other problems for her. A woman employee finds it difficult to do

justice to the two roles at the same time. An attempt to play one of the roles with

perfection leads to an inadvertent sacrifice of the other.

Women assuming multiple roles results in work- family conflict because time

and energy are shared, clubbed and even extended across the two spheres of activity.

When a women enters into gainful employment outside home she not only finds a

change in her role and status within the family and outside it, but she also finds

herself under increasing pressure to reconcile the dual burden of the two roles at her

home and her workplace because each is a full time job. Coping up with the situation

requires not only additional physical strength, personal ability and intelligence on the

part of a working woman but also requires the members of her ‘role set’ to

21

simultaneously make necessary modifications in their expectations. When conflict

between the two life domains occurs the consequences are reflected in both

organization and domestic life. For the employers such role conflict means

disillusionment, dissatisfaction and strained relations with women employees, their

lower standard of work performance and disregard of organizational goals. Since

society is not separate from organizations, the negative impact of role conflict will

have its effects on the society in general in the form of lower standards of

performance, lower quality of goods and services and a growing feeling of

interpersonal conflict being the obvious results. There is therefore, a growing

recognition by policymakers of the importance of supporting women in juggling work

and family life (Evandrou et al. 2002).

In order to help dual-career women to manage the demands of both work and

family, it is necessary to explore the origins and correlates of work stressors and

work-family conflict, and to try to find a support system at the level of the family,

workplace, community and government for resolving it.

Despite glamour and hefty salaries associated with the field, women in the

software industry suffer from physical discomfort and mental tension, even in their

plush office environments, a study revealed. High salaries and social status associated

with the IT sector has attracted women to take up these jobs, but many suffer on

account of various factors like late working hours, the time associated with long hours

of travel, pressure to submit to deadlines on projects, constant learning and up

gradation needed to keep abreast with the emerging trends in technology and

development, the study conducted by Kerala State Women's Commission said.

Covering 150 women in the IT sector and 50 others in allied areas, the study found

that long working hours at the desk and job related pressure creates a lot of physical

discomfort and mental tension to software employees. The study suggested that all IT

institutions conduct stress management counselling services for women employees,

and a law be enforced by the government to reschedule working hours. The necessity

to keep to deadlines as contracts are taken for foreign clients is very important to keep

contractual obligations. The study also found that this kind of pressure exists for both

22

men and women and it suggested that women should cope with practical problems of

balancing work at home and office in order to climb up the career.

1.4 Work –life conflict study on women employees:

Eby et al. (2004) examined that Work-family conflict predictors might be

measured by “having children at home, experiencing disagreements or tension with

spouse, and high involvement or time demands from family members”. Studies of

domestic work and care-giving consistently show that women spend more time on

such tasks than men (Moen, 1992; Bullock, 1994; Fagenson, 1993). The years during

which women are involved in child rearing usually fall between the ages of 25-35.

According to Moen (1992), this is also the decade most critical for their career

advancement because it is at this age that the experience upon which the career is

based is gained. All too often, women are punished (i.e. they lose opportunities) for

their choice of having children or a family no matter how well they perform in their

jobs (Moen, 1992). These decisions concerning household work affect the decisions

concerning work away from home and vice versa (Hatt, 1997) The additional work

done by women outside of their employment – and the resulting stress- increases the

pressures they face and therefore lead to some health problems that may be either

physiological or psychological. Studies found that women work on average one to

three hours per day more than men in their societies (Smyke, 1991; Moen, 1992).

Regardless of the number of working hours, and the place where work is carried out

through either home, labour market or both, women are left with less time for sleep or

rest. As a result, many health problems may occur such as: malnutrition, chronic

fatigue, stress and premature aging (Smyke, 1991; Marshall, 1995). Despite the fact

that women’s roles have been recently changing, men’s roles in the home and rules

for success in the office have not changed much (Swiss & Walker, 1993; Headlee &

Elfin, 1996; Belle, 1989).Women’s organizational promotions are less than those of

men, and men are more expected to be promoted to higher managerial levels (Lyness

and Schrader, 2006). According to Cavanagh and Fisher (2005) because women carry

most of the burden of care giving which requires time and attention, women are not

viewed as being dedicated to their careers, and as such do not receive the equivalent

23

promotions.Lim (1996), and Headlee and Elfin (1996) all agree that women are still

being forced to make a preference between family issues and career responsibilities.

Thus, they lack effective support for parenting issues in the workplace

subjecting them to discrimination in their choice of work. The discrimination that

women face in organizations may make women’s problems worse and make them feel

that they cannot cope with their careers (Hatt, 1997; Tanton, 1994).The higher the

position of a woman in an organization, the more she is subjected to higher levels of

burnout. These women appear in a “no win” situation due to the heavier family

demands than men, and heavier work demands than other women. This “no win”

situation is the origin of the high burnout levels (Duxbury and Higgins, 2003). Family

concern can and does affect business results, a fact that escapes many companies

(Moen, 1992; Hammonds, 1996). Business results may be affected either positively or

negatively depending on the company’s attitude towards family issues (Hammonds,

1996; Lawlor, 1994; Tanton, 1994; Moen, 1992). An example of negatively affected

results is the cost of turnover. Replacing a valued female employee can cost up to

150% of her annual salary (Lawlor, 1994). In general, family concern affects worker

performance, recruitment, retention, mobility, absenteeism, tardiness, and

unproductive time at work, energy expended on the job, motivation, and geographic

mobility (Ferber & O’Farrel, 1991).

With the increase in dual-income families and employed single parents,

conflict between work and family has reached a crisis (Beauregard, 2006). Rhona and

Robert N. Rapoport (1969, 1976) coined the terms “Dual Career Family” and “Dual

Career Couple” (DCC) at that time these have become increasingly significant

lifestyles (Greenhaus, 1989; Sekaran, 1983, 1985, 1986).

Work and family are the key domains of life to many people (Whitely and

England, 1977), and, not surprisingly, work-family conflict (WFC) research has

become a major area in organizational research (Parasuraman and Greenhaus, 2002).

Work-family stress has been identified as a major problem for working mothers

(Aryee et al, 1999, Ng et al, 2002).

24

Most family/work research emphasizes the idea that conflict has an impact

on individual’s emotional and physical condition, thus causing disadvantages for

companies due to absenteeism and diminishing productivity (Cooper and Williams,

1994). Not only conflicts between the two fields might affect productivity, spill over

theory (Caligiuri and Cascio, 1998) rather suggests that problems in one domain (e.g.

home-life) will affect the other (e.g. performance in the job). Thus the researcher felt

that this research was very relevant in the software industry where more women are

employed and the industry serves as a prospective industry for employment

generation and career.

1.5. Work and family linkage theories:

Many researchers pay attention to work-family linkage from 1960s.Work and family

become one of the important issues in domain of sociology, organization behaviour,

HR management.

There are four patterns in work-family linkage. Each one is related with its theory.

1.5.1 Separate spheres pattern -Roles theory

The separate spheres pattern sees family and work as distinctive systems, with

the family as a domestic haven for women and work as a public arena for men

(Zedeck 1992). Further, family and work should remain separate in order to function

properly and the division of labour by sex should be maintained in order to avoid

conflict. So work and family are separated, absolute from each other and not effected

mutually (Lambert, 1990).

In the separate spheres pattern, role segmentation comes from different

expectations on men and women. Women are expected to be good wife and mother.

Men are expected to work for family. Such social expectation is not changed much as

society development.

25

In China, traditional culture ranks women to family which gives a much

bigger influence on women. Not coming singly but in pairs, a research named “what

is the important thing in life” in America shows that 75% of married men give an

answer of “my work” and women “my family” contrarily. Based on the role theory,

the Separate spheres pattern treats work and family as independent domains.

Involvement in the two spheres does not therefore affect each other. But at present,

women are not only housewife but also businesswoman, politician etc. So this pattern

is rarely used by social scientists. Additionally, this pattern assumes actors can

separate the two spheres in terms of time, physical location, emotions, attitudes, and

behaviour .But this segmentation is not absolutely. Work and family are in another

mutual pattern.

1.5.2 Mutual Pattern-Spill Over Theory and Compensation Theory

From the 1970s, some researchers came to study the mutual effects between

work and family (Kate- Kahn, 1978). Spill over theory recognizes that either system

may have spill over effects on the other (Staines 1980). Excess work may have an

effect on family (Voydanoff, 1985) and experiences gained from family domain may

have effects on work (Belsky et al., 1985).

Simultaneous membership in the two systems often entails strain and overload

for individuals, families, and work units. In general, the spill over effects pattern

shifts attention from the effects of social institutions on each other to the effects of

family members on each other, ignoring the social and political consequences of the

context in which family and work are located. Spill over can be positive or negative.

Positive spill over refers to fact that satisfaction and achievement in one

domain may bring along satisfaction and achievement in another domain.

Negative spill over refers to the fact that difficulties and depression in one

domain may bring along the same emotion in another. Domain.

26

Compensation theory is the one most often contrasted with spill over (Zedeck,

1992). It hypothesizes that there is an inverse relationship between work and family

such that work and non-work experiences tend to be antithetical. It further proposes

that individuals make differential investments of themselves in the two settings

(Champoux, 1978), so that what is provided by one makes up for what is missing in

the other (Evans and Bartolome, 1984). Deprivations experienced in work are made

up or compensated for in non-work activities.

The theory of compensation views workers as actively seeking greater

satisfaction from their work or family life as a result of being dissatisfied with each

other (Lambert, 1990). It provides a plausible explanation of why some workers

become more involved in their work when experience family problems (Lambert,

1990).Therefore, when people experience compensation from work, it represents that

they feel more job satisfaction than family satisfaction. When compensation happens,

one would expect high involvement on one sphere to be accompanied by low

involvement in the other. In other words, when people try to compensate for a lack of

satisfaction at home, they become more involved in their work and their work

involvement will increase.

Generally speaking, unlike the separate sphere pattern, which denies the

connection between family and work, mutual pattern recognizes work and family are

mutual effect. But both spill over and compensation theories view the work-family

linkage statically. The developmental approaches proposed the longitudinal analysis

of work-family linkages in the life span of a person or a couple. The developmental

approach therefore adopted a psychological/developmental framework to explore the

dynamics of the relationship between individual, family and career developments in

the life span of person/couple. Furthermore mutual pattern regard individual’s

behaviour as passive ones not initiative.

27

1.5.3 Integration Pattern-Boundary Theory

Work and family linkage presents integration trend in the times of

information. Boundary between work and family are more illegible because of

Information Technology. Boundary theory was first brought forward by Sue

Campbell Clark (2000) who believes there is a boundary between work and family.

Mental boundary, time boundary, physiological boundary are the three forms. Many

individuals, then, are border-crossers who make daily transitions between the domains

of work and home. Boundary theory is widely used in work and family issues such as

work at home, flexible time, and etc. (Desrochers and Sargent, 2002) .Individuals try

to find a suitable boundary between work and family. Boundary is characterized by

permeability, flexibility and blending. Permeability refers to the bound one role

penetrates to another. Flexibility refers to boundary tactility between roles. For

example, telecommuting female also play a mother role. When permeability and

flexibility both exit in two or more roles, blending happens. Based on boundary

theory, though it is difficult to change some sides of work and family, individuals can

change the boundary between two domains to some extent (Desrochers & Sargent,

2002). It is indicated that individuals are reactive in work and family domain.

1.6. Definitions of Key Work–Family Constructs

The work-family constructs are used in terms of three major domains: work–

family conflict, work–family facilitation, and work-life balance.

1.6.1 Work–Family Conflict

Work–family conflict (WFC) has been broadly defined as a form of inter role

conflict as researched by Greenhaus and Beutall (1985) in which the role pressures

from the work and family domains are mutually incompatible in some respect. That

is, participation in the work (family) role is made more difficult by virtue of

participation in the family (work) role. Researchers also used terms such as work–

home interference (Geurts et al., 2003), and work–non-work interference (Dikkers et

al., 2005) interchangeably to denote work–family conflict. Also consistent with

28

research from the United States, researchers conducting studies in other countries

have recognized the bidirectional relationship between work and family life (Aycan

and Eskin, 2005; Hill et al., 2004; Kinnunen et al., 2003). Conflict may originate in

either domain, such that work interference with family (WIF) occurs when work

related activities spill over or interfere with family responsibilities; family

interference with work (FIW) arises when family-role responsibilities spill over or

impede work activities.

1.6.2. Work- Family Facilitation

Work–family facilitation is ‘a form of synergy in which resources associated

with one role enhance or make easier participation in the other role’ (Voydanoff,

2004); or ‘the extent to which participation in one role is made easier by virtue of the

experiences, skills, and opportunities gained or developed in another role’ (Frone,

2003). Similar to work–family conflict, work–family facilitation could originate from

both work and family domains. There are three types of work –family facilitation (1)

Time based work–family facilitation occurs when the time devoted to the work-family

role stimulates or makes it easier to effectively manage and use the time in the family-

work role.(2) Energy based work–family facilitation occurs when energy obtained in

the work role makes it easier to fulfil the requirements of the family role.(3)

Behavioural-based work–family facilitation occurs when behaviour required or

learned in the work role makes it easier to fulfil the requirements of the family role (

Van Steenbergen et al. 2007).

1.6.3. Work–Life Balance

Work–life balance has been defined as ‘an individual’s ability to meet both

their work and family commitments, as well as other non-work responsibilities and

activities’ (Parkes and Langford, 2008). Similarly, Hill et al. (2001) defined work–

family balance as ‘the degree to which an individual is able to simultaneously balance

the temporal, emotional and behavioural demands of both paid work and family

responsibilities’. It has also been defined as ‘achieving satisfying experiences in all

life domains’ (Kirchmeyer, 2000). Some researchers also regarded work–life balance

29

as ‘the absence of unacceptable levels of conflict between work and non-work

demands’ (Greenblatt, 2002). In some cases, researchers have used a related term

such as work–family balance (Lyness and Kropf, 2005; Wierda-Boer et al. 2008) to

denote work–life balance.

Work Life Balance Concept was first introduced in America in the year 1986.

The reasons for the introduction of the concept was the American employees were

working towards the achievements of corporate goals and could not able to

concentrate their time on their life activities such as family, self-care, social get

together, etc. In general, Organisational work for getting salary and relaxing at home

alone do not fulfil one’s life. In general every man has two types of activities. They

are work activity and life activity. Work activity consists of performing work itself

and career growth. On the other hand, life activity consists of self-care, family care,

participating in Religious/Spiritual and community activities. Self-care includes doing

exercise, Yoga and Meditations, engaging in Hobbies. Family care comprises of

spouse care children care, elder/dependent care, maintaining good relationship with

friends and relatives and also among the members of the family. However, a few

women engage themselves in self-employment to manage their work and family

needs. This happens for married woman following their child/children birth. In the

present scenario, the organisations have started caring about the wellbeing of the

employees which insists in the implementation of work life balance policies.

30

1.6.4 Constitutive definitions of Key Work-Family Constructs

Table 1. 1

Constitutive Definitions of Key Work–Family Constructs

CONSTRUCT DEFINITION Constructs with

similar meaning

Work–family

conflict

(global)

WFC is defined as ‘a form of interrole conflict

in which the role pressures from the work and

family domains are mutually incompatible in

some respect. That is, participation in the work

(family) role is made more difficult by virtue

of participation in the family (work) role’

(Greenhaus & Beutell, 1985: 77).

Work–home

interference

Work–non-work

interference

Negative work–

home Interaction

Work–family

facilitation

(global)

WFF is defined as ‘a form of synergy in which

resources associated with one role enhance or

make easier participation in another role’

(Voydanoff, 2004: 399); ‘the extent to which

participation in one role is made easier by

virtue of the experiences, skills, and

opportunities gained or developed in another

role’ (Frone, 2003: 145), and ‘the extent to

which participation in one role is made better

or easier by virtue of participation in another

role’ (Wayne et al., 2004: 109).

Work–life

balance

Work–life balance is defined as an

individual’s ability to meet both their work

and family commitments, as well as other

non-work responsibilities and activities.

(Hill et al. 2001: 49); Kirchmeyer (2000)

defined work–life balance as ‘achieving

Work–family

balance

31

satisfying experiences in all life domains’

and work–life balance is sometimes

characterized by ‘the absence of

unacceptable levels of conflict between

work and non-work demands’ (Greenblatt,

2002: 179).

Work–family

balance

Work–family balance has been defined as

‘the degree to which an individual is able to

simultaneously balance the temporal,

emotional and behavioural demands of both

paid work and family responsibilities’ (Hill

et al., 2001: 49)

Work

interference

with family

(WIF)

WIF conflict occurs when work-related

activities spill over or interfere with home

responsibilities

Work–family

conflict

( WFC )

Work–home

interference:

negative

Family

interference

with work

(FIW)

FIW conflict arises when family-role

responsibilities spill over or impede work

activities.

Family–work

conflict

( FWC )

Home–work

interference:

negative

Work

facilitation

with family

(WFF)

WFF represents the extent to which the

experiences, skills, and opportunities gained

or developed at work enhance home life

(Frone, 2003).

Work–home

interference:

positive

Family

facilitation

with work

FFW represents the extent to which the

positive mood, behaviours, sense of

accomplishment, support, or resources

Home–work

interference:

positive

32

(FFW) received at home positively affect one’s work

role.

Time-based

WIF

Time-based WIF reflects work demands that

deplete the time employees need for their

family activities.

Work– non-work

interference:

time-based

Strain-based

WIF

Strain-based WIF indicates that work

stressors create levels of strain that hamper

employees’ mood and energy even when

they are home.

Work–non-work

interference:

strain-based

Behaviour-

based WIF

Behaviour-based WIF indicates that

behaviours expected at work cause problems

if they are enacted with one’s family.

Psychological-

based

WIF

Psychological-based WIF is defined as ‘the

psychological preoccupation with work while

one is at home that interferes with one’s

ability to become engaged in one’s family

role’ (Carlson & Frone, 2003: 518).

Time-based

FIW

Time-based FIW reflects family demands

that deplete the time employees need for

their work activities.

Strain-based

FIW

Strain-based FIW indicates that family

stressors create levels of strain that hamper

employees’ mood and energy even when

they are at work.

Behaviour-

based FIW

Behaviour-based FIW indicates that

behaviours expected at home cause problems

if they are enacted within one’s work.

33

Psychological-

based

FIW

Psychological-based FIW is defined as ‘the

psychological preoccupation with family

while one is at work that interferes with

one’s ability to become engaged in one’s

work role’ (Carlson & Frone, 2003: 518).

Time-based

WFF

Time-based WFF occurs when the time

devoted to one’s work role stimulates or

makes it easier to effectively manage and use

the time in one’s family role (van

Steenbergen et al., 2007).

Energy-based

WFF

Energy-based WFF occurs when energy

obtained in one’s work role makes it easier to

fulfil the requirements of one’s family role

(van Steenbergen et al., 2007).

Behaviour-

based WFF

Behaviour-based WFF occurs when

behaviour required or learned in one’s work

role makes it easier to fulfil the requirements

of one’s family role (van Steenbergen et al.,

2007).

Psychological-

based

WFF

Psychological-based WFF occurs when an

individual is able to put matters associated

with family role into perspective by virtue of

work role, which makes it easier to fulfil the

requirements of the family role (van

Steenbergen et al., 2007).

Time-based

FFW

Time-based FFW occurs when the time

devoted to family role stimulates or makes it

easier to effectively manage and use the time

in work role (van Steenbergen et al., 2007).

Energy-based

FFW

Energy-based FFW occurs when energy

obtained in family role makes it easier to

34

fulfil the requirements of work role (van

Steenbergen et al., 2007).

Behaviour-

based FFW

Behavioural-based FFW occurs when

behaviour required or learned in family role

makes it easier to fulfil the requirements of

work role (van Steenbergen et al., 2007).

Psychological-

based

FFW

Psychological-based FFW occurs when an

individual is able to put matters associated

with work role into perspective by virtue of

family role, which makes it easier to fulfil

the requirements of the work role (van

Steenbergen et al., 2007).

Job–

homemaker

conflict

Conflict from incompatibility of work role

with homemaker role (Aryee, 1992).

Spill over: work to

home management

Job–parent

conflict

Conflict from incompatibility of work role

with parental role (Aryee, 1993).

Spill over: work to

parental

Job–spouse

conflict

Conflict from incompatibility of work role

with spousal role (Aryee, 1993).

Spill over: work to

marriage

1.7 Major theoretical perspectives in the international work–

family literature

Several researchers (Aryee et al. 2005) used scarcity theory to explain inputs

to the work–family interface. From this perspective, people with a greater number of

roles are more likely to deplete their resources, resulting in role overload or role

conflict. Active participation in non-work domains such as family, community and

recreation has been viewed historically as reducing the time available for work, as

well as individuals’ feelings of commitment to their jobs (Goode, 1960).

In contrast, those who adopted an expansion perspective (Nikandrou et al.(

2008) instead of depleting an individual’s psychological and physiological resources,

35

involvement in multiple roles provides a number of benefits that may outweigh the

costs, leading to net gratification rather than strain because personal resources are

abundant and expandable .

Several theories attempt to explain the work–family interface from a stress

perspective. According to the Conservation of Resources Theory (COR: Hobfoll,

1989) individuals strive to obtain, retain, protect, and foster those things that they

value, or that serve as a means of obtaining things they value, namely ‘resources’.

Hobfoll (2002) identified 74 work- and non-work-related resources that he divided

into four groups: objects, conditions, personal characteristics, and energy resources.

These resources are assumed to reduce stress, and several researchers have used this

perspective to explain the work–family interface.

Other researchers (Geurts et al. (2003)) have drawn upon role theory (Kahn et

al. 1964), which posits that multiple roles lead to role stress, and this stress results in

strain. Specifically, expectations associated with work and family roles can lead to

physical and psychological strain in two ways. First, role expectations can lead to role

overload within the work or family domain. Second, expectations surrounding either

of these roles can evoke pressures that dominate the time of an individual and

interfere with expectations associated with the performance of the other role.

A few researchers (Choi (2008)) have used the Job Demand-Control and

Support (JDCS) model (Karasek, 1979), which posits that job strain results from the

interaction of the two main dimensions of the work environment: perceived demands

and control. The demands may be psychological or physical in nature. Higher strain

arises when job demands are high and job control is low. The extended version of the

model includes social support and predicts that job strain is a result of the interaction

of three dimensions: demands, control, and social support. Another widely used

framework, the Job Demand-Resource (JD-R) model (Demerouti et al., 2001) is

developed on the basis of this JDCS model.

1.8 Definition of Work-Life Conflict

36

Work and family are the two most important domains in a person’s life and

their interface has been the object of study for researchers world-wide. There is a felt

need to avoid conflict and integrate family needs and career requirements (Sturges &

Guest, 2004) and research in the field of work-family interface has increased

dramatically in the past two decades (Frone, Yardley, & Markel, 1997). The changing

social structures arising out of increase in the number of nuclear families and dual

career couples, single parent families and increasing number of parents with

dependent care responsibilities for children, and ageing parents have all contributed to

increasing research in the area of work and family interface. There is a wide research

done on this from developing economies especially from countries like Canada where

more reports had been generated on Work-Life Conflict and ample research literature

on work and family is made available. Increased globalisation and the rapid growth of

the service sector coupled with the recognition that balancing work and family and

managing conflict is a challenge for employed parents in almost all modern societies,

suggests that a chapter of this research should be conducted in different cultural

contexts (Ayree, Srinivas, & Tan, 2005).

Work-family conflict is defined as a form of friction in which role pressures

from work and family domains are mutually incompatible in some respects

(Greenhaus & Beutall, 1985,) definition of work family conflict was formally brought

forward by Greenhaus in 1980s.

Work-family conflict, as defined by Kahn(1964), is a form of interrole conflict

in which the role pressure from the work and family domains are mutually

incompatible in some respect. That is, participation in the work (family) role is made

difficult by virtue of participation in the family (work) role (Higgins, Duxbury, Irving,

1992). Kopelman and Greenhaus defined interrole conflict as the extent to which a

person experiences pressures within one role that are incompatible with the pressures

that arise within another role.

Greenhaus and Beutell (1985) identified three types of antecedents or source

of the work-family conflict, which are time-based conflict, stress-based conflict, and

behavioural-based conflict. Time based conflict can take two forms: (1) time

37

pressures associated with membership in one role may make it physically impossible

to comply with expectations arising from another role; (2) pressures also may produce

a preoccupation with one role even when one is physically attempting to meet the

demands of another role. Strain-based Conflict exists when strain in one role affects

one’s performance in another role. The roles are incompatible in the sense that the

strain created by one makes it difficult to comply with the demands of another.

Behaviour-based conflict happens when the behavioural styles that one exhibit at

work (impersonality, logic, power, authority) may be incompatible with behaviours

desired by their children within the family domain. The table 1.2 shows the

multidimensional measure of work-family conflict.

Table 1.2

Multidimensional Measure of Work-Family Conflict

Direction to work-family conflict

WFC FWC

Origin of work and

family

Conflict

Time Time based WFC Time based FWC

Strain Strain based WFC Strain based FWC

Behaviour Behaviour based WFC Behaviour based FWC

38

Figure 1.1 – Work Family Role Pressure Incompatibility

Early research treated work-family conflict primarily as a one-dimensional construct,

recent research (Frone,Russell,&Cooper,1992) suggests that it is reciprocal in nature,

in that work can interfere with family (work-to-family conflict; WFC) and family can

interfere with work (family-to-work conflict; FWC).WFC and FWC are generally

considered distinct but related constructs. Research to date has primarily investigated

how work interferes or conflicts with family.

Work Domain

Illustrative Pressures

Hour workedInflexible worksheduleShiftwork

RoleconflictRole ambiguityBoundary - spanningactivities

Expectations forsecrelivenessand objectivity

Behavior

Strain

Time

Role PressureIncompatibility

Time devoted to one role makes it difficult to fulfill requirements of anotherole.

Strain producted by onerole makes it difficult tofulfill requirements ofanother role.

Behavior required in onerole makes it difficult to fulfill requirements of another role.

Family Domain

Illustrative Pressures

Young childrenSpouseemploymentLarge families

Family conflictspouse support

Expectationsfor warmthand openness

Strain

Time

Figure 1

39

1.8 Models of Work-Life Conflict

1.8.1 Role conflict model

Kopelman et al.(1983)provided a conflict model which proposed that work

conflict and family conflict had a positive relationship with inter role conflict and the

these three kinds of conflict individually had a negative relationship with job and

family satisfaction; at last the job and life satisfaction were related to life satisfaction

positively.

Figure 1.2 Model of work-family conflict 1

Kopelman, R.E., Greenhaus, J.H. & Connolly, T.F. (1983)

In this model, work-family conflict is based on role conflict. This model views work-

family conflict statically which regards work and family separately.

1.8.2 Sex Difference model

Higgins, Duxbury and Irving (1992) extended the previous model and

developed a more extensive and complete one. They added two more antecedent

variables, which are role involvement and role expectation. As to the consequence

variables, they also substituted quality of work and family life for job and family

satisfaction in order to eliminate the weakness–the lack of a significant relationship

between work-family conflict and job and family satisfaction.

Interrole Conflict

workd conflict

Family conflict

Job Satisfaction

Life Satisfaction

Family Satisfaction

40

Higgins, Duxbury and Irving (1992) paid attention to sex difference in work-

family conflict. Afterward many researchers study the sex effects to conflict. Addition

of role involvement and role expectation makes it possible to view work-family

conflict in the sight of sociology. Social judgment for men usually comes from work

role. If men involve much in family, it will differ from social expectation which will

lead to work-family conflict in a high degree. Social judgment for women usually

comes from family role. If women involve much in work, it will differ from social

expectation which will lead to work-family conflict in a high degree.

But this model still views work-family conflict statically. The roles of men

and women are in a change which leads to new role expectation and so contents of

work-family conflict for men and women are in a change accordingly.

Figure 1. 3 Model of work-family conflict 2

Higgins, C.A., & Duxbuy, L.E. (1992)

Work Expectation

Job Involvement

FamilyInvolvement

FamilyConflict

FamilyExpectation

Quality ofWork Life

LifeSatisfaction

Quality ofFamily Life

Work-FamilyConflict

Work Conflict

41

1.8.3 Double Direction model

Frone (1992) gave a Double Direction model considering the direction of

work-family conflict in which of stressors variable and depression outcomes are

added.

Figure 1.4 Model of Work-family Conflict 3

Frone, M.R., Russell & Cooper, M.L. (1992)

Based on this model, job stressors and FWC are positive to job distress; job

involvement is negative to job distress. Family stressors and WFC are positive to

family distress; family involvement is negative to family distress. Job and family

distress are positive to depression. This model gives a way to think work-family

conflict in a double direction which is important for future study.

Job Stressors

Job Involvement

Job Stressors

W

F

-F Conflict

-W Conflict

Job Distress

Depression

42

Conceptual Framework of Work-Life Conflict

Researchers have developed various framework on Work-Life Conflict and two of

such conceptual framework is discussed in this report.

Kim (2001) in his model has elaborated that work-family conflict arises from factors

within the work domain and family domain and the research model on WFC shown in

Figure 1.5 developed by Kim is

Figure 1.5 - Conceptual frame work of work life conflict

developed by Kim (2001)

43

Yavas et.al .(2008) has developed a model which is shown in figure 1.6 below where

inter-role conflicts emanating from the demands of the two universal domains of adult

life, work and family, lead to emotional exhaustion. According to this model,

emotional exhaustion results in poor job performance and a higher propensity to leave

the organization. Hence, the key underlying premise of this model is that work-family

conflict and family-work conflict impact the two critical job outcomes of performance

and turnover intention both directly as well as indirectly through the mediating role of

emotional exhaustion.

Figure 1. 6 Showing the conceptual model of work life conflict by Yavas (2008)

44

1.9 Work-Life Conflict of Women in software companies and need

for the study:

In a transitioning society like India, where the traditional roles of women as

homemakers and caretakers are deeply entrenched, the effective management of work

and family and their interface becomes a challenge for women and their employers.

Over the last decade, Indian society has witnessed a surge in the participation of

women in the workforce, especially in the software industry. The growing number of

women in the Indian IT workforce has led to an increasing interest from academia and

practitioners in the topic of work -life balance, work life conflict, stress management,

quality of work life etc., specifically of working women in the IT industry. In the light

of the increasing number of women in the IT industry, there is a need to examine the

phenomenon of the work - life conflict of Indian women IT professionals in

greater depth.

The software industry has contributed much to the confidence of women at

work place. Advances have been made with regards to gender equality and financial

independence of women in the software industry, considering the condition of women

workforce in other industries. Women constitute 37% of the workforce in Indian

software industry. Greater use of technology, exposure to modernity, lesser or

negligible reliance on physical strength to carry out the work are the distinguishing

factors which has made this possible, along with higher salaries compared to other

traditional industries.

In the present world, information technology plays a crucial role in human life.

The many new developments and inventions enable people to easily communicate

throughout the world and develop new solutions to existing ways of operating and

doing business. People and their lives are made more convenient with many kinds of

useful devices such as mobile phones and other portable gadgets. The more new

technology is desired by consumers, the more is the need for modern software to be

developed .Therefore, and the software industry has been expanded and developed not

only in Europe and North America but also in the Asia-Pacific region. In India,

government incentives offer low taxes and good infrastructure to attract more foreign

45

investors. The revenue of a city of central information technology services such as

Bangalore is forecasted to be doubled by 2012. Likewise foreign investors are

motivated to participate in the software industry in India and many more countries

because of its favourable government policies supporting software development

programs, competitive labour costs, abundance of available knowledge workers, and

its central location in Asia. Even though multinational companies can benefit from the

business environment, a difficult aspect is how to motivate local employees to work

according to the company’s goals to increase productivity and to tap their potential.

Many employees suffer from severe conflicts owing to the inability to balance

work and family and to deliver a successful work product, including; work planning,

understanding customers’ desires, and dealing with managers and co-workers.

In daily working life, employees may experience work conflict due to tasks

they are entrusted with and the frustration in their job. Work family conflict is related

to the spill over of family issues to work or vice versa. It occurs when people are

faced with threatening situations on both sides. They cannot cope with these difficult

situations which they feel are beyond their control and this results on their intention to

leave the job owing to the frustration from the work and inability to balance work and

family.

Concerning software developers, it has been noted that a software project can

fail for various reasons such as a lack of understanding of the requirements of a

project, insufficient time or discipline to plan the project properly from the beginning,

a loss of focus when the project is under way. This signifies that work life conflict can

have an effect on the balance of employees’ work-life. This research presents some

root causes of work-life conflict by carrying out a study of women software

professionals in Chennai which is a hub of software companies and which employs a

huge work force.

The presence of large number of women in the workforce and their drive for

careers has resulted in increasing attention to work-family balance issues. Literature

on female software workers clearly demonstrates that women experience a sense of

empowerment from their work (Fuller & Narasimhan, 2007). Software professionals

46

are known to derive their identity from their occupation (Deetz, 1995). Many women

value their careers and their development as central concepts of their identity (King,

1997; Shaffer, Francesco, Joplin, & Lau, 2003). However, evidence from the US and

the UK does not appear promising. In a survey on 40information system professionals

(IS), demographics, salaries and job satisfaction reveal that the ‘glass ceiling’ keeps

women in midlevel jobs in the IS department (Brett & Stroh, 1999). The survey

confirmed the existence of a salary gap by gender. The authors suggested that the

reasons for the salary gap might be both structural and social in nature. The reasons

presented include the observation that women did not enter the IS field in large

numbers until the early 1980s. Another reason is that some women may pass up the

chance to take higher paying jobs because they choose not to relocate. The gender

differences in IT careers appear to be affecting the competitiveness of countries

globally.

As Ahuja (2002) sums up, the statistics do not bear out the initial optimism

shown regarding women’s participation in the field of IT. Since IT is a relatively

young field, it had initially been assumed that impediments to the advancement of

women long existent in other fields, such as an established ‘old boys’ network’, a

large pool of more qualified and experienced male professionals, the lack of female

role models and mentors, and established discriminatory practices, would not present

the same barriers to women (Berney & Jones, 1988). Given this background, the

context for our present study becomes very relevant. Research on the work-family

balance in women in other sectors has recognised that in comparison to occupation

roles, the salience of women’s commitment to family roles so often emphasised in

Indian culture as being central to their very being remains undiminished (Bhatnagar &

Rajadhyaksha, 2001). Additionally, the authors emphasise that, in contrast to women

in Western societies, many Indian women, especially those in traditional joint and

extended families, are obligated to care for elderly relatives.

In a study done by Kapoor, Bhardwaj, and Pestonjee (1999), married women

employees reported that they face difficulties in maintaining a balance between work

and family and their careers suffer because of family responsibility. A reason for this

difficulty is likely to be the lack of help from their husbands. A survey conducted by

47

Rajadhyaksha and Smita (2004) indicated that only 34% of husbands extended help

willingly to their wives. Twenty two percent of husbands sometimes helped out but a

large proportion still subscribed to the traditional role and did not extend help to their

wives. Parikh (1998) found that motherhood makes balancing difficult, because

women have to manage the external interfaces of work and career, management of

home and children. A survey on parenthood among 2700 Indian couples found that

the ideal scenario, according to 60% of working mothers polled, is a part-time job.

Only 19% of them feel full-time motherhood is a viable option. The men, not

surprisingly, feel that an at-home mom is the best solution (Banerjee & Dutta-

Sachdeva, 2008). Workplace support in India seems conditional though. In a study

conducted by Parikh (1998), women experienced support from supervisors, but this

mainly occurred when a woman had proved to be capable and competent and had

earned respect at the workplace. In a society where a large number of women who are

entering the workforce in the IT industry are first generation women professionals, it

would appear that the perceptions of work and family balance may reflect some

unique elements hitherto not addressed in the literature. The nature of the software

services industry in India, which is a unique global delivery model, also poses some

unique challenges for professionals in general and women professionals in particular.

The researcher has chosen Chennai which is a metropolitan city and has several

software companies which has witnessed growth and employs professionals and

graduates from the country.

The research looks at exploring on the work life conflict of women software

professionals and their means of managing the conflict at work and family, their

expectation to manage the conflict at family front and the work environment. The

research was done by administering questionnaire to 500 women software employees

and some interviews. The research also discusses the ways of better managing work -

family conflict.

48

1.10 Antecedents of Work –Family Conflict

Work and family domain antecedents includes broad categories of

demographics, demands, and resources, whereas the personal domain antecedent

category includes demographics and attributes.

1) The majority of work demographics such as tenure, work schedule, and

occupation/rank serve as antecedents.

2) Work demands includes broad categories of hours/time pressure, job

expectations, and role stressors.

3) Work resources are categorized into broad categories: positive work attitudes,

support, job autonomy/flexibility, and organizational climate/practices.

1.11 Aim of the Study

The present study aims at understanding the extent to which women

professionals in software companies experience work life conflict, manage the work

life conflict and find out strategies to resolve the conflict. This research helps to

understand the factors which influence work-life conflict in their lives and the means

of managing the work-life conflict. It also aims in understanding the satisfaction level

in managing the work-life conflict and identify the opinion of the employees with

regard to their life and work. The present research also aims to identify whether the

employees are frustrated in their job and also rate their organization. The research also

identifies whether the employees receive support in their work and family

This research thus examines the issues associated with work-life conflict,

identifies if the women employees are at risk and articulates about how organization

and the family could care and provide ways enable the employees resolve their

conflict and maintain a work-life balance.

49

1.12 Need for the study

Studies reviewed have revealed that as a consequence of work life conflict

among women professionals in software companies in Chennai may lead to

frustration in the job, burnout, and dissatisfaction in the work and may give rise to

health problems to the individuals. It may also have a negative impact on the family

with lack of care to children and dependents, conflict with the spouse and

dissatisfaction with life.

The failure of women to effectively manage the conflict may lead to further

consequences which may have an impact on their life. Women in software companies

should be aware of the factors which lead to the conflict and adopt coping strategies

to overcome the conflict.

Hence it becomes the need of the day to understand the measures to be

adopted to overcome the work life conflict and do the needful to enable the women to

be free of negative effects of the conflict. It is evident from the review of research that

many researchers have studied the concept of work life conflict among women but

there is a dearth of literature on the work life conflict of women in software

companies in Chennai.

The influence of demographics on the work life conflict of women employees

in software companies in Chennai should be studied. The investigator has identified

the conflict among women professionals in software employees in Chennai owing to

the extended hours of work and the pressure on the work to complete the projects in

time. The long distance of travel to the offices which are located on the outskirts of

the city also results in the work life conflict of women employees. The study of the

work life conflict of women employees will help the organization and the individual

to pay attention to the needs and problems of women employees on whom the society

at large depends for the future growth of the nation.

50

1.13 Statement of the Problem

It is evident from past studies that many software women employees suffer

from severe conflicts owing to the inability to balance work and family and to deliver

a successful work product, including work planning, understanding customers’

desires, and dealing with managers and co-workers. In daily working life, employees

experience work conflict due to the variable tasks they are entrusted with and the

pressure of completion associated with these tasks and this leads to frustration in their

job. The family life also poses challenges to these working women as they have to

take care of their children and elders at home. The relationship with the spouse is also

strained owing to the inability to keep up to the commitments in the family. Work life

conflict is related to the spill over of family issues to work or vice versa. It occurs

when people are faced with threatening situations on both sides. They cannot cope

with these difficult situations which they feel are beyond their control and this results

on their intention to leave the job or end up with severe health problems. This

situation is owing to the frustration from the work and the inability to balance work

and family. This research presents some root causes of work life conflict by carrying

out a study among women software professionals in Chennai which is a hub of

software companies and which employs a huge work force. The researcher has chosen

Chennai since it is a metropolitan city and has several software companies which has

witnessed growth and employs professionals and graduates from the country.

51

1.14 Objectives of the study

To analyse the factors which influence the Work-Life Conflict of Women in

Software Industry in Chennai.

To identify the level of satisfaction of women employees with regard to the

management of work-life conflict.

To identify the level of expectation of women employees in managing work-

life conflict.

To identify the feeling of women employees towards their professional work

and personal life and their opinion pertaining to Work and Life.

To analyse the impact of demographic variables on Work-Life Conflict of

women employees in software industry in Chennai.

52

1.15 Scope of the Study

This research examines the issues associated with work-life conflict, identifies

the prevalence of conflict at work in the software industry and in the family and the

frustration of employees at work. The employers could take a cue from this research

and make this a case for changes to be implemented in the organization. The research

provides a clearer picture of the extent to which the work-life conflict is affecting the

employees in the software industry. The research helps the organization appreciate

changes in the management of employees in relation to their work-life conflict.

53

CHAPTERISATION

The present study has been divided into five chapters.

The first chapter deals with the identification of variables related to the work

life conflict. The variables like work-life conflict, satisfaction with regard to

managing conflict, expectation level for the betterment of managing conflict are

studied. It also includes need for the study, objectives of the study and chapterisation.

The second chapter is devoted to the review of related studies. It deals with

the exhaustive literature on the variables selected for the study. It also highlights the

research gap from the previous studies.

The third chapter is concerned with the research methodology and the

formulation of hypothesis. This chapter embodies the description of instruments,

selection of samples, the sampling techniques, the method of data collection and the

procedure followed in the conduct of the present study.

The fourth chapter accommodates the analysis and interpretation.

The fifth chapter comprises the summing up of the findings and the

conclusion of the present investigation. Further it includes the implications of the

study and provides suggestions for future research.

54

CHAPTER II

REVIEW OF LITERATURE

A literature review is a body of text that aims to review the critical points of

current knowledge and or methodological approaches on a particular topic. Literature

reviews are secondary sources and as such, do not report any new or original

experimental work. Its ultimate goal is to bring the reader up to date with current

literature on a topic and forms the basis for another goal, such as future research that

may be needed in the area. A well-structured literature review is characterized by a

logical flow of ideas; current and relevant references with consistent, appropriate

referencing style; proper use of terminology; and an unbiased and comprehensive

view of the previous research on the topic.

Review of related studies is an indispensable task of every researcher

in his/her area. Thus the researcher has the responsibility of compiling all work done

by previous researchers. The review of studies helps an individual to gain more

insight into the problem. It also enables the researcher to decide the course of

objectives and hypotheses. In this chapter an exhaustive attempt has been made to

present exhaustively about the previous researches conducted in the respective areas.

This has been done on the basis of the key concepts identified in chapter one. The

present research work intends to find out the work-life conflict of women employees

in software industry and ultimately what factors lead to life satisfaction.

Kahn et al. (1964) described work-family conflict as a type of inter role

conflict in which demands from the work role conflict with demand from the family

role. This field has been dominated by role theory which predicts that multiple roles

lead to role stress which in turn results in strain and that is one reason for work-family

conflict.

55

Pleck (1977) in his asymmetric boundary permeability theory examined that

work and family boundaries are asymmetrically permeable. That is, work was allowed

to interfere with family to a greater extent than is the case in reverse. He considered

gender as an important factor in work-family conflict in his theory of the work-family

role system. He has conceptualized work-family interface that includes gender as an

important factor. Further he explained that the work-family role system is composed

of the male work role, the female work role, the female family role, and the male

family role. Each of these roles has been fully actualized, or may be only partly

actualized or latent, as was often the case with the female work role and the male

family role.

Kanter (1977) observations about the myth of the separate spheres of work

and family have left a powerful legacy for work–family literature. The ‘myth of the

separates spheres’, in part, contends that the different domains of our lives, such as

work and family, indeed do affect one another. He had challenged assumptions about

the insularity of life experiences, scholars in the work–family area of study and has

been able to examine the work–family interface and the adaptations that

individuals/families/organizations make in response to priority work–family

experiences. Much of the work–family literature reflects assumptions that the

interface of work and family is typically characterized by tension and conflict. The

construct of work-family conflict has shaped a significant portion of the work-family

literature

Jerome M Rosow (1981), founder and chairman of the Work in American

Institute, Inc., which had a mission ‘ to advance productivity and the Quality of Work

Life through the principles of sound human resource practices applicable in all

industries ‘, has identified seven critical factors which will affect the quality of work

life during the years ahead. These are pay, employee benefits, job security, alternative

work schedules, occupational stress, participation and democracy in the workplace.

Sayed and Sinha (1981) examined the relationship between Quality of

Work Life, job stress and performance. The results indicate that higher Quality of

Work Life led to greater job satisfaction.

56

Beverly and Verdin (1983) identified ten sources between the years 1964 to

1980 on job satisfaction in libraries. The relationships of gender, age and tenure to

the job satisfaction of library employees were explored. No significant differences

were found between Age and Job Satisfaction or between Tenure and Job

Satisfaction. Satisfaction tended to increase with Experience, Mobility, with

Seniority of the post and with Managerial level. The researcher had also put

questions about job and life satisfaction in the present research to find the effects of

work-life conflict.

Rahman (1984) found that demographic factors such as age, education,

experience and income had influence on the subjects. Subjects having low

educational background and lower income had better perception of Quality of Work

Life than those having higher education and higher income. Their study established

that private sector worker perceived significantly higher Quality of Work Life than

their counter parts in the public sector.

Cohen and Wills (1985) have studied the role of social support as an

antecedent, mediator or postulated to be a buffer against stress referred to as the

buffering hypothesis or directly related to promoting personal well-being referred to

as the main effect hypothesis.

Greenhaus and Beutell (1985) in their study found that work-life conflict is

a type of inter role conflict that occurs as a result of incompatible role pressures from

the work and family domains and they also found that the direction of the conflict

between work and family was inherently bidirectional. They identified three types of

work-family conflicts. They were: time-based conflict, strain-based conflict and

behaviour-based conflict. According to them, time-based conflict occurred when

time spent on activities within one role cannot be devoted to activities within another

role. This implies that time obligations from role make it physically impossible to

fulfil expectations from another role. Strain-based conflict occurred when roles were

incompatible such that the strain created by one makes it difficult to comply with the

57

demands of another. Strain-based conflict occurred when the strain from a given role

affects one’s performance in another role. In this way strain from one role which can

include another competing role. The final type of conflict defined by them was

behaviour-based conflict in which specific stress, tension, anxiety and fatigue made

it more challenging to fulfil obligations from patterns of in-role behaviour may be

incompatible with expectations regarding behaviour in another role. The researcher

has used these three types of conflicts to measure the experience of conflict at family

and at work.

Uma Sekaran (1985) in her article “the perceived Quality of Working Life

in banks in major cities in India” observed the Quality of Work Life in the Indian

Banking industry According to her, organizational members at different

organizational levels and in different job positions perceived highly about the

Quality of Work Life and she found that Quality of Work Life in the banking

profession is not high. People recruited were over qualified for routine job.

Inequitable reward system demotivated the better performers. Lack of alternative job

avenues, scarce chance of promotion, and alienation from work etc. were the reasons

for poor Quality of Work Life.

Lawler and Mohrman (1985) portray Quality of Work Life in two ways.

According to them, “One way equates Quality of Work Life with a set of objective

organizational conditions and practices. E.g. job enrichment, democratic supervision,

employee involvement and safe working conditions. The other way equates Quality

of Work Life with employees’ perception that they are safe, relatively well satisfied

and able to grow and develop as human beings. While defining Quality of Work life

in Japan, according a web source, Professor Takashi Kawakita wrote that the results

of 1987 JPC survey of white-collar attitudes at major companies showed that white-

collar workers wanted more free rein to do a better job. In this survey, respondents

were given a list of eleven workplace changes that could enable them to do a better

job and asked to say which they think were most important.

Chassinet al. (1985) found three types of conflicts in their research on a

sample of 83 dual worker couples with pre-school children. The types of conflicts

58

they faced can be described as the conflict between demands of multiple roles,

conflict between role expectations of self and spouse and conflict created by lack of

congruence between expectation and reality of roles. The authors stated that self-role

congruence in women leads to better mental health.

Moos (1987) stated in the opinion of employees, the quality of their work

life owes mainly to three factors: acquiring new experience (28.1 per cent), realization

of social contacts (25 per cent) and existing way of organization of the work (15.6 per

cent). Proposals for an improvement of work quality and increase of job satisfaction

represent: permanent changes and innovations in the organization of the work (25 per

cent), increase of income (21.9 per cent) and convenient work time (15.6 per cent).

Grenier et al. (1987) had given that Quality of Work Life was a way to

improve working conditions, morale and productivity by providing a more congenial

workplace. The other side of the study claimed that quality of work life programs

were sophisticated disguises for deskilling and speed-ups, and were manipulative

union-busting tools which U.S. management has borrowed from the Japanese.”

Wyatt (1988) Quality of Work Life was the result of socio-economic

conditioning. In his words, ‘Quality of Work Life was different for a given person in a

particular place and time than for other people in other circumstances.’

Voyandoff (1988) has studied the role of work place support, i.e., the support

received from supervisors and co-workers as another critical element of work-family

balance.

Bedeian et al. (1988) evaluated the relationship between work-family conflict

and satisfaction. Specifically, they were interested in looking at the process by which

work stress and family demands interact and subsequently relate to work satisfaction,

marital satisfaction, and overall life satisfaction. In a sample of 432 male and 335

female accounting professionals, he predicted that conflict within each role would be

directly related to satisfaction within that role. That is to say that work-related role

stress would be directly related to work satisfaction, while family-related role stress

59

would be related to marital satisfaction. The researchers also predicted an indirect

relationship between work-related role stress and parental demands and satisfaction

(work, marital, and life), through work-family conflict. Participants, all of whom were

married and employed full-time, completed measures of work-related role stress,

parental demands, work-family conflict, job satisfaction, marital satisfaction, and life

satisfaction. Results suggested that work/family conflict was related to domain

specific satisfaction as well as overall life satisfaction. A relationship between work-

related role stress and Work-family conflict was also supported. He also found that as

work related role stress increases, life satisfaction decreased because of subsequent

increases in work-family conflict. These results provide evidence of a relationship

between work-family conflict and satisfaction.

Chaipol (1989) compared Thai middle managers working in American–

owned companies with Thai-owned and Japanese-owned companies. It was found that

they prefer American management practices to Japanese management practices in

terms of pay, promotion and training.

Rodgers (1989) has emphasized the importance of supervisory support so

much in the literature that some researchers believe that well-being of family lies

largely in the hands of first-line supervisors. It is expected that work demands,

including work overload, overtime work, irregular work schedules, and related to job

and life satisfaction. It is also proposed that supervisory support moderates the

relationship between work demands and work-to-family conflict, and between work-

to-family conflict and satisfaction with job and life. More specifically, employees

with heavy work demands will experience less work-to family conflict when they

receive social support from their supervisors, compared to those who receive

supervisory support to a lesser extent. Also, employees who are experiencing work-

to-family conflict will be more satisfied with their job and life when they receive

social support from their supervisors, compared to those receiving such support to a

lesser extent.

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Cummings and Huse (1989) in their Comparisons of American and Japanese

Management Styles reveal that much of the Japanese companies could be explained

by their strong corporate cultures emphasizing employee participation, open

communication, security and equality.

Gutek et al. (1991) studied the work-family conflict of professional women

and men to explore sex differences in work-family experiences. Two measures of

work-family conflict were used to assess family interference with work (FIW) and

work interference with families (WIF). A systematically selected sample of 209 senior

managers who were members of American Psychological Association (APA) were

included in the study. The study were tested with t-tests and regression analysis,

sublimated with analysis of co-variance and correlation matrices. The bivariate

relationships among the time and conflict variables were calculated separately for

men and women. Both men and women reported greater WIF and FIW because both

men and women spent more time in work than in family. Women reported more WIF

than men.

Garrison and Deborah (1991) in their study supported the concept of

Japanese Management Style and found it more stressful than the contingency

American Style. Also it was found out that concept that occupational stress was

negatively correlated to job satisfaction was supported by both the groups.

Jain (1991) had an opinion that Quality of Work Life was not a single or a

specific notion. It consisted of a whole parcel of terms and notions, all of which really

belong under the working life namely: Industrial effectiveness, Human resource

development, Organizational effectiveness, Work restructures, Job enrichment, Socio-

economic systems, Working humanization, Group work concept, Labour

management co-operation, Worker’s participation and involvement and Co-operative

work structure.

According to a Quality of Work Life survey in Japan published by Asian

Productivity Organization, Japan (1991), “education did not seem to be a factor for

men but for women there were more discontent among high school graduates than

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among junior college graduates regarding the Quality of Work Life. Older employees,

both men and women said that the system was unfair. Looking only at men in their

forties, dissatisfaction seemed to be centred on high-school-graduate clerical staff and

college-graduate lower-level managers.”

Shallenberger (1992) studied the work – family conflict issues faced by

electrical and computer engineers. They would consider changing Jobs for better

family benefits. The study revealed that when employees have adjusted their work

scheduled to attend to a sick child to balance between career and family.

Haque (1992) found out that no relationship exists between perceived

Quality of Work Life and workers’ age, education and job experience.

Kahn and Bossier (1992) had stated in their stress literature that social

support has traditionally been treated as a moderator among life demands (stressors),

stress and well-being. The study took the same theoretical perspective and proposed

that family support and support from the management moderates the relationship

between work demands and work-to-family conflict, and between work-to-family

conflict and life and job satisfaction of software professionals. The study focused on

the role of supervisor support (especially from the immediate manager/supervisor) as

a key moderator.

Frone et al. (1992)found in their study that employees perceive that work

interferes with their family life (work-to-family conflict), rather than the other way

around (family-to-work conflict).They also found that work-to-family conflict was

reported three times more frequently than family-to-work conflict by both male and

female employed adults with a spouse and or with children. They had stated that work

and family boundaries are asymmetrically permeable. A higher level of work-family

conflict has been related to higher levels of family distress.

Ghosh (1993) studied organizations engaged in manufacturing, mining,

power generation and service sectors covering 67 enterprises including both public

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and private sector. His study covered the management perception regarding

significance of Quality of Work Life, organizational supportive activities of

management and its involvement in Quality of Work Life programmes. The finding

was that the core determinant of Quality of Work Life is ‘the management’s

perception of Quality of Work Life in affecting organizational effectiveness’

Thomas and Ganster (1995) examined the direct and indirect effects of

organization policies and practices that are supportive of family responsibilities on

work – family conflicts. Survey data were gathered from 398 health professionals

who had children aged 16yrs or younger at home. The study related with work family

conflict and depression. The result of this study indicated that family supportive work

policies and practices might produce significant benefits in terms of employee

attitudes and wellbeing.

Burley (1995) examined social psychological processes within the family as

potential mediators of the relationship between work-family conflict and marital

adjustment among career men and women in the US. A path analytic model was used

to test two specific family variables – perceptions of equity in spousal home division

of labor and perceptions of spousal social support as potential mediators of the

proposed negative relationship between work – family conflict and marital

adjustment. He also found that gender exhibited no overall indirect effect on marital

adjustment.

Beckworth and CherryKay (1996) had determined the relationship

between organisational changes, job stressors, job satisfaction, organisational

commitment and turnover of human service workers. The sample consisted of 98

social workers and 324 registered nurses employed in hospital settings. The model

proposed that organisational change of re-structuring, re-engineering and job redesign

led to increased job stress.

Wadud N (1996) found out that Quality of Work Life was significantly

higher among the private sector women employees than their counterparts in the

public sector. It was also found out that younger groups and higher experienced

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groups had significantly higher perception of Quality of Work Life than the older and

the lower experienced groups.

Netemeyer et al. (1996) had studied that Work-family conflict and Family-

work conflict are distinctive, but are conceptually related forms of inter-role conflict.

Work-family conflict refers to "a form of inter-role conflict in which the general

demands of time devoted to and strain created by the job interfere with performing

family-related responsibilities and family-work conflict refers to a form of inter-role

conflict in which the general demands of time devoted to and strain created by the

family interfere with performing work-related responsibilities. They established

convergent validity for the measure by exploring their relationship between their

measure of work-family conflict and life and job satisfaction.

They made predictions regarding the relationship of work-family conflict and

family-work conflict to various on-job and off-job constructs. The researchers

explored the relationships of work-family conflict and family-work conflict to 16

constructs such as life satisfaction, job satisfaction, role conflict, and role ambiguity.

Life satisfaction and job satisfaction were negatively related to work-family conflict

and family-work conflict.

Ezra and Deckman (1996) found that organisational and supervisor

understanding of family duties were positively related to satisfaction with the balance

between work and family life. Workplace support via an organisational approach

involved the implementation of family friendly policies, which were associated with

satisfaction with the work-family balance.

Ezra and Deckman (1996) found that organisational and supervisor

understanding of family duties were positively related to satisfaction with the balance

between work and family life. Workplace support via an organisational approach

involved the implementation of family friendly policies, which were associated with

satisfaction with the work-family balance

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Frone et al. (1997) has studied that supervisory support could be

conceptualized as having two components: instrumental and emotional support.

Instrumental supervisory support refers to the provision of direct assistance and

advice with the intent of helping an employee meet his or her family responsibilities.

They did not find a significant relationship between work-family conflict and overall

health or hypertension over a 4-year period.

Frone et al. (1997) has studied that supervisory support could be

conceptualized as having two components: instrumental and emotional support.

Instrumental supervisory support refers to the provision of direct assistance and

advice with the intent of helping an employee meet his or her family responsibilities.

They did not find a significant relationship between work-family conflict and overall

health or hypertension over a 4-year period.

Quich et al. (1997) studied on a new discipline called occupational health

psychology (OHP) is focused on the individual, work and the work family interface in

the prevention of injuries, stress and illness in the work place OHP focuses on

prevention rather than treatment. Such prevention approaches include work and job

design, monitoring of stress and distress in the work place, education and training and

the provision of mental health services such as employee assistance programme.

With organization intervention focused on the prevention of stress and illness in the

work place, OHP emphasizes the importance of promoting the positive work family

interface among organizational researchers and practitioners.

Parikh (1998) found that motherhood made balancing difficult, because

women had to manage the external interfaces of work and career, management of

home and children. A survey on parenthood among 2700 Indian couples found that

the ideal scenario, according to 60% of working mothers polled, was a part-time job.

Only 19% of them felt full-time motherhood was a viable option. The men, not

surprisingly, felt that an at-home mom is the best solution. Workplace support in India

seemed to be conditional. Women experienced support from supervisors, but this

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mainly occurred when a woman had proved to be capable and competent and had

earned respect at the workplace.

Luthans et al. (1999) concluded that work and family are both “allies” and

“enemies” in that resources and emotions and can be shared crossed domains but they

can also be depleted by an overly demanding role.

Perrewe et al. (1999) investigated the relationship between work-family

conflict and job and work satisfaction. It was hypothesized that work-family conflict

would be negatively related to job and life satisfaction. Participants included 267

hotel managers, all of whom completed a series of questionnaires assessing work-

family conflict, value attainment, job satisfaction, and life satisfaction. Results

suggested that work-family conflict is negatively related to job and life satisfaction.

Kapoor et al. (1999) in their study on married women employees reported

that they face difficulties in maintaining a balance between work and family and their

careers suffer because of family responsibility. A reason for this difficulty is likely to

be the lack of help from their husbands.

Kossek and Ozeki (1998) have shown in their study that work- family

conflict has consistently been shown to decrease life satisfaction, one of the key

indicators of psychological wellbeing especially for women. Employees experiencing

work-to-family conflict were likely to blame their jobs and working conditions for

this, and felt dissatisfied with their jobs, as well. They found that not everyone with

heavy work demands experienced work-to-family conflict to the same extent.

Similarly, those experiencing work-to-family conflict were not guaranteed to suffer

from lower life and job satisfaction. This prompted the researcher to take up a study

on women software professionals whose excessive work demands interfere with their

family responsibilities and who were torn apart between the two domains and unable

to satisfy both without compromise. This was expected to result in their

dissatisfaction with life and hence this variable was chosen for the study.

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A survey conducted by the European foundation for the Improvement of

Living and Working Conditions (1998) found, ‘women prefer to work fewer hours

than men, on average, because women are devoting more time to childcare and unpaid

domestic work… clearly women’s greater involvement in unpaid domestic work is

related to their preference for a shorter work week and a desire to balance work with

other life demands.’

Valmiria and Suzana (1998) found out that the best country to work was

Brazil where they exhibit the disjunctions between theory and practice. They sent the

questionnaire to 4000 companies and only 30 companies came into the research. Of

the thirty companies, when evaluated eight items considered were essential so that a

company was an excellent place to work, eleven of them only obtain to have a

maximum performance in relation to more four items.” According to them, quality of

work life was not seen in many companies in Brazil practically.

Burke and Greenglass (1999) found that job stressors and work demands are

the strongest predictors of work-family conflict. They also found that role demands

play an important role in aggravating Work-Family Conflict. Their research also

highlighted that work role characteristics associated with work demands refer

primarily to pressures arising from excessive workload and time pressure.

Nini Yang et al. (2000) in their study researched upon the sources of work-

family conflict and compared the work and family demands of China and U.S. They

set up the hypothesis that Americans experienced greater family demand which had

an impact on work-family conflict whereas Chinese experienced greater work demand

which had an impact on work- family conflict and the hypothesis was supported. They

also found that work demand did not differ significantly between the two countries

and did not have a greater effect than family demand on work family conflict in

China.

Margaret and James (2000) focused on the work-family conflict experienced

by senior female international managers within a European context. They chose 50

senior female expatriate managers from a wide diversity of industry and service

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sectors. Their study established that work family conflict prevents many female

managers from progressing to senior management. Their results showed that the

senior international career move has largely been developed along a linear male

model of career progression and with gender disparity both in organizations and

family responsibilities frequently prevents women employees from reaching senior

managerial positions. The study served helpful to the researcher to understand the

problems faced by female managers in their career progression.

Higgins et al. (2000) showed that work demands such as number of hours

worked, workload, shift work were positively and strongly associated with Work-

Family Conflict. Working long hours, evenings and weekends limits the time that

employees were available for family activities. Therefore this has enabled the

researcher to expect that higher work demands such as work overload, long hours of

work per week, irregular work schedules and working overtime would be associated

with higher work-life conflict among women working in software industry.

They have empirically examined whether part time work helps woman balance the

work and family for two classes of part time workers, those in career oriented jobs

(Managers and Professionals) and those in earner positions (technical, clerical,

administrative, retail, production). A random sample of all Canadian federal public

sector employees working in national capital region and cross section of private sector

employees were selected. The final study sample consisted of 712 mothers in part

time earner position and 117 mothers in part time career position. In this research

they focused on the psychological experience of work family balance and perceived

ability to manage individual and family. Results of the study was part time work was

significantly associated with role over load among earners, and there was no relation

between job status and role overload with career woman. Employees in earner

occupation had significantly higher depressed mood and significantly lower life

satisfaction and those in career position. Part time work was associated with higher

life satisfaction. Perceived stress was unrelated to job type or job status. Woman in

earner position reported significantly higher depressed mood than career woman +

lower life satisfaction. Stress was unrelated either job type or job status and

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organisation that employed large size of non-career woman might also have a role to

play in improving the quality of work life for the employees. The analysis of

individual outcomes suggested that work in earner occupation was associated with

higher depressed mood and lower satisfaction than career work, regardless of full or

part time status. The research data strongly suggested that job type differently affect

women’s ability to balance work and family.

Pattanayak et al. (2000) have conducted a study about Role Stress and

Quality of Work Life specifically at Steel Authority of India (Rourekela Steel Plant)

and National Aluminium Co. (NALCO) taking into account type of organization (new

and old), area of work (production and service) and the position in the Organization’s

hierarchy (executive and nonexecutive) with regard to Organizational Role Stress

(ORS). It explained that all the three dimensions jointly contribute to the differential

experience of role expectation conflict as ORS variables.

Frone (2000) showed that, depending on the type of work-family

conflict and type of disorder, employees who often experienced work-family conflict

were about 2 to 30 times more likely to experience a clinically diagnosed mental

health problem, than were employees who reported no work-family conflict.

Choudhury (2000) in a case study in west Bengal Tea industry compares

the quality of work life in tea industry by dividing the period into three stages since

18th

century till date and says that the working conditions are not yet changed. He

reproduced the excerpts about the quality of work life constructs by Radhakrishnan,

(1998) as “The loyalty to the organization, commitment, participative culture,

communication, goal setting, properly stated attitudes and attributes of workmen

towards the fulfilment of organizational objectives and development.”

Anna Riley (2000), while writing about the Quality of Work Life of African

Americans, conveys, ‘the quality of work life among African Americans has been

associated with persistent poverty, family structure, psychological distress and

problems in other areas of life and Younger African American workers have had

better opportunities to pursue occupations in the primary sector of the labour force

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than older workers. Increased autonomy was positively associated with higher levels

of self-esteem and self-efficacy, which may have positive effects on satisfaction with

life in general. On the other hand, high educational attainment could stimulate high

job expectations. Younger African American workers may experience higher levels of

job dissatisfaction due to perceived work role marginality, which can spill over and

affect self-evaluation and life satisfaction.

According to Gillian et al. (2001) the difference in the opinion of employees

about quality of work life factors was based on the demography. They found while

surveying 1001 employees of different organizations in Australia that the

‘dissatisfaction clearly increased with age.’ When income groups were compared,

‘73% of full time high-income earners was satisfied with their remuneration whereas

only 47% of full time low-income earners were satisfied. Work was interesting for

only half of the low-income earners. High income and long hours meant more stress.

When gender was considered, though women were more likely to agree that they trust

senior management their opinion did not differ significantly from men.

Jean et al. (2001) studied the work-family conflict of women entrepreneurs in

Singapore. Their work-family conflict was divided into three parts, job-parent, job

spouse, and job Home maker conflict. They applied correlation and multiple

regressions as a statistical tool for analysis. Their findings revealed a need for greater

spouse support, flexible work schedule and full day school in order to alleviate work-

family conflict. They also state that spouse support and flexible working schedule play

an important role in reducing work-family conflict of women entrepreneurs. Among

the three types of work-family conflict, job-spouse conflict has the most significant

negative influence on the women entrepreneur’s wellbeing, in terms of the satisfaction

with business, marriage and life.

Gillian and Ron (2001) also found out in their study that employees of

small organizations were substantially more satisfied than employees of large

organizations. Similarly, private sector employees were more satisfied with the extent

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to which they could exercise control over the way in which they did work but, once

again, this only differed slightly from public sector employees. Private sector

employees indicated that they had a higher quality of work life than public sector

employees did. Thus according to this study private sector employees are more

satisfied than the public sector employees.

Wyatt and Wah (2001) in their comparison of Quality of Work Life in

different countries state that ‘with the exception mainly of Japan, Asia has

emphasized Quality of Work Life to a far lesser degree than North America and

Europe. Therefore, not only were there probably fewer organizations

operating Quality of Work Life programs in Singapore, but there were also fewer

published Quality of Work Life research papers in Singapore.’ This showed that the

Quality of Work Life in Asian countries other than Japan was comparatively less

emphasized.

Megan et al. (2002) in their study had given that Gender and managerial

status have previously been found to relate to work-family conflict, though the

combination of gender and managerial status had received less attention. This study

explored differences in levels of work-family conflict and related job attitude and

health and coping variables among women managers, men managers, women non-

managers, and men non-managers at a large organization. Women managers

experienced higher levels of work-family conflict, work role overload, and problem

drinking. But the levels of work to family conflict were unexpectedly similar between

women and men managers. Possible explanations for this are considered.

Eby et al.(2002) in his study has related Work-Family Conflict (WFC) to

negative psychological and organizational outcomes such as increase in depressive

symptoms, increase in use of alcohol and substance abuse, decrease in life

satisfaction, job satisfaction and marital satisfaction and increase in tendency to quit

the job. From this study the current research also intends to focus on life and job

satisfaction. The negative relationship between Work-Family Conflict and job

satisfaction was also well established in the study. They have also established in their

study in 2004 that Work-family conflict predictors might be measured by having

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children at home, experiencing disagreements or tension with spouse, and high

involvement or time demands from family members.

Clare Leonett et al. (2002) in their study on full time working respondents in

both Portugal and Britan were assessed for country, gender and occupational class

differences in work life conflict focussing on both work and domestic spheres. They

identified two distinct groups as having very high levels of conflict: routine and

manual women in Portugal and professional and managerial women in Britan. Their

study suggested that very long hours of domestic work, combined with worries over

unsatisfactory child care arrangements and a lack of support from partners and

informal networks, contribute to the high levels of conflict experienced by women

working in routine and manual occupations in Portugal. The pressures of very long

working hours, combined with a perception of increasing work demands, as well as

additional domestic work, contribute to the high levels of work life conflict for

women working in professional and managerial occupations in Britain.

Ruderman et al. (2002) in a sample of 61 female managers and executives,

explored developmental issues facing managerial women. Participants were recruited

at a leadership development program for women at a large management development

organization. The researchers found that 23% of the participants reported that

psychological benefits of their personal lives, such as self-efficacy and confidence,

enhanced their ability to be an effective manager. Results suggest that self-efficacy in

one domain of an individual’s life can have an impact on how the individual

experiences another domain. Given what is known about self-efficacy as it relates to

managing multiple roles, it appears that work-family conflict self-efficacy could serve

as an important predictor in a model of work-family balance. In the current study,

work-family conflict self-efficacy is conceptualized as a predictor of both Work-

family conflict and work-family enrichment.

Webster (2002) points out that family structures and female roles vary across

countries, but overall, women continue to be the primary provider for domestic and

childcare responsibilities. The presence of large numbers of women in the workforce

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and their drive for careers has resulted in increasing attention to work-family balance

issues.

Parasuraman and Greenhaus (2002) suggest that the consequences of work-

family conflict have been investigated widely, finding high levels of conflict

producing dissatisfaction and distress within both the work and family domains.

However, the mutually enriching effects that work and family can have upon each

other have been very rarely considered. They also suggest that there has been an over-

emphasis on the impact of environmental and situational factors on WLB, at the

expense of investigating individual differences, such as personality constructs.

Jones and McKenna (2002) investigated women’s work-home conflict in

multinational IT companies using quantitative and qualitative methods. At first, a

questionnaire was distributed to all women employees. All participants were then

asked to join an on-site focus group. Four focus groups were composed of 31 female

employees in total. The findings revealed that women perceived work interfering with

home as their main reason of conflict as a result of their being tired after working for

long hours.

Yi Wang (2002) involved herself in an in-depth study of ten women managers

to understand how gender influences the experience of woman managers’ in Mainland

China and found the reciprocal influence of relationships with family members and

work. Her study revealed the inelasticity in the expectations, self-imposed as well as

imposed by family members facing women managers. A key finding was that in

China, support from in -laws for child care and house work alleviate the physical but

not the mental work of managing families which still falls to women. Any support

they receive seems to emphasize that they have not fulfilled their domestic role and

makes them feel guilty and stressed. All the participants in the study felt that an ideal

woman should fulfil her responsibilities at home.

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Anderson et al. (2002) in their study have found that supervisory support was

an important source of social support in coping with problems associated with WFC.

They found that if a manager gives employee’s flexibility even when informally

supporting such an option even in the absence of an organizational policy, employees

balance work and family more easily.

Eby et al.(2002) has studied that Supportive supervisors are instrumental in

making and interpreting organization’s work–family policies .On the other hand,

emotional supervisory support refers to emphatic understanding and listening,

sensitivity toward the WFC issues, and genuine concern for the well-being of the

employee and his or her family.

Ahuja (2002) studied about the gender differences in IT careers

appear to be affecting the competitiveness of companies globally. It was found that

the current labour shortage in the IT industry has become more important than ever to

reduce sources of leakage in the IT career paths of women. A model of barriers faced

by women in the field of information technology was presented. Three distinct career

stages of career choices, persistence and advancement were analysed. At each stage,

the effects of social and structural factors which may act as barriers were identified

and discussed. Social factors include social expectations, work–family conflict and

informal networks, while the structural factors were occupational culture, lack of role

models and mentors, demographic composition and institutional structures. A

proposed research agenda was offered. It also suggested that these social and

structural factors as well as their interactions would result in turnover of women in IT.

Hyman (2003) evaluated the centrality of work to employees in two growing

employment sectors, call-centres and software development. He examined the

extension of work into household and family life in these two sectors. Extensions are

identified as tangible, such as unpaid overtime, or intangible, represented by

incursions imported from work, such as exhaustion and stress. The study found that

organizational pressures combined with lack of work centrality resulted in work

intruding into non-work areas of employee lives though intrusions manifest

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themselves in different ways according to type of work, levels of worker autonomy

and organizational support.

Lo and Stone (2003) conducted a study to examine the kind of work-life

conflict that Hong Kong women of high status faced and the strategies they used to

cope with work-life conflict. The sample included married professional women with

children who were interviewed face to face or over the telephone. The results showed

the inefficiency of the coping strategies practiced by the participants. Accordingly as

stated by the authors, organizations and institutions in Hong Kong realized the

importance of organization support for the working mothers in order to maintain a

work-life balance. Lo also studied the family-friendly guiding principles in Hong

Kong. One-hour personal interviews were conducted with 50 “married professional

women” in order to investigate and explore the way they managed work and family.

The findings showed that the conservative family environment in Hong Kong led to a

more strenuous way of life for nearly all the interviewed professional married female.

The results discovered an apparent indication that women need time flexibility to

improve handling work-family issues.

Batt and Valcour (2003) suggested that the most effective organizational

response to work-family conflict and to turnover are those that combine work-family

policies with other human resources practices, including work redesign and

commitment-enhancing incentives.

Drew et al. (2003) male senior managers are finding it difficult to achieve

their desirable work-life balance due to developments in information technology

which mean senior managers can be expected to be “on call” at almost any time of the

day or weekend. They also found that all of the senior managers they interviewed

were opposed to the idea of working from home because they thought this would be

required in addition to their already lengthy office work schedule.

Wentling, R.M. (2003) his shown that the twin roles of women cause tension

and conflict due to social structure. In this study on working women in Delhi, it is

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shown that traditional authoritarian set up of Hindu social structure continues to be

the same and hence women face problem of role conflict and it is suggested that

change in attitudes of men and women according to the situation can help to

overcome their problem.

Pocock (2003) has nicely explained the work/life collision theory in which he

argued that the ever-increasing working hours leave the individuals with less time for

themselves, and to pursue his hobbies or leisure activities. This hinders the growth of

the person as an individual in terms of his personal and spiritual growth.

Judy de Villiers and ElizeKotze (2003) found that work-life balance is a

personal issue that varies across time and situations and the underlying conflict

experienced pertains to role overload and role interference. The most significant

work-life conflict arises from complex workplace issues, including managing change,

supervisory and technical competences, leadership, roles and accountabilities, and

culture. The results suggest that leadership, supervisor/manager recognition and

support for individuals and their needs, influence work-life balance and work life

balance can be improved by nurturing individual balance-enabling skills as well as

developing organizational balance-supportive capabilities.

Fisher and Layte (2003) consider three distinct sets of measures of work-life

balance, viz. proportion of free time, the overlap of work and other dimensions of life,

and the time spent with other people.

Greenhaus and Powell (2003) showed that work-family conflict occurs when

participation in work activity interferes with participation in a competing family

activity or when work stress has a negative effect on behaviour within the family

domain. For example, conflict may occur when an employee is accepting a promotion

that requires more hours which in turn decreases the number of hours at home with

the family. On the other hand, family-work conflict is experienced when participation

in a family activity interferes with participation in a competing work activity or when

family stress has a negative effect on performance in the work role.

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Kanaga Lakshmi and Nirmala Devi (2003) conducted a survey of 210

workers from five companies belonging to textile manufacturing industry in

Tirunelveli, Tamil Nadu. They showed that the workers of the manufacturing

industries have significant relationship with the work related factors of working

environment, welfare measures, safety measures, supervision measures, participation

in decision making and intercommunication. They concluded that “Insecurity of job

leads to discouragement, anxiety and even bitterness for negative perception of quality

of work life. Providing sittings, suitable restrooms, transport facilities to all the

employees may encourage them to work continuously in the same industry. Allowing

employees to participate in decision making make them to work enthusiastically and

give recognition to them in their work. Providing training in using safety measures

may build loyalty in their work. If the management provides permanent job, it will

definitely lead to good quality of work life. They had showed the results that textile

workers perceive significantly according to the demographic factors of age, income,

and education. Their finding supported the earlier findings by Haque (1992), Hossain

(1999), Rahman (1984), Hoque and Rahman (1999) but against the factors of

experience, wealth and family size which show no close relationship with the level of

perception on Quality of Work Life’.

Poornima (2003) had reported that Quality of Work Life programs could be

evaluated by the following six factors: 1.Fair compensation and job security, 2.

Employee health, 3. Personal and career growth opportunities, 4. Participative

management style and recognition, 5. Work-life balance and 6.Fun at workplace.”

Sariati et al. (2003) in their study of Singapore workers held that Work and

family are the two most important aspects of people’s lives and they often conflict.

The paper examined the nature of that conflict and its effects on managers. An

empirical survey was described, aimed at enhancing the understanding of the conflicts

that individuals' experience, soliciting views on how individuals’ challenge/balance

work and family life. This showed that, although most of the respondents would trade

some earnings for family time, job related issues involving security, flexible working

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hours and high profile are valued ahead of leisure activities, but at a cost of

behaviour-based, time-based and strain-based conflicts in that order.

Helen and Jasmine (2003) conducted a study on women in the Australian

construction industry to examine the relationship between career, family and work

environment variables on women’s organizational commitment. They had chosen a

sample of 300 women and found that Career choice commitment, satisfaction with

career progression, job involvement, supervisory support and perception of the

organizational diversity climate were significantly correlated with respondents’

organizational commitment. The demographic or family variables were not correlated

with organizational commitment. The organizational commitment did not differ

significantly between women with dependent children and childless women or women

with non-dependent children. It was concluded that construction firms aimed to

improve organizational commitment among female employees and should ensure

women have access to career development opportunities and ensure just processes are

used in allocating organizational rewards. This helped the researcher to choose

organization commitment as a variable when conducting a study on work life conflict.

Noraini (2003) carried out a study to test an exploratory model consisting of

three sets of variables (demographic, personality and work- and family-related

variables) in the prediction of well-being of an individual. The model also provided a

test of the indirect effect of these variables on well-being, via perceptions of work-

family conflict. They took a sample of 147 employed British women with children,

the results showed that these three sets of variables had both direct and indirect

influence on well-being. Although work-related variables explained the most variance

in the prediction of work interfering with family conflict and job satisfaction,

personality variables accounted for the most variance in the prediction of family-

interfering-with-work conflict. The proposed model appears to provide a better fit of

the complex relationships that may exist between the many variables encompassing

women's work and family lives than previous ones that have considered only one set

of variables.

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Sussanna et al. (2003) has discussed in their study the current status of Hong

Kong professional women and the difficulties and conflicts they encounter in

combining home and work roles. The study by means of an in-depth interview

examined their feelings towards their personal and professional lives. The respondents

were satisfied with both job and family life and they accepted their traditional social

roles. The study also suggested that Managers should become more aware of both the

psychological stresses on their female employees and the nature of the balancing act

between life and work that they have to perform so as to gain competitive advantage

by attracting and retaining qualified women in the workforce.

Drew et al. (2003) male senior managers are finding it difficult to achieve

their desirable work-life balance due to developments in information technology

which mean senior managers can be expected to be “on call” at almost any time of the

day or weekend. They also found that all of the senior managers they interviewed

were opposed to the idea of working from home because they thought this would be

required in addition to their already lengthy office work schedule.

Wentling, R.M. (2003) his shown that the twin roles of women cause tension

and conflict due to social structure. In this study on working women in Delhi, it is

shown that traditional authoritarian set up of Hindu social structure continues to be

the same and hence women face problem of role conflict and it is suggested that

change in attitudes of men and women according to the situation can help to

overcome their problem.

Pocock (2003) has nicely explained the work/life collision theory in which

he argued that the ever-increasing working hours leave the individuals with less time

for themselves, and to pursue his hobbies or leisure activities. This hinders the growth

of the person as an individual in terms of his personal and spiritual growth.

Judy de Villiers and ElizeKotze (2003) found that work-life balance is

a personal issue that varies across time and situations and the underlying conflict

experienced pertains to role overload and role interference. The most significant

work-life conflict arises from complex workplace issues, including managing change,

supervisory and technical competences, leadership, roles and accountabilities, and

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culture. The results suggest that leadership, supervisor/manager recognition and

support for individuals and their needs, influence work-life balance and work life

balance can be improved by nurturing individual balance-enabling skills as well as

developing organizational balance-supportive capabilities.

Fisher and Layte (2003) consider three distinct sets of measures of work-

life balance, viz. proportion of free time, the overlap of work and other dimensions of

life, and the time spent with other people.

Amha and Ademassie (2004) believed that more than half of all women

entrepreneurs in Ethiopia face gender-related challenges to establishing, operating and

expanding their entrepreneurial activities.

Lingard and Lin (2004) studied 109 females and showed that women in

the construction sector valued work-life balance policies because of the transparency

and support and felt more commitment to such employers. They found that

participants did not perceive construction careers as compatible with family life and

felt forced to choose between work and family. Organizational commitment to work

life balance was found to be a determinant of employee turnover, motivation and

productivity for females.

Mattis (2004) ascertained the reasons for starting own business as

childcare obligations; participation in community affairs; personal health concerns;

elder care; and other family obligations and caring for family is a strong driver for

women to become self-employed. It is suggested that many female owned and

managed SMEs may operate with the primary purpose of fulfilling the SME owner-

manager’s personal needs.

Liz Doherty (2004) research conducted in the UK hospitality industry to

explore the effectiveness of work-life balance initiatives in helping women progress

to senior management. This research suggests that it is unlikely that much progress

will be made in challenging the long hour’s culture until senior male managers are

prepared to take a greater role in family responsibilities and participate actively in the

challenge. Only then will the social costs of parenthood be shared more equally

between men and women and more weight brought to the case for humanizing

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managerial hours for everyone. These are pointers that there are gender differences in

coping with work family issues.

Adam and Amie (2004) conducted a laboratory study examining the effect of

a family conflict with work on performance appraisal ratings given to men and

women. They found that the experience of a family conflict was associated with lower

performance ratings, and sex moderated this relationship. They also found that men

who experienced a family conflict received lower overall performance ratings and

lower reward recommendations than men who did not, whereas ratings of women

were unaffected by the experience of a family conflict. The sex bias was not evident

when performance was evaluated on the more specific dimension of planning.

Implications for future research lies in this study as more research needs to examine

the effects of work family conflict on performance appraisals.

Carnicer et al. (2004) conducted a study in a Southern European country on

work-life conflict using quantitative methodology, i.e. questionnaire. The sample was

composed of 1,182 Spanish employees located in Aragon. Bivariate analysis was

applied to test the relationships between the antecedents, followed by multivariate

regression analysis to analyse the significant level of antecedents in work-life conflict.

The findings suggested that the two groups of factors are antecedents of work-life

conflict. Although gender was not a determinant factor of conflict, however, some

differences were noted between men and women’s work-family conflict. In addition,

family perceptions, such as the importance of family, job mental, physical

requirements, job flexibility and gender roles had a strong effect on work-life conflict.

Educational level and Functional mobility were antecedents of work-life conflict also.

Their findings revealed that social benefits and job status did not affect work-life

conflict.

Ulla Kinnunen et al.(2004) in their study produced new knowledge about

gender differences with respect to work-to-family conflict and its longitudinal relation

with indicators of satisfaction and well-being. The study examined the longitudinal

relations between work-to-family conflict and self-reported satisfaction and well-

being in the domains of work (job satisfaction), family (marital satisfaction, parental

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distress) as well as overall (psychological and physical) symptoms. Data were

obtained from a random sample of 208 Finnish men and 218 women who were

employed and had either a partner or/and children. A survey was conducted at two

points in time, in 1999 (Time 1), and one year later, in 2000 (Time 2). The results

revealed that, among women, work-to-family conflict perceived at Time 1

significantly predicted job dissatisfaction, parental distress as well as psychological

symptoms at Time 2. However, among men, a low level of satisfaction or well-being

at Time 1 (marital dissatisfaction, parental distress, psychological and physical

symptoms) functioned as a precursor of work-to-family conflict perceived at Time 2.

In addition, the experience of work-to-family conflict turned out to be relatively stable

for both genders over the time period of one year. Hence this research predicts that

work to family conflict will continue to affect employees and could be taken up for

research frequently to help individuals and organizations to cope up with this conflict.

Simpson et al. (2004) explored the career development of 221 female MBA

graduates in UK and 225 MBA graduates in Canada along with the types of career

obstacles they were subjected to in each milieu. The results of the studies from UK

and Canada were then compared under diverse groupings in order to highlight the

similarities and differences. The findings suggested that although women and men in

Canada had similar career profiles, UK men surpass their female counterpart after.

They found that UK women run into added thorny career obstacles in the form of

negative attitudes and chauvinism.

Sheri Todd (2004), in her ‘Improving Work-Life Balance-What are other

countries doing?’ says that there is no ‘one size fits all’ approach to improving work

life balance. According to her, “The Government of U.K. seeks promotional

activities and workers’ voluntary involvement programs. In contrast, Denmark and

Sweden both have a strong history of social and family policy focused on the well-

being of citizens. The Governments of the U.K., New Zealand and Australia have

developed promotional programs … Ireland’s proclamation of a “Work-life Balance

Day’ and the U.S. resolution to create a ‘Work and Family Month’ are also ways

governments are raising the importance of Work-life Balance.” All these show that

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European countries provide benefits to all the citizens and workers and Quality of

Work Life is well established there.

Alicia et al. (2005) had researched that Job satisfaction is one of the most

frequently studied outcomes in the work–family conflict literature. Work interfering

with Family was related to job satisfaction cross –sectionally for men and women and

this effect existed beyond negative mood, job autonomy and monotony and Family

interfering with work. The fact that WIF predicted job satisfaction for women beyond

affective and job characteristic variables, over time, and with non-self-reported

measures, provides more confidence in this directional relationship than could

previously be assumed.

Byron (2005) completed a meta-analytic review of work-family conflict and

its antecedents, in which she explored several variables related to work-family

conflict. After reviewing 61 studies, Byron examined specific relationships between

work-family conflict and support variables. Of the 61 studies included in the meta-

analysis, 17 explored the relationship between work-family conflict and work support,

resulting in a total of 4,165 subjects. Meta-analytic results suggest a significant

relationship between work-family conflict and work support (r = -.19) as well as

between family-work conflict and work support (r = -.12). Several studies included in

Bryon’s meta-analysis also explored the relationship between work-family conflict

and family support. Aggregate results, including 14 studies, for a total sample size of

2,886, revealed a significant relationship between work-family conflict and family

support (r = -.11), as well as between family-work conflict and family support (r = -

.17). These results suggest that an individual’s level of work/family conflict decreases

as support from the work and family domains increase.

Roopali Johri (2005) studied that the elements that are relevant to an

individual's quality of work life include the task, the physical work environment,

social environment within the organization, administrative system and relationship

between life on and off the job. Quality of Work Life consisted of opportunities for

active involvement in group working arrangements or problem solving that are of

mutual benefit to employees or employers, based on labour-management cooperation.

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People also conceive of Quality of Work Life as a set of methods, such as autonomous

work groups, job enrichment and high-involvement aimed at boosting the satisfaction

and productivity of worker. Thus, Quality of Work Life was a comprehensive

construct that includes an individual's job-related well-being and the extent to which

work experiences are rewarding, fulfilling and devoid of stress and other negative

personal consequences.

Jeanette et al. (2005) in their study on faculty participants examined the

individual, additive and interactive effects of employee gender and two organisational

climate variables on employee ratings of role conflict, work-family conflict, family-

work conflict and time-energy imbalance. The study indicated that women report

greater role conflict and work-family conflict than men while spousal employment

showed no effect on individual perceptions of conflict. Results also showed that

perceived increase in work demands have perceived negative effects on employee

well-being. The results highlight the important role that organisational climate

variables play in our understanding of the work-family interface.

Rafael and Enrique (2005) analysed the effect of job satisfaction as an

indicator of quality of work. They studied job satisfaction in 23 countries including

Denmark, Norway, and Spain and found that ‘the variability of job satisfaction is

surprisingly low and bears no relation to any relevant social or economic variable.’

This is true both at aggregate level and at individual level. They used income, team

work, and type of contract, public or private sector, length of service, social class and

size of the work place as indicators of job quality indicators and age, gender,

education and experience of unemployment as indications of job expectations. Thus

the effect of job satisfaction as an indicator of quality of work is the same in almost all

the countries.

Wilson (2005) explored how women acknowledge the notion that they were

receiving dissimilar and disparate handling in appraisal at two British Universities.

The author used In-depth interviews and randomly selected 30 women from the total

female academic interrelated community at each university. The first part of the

analysis entailed creating a sequence of analytical tables which condensed factual

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information. The second part entailed listening to each interview to look for

statements with respect to equality and differences. The results demonstrated that,

even though women did not perceive themselves as being different, men perceived

them as having uncommon and lower qualities. Women were seen as “other” when

appraised against the values and norms established by men. This prompted the

researcher to develop a Questionnaire with details about their treatment in work

environment with regard to men.

Herta Toth (2005) analysed the gendered nature of work-life

balance dilemmas based on in Hungary. The results reveal that men and women have

different perceptions of work-life balance and adopt different coping strategies to

manage work and family commitments. Overall it is found that work-life balance is

constructed as an individual, rather than a corporate responsibility and this also

creates gendered inequalities and it suggests ways in which family- friendly initiatives

can be introduced within the Hungarian organizational context.

Metcalfe and Afanassieva (2005) found that women managers did not

want to compromise on their family roles. The unavoidable difficulties in trying to

achieve this balance were interpreted as personal failures, thus frustration; stress and

guilt feelings were often recalled in their stories.

Byron (2005) argues that family-interfering-with-work (FIW – family

issues impacting upon the work domain) and work-interfering-with-family (WIF –

work issues impacting upon the family domain) have different antecedents, namely

that work variables tend to be associated with WIF and non-work variables with FIW,

and therefore studies should take account of both types of conflict/interference.

Eileen Drew, Eamonn M. Murtagh (2005) examined the experience

of, and attitudes towards, work-life balance (WLB) by female and male senior

managers in a major Irish organisation. The study found that the greatest obstacle to

achieving WLB is seen as the “long hours” culture in which availing one of flexible

option is incompatible with holding a senior management post. Many of the senior

men have followed the “breadwinner” model by being able to delegate family and

caring activities to their wives. This option has not been possible for the majority of

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women in senior posts. Hence, men seek WLB to resolve commuting/working time

issues and women want to avail themselves of more flexible arrangements.

Imada and Ikeda (2006) observed that the majority of younger women quit

their jobs during pregnancy. Therefore, supporting job continuity during pregnancy is

important. In addition, only the childcare-leave system had no effects on female

employee retention. Help from family and relatives and childcare centre use are

necessary.

Mesmer-Magnus and Viswesvaran (2006) conducted a meta-

analysis and concluded that having a family supportive work culture is actually more

important for WLB than having a number of WLB policies in existence. Negative

relationships between WFC and supervisor support, co-worker support and work

family culture were identified. They conclude that two components contribute to a

Family Friendly Working Environment (FFWE); firstly work family

programmers/policies/benefits e.g. flexible working, maternity leave, child care

vouchers etc, and secondly a family friendly culture: the flexibility and supportiveness

of managers and colleagues.

Babita Mathur-Helm (2006) examined the reality of the glass-ceiling

phenomenon in South Africa’s four major retail banks with women managers and

identified the growth barriers existing in their organizations, leading their women

workforce towards a glass ceiling. The results indicated that the glass ceiling

considered a myth by many was real and are nurtured by the organizational culture,

policies and strategies besides women’s own inadequacies and concluded that only

the most decentralized organizations, characterized by a culture that supports top

positions of women top positions, will help in breaking down the glass ceiling, along

with women’s own efforts to grow, develop and empower themselves through

academic and career development.

D. Jamali, et al. (2006), made a study to explore the salience of glass

ceiling type barriers in the Lebanese banking sector, based on the perceptions of a

sample of Lebanese top and middle level women managers from 12 different banks. It

is found that the common precepts of the glass ceiling theory were not supported in

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the context of Lebanese banks with overall positive inferences and perceptions

reported by Lebanese women managers in relation to their work environment and

daily work experiences. These findings were explained by the progressive evolution

of the Lebanese banking sector over the past few decades.

Hamilton et al. (2006) conducted a study to examine work-life conflict of

single women with no children. The data was retrieved from financial and health care

organizations. They used Quantitative analysis such as mean and descriptive statistics,

ANOVA, and chi-square in order to test the independent variables and the hypotheses

proposed. The results confirmed that non-married women with no children did suffer

conflict, especially work-to-life conflict. Moreover, the results indicated that benefits

related to work-life normally offered by associations were often considered less

crucial and utilized less frequently by single women with no children than by working

married women.

Oplakta (2006) conducted a study to examine the role of women holding

leadership positions and working in educational institutions in developed countries.

She thoroughly examined published researches relating to gender studies in education,

educational administration and comparative education in many peer-viewed and

refereed journals and concluded that there are still a number of specific impediments

to the development of the career of women in educational Institutions. Among the

listed impediments were low level of girl education, strong family responsibilities and

exclusive career encounters, high member of men compared to women faculty, and

the embracing of “asexual” leadership style by the small number of women holding

administrative positions in these countries.

Thanacoody and Jacobs (2006) investigated the Western and Indian cultural

situation of female academics to achieve a thorough comprehension of the causes

underlying their career development. The research took place at two different

universities with diverse cultures one being in Australia and the other in Mauritius.

Thirty women at diverse levels of academia were interviewed. The results

demonstrated that the impediments to advancement were astonishingly comparable in

both universities despite their diverse cultural background. In addition, women from

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both cultures confronted major obstacles to career development in their academic

positions. The researcher was able to understand the obstacles that women face in

their career development and was able to relate this to her study on women in

software industry.

Sandhu and Mehta (2006) studied the factors affecting the work-family

conflict among women executives in service sector in Punjab. Using factor analysis

and analysis of variance, their results indicate that women perceive gender role

attitude and spill over between work and family roles as the most important factors

affecting their career. The study revealed that the nature of organization and education

has a significant impact on work-family conflict, but marital status does not have any

influence on work-family conflict.

Dilek et al. (2006) in their study examined the extent to which work demands

(i.e., work overload, irregular work schedules, long hours of work, and overtime

work) were related to work-to-family conflict as well as life and job satisfaction of

nurses in Turkey. The role of supervisory support in the relationship among work

demands, work-to-family conflict, and satisfaction with job and life had been

investigated in their study. The variables were measured under four categories: work

demands, work support (i.e., supervisory support), work-to family conflict and its

outcomes (i.e., life and job satisfaction).The structural equation modelling results

showed that work overload and irregular work schedules were the significant

predictors of work-to-family conflict and that work-to-family conflict was associated

with lower job and life satisfaction. Moderated multiple regression analyses showed

that social support from the supervisor did not moderate the relationships among work

demands, work-to-family conflict, and satisfaction with job and life. Exploratory

analysis suggested that social support could be best conceptualized as the main effect

directly influencing work-to family conflict and job satisfaction. They had concluded

in their research that nurses’ psychological well – being and organizational attitudes

could be enhanced by rearranging work conditions to reduce excessive workload and

irregular work schedule. They added that leadership development programs should be

implemented to increase the instrumental and emotional support of the supervisors.

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Lilis and Tarmizi, (2006) made the largest Quality of Work Life

investigation of health care workers in Iran with 908 completed questionnaires

collected from employees at 15 hospitals. They used 30 variables to find satisfaction

with Quality of Work Life. The Nursing Work life Satisfaction survey results showed

that Pay and Autonomy were the two most important components of nurses’ quality of

work life. These results are similar to American hospitals where Pay and Autonomy

are usually ranked as most important’.

Rossi et al (2006) in their study had given that the concept of Quality of

Work Life was multi-dimensional but it may not be universal. The key concepts tend

to include job security, reward systems, pay and opportunity for growth among other

factors.”

Vanitha et al. (2006) has shown that organizational commitment and stress

among IT professionals was high and that gender and experience of the professionals

does not influence these factors.

Lois (2006) in his study has extended the theory to predict the effectiveness of

strategies for structurally reducing work–family conflict by manipulating roles, given

the salience of work and family roles and resources available to the female

entrepreneur. He developed a conceptual framework based on the constructs of role

involvement and role conflict to examine whether high-growth female entrepreneurs

choose more appropriate strategies for reducing work–family conflict than their less

successful counterparts. He discussed about three basic strategies for manipulating

roles such as role elimination, role reduction and role sharing. He also discussed that

work family management strategies were a significant determinant of venture growth

which helps them to reduce work – family conflict by choosing strategies better

matched with their internal needs.

Hamilton et al. (2006) conducted a study to examine work-life conflict of

single women with no children. The data was retrieved from financial and health care

organizations. Using Quantitative analysis such as mean and descriptive statistics,

ANOVA, and chi-square in order to test the independent variables and the hypotheses

89

proposed. The results confirmed that non-married women with no children did suffer

conflict, especially work-to-life conflict. Moreover, the results indicated that benefits

related to work-life normally offered by associations are often considered less crucial

and utilized less frequently by single women with no children than by working

married women.

Oplakta (2006) conducted a study to examine the role of women holding

leadership positions and working in educational institutions in developed countries.

She thoroughly examined published researches relating to gender studies in education,

educational administration and comparative education in many peer-viewed and

refereed journals and concluded that there were still a number of specific impediments

to the development of the careers of women in educational Institutions. Among the

listed impediments were low levels of girl education, strong family responsibilities,

and exclusive career encounters, high member of men compared to women faculty,

and the embracing of “asexual” leadership style by the small number of women

holding administrative positions in these countries.

Cinnamon (2006) explored the relationship between work-family conflict,

self-efficacy, gender, and family background. Of most interest to this study, the

researcher posited a negative relationships between work-family conflict and work-

family conflict self-efficacy. Additionally, she hypothesized that women would

experience lower levels of work-family conflict self-efficacy. Participants were 358

unmarried students, ranging in age from 19 to 29 (M = 26.5, SD = 2.30 years). The

sample was composed of 145 men and 213 women. Sixty-percent of participants

worked in on campus student jobs or work-study positions (M = 19.14 hours per

week, SD = 7.40). Results supported the hypothesized relationship between work-

family conflict and work-family conflict self-efficacy. Negative correlations emerged

between work-family conflict and work-family conflict self-efficacy (r = -.38, p =

.001), as well as between family-work conflict and work/family conflict self-efficacy

(r = -.33, p = .001). As was hypothesized, there were significant gender differences

with regard to levels of Work-family conflict self-efficacy. More specifically, male

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participants reported significantly higher levels of family-work conflict, self-efficacy

than did women.

Perrone et al. (2006) explored the relationship between work-family conflict,

commitment, coping, and satisfaction. Participants included 40 male and 114 female

college graduates. All of the participants were employed outside the home and were

married. Twenty-three percent of the participants had no children, 16% had one child,

37% had two children, 17% had three children, and 7% had four or more children.

Participants completed measures of work and family commitment, work-family

conflict, coping, work satisfaction, and family satisfaction. Results suggested that

work-family conflict and family satisfaction were significantly negatively correlated

(r = -.24). The researchers did not report the correlation coefficient for the

relationship between work/family conflict and work satisfaction. Additionally, it was

not clear whether work-family conflict was explored using both directions (work-

family and family-work conflict).

Victor and Thavakumar (2006) studied the work-life conflict among married

women employees in banking sector. The data was collected from 100 married

women in private and public Banks. The extent of work characteristics and family

characteristics influencing work-family conflict was analysed in the research. They

found that there was a greater need for spousal support, flexible work schedule, child

care centres, and family support in order to alleviate work-family conflict.

Jeff Hyman, Juliette Summers (2007) assessed the influence of different

forms of organizational representation on the provision of work-life balance

employment policies. The study found that employees do influence work-life balance

issues in the financial services sector, and work-life balance initiatives had greater

breadth, codification and quality where independent unions were recognized. It

demonstrates that organizations and unions need to retain and develop a focus on

work-life balance applications.

John Burgess, Lindy Henderson, Glenda Strachan, (2007) assessed the

ability of formal equal employment opportunity (EEO) programmes and workplace

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agreement making to facilitate work and family balance for women workers in

Australia. The study found that Formal EEO programmes and agreement making are

limited in their ability to promote work and family- friendly arrangements at the

workplace. Informal arrangements and managerial discretion are important in

realizing work and care balance and concluded that formal mechanisms cannot

achieve work and care reconciliation for women workers if they are built upon very

limited minimum requirements, are voluntary and are dependent upon a bargaining

process at the workplace.

Silva et al. (2007) in their study reported the results of 248 survey

questionnaires and 26 interviews with full-time and part-time female faculty members

at a Lebanese Higher Education Institution. The researchers focused on working

women at a Lebanese higher educational Institution to assess the origins and the

impact of their work-life conflict in their careers and family. This research’s aim was

to determine the effect of the independent variables marital status, having children,

having dependents, years of experience and status in an organization on work-conflict

and home-conflict (the dependent variables). The work conflict was affected

positively by the marital status, the years of experience and the position in the

organization. The participants described the University as a good institution to work

for and saw themselves as privileged since the University does not discriminate

against women and allowed them to achieve higher and leadership positions.

Kelly and Robert (2007) in their research project presented and tested an

integrative conceptual model of work-family balance which included the predictors

and consequences of work-family conflict and work-family enrichment. The

predictors in their study included work-family conflict, self-efficacy and support,

while the dependent variable was domain satisfaction. Work-family balance could be

thought of as an individual’s overall experiences related to the interface between work

and family related roles, tasks, and responsibilities. In their study work-family balance

was represented by the relationship between work-family conflict and work-family

enrichment. Participants for their study included 161 women who were employed

either part- or full-time, were in a heterosexual marriage, and had a least one child

under the age of 18 living at home. Path analysis was used to test the model of work-

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family balance. Two basic variations of the model of work-family balance were

tested. First, a mediated model, which implied that the relations of support and self-

efficacy to work and family satisfaction was mediated by the conflict and enrichment

variables and was tested. Second, a direct effects model was tested.

Ford et.al. (2007) in his meta-analysis examined the relations among

stressors, involvement, and support in the work and family domains, work-family

conflict, and satisfaction outside of those domains. The results suggested that a

considerable amount of variability in family satisfaction was explained by work

domain-specific variables, whereas a considerable amount of variability in job

satisfaction was explained by family domain-specific variables, with job and family

stress having the strongest effects on work-family conflict and cross-domain

satisfaction. This research has aided the researcher towards future directions for

research on work and family issues focusing on other explanatory mechanisms and

moderators of cross-domain relations.

Anne Gronlund (2007) conducted a research on 800 Swedish employees and

showed that job demands spill over negatively into family life, while job control

reduces work to family conflict. They reported that the quantity of work and quality

of work was important in the job control demand control model. They also reported

that women in jobs with high demands and high control do not experience more

work to family than men even when working the same hours.

Charles et al. (2007) examined the work-family role conflict experienced by

female managers and the variables affecting this conflict. The sample was drawn from

633 women respondents. Regression analysis showed that women with higher family

role salience and long work hours experienced highest levels of work-life conflict.

Women with highest levels of job satisfaction and family satisfaction showed lower

levels of work-family conflict.

Jennings and McDougald (2007) found that female entrepreneurs are more

likely to make accommodations within the work sphere rather than the family domain.

Jennings and McDougald also suggest female entrepreneurs are prone to greater

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levels of work-family conflict as a consequence of gendered role expectations and

they priorities elder care and to scale back their business involvement.

Caroline Straub (2007) analyzed the work-life balance practices and policies

in 14 European countries, and to test whether these practices actually enhance the

career advancement of women to senior management positions. And it is found that

there are certain differences in the provision of work-life balance practices and

women’s participation in the labour force among European companies. A positive

influence of work-life balance policies and practices on women’s career advancement

into senior management positions was confirmed in only one case – the payment of an

additional amount for maternity leave.

Fiona Moore (2007) clearly demonstrates that workers and managers have

quite different issues and needs when it comes to work-life balance. The managers

focus more on achieving status and the workers on personal satisfaction. The findings

challenge assertions that “flexible” working practices are good for work-life balance,

that managers are better able to maintain a good work-life balance than workers, and

that the development of an appropriate work-life balance policy assists in ensuring

company loyalty and positive attitudes to work.

Meghna Virick et al., (2007) examine how increased work overload of layoff

survivors relates to their work-life balance and job and life satisfaction. The study

examined work-life balance as a mediating mechanism through which role overload

exerts its influence on job and life satisfaction and it is found that layoff survivors

experience higher levels of workload which impact overall role overload that

negatively affects work-life balance and it is concluded that high workloads

experienced by layoff survivors contribute to reduced job and life satisfaction through

work-life balance as a mediating mechanism.

Wendy C. Marcinkus et al, (2007) analysed the relationship of a network of

social support for midlife women with their attitudes toward work-family balance and

work outcomes and indicated that the women generally received more personal social

support than work-based social support. Work-based social support was positively

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associated with job satisfaction, organizational commitment, and career

accomplishment; personal social support was also associated with job satisfaction and

organizational commitment. Midlife women can also get benefit by seeking and

accepting assistance from organizations, family, and friends, thereby ending attempts

to be a superwoman, who singly manages work and home responsibilities.

Ahmad and Aminah (2007) examined the work-family conflict experienced

by 239 married female production operators in dual-career families, the social support

they received and the coping strategies used to manage the conflict. The women

experienced more work interference with family than family interference with work.

The intensity of work interference with family was significantly higher in the earlier

life-cycle stage than in the later stage. About two thirds of the women indicated that

they intended to leave their job upon having another child, mainly due to the rising

cost of childcare services. They received the least social support from their

supervisors compared to other sources, and tended to cope with conflict using reactive

role behaviour and personal role redefinition strategies.

Gunavathy and Suganya (2007) in their study among married women

employees of BPO companies traced the causes, consequences of work life imbalance

and interventions for work life balance. The causes for work life imbalance were

classified as organizational and personal factors. The organizational factors included

work-related factors, time-related factors and relationship-related factors. The

personal factors included lack of family support, marital conflicts and frequent change

in sleeping patterns. According to the study, the three main consequences of work-life

imbalance were stress and burnout, ill-health and poor work performance. The

respondents also experienced guilt of not being able to spend time with family,

anxiety about poor performance, displacement of negative emotions on family

members and on co-workers.

Dilek and Zeynep (2008) conducted a questionnaire survey on the Nurses

work demands and their work-life conflict. They examined the extent to which work

demands (i.e., work overload, irregular work schedules, long hours of work, and

overtime work) were related to work-to-family conflict as well as life and job

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satisfaction of nurses in Turkey. The role of supervisory support in the relationship

among work demands, work-to-family conflict, and satisfaction with job and life was

also investigated. The sample was comprised of 243 participants: 106 academic

nurses (43.6%) and 137 clinical nurses (56.4%). All of the respondents were female.

The research instrument was a questionnaire comprising nine parts. The variables

were measured under four categories: work demands, work support (i.e., supervisory

support), work-family conflict and its outcomes (i.e., life and job satisfaction).

Results: The structural equation modeling results showed that work overload

and irregular work schedules were the significant predictors of work-to-family

conflict and that work-to-family conflict was associated with lower job and life

satisfaction. Moderated multiple regression analyses showed that social support from

the supervisor did not moderate the relationships among work demands, work-to-

family conflict, and satisfaction with job and life. Exploratory analyses suggested that

social support could be best conceptualized as the main effect directly influencing

work-to family conflict and job satisfaction. They concluded that Nurses’

psychological well-being and organizational attitudes could be enhanced by

rearranging work conditions to reduce excessive workload and irregular work

schedule. Also, leadership development programs should be implemented to increase

the instrumental and emotional support of the supervisors.

Leila Karimi (2008) in her study aimed at examining gender differences in

the experience of Work-family interference and perceived job–life satisfaction in a

group of Iranian employees. The participants in the study consisted of 387 Iranian

male and female employees from a variety of organizations. The results of t tests and

multiple regression analysis using EQS 6.1 support the hypothesis that Iranian male

and female employees experience similar interference in their work–family domains

although they spend different numbers of hours in the workplace. The findings also

showed that whereas work-to-family interference has significant and negative effects

on job–life satisfaction among male employees, for female employees, working hours

and family-to-work interference had even more significant and negative effects on

their job–life satisfaction.

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Elianne et al. (2008) examined whether cognitive appraisals regarding work–

family role combination can be influenced by providing informational support. They

conducted an experiment among 149 female employees with young children working

in a financial services organization. The results showed that the employees appraised

the task of combining their work and family roles more positively after exposure to an

expansion rather than a scarcity message. The research offered new theoretical

insights into the role of cognitive appraisal in work–family research and offered scope

for designing intervention programs that help employees to view role-combining more

positively.

Solamalai (2008) states ‘three broad types of work-life strategies have been

created to help employees balance their work and non-work lives: flexible work

options, specialized leave policies and dependent-care benefits.’

Les Worrall, Margaret Lindorff and Cary Cooper (2008) compared the

perception of UK managers and Australian (Victoria) managers about Quality of work

life (2008) by a survey. UK sample consisted of 1451 responses and Australian

sample consisted of 1283 responses. The samples were consistent respondents

consisting of different age, gender and work experiences. Forty percent of the UK

respondents were working in public sector as against 20.7 percent of the Australian

respondents. According to the authors, their health, social lives and personal

relationships were affected by the long hours they worked. They found out that the

Australian Managers were less authoritarian, less bureaucratic, more accessible and

more innovative than their UK equivalents. They also found out that in Australia, job

satisfaction was markedly higher, reciprocal trust was higher and respondents felt

more fairly treated. They were more likely to think that organizational change

improved their motivation, productivity, employee participation, well-being and

morale than their UK counterparts. They also found that UK public sector was

characterized by high levels of change and a considerable focus on cost reduction.

Thus this report shows that Australian managers generally have more positive views

about their organization and quality of work life than their counterparts in U.K. This

study was undertaken from the sample of managers from the two countries.

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Rajib Lochan Dhar (2008) conducted fifteen interviews with the drivers at

four different bus depots of Pune Municipal Transport. In his research findings from

the analyses of interviews he uncovers four main themes: a) work demands and

Quality of Work Life b) coping strategies to reduce stress c) organizational initiatives

to reduce stress and d) humor, team work and work life balance. According to the

study ‘the bus drivers were going through heavy amount of work stress causing

deterioration in their quality of life at work. Acute shortage of staff, deteriorating

conditions of the buses and bad roads were found to be the cause of this.

Saad, Samah and Juhdi (2008) in a study among the private higher

learning institutions in Malaysia, have collected information from 251 employees in a

private university about the perception on quality work life. Ten variables were

selected to measure Quality of Work Life and they were: support from organization,

work-family conflict, relationship with peers, self-competence, impact on job,

meaningfulness of job, optimism on organizational change, autonomy, access to

resources and time control. The study indicated that each of the variables is a salient

predictor of job satisfaction. Using multiple regressions, it was found out that

meaningfulness of job, optimism on organizational change and autonomy were

significantly related to job satisfaction and the other seven are found to have no

significant relationship with job satisfaction.

GunaSeelan and Manimunah Ismail (2008) have studied the work

condition and predictor of Quality of Work Life of Information system personnel in

Malaysia by conducting research on 453 IS personnel. ‘This study was based on

Karasek’s (1979) and Kristensens’s (1995) studies specifically to investigate the job

demand, control and support in relation to Quality of Work Life’. It is concluded that

IS personnel are enjoying their profession as they have substantial control and support

in their job although the nature of their job was demanding.

Sardzoska Elisaveta (2008) analysed 32 employees from trade enterprise

specialized for distribution of electronic apparatuses and devices, “E-trade.” The study

was based on Hertzberg’s theory. The factors of job satisfaction were the motivators

and causes of job dissatisfaction were the unfavourable hygiene factors specified by

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Hertzberg. The findings supported the well-known cognition that job satisfaction’s

data can replace measures of work life quality.

Justin Anthony (2008) while writing about the HR practices in Japan

conveys that pay increases based on age because as the age increases the experience

and the responsibility as a provider of security for the family also increase.

Foder and Redai (2008), in their ‘Difference between men and women in

work quality’ report that they identified small yet remarkable gender difference in

quality of work and people’s perception of their quality of work. According to them,

“women worked shorter hours than men and this was especially true for the more

developed economies as women’s relative work load seemed higher in Bulgaria,

Hungary and Portugal.” They also explored determinants of job satisfaction and

found that they were by and large similar for men and women. In their report in 2009

they state: “Both men’s and women’s quality of life is affected by their perceived

satisfaction with their jobs. Jobs which guarantee more autonomy, more support from

colleagues and supervisors less pressure in daily demands contribute to a happier life

for both genders”.

Sara J. Wilkinson (2008) study seeks to posit that it is vital to comprehend

the levels of awareness of work-life balance issues within the surveying profession.

The results showed reason to be both optimistic and pessimistic about work-life

balance within the Australian and New Zealand qualified surveying profession. In

terms of flexible working conditions most can work part time or remotely, take time

off in lieu but are unable to job share, work in term time, take a career break or work

compressed hours.

Skinner and Pocock (2008) investigated the relationship between work

overload, work schedule control, work hours and their fit with preferences and work-

life conflict among full- time employees. It was found that the strongest association

with work-life conflict was demonstrated by work overload, followed by work

schedule control, work hours and work hours fit. Time-based work life policies,

procedures and interventions were found necessary, but not sufficient, for addressing

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work-life conflict. They called for effective management of work overload to support

a healthy work-life relationship.

Margaret Deery (2008) analysed retention of good employees and the role

that work- life balance (WLB) issues have in an employee’s decision to stay or leave

an organization. The study also includes the need for minimum working hours, good

role models at the workplace , flexible working hours and arrangements, sound

recruitment and training opportunities and company family friendly work policies.

The recommendations are made to assist organizations to retain their talented staff

and to not only retain them but to provide a more holistic experience that includes a

balance between their work environment and their home life.

Lakshmipriya and Neena (2008) stated that a great number of women work

40-45 hours per week and 53 percent of those are striving to achieve work life

balance. Women consider their lives a juggling act that involves responsibilities at

work (such as heavy meeting schedules, business trips, etc.) and managing the routine

daily responsibilities of life and home. "Successfully achieving work/life balance will

ultimately create a more satisfied workforce that contributes to productivity and

success in the workplace".

Kreiner et al and Cohen et al. (2009) found that the women enacted a range

of specific tactics to manage challenges associated with elder care and business

ownership. These tactics appeared to be a critical vehicle through which the women

were able to exert control, reduce uncertainty and unpredictability, and where

necessary restore a sense of orderliness to the work- family interface.

Lhufrw (2009) indicated that there are some historical and cultural problems

as well as individual circumstances which make it difficult to combine work and

family life. The study conducted in Austria, Denmark and the UK with women found

that for balancing their work and life women take multiple roles as a complex

challenge. Women need support from their family help from their partners and

companies’ flexibility are identified as the most important things to reach a

satisfactory work-life balance. This study concluded that women have to invest

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considerable personal resources, such as time and energy in order to achieve a

satisfactory work life balance through their career life cycle. In addition, it is

suggested that a satisfied work-life balance has a positive impact on work

performance.

Knud Knudsen (2009) analysed a large survey of Norwegian managers of

men and women to explore how male and female managers may regulate their

workload differently in response to conflicting job-home pressures. The study

investigated this postulated link between managers gender and work-family conflict

via their workload, based on a conceptual model. It is found that female managers

have a lighter workload, more frequently perceive glass ceiling constraints and less

often experience work-family conflict.

Rachel (2009) conceptualized career development in a cultural and contextual

framework and examined gender differences between role salience and work-family

conflict (WFC) among Jewish and Arab female teachers from central Israel. The

contribution of social support to women’s conflict was also examined. Results

highlighted various differences in contrast to expectations, Jewish teacher’s

demonstrated higher spouse and parent values than Arab teachers, who demonstrated

higher work values and work commitment. Jewish women reported higher levels of

WFC compared to their Arab colleagues. Support systems in Jewish culture were

related to lower WFC but not in Arab culture. Theoretical and practical implications

emphasize the need for culture-sensitive models of work–family relations and for

career counselling interventions.

Jacqueline (2009) in her study considered the relationship between

perfectionism and perceptions of work- family conflict. Participants were 288

working adults with family obligations (178 women, 109 men, and 1 unspecified)

recruited by undergraduate students enrolled in psychology courses in a Midwestern

American university. A situational component to perfectionism was found, with

higher standards and a higher perceived discrepancy between standards and

performance at home versus at work. Findings suggested perfectionism predicts work-

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family conflict, beyond the effects of the trait affectivity and achievement. The

findings indicated those with adaptive perfectionism ( work and home) tend to have

lower strain and time-based family interfering with work and lower behaviour-based

work interfering with family, compared with maladaptive perfectionists (home) and

non-perfectionists(work and home). Gender differences were found and considered in

a more exploratory manner.

Lyn and Pooja (2009) investigated how work–family balance and the gender

division of labour differ according to whether children are in early childhood, middle

childhood or the early teen years. It uses measures of both behaviour and attitudes,

drawing on two nationally representative Australian data sets, the Bureau of Statistics

Time Use Survey and the Household Income and Labour Dynamics in Australia.

Women have more responsibility for care than men, but with older children there is

greater gender equity in the division of labour, a less pressing domestic burden and

less maternal time stress. This occurs because women recalibrate their commitments

to work and home, not because domestic labour is redistributed between mothers and

fathers. Further, it does not hold if women replace unpaid with paid labour; mothers

who work full time have high total workloads and high stress levels regardless of the

age of children. Fathers are more satisfied with their work–family balance the more

they participate in childcare and the more they feel supported by their workplace to

access family-friendly work policies.

Leila (2009) in her study examined gender differences in the experience of

Work-family interference and perceived job-life satisfaction in a group of Iranian

employees. The participants in the study consist of 387 Iranian male and female

employees from a variety of organizations. The results of t tests and multiple

regression analysis using EQS 6.1 support the hypothesis that Iranian male and female

employees experience similar interference in their work–family domains although

they spend different numbers of hours in the workplace. The findings also showed

that whereas work-to-family interference has significant and negative effects on job-

life satisfaction among male employees, for female employees, working hours and

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family-to-work interference had even more significant and negative effects on their

job–life satisfaction.

Jenny (2009) examined one potential reason for the persistence of the glass

ceiling: bosses perceptions of female subordinates’ family-work conflict. Person

categorization and social role theories were used to examine whether bosses (both

male and female) perceive women as having greater family-work conflict and

therefore view them as mismatched to their organizations and jobs. The results

supported their model: bosses perceptions of family-work conflict mediated the

relationships between subordinate sex and perceptions of person organization fit,

person-job fit, and performance. Both types of fit were related to promotability

(nomination for promotion and manager assessed promotability).

Subburethinaet al. (2009) had undertaken a study among 239 college

teachers in Tiruchirappalli, India to find the impact of Quality of Work Life. They

researched the effect of independent demographic variables on two dependent

variables namely, perceived level of overall Quality of Work Life and the overall

quality in teaching environment. They found out that there is no significant

difference between the perceived level of Quality of Work Life and gender, type of

family, age, designation, type of college, income, native place and length of service

(experience) of the respondents. When comparing the overall quality in teaching

environment, there is significant difference between gender, age, type of college,

native place and length of service.

Karthikeyan (2009) made a study and found out that older employees were

more satisfied on the work environment dimension compared to the younger

generation employees.

Zohurul Islam and Sununta (2009) in Dhaka Export Processing zone,

made a study with 216 respondents in different non-managerial level jobs of

different industries (maximum from textile industries). They checked the

organizational performance and Quality of Work Life and found that Quality of

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Work Life is positively related to job satisfaction and employee job satisfaction is

positively related to organizational performance.

Indira Kandasamy and AncheriSreekumar (2009) developed a model in

their research that has two dimensions namely expectations of work life attribute and

perceptions of work life attribute which is given below:

This model drew attention to the difference between the expectation and the

perception on various Quality of Work Life dimensions. The scores for the two

dimensions were assessed by statements pertaining to them and the quality of

particular work life dimension (QDi) was found to be depending on the total

difference between the perception (Pij) and expectation (Eij) scores of the attributes.

Julia Connell and ZeenobiyahHannif (2009), in their research to seek the

variance between call centres in the outsourced, public and private sectors have

formulated a model for QWL. They found that the public sector Call centres were

found to be inferior in terms of job content, working hours and managerial style and

strategies to the private sector call centres. Conversely the sales plus features a

management model that is more akin to what would be expected in a Call centre

operating under professional service model.

Rajeswara Rao and Bakkappa (2009) in their modeling approach on

Quality of Work Life in call centre industries, observe that ‘Quality of Work Life is

influenced by organizational perception, provisions, health and opportunity’ and

proposed a model using optimization techniques.

Warner and Hausdorf (2009) had conducted a study on 207 health care

workers over 90 % of whom were women and they suggested that organization and

supervisor support for work-life issues can best be conceptualized as antecedents to

job stressors (e.g., work overload), which subsequently reduce work-to-family

conflict. They found that work overload was positively related to work-to-family

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conflict and partially mediated the relationship between organization support for

work-life issues and work-to-family conflict.

Higgins et al. (2010) found that family demands were a stronger predictor of

role overload for women than men, and that when women felt overloaded and

stressed, they used coping strategies, such as seeking support and scaling back their

efforts, more than men. Despite their propensity to use coping strategies, women had

higher levels of overload and stress than men even though their work demands were

less, and family demands were the same. They also found that family demands were

a stronger predictor of role overload for women than men, and that when women felt

overloaded and stressed, they used coping strategies, such as seeking support and

scaling back their efforts, more than men. Despite their propensity to use coping

strategies, women had higher levels of overload and stress than men even though their

work demands were less and family demands were the same.

Abdul and Roshan (2010) studied the causes, consequences and correlated

the Work-family conflict among dual career women in Kashmir Valley. They

analysed the data using simple average scoring scale, chi- square tests and ranking

methods. They attempted to study the causes, consequences and correlates of work-

family conflicts among dual-career women. The study examined if the working

women were able to combine their work and family, and identify the constraints they

faced and the family and organizational support they received in the process. The

study also examined the strategies that working women adopt to contain the stresses

of contradictory and competing dual role demands. The sources of conflict are

dependent on the availability of various support systems within and outside the family

as well as the organization where she worked.

They found that despite obstacles a satisfying balance between work and

family life was achievable. However they did not study the factors responsible for the

role conflict situations. Another limitation of their research is heterogeneity of the

sample as educational institutions and the government offices were also included in

the sample in which the work-family conflict issues were distinctly different from the

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private business organizations. This study enabled the researcher to concentrate on

one single industry to study the work-life conflict of women.

Robert et al. (2010) in their study examined the work-family conflict

approach to the turnover intentions of highly educated male and female employees

within the hospitality industry. The results showed that work-family conflict and

organizational support could explain a substantial amount of variance among highly

educated employees regarding their intention to leave an organization. This study also

found that for men work-family conflict could be explained by lack of organizational

support, while for women work-family conflict could be explained both by

dissatisfaction with workplace flexibility and lack of organizational support. In

addition, with regard to women, the study had shown that organizational support has a

moderating effect on the relation between workplace flexibility and work-family

conflict. The study suggested that maintaining a good organizational climate and

offering the possibility of flexible work hours to improve the balance between work

and family were important factors when it came to retaining highly educated staff.

Peng et al. (2010) examined the relationships between two types of work–

family conflict (work interfering with family [WIF] and family interfering with work

[FIW]), job-related self-efficacy, work satisfaction, and supervisor satisfaction in

China and India. The author in their analysis compared men and women and

important differences that existed between them. Their results showed that FIW was

negatively associated with self-efficacy. WIF was negatively associated with work

satisfaction. The relationships between WIF and work satisfaction and between FIW

and self-efficacy were more negative for women than for men. They found no

significant differences in any of the relationship between China and India.

Melien et al. (2010) in their study used bidirectional interrole conflict

measures to examine the permeability of work and family domains, and to further

investigate the relationships of work–family conflict with business and marriage

outcomes in copreneurial women. Analytical results from 202 Taiwanese copreneurial

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women were summarized as follows:(1) Family boundaries were more permeable

than work domains; (2) Work–family conflict was negatively related to perceived

business success and marriage satisfaction and (3) work-to-family conflict predicts

marriage satisfaction, whereas family-to-work conflict predicts perceived business

success.

Estryn et al. (2010) in their study had pointed out that France encountered difficulty

attracting physicians to work in hospitals. They found that conflict at work and at

home may be at the heart of the problem for female as well as for male physicians.

They distributed an online questionnaire to 1924 Physicians and analysed the risk

factors for burnout and intent to leave the profession. According to 41.3% of female

physicians their profession was an obstacle to having children and major factors

which contributed to their burnout were Effort/ reward imbalance, work-family

conflicts and low quality of team work. They found that excessive job demands were

linked with burnout and with work-family conflicts found it difficult to organise one’s

life in order to have and raise children. Potential solutions included facilitating

teamwork in order to reduce departure which increase workload on those who stay

increasing their work-family conflict.

Anne and Redouane (2010) investigated the effect of family-friendly

practices (FFPs) on organizational attractiveness. Using a policy-capturing research

design, they tested the distinct effect of four FFPs (i.e., on-site child care; generous

personal leaves; flexible scheduling; and teleworking) on applicant attraction. They

also tested the effect of organizational reputation and candidates’ desire for

segmentation. Their results indicate that FFPs do have a main effect on attractiveness.

More specifically, the two scenarios that received the highest scores on attractiveness

were personal leaves and flexible scheduling. Corporate reputation does have a

significant main effect of attractiveness. They had concluded that implementing even

one practice increases the likelihood of attracting candidates and hence organizations

facing labour shortage should consider offering opportunities to reduce Work- Family

Conflict.

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Artemis et al. (2010) in their study reviewed methodological choices

(sampling frames, constructs investigated and measures used) in 245 empirical work-

life balance papers published in a range of discipline-based peer-reviewed journals

between 1987 and 2006. Their results showed that work-life balance studies need to

establish greater consistency between the conceptualization of constructs and the

operationalization of measures. They had given in their study that there was also

scope for well-designed field experiments to establish clear causal relationships

between variables. They had added that sampling choice in previous literature was

somewhat constrained and may be enhanced by targeting single and same-sex parent

families, manual and lower skilled service workers, and employees providing

eldercare. They added that researchers should also be more transparent in providing

rationales for their choices of organizations or group lists used to target respondents.

Their findings have significant implications for understanding, interpreting, and

utilizing the contemporary work and family literature.

Donna (2010) conducted a comparative study on changes in the Canadian and

Australian non-profit social services sector (NPSS). Drawing on qualitative interview

data, the article explored the links between social and industrial relations policy and

the strategies women employed in the NPSS to balance work-family demands. The

article suggested that the existence or absence of social entitlements and support

services may impact more than one generation of women, thus having unanticipated

outcomes and shaping the way that multiple groups of women participate in the

workforce and larger society or are positioned marginally within them. The article

also contributes to debates on comparative welfare regimes and gender inequity in the

lives of those working in and using the services of the non-profit sector.

Subramanian and Anjani (2010) compared the quality of work life

constructs of quality of work life for 500 employees in textile and engineering

industry, by collected a sample of 250 from each industry in Coimbatore District,

Tamil Nadu. The constructs of quality of work life found out from the study are

nature of job, pay and compensation, development and encouragement, human

relations and social integration, workers participation in management, working

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conditions, steps for Occupational stress reduction, alternative work schedule,

grievance procedure and promotion policy.

Meenakshi Gupta and PaulSharma (2010) conducted survey among 200

employees at BSNL in Jammu region regarding the factor credentials boosting

Quality of Work Life. The study found that there is a high level of satisfaction with

Quality of Work Life among the BSNL employees. The factors determining the

satisfaction were “adequate income & fair compensation, safe & healthy working

conditions, opportunities to use and develop human capacity, opportunity for career

growth, social integration in the work force, constitutionalism in work organization,

and eminence of work life and social relevance of work.” According to the authors,

all the above factors are positively correlated with the quality of work life in BSNL.

RochitaGanguly (2010) made a study on Quality of work life and the job

satisfaction of the clerical employees working in the university. In her study she said

that the results indicated that the selected group of university employees perceived

different aspects (Autonomy, top management support and worker’s control) of their

quality of work life as either uncongenial or they have had a certain amount of

dilemma to comment on.

Patil and Chavan (2010) concluded in their study of Quality of Work Life in

small scale industries of Dharwar District that Semi-skilled workers of the security

department were lacking in quality of work life. According to the authors, ‘The

cumulative effect of lengthy hours and uncertainty in their working conditions may

have resulted in this pattern of scoring’.

Subramanian and Anjani (2010) made a comparison of engineering and

textile industry employees and found out that engineering industry employees were

found to be relatively more satisfied than textile industry employees in all the

constructs except pay and compensation where textile industry employee show a

slightly higher (51.3%) satisfaction.

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Varshasingh et al (2010) in their study drew 28 dual-income couples from

four occupational sectors namely, IT, public service, self-employment and social

service and tested the assumption that decision-making in household follows a single

set of preferences. They found out that ‘the effects of key demographic variables

(marital role, age, occupation and level of education) suggest that only marital role

had a significant influence on discrepancy found in reported in Easton Simon (2010)

argues that stress at work and job satisfaction need to be considered within the

broader context, but that the bigger pictures, or overall quality of working life, remain

relatively unexplored and unexplained.

Meenakshi Gupta and Paul Sharma (2010) conducted a survey in BSNL in

India on the different constructs by Walter, Rosow and others and developed a model

based on the survey conducted.

Rafidah Abdul Aziz et al. (2011) developed the research questions, which

served as a foundation of the study and focused on the relationship between work and

non-work variables and quality of work life. Respondents were all librarians working

in government academic libraries in the Klang Valley, Malaysia. The data were

analysed using Pearson Correlation Analysis. Findings from the study indicated that

both work variables and non-work variables do matter in determining the quality of

work life.

Margarita et al. (2011) used a demands–control perspective and data from

103 manager–spouse couples in their paper examined how job control neutralizes the

negative effects of managers’ job demands on their contributions to housework as

rated by their spouses. They hypothesized that managers’ contribution to housework

chores would be positively associated with spousal rating of family satisfaction. The

empirical evidence showed that managers with frequent business trips were less

cooperative in housework and that this association was moderated by the extent of job

control. In turn, managers ‘cooperation in housework was positively related to

spouses’ family satisfaction. The study has offered implications for attracting and

retaining managerial talent.

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DiRenzo et al. (2011) explored the differences in work – family conflict for

lower-level and higher-level employees. It was found that both WIF (Work

Interference with Family) and FIW (Family Interference with Work) were significant

among higher level workers. Also work-based resources were more strongly related to

WIF for higher-level employees as well as lower level employees. The implications

for Future research should examine individuals who have moved from lower- to

higher-level positions, or vice versa, the degree to which the demands of the job or

one's personal characteristics explain the levels and antecedents of work-family

conflict, enrichment and balance.

Margaret et al. (2011) reviewed and synthesized 219 empirical work–family

studies that have targeted employees outside of the United States. Their review

answered four questions about international work–family research. First, what

constitutes the work–family interface and is there consensus about how to measure it?

Second, what theories have researchers used to explain the work–family interface?

Third, which antecedents and consequences of the work–family interface are common

across countries and which are unique to particular countries? Fourth, what can we

learn from this review that will inform future research in this area? Based on their

review, a universal theoretical framework that integrates both work–family conflict

and facilitation was provided.

Saija et al. (2011) in their study examined whether perceived work–family

conflict would function as a mediator in the link between work–family culture

perceptions and self-reported distress. Data were obtained from employees (N=1,297)

of five Finnish organizations representing both the public (local social and health

care, school, and labour departments) and the private sectors (paper mill, IT

company). The results showed that perceived work–family conflict functioned as a

partial mediator between employees' perceptions of work–family culture and self-

reported distress in two organizations (i.e. in the social and health care department

and paper mill), whereas the relationship turned out to be direct in the other three

organizations (i.e. the education, labour departments and IT company). Thus, a

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supportive work–family culture was related directly and indirectly, through reduced

work–family conflict, to the well-being of employees.

Sayeed et al. (2011) in their research paper investigated the work-family

conflict (WFC) of women managers in Dhaka. Through stratified sampling four strata

were selected (Doctors, Teachers, Bankers and Managers) and then total forty

samples were chosen from different strata. From this study it was revealed that longer

working hours affect work family balance directly and children were the worst

victims of this WFC. This study confined itself within Dhaka metropolis.

Kalliath and Singh (2011) explored the work-family conflict and coping

mechanism from an affected by time based and strain based conflict as compared to

females. Religious belief, support of family, attitude to life, and helping others emerge

as mechanism for handling conflict by the participants. A sample of 21 employees

may not be sufficient enough to generalize the findings as 3 important sectors are

considered for study. Also the family structure is largely considered to be nuclear

which may not be the case for the population.

Guanglin (2011) chose female staff’s family-work conflict as independent

variables and job content plateau, hierarchical plateau as dependent variable and

analysed the data by structural equation model, which was collected through

questionnaire survey in Zhenjiang, Yancheng and the Kunshan, and the result showed

that female staff’s family-work conflict had a significantly positive effect on job

content plateau and hierarchical plateau.

Nien and Chih (2011) has studied the crucial impact of work–family issues

on employee’s well-being which has been recognized and responded with a variety of

research in field of organizational behaviour. The impact of how work–family

practices affect productivity at firm-level is not examined. Following the research

stream of strategic human resource management, they proposed that work–family

may form the norm of reciprocity, which is a more sophisticated and more critical,

internal social-structure component to enable organizational performance. They also

examined the contingent effect, work–team structure on the extent to which the work–

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family practices were appreciated by employees – and then create complementarities.

They conducted a longitudinal study and utilize a data set of 204 Taiwanese public-

traded firms to test their hypotheses. The results showed that, contrary to their

prediction, utilizing work–family practices does not have a significant positive impact

on organizational productivity. However, the most important finding of their study

was that there were synergies between work–family practices and work–team design

on organizational productivity. Work–team design is an important situation in which

the returns of work–family practices could be enhanced.

Beham et al. (2011) tested the extended version of Voydanoff's "differential

salience vs. comparable salience model" and found that work demands and resources

are differentially related with WHE and WHI whereas boundary-spanning demands

and resources are related with both. Also, job control and job variety were not found

to be significantly related to WHI. The study was only confined to WHI (Work Home

Interference) and WHE (Work Home Enrichment) but how HWI (Home Work

Interference) and HWE (Home Work Enrichment) affects work can be a future scope

for researchers.

Valk and Srinivasan (2011) explored the work and family factors that

balance work-life of Indian women IT professionals. The study identified factors like

familial influences on life choices, multi role responsibilities and attempted to

negotiate them. They also studied about self-identity, work-life challenges, coping

strategies, organizational policies and practices and social support as important from

the view point of work life balance. They also discussed about future research in the

IT sector which could focus on factors that results in conflict and factors that

enhances enrichment and further how these two aspects could be integrated.

Yusuf and Zeina (2012) in their study addressed work–family conflicts and

job attitudes of white-collar single women and the ensuing work-related attitudes in a

developing country context. They gave an overview of gender roles in Arab society,

several hypotheses were advanced and tested. Although married female reported

higher family–work conflicts than single females, the latter group faced a host of

strains, which were presented and analysed.

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Despite being educated, single females were underpaid and their upward mobility

seemed to be significantly hampered. They reported lower job satisfactions and had

high intentions to leave their organization.

ChandaranshuSinha (2012) in his research explored the factors of quality of

working life experiences in organizations. The study focused on 100 employees

holding middle managerial positions in various organizations in India. According to

the study, “The three emerging factors were ‘relationship-sustenance orientation’,

‘futuristic and professional orientation’ and ‘self-deterministic and systemic

orientation’. The results indicated that these factors have substantial roles to play in

satiating the needs of the employees.

Sarika and ShreeKumar (2013) in their review on work-family balance

explored the meaning, antecedents, consequences and moderators of work - family

balance from conflict as well as enrichment perspectives. The paper discussed the role

of turn over intention which have given mixed results in different settings. The review

also focused on the role of individuals' personality dimensions such as core self-

evaluation which were yet to gain prominence in work-family studies but were

important enough to invite further research. The paper finally suggests the

development of an integrated framework to understand the concept of work – family

balance.

Christiana (2013) examined academic women’s experiences of work- family

conflict and determined their implication on their job performance. It also identified

the factors that trigger academic women’s work-family conflict in Nigerian

universities. Primary data were generated from 250 female academic staff from 3

public universities in Nigeria. Several factors such as long hours of work,

overcrowded job schedules, inadequate working facilities, family responsibilities,

teacher-student ratio, cohesive HOD’s accounted for greater work-family conflict. It

also accounted that women’s experiences of work-family conflict impacted negatively

on their job performance and wellbeing. They concluded their research by saying that

universities had to pay attention to the interface of work and family by initiating

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family friendly policies that take into consideration the multifaceted roles of women.

Vasavi et al. (2005) pointed out in their study that conditions of work in the

software industry present greater obstacles to women than men the prevalence of long

working hours, the high pressure work atmosphere, and the necessity of frequent

travel abroad force many women to drop out of the industry or to stagnate. HR

managers and corporate leaders had failed to recognise that although they might treat

women employees on par with men and even provide special facilities such as

crèches, to cater to their needs women still live in highly unequal domestic situations

which make it difficult for them to manage such high pressure jobs. She added that

despite the entry of number of women in this sector, information technology was still

a male-dominated industry, and in many companies a masculine culture has

developed that tends to exclude or marginalize women. The ‘work culture’ of

software companies also tends to be male-dominated as stress on informal networking

and ‘teamwork’ may work to exclude women.

Reimara and Vasanthi (2010) attempted to understand from their Qualitative

study how work and family related factors influence the work-family balance of

Indian women IT professionals. The narratives revealed six major themes: (1)

Familial influences on life choices which refers to the extent to which the immediate

family plays a role in creating the values and meaning around work and life for the

women.(2)Multi-role responsibilities and attempts to negotiate them refers to the

aggravation and accentuation of the role conflict in the context of the software

services industry.(3)Self and professional identity which became apparent that

women saw their work and careers as a prime element in their self-identity-building.

Women described feelings of challenge, accomplishment, morale boost, satisfaction

of using skills, drive to explore, drive for self-development, growth as a person, and

personal satisfaction derived from work to define their identity.(4)Work life

challenges and coping strategies which emphasized that the projects had to be

completed with tight deadlines, extensive travelling and long and/or odd working

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hours, affected the work family balance.(5)Organizational policies ,practices and

social support. Women reported the existence of work-family friendly policies and

programmes that facilitated work-family balance like flexi time, work from home

policy, leave of absence policy, and one month leave a year, maternity leave, child

care facilities and sabbatical leave.

Mohan and Ashok (2011) in their study showed that the women software

professionals experienced moderate level of stress and stress dimension. This study

revealed that more than half of the respondents experience medium level of

depression and also suggested the age and experience significantly influence the

overall stress and depression experienced by the employees. Their study revealed that

there might be a strong relationship between overall stress and depression. This

enabled the researcher to choose stress at work as one dimension of work- life

conflict.

Mantalay (2011) conducted his study among Thai software developers in a

German-owned company in Chiang Mai, Thailand and found that work stress causes

the organizational work-life imbalance of employees. He further added that workers

perform with lower effort to finish assignments and thus an organization would

experience reduced productivity. The fishbone diagram showed the relationship

between cause and effect clearly and found that an organizational work- life

imbalance among Thai software developers was influenced by management team,

work environment, and information tools used in the company over time.

Madhavi et al. (2011) examined the impact of work-family issue over the role

stress dimensions. The result of the study reveals that the work-family issues

significantly influence all the dimensions of role stress except Role Erosion, Personal

Inadequacy, Self-Role Distance, and Resource In adequacy. They found that 36.2

percent of respondents expressed high work-family issues. They suggested that family

members’ role was vital to bring down this problem and their responsibility of sharing

and moral support alone could help them to tide over the work-family issue.

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Xiaoni & Foster (2011) examined the experiences of women working in a

Chinese airline. They conducted a survey with female employees and managers and

explored on work–family conflict and gendered organizational perceptions of

women’s needs. Their findings suggested that work rather than family-related factors

were the most influential causes of conflict for Chinese women. Cultural and social

factors that shape familial relationships prove important in explaining these

differences, but they also highlighted the significant role played by gendered

organizational culture.

Sujatha and Neeta (2012) reported on the work-family conflict among the

married working executives in the Greater Mumbai Region, a place known for its

business vibrancy. They found that work family conflict still existed and women were

taking more than what they could deliver to satisfy themselves and they concluded by

saying that women need to redefine role expectations for themselves and their

families. The consequences of WFC include exit from the workforce permanently or

temporarily to accommodate family demands.

Jawahar Rani et al. (2012) investigated the intensity of work-family conflict

creating organizational role stress and found the relationship between life satisfaction

and organisational role stress. The data were collected from 491 women professionals

using anonymous questionnaire. They concluded in their research that stress among

women were due to the work-family conflict and doctors were more stressed than any

other profession and there was no significant relationship between stress and life

satisfaction. They also added that life satisfaction increases with a positive work

environment. They suggested that introduction of more flexible work schedules would

produce positive benefits for employees and stress management training could be

offered to the employees.

Kanwar et al. (2012) in their study emphasized the need for organizations

to strive to augment job satisfaction in the workforce for it was conducive to lower

employee turnover, higher engagement and greater productivity. Their study

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examined the impact of work life balance and burnout on job satisfaction in the

context of the Information Technology (IT) and IT Enabled Services (ITES)

industries. Burnout was measured through three dimensions, i.e., meaninglessness,

de-motivation, and exhaustion. The findings revealed that while work-life balance and

job satisfaction were positively related to each other, de-motivation, exhaustion and

meaninglessness were negatively related to job satisfaction. The significant

contribution to job satisfaction came from work life balance in both the IT and ITES

industries. However, it was higher in the ITES group compared to the IT group. The

findings showed that job satisfaction was higher among the male respondents in

comparison to the female respondents. Interestingly, the IT group had lower work-life

balance and job satisfaction, while it had higher meaninglessness, de-motivation and

exhaustion compared to the ITES group.

Ranjit & MahesPriya (2012) focused on job stress and quality of women

software employees. Descriptive research design was adopted and 201 women

employees of software industry in Bangalore was chosen for the study. It was

concluded in their research that job stress influences the quality of life of software

employees and they added that the demographic variables do influence the level of

job stress and quality of life of software employees.

Hatice et al. (2013) had undergone a study on the relationship between work

intensity factors and work-family conflict factors in the collectivist culture pattern of

Turkey. The structural equation modelling results showed that work intensity factors

were the significant predictors of work-to-family conflict factors for Turkish health

care professions. Hierarchical multiple regression analysis showed that personal

demographics and work situation characteristics accounted for a significant increment

in explained variance on the time based work-family conflict factors measure. The

study also found support for the hypothesis that samples would demonstrate a positive

relation between work intensity and work-family conflict for Turkish health care

professions. There were statistically no significant differences of time, strain and

behaviour based work-to-family conflict according to gender, age, marital status,

having children and function. They found significant difference between the work-

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family conflict levels of health care professionals according to number of children,

education level, work hours per week and organizational position.

Aishwarya and Ramasundaram (2013) have conducted an empirical

analysis of the role conflict of women in IT field and found that there were three

predominant factors that influence work family conflict - time dimension are work

exhaustion, work thought interference and perceived workload in the order of merit. It

was work exhaustion that influenced the time dimension of work-family conflict the

highest followed by work thought interference and perceived workload the least. The

influence of organizational commitment, organizational climate, perceived family

demand, family involvement, and job autonomy and job involvement was less and not

considered as a cause for the occurrence of work-life conflict with time.

RESEARCH GAP

An extensive literature review is made to extract exclusive information on Work-Life

Conflict of women and alienate it from the generic concepts. However, commonality

between various sectors cannot be ruled out since work and family linkage theories

are universal and holds good for varied consideration. Based on the literature review

mentioned above, it is evident that the concept of work-life conflict is complex and

involves various theories and models which has been tested effectively by researchers.

The end results of various research cannot be formulated as thumb rules. The

changing nature of the employees with the ever changing industry and technology

poses various challenges and emerging trends which enables the researcher to

undertake a current study on the work life conflict of women software employees in

Chennai. The literature review generated curiosity to dwell more on the subject. The

knowledge gained was utilized for formulating the questionnaire to include the

appropriate questions that would provide input for decision making. The factor that

influence work life conflict could be drawn out and grouped under specific heads to

enable a clear study on the causes of the conflict and measures to be taken to

overcome the conflict and manage the work life conflict. Chennai was chosen

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because it is a hub of software companies and also has majority of the well qualified

workforce. The review also enabled clarity in thought process on how to approach

the problem especially framing the objectives of the study and to full fill the gap

between the previous researcher’s analysis and to the present study.

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CHAPTER III

RESEARCH METHODOLOGY

This chapter focuses on the research design, operationalization of

variables, data collection method, and data analysis plan. This chapter has dealt with

the main objectives and hypothesis of the present study. An overview of the design of

the study included methods of selection of respondents, method of data collection,

tools for analysis and choice of test statistics. Further a well-designed questionnaire

was also used. The details of the questionnaire used and the sampling procedure

adopted in the study are described in the following pages.

3.1 Research

Research is an organized set of activities to study and develop a model or

procedure/technique to find the results of a realistic problem supported by literature

and data such that its objectives are optimized and further make

recommendations/interferences for implementations. Redman and Mory define

research as “a systematized effort to gain new knowledge”. Research is an academic

activity and as such the term should be used in a technical sense. According to

Clifford Woody research comprises defining and redefining problems, formulation

hypothesis or suggested solutions; collecting, organizing and evaluating data; making

deductions and reaching conclusions; and at last carefully testing the conclusions to

determine whether they fit the formulating hypothesis. Research methodology are

system of models, procedures and techniques used to find the results of research

problem

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3.2 Research Design

Research design is the blueprint for conducting research aimed at

answering the research question. It ensures that the study is relevant to the problem

and economical in procedures by guiding the researcher on major research issues such

as data collection techniques, sampling procedure, monetary costs and time required

for the study and techniques used for data analysis. They have classified research

design into several categories based on eight different descriptors.

According to their frame work, this study follows a formal research design

where the objective is to answer the research question and testing of hypothesis .In

terms of control of other variables, research design follows an ex post facto design

where in the researcher’s ability to manipulate the variables is limited. In terms of

purpose, it is more of a causal study, wherein the objective is to explain the

relationship between variables. Data were collected at once to represent a snapshot,

and hence on time dimension, the research design is considered to be of cross

sectional nature.

3.3 Selection of Company

For the purpose of this study, leading software companies in the software

industry in Chennai were taken for the study. The companies were selected with the

perspective of choosing the organization facing high level of burnout, job tension

which is inferred from the attrition rates and the organizations were shortlisted based

on manpower distribution. These organizations contribute for highest women

manpower distribution among Chennai. So analysing their work-life conflict of their

women employees would help to study the objectives specified.

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3.4 Data Collection Method

The study involved the measurement of the socio-economic profile of

women employees working in software industry in Chennai. Confirmatory factor

analysis has been done to confirm the factor structure of experiencing conflict in the

family life and work environment, managing work-life conflict at family and work

environment, betterment of managing work-life conflict and feeling of present life and

work environment. Experience levels of conflict at family and work environment

were discussed. Important aspects of work-life conflict at family side and work

environment, and its betterment are identified. Expectation levels in present family

life and work environment are also enumerated. Influence of employees’

demographics over experiencing conflict, managing work-life conflict, betterment of

work-life conflict and expectations in present family life and work life are discussed

in detail both in the aspects of family life and work life. Frustration in job and its

reasons are also elaborated. Correlation analysis has been done for family life and

work life. Hence the data were collected only from women employees. Based on the

above specified objectives both primary and secondary were collected. Primary data

were collected by administering questionnaire mainly to study and secondary data

were collected from various journals and the reviews of past studies helps the

researcher to identify the previous gap.

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3.4.1 Variables for the Study

The below describes the variable and its nature is shown in Table 3.1.

Table 3.1 Variables for the study

S.No. Variable

1 Experiencing conflict at family side

2 Experiencing conflict at work environment

3 Managing work-life conflict at family side

4 Managing work-life conflict at work environment

5

Betterment of Managing work- life conflict at family and work environment

6 Feeling about present family life

7 Feeling about present work environment

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3.4.2 Questionnaire Construction

The questionnaire was constructed with nine sections, Section A analyses

the experience of conflict at the family side, Section B analyses the experience of

conflict at the work environment, Section C measures the level of satisfaction

towards managing the work-life conflict at family side, Section D measures the level

of satisfaction towards managing work-life conflict at work environment, Section E

measures the level of expectation towards the betterment of managing work-life

conflict at family and work environment, Section F assess their feeling about their

family life, Section G assess their feeling about work environment, Section H about

the organization they work and Section I has all the demographic details about the

respondents. The reliability of the questionnaire was tested through pilot study the

values indicated have proved the reliability and validity of parameters taken for the

study.

3.4.3 Research Questions

The study was designed to gain reasonable answers to the following questions. The

main research questions of this study are:

1) How do work and family related factors influence the work-family conflict of

women software employees in Chennai?

2) How do work and family related factors influence the satisfaction level at

work and family respectively of women software employees in Chennai?

3) How do work and family related factors influence their expectation for

managing work life conflict at work and family respectively?

4) How do the women software employees in Chennai feel about their present

work environment and present family situation.

5) What moderator effect does family support and work support play in the work

and family situation?

6) How do they like to retain themselves in the company they work or they have

left the company for various reasons?

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7) How do they rate the organization that they work for?

8) What challenges do they face and what coping strategies do they use to avoid

conflict?

3.4.4 Pretest

The pretest was conducted with an idea of testing the reliability of the

questionnaire designed and to understand the respondent’s ease in answering the

questionnaire. Primary concern was regarding the length of the questionnaire, since it

has 81 questions to measure 7 variables, in addition to the demographic variables and

job related variables. A sample of (20% of 500(N=100)) software women employees

in Chennai were selected for this purpose.

Respondents were required to mention the time required to complete the

questionnaire, items that were difficult to understand or answer and other general

remarks. Respondents to pilot testing identified some words as difficult to understand

and answer .Based on the views of the respondents the needed modifications are

carried out and the questionnaire was standardized.

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3.4.5 Sampling Size

The sample size was determined by a sampling proportion method using

the following formula:

2ZS

nE

2(1.96) (0.93)

0.01

= 500 (3.1)

Where Acceptable error E is 10% = 0.01

S = Sample SD/SD of population = 0.93

Z = Standardized value corresponding to a confidence = 1.96

3.4.6 Sampling Design

As the population is indefinite, Convenience sampling was adopted for the

study. The questionnaire was administered to a non- probability sample of 500

software women employee in Chennai.

3.4.7 Non-Response Bias Checks

The non-response bias was checked by both a field and data. As in any

survey method, there will be non-response. The initial non-response, from the survey

carried out by the researcher was deemed as acceptable as the calculated final

response rate was high (94%). The main reason given for non -response was refusal to

answer the survey and the lack of time for enumerators to obtain responses.

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3.4.8 Reliability and Validity test

Reliability

Reliability of an instrument refers to the degree of consistency between

multiple measurements of variables. It is extent to which an experiment tests or any

measuring procedures yield, the same result on repeated attempts. Reliability was

estimated through internal consistency method which is applied to measure the

consistency among the variables in a summated scale. In the present study, the

Cronbach’s Alpha co-efficient of reliability was found based on primary data of the

present study and the details are as follows:

Table 3.2

Reliability measures for the study

Source: Primary data

No. Variables No. of items Alpha

1 Experiencing conflict at family 12 0.83

2 Experiencing conflict at work environment 16 0.84

3 Managing work-life conflict at family side 13 0.81

4 Managing work-life conflict at work environment 17 0.83

5 Betterment of managing work-life conflict 10 0.82

6 Expectation in Present family life 6 0.85

7 Expectation in Present work environment 5 0.87

Overall reliability of the study 79 0.85

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Validity

Both Face and Content validities were established in the study. The face

validity was done by the investigator and the content validity was established by the

experts in the field of investigation. Face validity, it appears to measure whatever the

author had in mind, namely, what he thought he was measuring. The rationale behind

content validity is that to examine the extent to which a measuring instrument

provides adequate coverage of the topic under study.

3.5 Data Analysis

All data analysis was conducted using SPSS V-15. Sample means,

standard deviation and N are presented in the analysis chapter for all the variables of

the study. The classification tools serve as data presentation techniques for clear

interpretations.

3.5.1 Statistical Tools Applied for the Study

The data collected was statistically analysed by applying various tools like

simple percentage, t-test, ANOVA followed by Duncan multiple range test, Chi-

square, Fried man test, correlation analysis and multivariate tools like multiple

regression and discriminant analysis

3.5.1.1 Analysis of Variance (ANOVA)

ANOVA allows for the study of a single factor or several factors, but will

only measure one variable. An ANOVA works by measuring the variance of the

population in two different ways; the first is by noting the spread of values within the

sample; the second is by the spread out of the sample means. If the samples are from

identical populations, these methods will give identical results. The basic assumptions

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for ANOVA are random sampling independent measurements, normal distribution

and equal variance

3.5.1.2 Non-Parametric Chi-square Analysis

Chi-square association test is a non-parametric test useful to establish an

association between two categorical variables. The frequency dumping in each cell of

the cross tabulation allows identification of the association between two types of

heterogeneous groups and also the nature of cases in that particular cell. It also

exhibits linear by linear relationship, and Crammer’s Phi-statistics to study the

relationship.

3.5.1.3 t-Tests

t-Tests are used in situations where the research wants to compare two

statistics. The basic utility of a t-test is that it produces a straight forward easy to

interpret results of significance. In the case of this thesis, two tailed t-tests were used

after all other analysis was completed only to note the differences of assumed mean

and computed mean directly. The basic assumptions for t-tests- one random sampling,

independent measurements, normal distribution and equal variance.

3.5.1.4 Correlation Analysis

Correlation is the degree of association between two variables and it is

represented in terms of coefficient known as correlation coefficient. The range of

correlation coefficient is in between -1 and +1; if the coefficient is 0, there is no

association between variables. If the coefficient is positive, then the variables are

associated directly and it is maximum when it is +1.

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3.5.1.5 Multivariate Analysis

Multivariate analysis for this study involved the use of multiple regression

and discriminant analysis multiple regression.

If the number of independent variables in a regression model is more than

one, then the model is called multiple regression. Stepwise hierarchical regression is

preferred in this model compare to enter method, due to its ability to deal with

multicollinearity issues.

Discriminant analysis is dependence multivariate techniques. The purpose

of dependence technique is to predict a variable from a set of independent variables.

This is used primarily to identify variables that contribute to differences in the a priori

defined groups with the use of discriminant functions.

3.5.1.6 Structural Equation Modelling

Structural equation modelling (SEM) is a statistical technique for testing and

estimating causal relations using a combination of statistical data and qualitative

causal assumptions. Structural equation models (SEM) allow both confirmatory and

exploratory modeling, meaning they are suited to both theory testing and theory

development. Confirmatory modeling usually starts out with a hypothesis that gets

represented in a causal model. The concepts used in the model must then be

operationalized to allow testing of the relationships between the concepts in the

model. The model is tested against the obtained measurement data to determine how

well the model fits the data. The causal assumptions embedded in the model often

have falsifiable implications which can be tested against the data.

With an initial theory SEM can be used inductively by specifying a

corresponding model and using data to estimate the values of free parameters. Often

the initial hypothesis requires adjustment in light of model evidence. When SEM is

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used purely for exploration, this is usually in the context of exploratory factor analysis

as in psychometric design.

Among the strengths of SEM is the ability to construct latent variables:

variables that are not measured directly, but are estimated in the model from several

measured variables, each of which is predicted to 'tap into' the latent variables. This

allows the modeler to explicitly capture the unreliability of measurement in the

model, which in theory allows the structural relations between latent variables to be

accurately estimated. Factor analysis, path analysis and regression all represent

special cases of SEM.

In SEM, the qualitative causal assumptions are represented by the missing

variables in each equation, as well as vanishing covariances among some error terms.

These assumptions are testable in experimental studies and must be confirmed

judgmentally in observational studies.

3.6 Hypotheses of the Study

The following null hypotheses have been examined for the study:

H01 (a): The experience level of conflict at family side of women

employees working in software companies do not differ with the

average score.

H01 (b): The experience level of conflict at work environment of women

employees working in software companies do not differ with the

average score.

Null hypothesis H0 2: All the aspects of managing work life conflict at

family side gives equal satisfaction to the women employees.

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Null hypothesis H0 3: All the aspects of managing work life conflict at

work environment gives equal satisfaction to the women employees.

Null hypothesis H0 4: All the aspects of betterment of managing work life

conflict at work environment carry equal expectation among women

employees.

H05: The expectation level in present family life of women employees

working in software industry do not differ with the average score.

H06: The expectation level in present work environment of women

employees working in software industry do not differ with the

average score.

H07: There is no significant influence of women employees’

demographics (a) Age (b) Marital status (c) Category of Job (d)

Work experience (e) Educational qualification (f) Monthly income

(g) Working hours per week on experiencing conflict in their family

life.

H08: There is no significant influence of women employees’

demographics (a) Age (b) Marital status (c) Category of Job (d)

Work experience (e) Educational qualification (f) Monthly income

(g) Working hours per week on experiencing conflict in their work

environment.

H09: There is no significant influence of women employees’

demographics (a) Age (b) Marital status (c) Category of Job (d)

Work experience (e) Educational qualification (f) Monthly income

(g) Working hours per week on managing work-life conflict at

family side.

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H010: There is no significant influence of women employees’

demographics (a) Age (b) Marital status (c) Category of Job (d)

Work experience (e) Educational qualification (f) Monthly income

(g) Working hours per week on managing work-life conflict at work

environment.

3.7 LIMITATIONS OF THE STUDY

1. The study is a sample based study and analysis and interpretations are bound

to be representative of the total population.

2. The present study is confined only to software women employees of Chennai

city and does not include other states of India.

3. The analysis is based completely on the responses given by the respondents in

the questionnaire. The authenticity of the responses is the limiting factor.

4. There is a possibility of employee bias in responding to certain questions.

5. Time was a major constraint and owing to the hectic nature of their job some

of the women employees were not able to spend time in filling the

questionnaire completely.

6. The sample taken from the population does not include all the companies in

the software industry.

134

CHAPTER IV

DATA ANALYSIS AND INTERPRETATION

This chapter provides data analysis and interpretation. It explores the socio-

economic profile of women employees working in software industry in Chennai.

Confirmatory factor analysis has been done to confirm the factor structure of

experiencing conflict in the family life and work environment, managing work- life

conflict at family and work environment, betterment of managing work life conflict

and feeling of present life and work environment. Experience levels of conflict at

family and work environment were discussed. Important aspects of work- life

conflict at family side and work environment, and its betterment are identified.

Expectation levels in present family life and work environment are also enumerated.

Influence of employees’ demographics over experiencing conflict, managing work-

life, betterment of work- life and expectations in present family life and work life are

discussed in detail both in the aspects of family life and work life. Frustration in job

and its reasons are also elaborated. Correlation analysis has been done for family- life

and work- life. Predictor variables for rating of organization in software industry in

Chennai are also identified. Final section is dealt with a proposed model for

managing work- life conflict in software industry in Chennai. The information about

the background of 500women employees working in software industry in Chennai is

explored. Well-structured questionnaire is prepared to collect the relevant responses

from the selected women employees of the software industry in Chennai.

135

4.1 Profile of Women Employees

Women employees working in software industry in Chennai were selected for

the study. Women employees are classified according to their age, marital status, job

category, work experience, educational qualification, monthly and income and

working hours per week. Table 4.1 shows the details of demographic profile of the

women employees working in selected software companies in Chennai.

136

Table 4.1

Profile of Women Employees Working in Software Industry

Particulars Classification Number of

Employees Percentage

Age

Below 25 years 134 26.80

25-35 years 140 28.00

36-45 years 132 26.40

Above 45 years 94 18.80

Marital status Single 125 25.00

Married 375 75.00

Category of job

Professional 254 50.80

Non professional 102 20.40

Others 144 28.80

Work experience

Less than 5 years 109 21.80

5-10 years 267 53.40

11-15 years 72 14.40

Above 15 years 52 10.40

Educational

qualification

Graduate 213 42.60

Post graduate 197 39.40

Professional degree 90 18.00

Monthly income

Less than Rs.20,000 132 26.40

Rs.20,001-40,000 199 39.80

Rs.40,001-50,000 113 22.60

Above Rs.50,000 56 11.20

Working hours per

week

35-39 hours 42 8.40

40-44 hours 259 51.80

45-49 hours 182 36.40

Above 50 hours 17 3.40

Source: Primary data

137

Out of 500 women employees, 28.00 % of the women employees are in the

age group of 25- 35 years, 26.80% of the women employees are in the age group of

below 25 years, 26.40% of the women employees are in the age group of 36 - 45

years and 18.80% of the women employees are in the age group of above 45 years. It

is observed that most of the women employees (28.00%) working in software industry

in Chennai are in the age group of 25 - 35 years.

Out of 500 women employees, 75.00% of the women employees were married

and the remaining 25.00% of the women employees are living as single. It is observed

that majority of the selected women employees (75.00%) working in software

industry in Chennai were married.

Out of 500 women employees, 50.80 % of the selected women employees are

working in professional category, 28.80 % of the selected women employees are

working in several other categories and 20.40 % of the selected women employees are

working in non-professional category. It is observed that the most of the women

employees (50.80%) working in software industry in Chennai are working in the

professional category.

Out of 500 women employees, 53.40 % of the selected women employees are

having work experience of 5 – 10 years, 21.80 % of the selected women employees

are having work experience less than 5 years, 14.40 % of the selected women

employees are having work experience of 11 - 15 years and 10.40 % of the selected

women employees are having work experience above 15 years. It is observed that the

majority of the women employees (53.40%) working in software industry in Chennai

are having work experience of 5 – 10 years.

Out of 500 women employees, 42.60 % of the selected women employees are

graduates, 39.40 % of the selected women employees are possessing post-graduation

as their having educational qualification and 18.00 % of the selected women

employees are having professional education. It is observed that the majority of the

women employees (42.60%) working in software industry in Chennai are graduates.

138

Out of 500 women employees, 39.80% of the women employees are earning

Rs. 20,001 - Rs.40,000, 26.40% of the women employees are earning less than

Rs.20,000 as their monthly income, 22.60% of the women employees are earning

Rs.40,001 to Rs. 50,000 per month and 11.20 % of the women employees are earning

above Rs.50,000. It is observed that majority of the women employees (39.80%) in

software industry in Chennai are earning Rs. 20,001 - Rs. 40,000 per month.

Out of 500 women employees, 51.80% of the women employees are working

40-44 hours per week, 36.40% of the women employees are working 45-49 hours per

week, 8.40% of the women employees are working 35-39 hours every week and

3.40% of the women employees are working more than 50 hours per week. It is

observed that most of the women employees (51.80%) working in software industry

in Chennai are working 40-44 hours per week.

139

4.2 Information Relevant to the Employee and Work Environment

4.2.1 Spouse employment status

Women employees working in software industry in Chennai were selected for

the study. Women employees have given information regarding the status of their

spouse employment. Table 4.2 shows the information regarding the employment

status of spouse of women employees working in software industry in Chennai.

Table 4.2

Spouse employment status

Particulars Number of women

employees Percentage

Yes 267 71.20

No 108 28.80

Total 375 100

Source: primary data

Table 4.2 explores the information regarding employment status of spouse of

women employees working in software industry in Chennai. Out of 500 employees

71.20% of the employees’ spouse are employed in organizations and the remaining

28.80% of the employees’ spouse are not salaried employees. This shows that

majority of the women employees’ spouse (71.20%) are employed in organizations.

140

4.2.2 Status of having children

Women employees working in software industry in Chennai were selected for

the study. Women employees have given information regarding the status of having

children. Table 4.3 shows the information regarding the status of having children of

women employees working in software companies in Chennai.

Table 4.3

Status of having children

Particulars Number of women

employees Percentage

Yes 371 99.00

No 4 1.00

Total 375 100

Source: primary data

Table 4.3 reveals the information regarding the status of having children. Out

of 500 employees 99.00% of the women employees are having children and the

remaining 1.00% of the women employees doesn’t have children. This shows that

most of the women employees (99.00%) are having children.

141

4.2.3 Age of children

Women employees working in software industry in Chennai were selected for

the study. Women employees have given information regarding the age of children.

Table 4.4 shows the information regarding the age of children of women employees

working in software industry in Chennai.

Table 4.4

Age of children

Particulars Number of women

employees Percentage

4 and less 110 29.40

5-10 years 167 44.40

11-16 years 67 17.80

17 and above 31 8.40

Total 375 100

Source: primary data

Table 4.4 describes the distribution of women employees working in software

industry according to their age of their children. Out of 500 employees 44.40% of the

women employees are having children with a age group of 5 – 10 years, 29.40% of

the women employees are having children with a age group of 4 and less years,

17.80% of the women employees are having children with a age group of 11 – 16

years and the remaining 8.40% of the women employees are having children with age

17 years and above. Most of the women employees (44.40%) are having children with

age of 5-10 years.

142

4.2.4 Dependents at home

Women employees working in software industry in Chennai were selected for

the study. Women employees have given information regarding the dependents at

home. Table 4.5 shows the information regarding the dependents at home of women

employees working in software industry in Chennai.

Table 4.5

Dependents at home

Particulars Number of women

employees Percentage

Yes 259 69.00

No 116 31.00

Total 375 100

Source: primary data

Table 4.5 explores the information regarding the dependents at home. Out of

500 employees 69.00% of the women employees are having dependents at home and

the remaining 31.00% of the women employees doesn’t have dependents. It is

observed that 69.00% of the women employees working in software industry are

having dependents at home.

143

4.2.5 Domestic help at home

Women employees working in software industry in Chennai were selected for

the study. Women employees have given information regarding the domestic help at

home. Table 4.6 shows the information regarding the domestic help at home of

women employees working in software industry in Chennai.

Table 4.6

Domestic help at home

Particulars Number of women

employees Percentage

Yes 421 84.20

No 79 15.80

Total 500 100

Source: primary data

Table 4.6 depicts the information regarding the domestic help at home. Out of

500 employees 84.20% of the women employees expressed that they are getting

domestic help at home and the remaining 15.80% of the women employees doesn’t

get domestic help at home. It is observed that 84.20% of the women employees

working in software industry are getting domestic help at home.

144

4.2.6 Employment status

Women employees working in software industry in Chennai were selected for

the study. Women employees have given information regarding the status of

employment. Table 4.7 shows the information regarding the status of employment in

software industry in Chennai.

Table 4.7

Full time employee

Particulars Number of women

employees Percentage

Yes 423 84.60

No 77 15.40

Total 500 100

Source: primary data

Table 4.7 depicts the information regarding the status of employment. Out of

500 employees 84.60% of the women employees expressed that they are full time

employees and the remaining 15.40% of the women employees not working as full

time employees. This shows that 84.60% of the women employees are working as full

time employees.

145

4.2.7 Working mode

Women employees working in software industry in Chennai were selected for

the study. Women employees have given information regarding the working mode.

Table 4.8 shows the information regarding working mode of women employees

working in software industry in Chennai.

Table 4.8

Working in shift

Particulars Number of women

employees Percentage

Working in shift 399 79.80

Not working in shift 101 20.20

Total 500 100

Source: primary data

Table 4.8 explores information regarding working mode of women employees.

Out of 500 employees 79.80% of the women employees expressed that they are

working in shifts and the remaining 20.20% of the women employees not working in

shifts. It is observed that 79.80% of the women employees in software industry are

working in shifts.

146

4.2.8 Job related travel

Women employees working in software industry in Chennai were selected for

the study. Women employees have given information regarding the job related

travels in their profession. Table 4.9 shows the information regarding the job related

travels of women employees working in software industry in Chennai.

Table 4.9

Job related travel

Particulars Number of women

employees Percentage

Yes 319 63.80

No 181 36.20

Total 500 100

Source: primary data

Table 4.9 depicts the information regarding job related travel of women

employees working in software companies. Out of 500 employees 63.80% of the

women employees are engaged with job related travelling and the remaining 36.20%

of the women employees are not engaging with job related travelling. It is observed

that 63.80% of the women employees are engaged with job related travelling in

software companies.

147

4.2.9 Frustrated in job

Women employees working in software industry in Chennai were selected for

the study. Women employees have given information regarding frustration in the job.

Table 4.10 shows the information regarding frustration in the job in software industry

in Chennai.

Table 4.10

Frustration in job

Particulars Number of women

employees Percentage

Yes 457 91.40

No 43 8.60

Total 500 100

Source: primary data

Table 4.10 depicts the information regarding frustration in the job in software

industry in Chennai. Out of 500 employees 91.40% of the women employees

expressed that they are frustrated in their job and the remaining 8.60% of the women

employees aren’t frustrated in their job. It is observed that 91.40% of the women

employees expressed that they are frustrated in their job in software industry in

Chennai.

148

4.2.10 Reasons for frustration in job

Women employees working in software companies in Chennai were selected

for the study. Women employees have given the reasons for frustration in the job.

Table 4.11 shows the reasons for frustration in the job among women employees

working in software companies in Chennai.

Table 4.11

Reasons for frustration in job

Particulars Number of

women employees Percentage

Work Pressure 88 19.25

Unrealistic expectations from the company 28 6.13

Family commitment 37 8.09

Health issues 21 4.59

HR Policies of the company 34 7.44

High Salary expectations 47 10.28

Lack of recognition 35 7.66

Job is monotonous and lack creativity 29 6.34

Low opportunity of advancement 29 6.34

Less time for family and personal activities 28 6.13

Not a supportive work environment 35 7.66

Company Values doesn’t match with my values 27 5.91

Personality conflicts with team members and

manager 19 4.18

Total 457 100

Source: primary data

149

Table 4.11 depicts the reasons for frustration in the job among women

employees working in software industry in Chennai. Out of 500 employees 19.25%

of the women employees are frustrated due to work pressure, 10.28 % of the women

employees are frustrated due to high salary expectations,8.09 % of the women

employees are frustrated due to family commitment, 7.66 % of the women employees

are frustrated due to lack of recognition,7.66 % of the women employees are

frustrated due to non-supportive work environment,7.44 % of the women employees

are frustrated due to HR policies of the company,6.34 % of the women employees are

frustrated due to low opportunity of advancement,6.34 % of the women employees

are frustrated due to monotonous job and lack creativity,6.13 % of the women

employees are frustrated due to unrealistic expectations from the company,6.13 % of

the women employees are frustrated due to less time for family and personal

activities, 5.91 % of the women employees are frustrated due to company values not

matching with their values and4.59 % of the women employees are frustrated due to

health issues. 4.18 % of the women employees are frustrated due to personality

conflicts with team members and manager.91.40% of the women employees

expressed that they are frustrated in job and the remaining 8.60% of the women

employees expressed that they aren’t frustrated in their job. It is observed that

91.40% of the women employees expressed that they are frustrated in the job in

software industry in Chennai. It is observed that most of women employees (19.25%)

are frustrated due to work pressure in software industry in Chennai.

150

4.2.11 Left the company

Women employees working in software industry in Chennai were selected for

the study. Women employees have given information regarding number of times they

had left the company. Table 4.12 shows the information regarding number of times

they had left the company.

Table 4.12

Left the company

Particulars Number of women

employees Percentage

Once 77 15.40

Twice 236 47.20

Thrice 139 27.80

More than thrice 48 9.60

Total 500 100

Source: primary data

Table 4.12 depicts the information regarding number of times they had left the

company. Out of 500 employees 47.20% of the women employees left their company

twice, 27.80% of the women employees left their company thrice, 15.40% of the

women employees left their company only once and the remaining 9.60% of the

women employees left their company more than thrice. It is observed that 47.20% of

the women employees have left their company twice.

151

4.2.12 Reasons for leaving the company

Women employees working in software industry in Chennai were selected for

the study. Women employees have given reasons for leaving the previous companies.

Table 4.13 shows the reasons for leaving the previous companies.

Table 4.13

Reasons for leaving the company

Particulars Number of women

employees Percentage

Better Corporate Image 81 16.20

Family reasons 47 9.40

Financial Benefits 57 11.40

Promotion and better position 35 7.00

Work Pressure and stress 25 5.00

Team members pressure 45 9.00

Superior relationship is strained 26 5.20

Frustration in work 59 15.20

Travel woes 76 11.80

No recognition of work done 49 9.80

Total 500 100

Source: primary data

152

Table 4.13 depicts the reasons for leaving the previous companies. 16.20 % of

the women employees left the previous organizations for better corporate image.

15.20 % of the women employees left the previous organizations for frustration in

work. 11.80 % of the women employees left the previous organizations for travel

woes. 11.40 % of the women employees left the previous organizations for financial

benefits. 9.80 % of the women employees left the previous organizations for non-

recognition of work done. 9.40 % of the women employees left the previous

organizations for family reasons. 9.00 % of the women employees left the previous

organizations for pressure given by team members. 7.00 % of the women employees

left the previous organizations for promotion and better position. 5.20 % of the

women employees left the previous organizations for superior relationship are

strained. 5.00 % of the women employees left the previous organizations for work

pressure and stress. It is observed that 16.20 % of the women employees have left

their previous organizations for better corporate image.

153

4.2.13 Present family environment supporting the work

Women employees working in software industry in Chennai were selected for

the study. Women employees have given information regarding the opinion about

family environment supporting the work. Table 4.14 shows the opinion about family

environment support for the women employees working in software industry in

Chennai.

Table 4.14

Feeling about family environment supporting the work

Particulars Number of women

employees Percentage

Almost always 182 36.40

Frequently 263 52.60

Sometimes 55 11.00

Total 500 100

Source: primary data

Table 4.14 explores the information regarding family support given to the

women employees. Out of 500 employees 52.60% of the women employees felt that

they are getting family support frequently, 36.40% of the women employees

expressed that they are always getting family support and 11.00% of the women

employees felt that they get family support sometimes. It is observed 52.60% of the

women employees expressed that they are getting frequent family support.

154

4.2.14 Organization support for peaceful family life

Women employees working in software industry in Chennai were selected for

the study. Women employees have given information regarding the company support

extended to the women employees in peaceful family life. Table 4.15 shows the

information regarding the company support extended to the women employees in

software industry in Chennai.

Table 4.15

Organization support for peaceful family life

Number of women

employees Percentage

Almost always 170 34.00

Frequently 282 56.40

Sometimes 48 9.60

Total 500 100

Source: primary data

Table 4.15 depicts the information regarding the organization support

extended to the women employees for peaceful family life. Out of 500 employees

56.40% of the women employees expressed that they are getting frequent support

from the organization, 34.00% of the women employees felt that they are getting

support from the organization always and 9.60% of the women employees felt that

they are getting organization support sometimes. It is observed that 56.40% of the

women employees expressed that they are getting frequent support from organization.

155

4.2.15 Rating of organization

Women employees working in software industry in Chennai were selected for

the study. Women employees have given information regarding the rating of

organization. Table 4.16 shows the information regarding the ratting of current

organization.

Table 4.16

Rating of organization

Number of women

employees Percentage

One of the best 262 52.40

Above average 183 36.60

Average 54 10.80

Below average 1 0.20

Total 500 100

Source: primary data

Table 4.16 depicts the information regarding the ratting of current

organization. Out of 500 employees 52.40% of the women employees rated that their

organization as one of the best, 36.60% of the women employees rated that their

organization are rated above average, 10.80% of the women employees rated that

their organization as an average one and 0.20% of the women employees rated that

their organization below average. It is observed that 52.40% of the women employees

rated that their organization as one of the best in the industry.

156

4.2.16 Retaining in the same company

Women employees working in software industry in Chennai were selected for

the study. Women employees have given information regarding their decision to

retain themselves in the same company. Table 4.17 gives the information regarding

their decision in retaining in the same company.

Table 4.17

Retaining in the same company

Number of women

employees Percentage

Certainly 225 45.00

Probably 222 44.40

Not at all 53 10.60

Total 500 100

Source: primary data

Table 4.17 reveals the information regarding retaining the women employees

in the same company. Out of 500 employees 45.00% of the women employees

expressed that they are certainly retained in same company, 44.40% of the women

employees expressed that they are probably retained in same company and the

remaining 10.60% of the women employees expressed that they are not at all retained

in same company. 45.00% of the women employees expressed that they are certainly

retained in same company and they are not interested in quitting the company.

157

4.3 CONFIRMATORY FACTOR ANALYSIS

Confirmatory factor analysis was performed for Experiencing conflict at

family side, Experiencing conflict at work environment, Managing work life conflict

at family side, Managing work life conflict at work environment, Betterment of

Managing work life conflict at family and work environment, Feeling about present

family life and Feeling about present work environment by using Analysis of moment

structure (AMOS 16.1) to verify factor structure of the variables. The Goodness of fit

index ranges between 0 to 1 and closer to one point to a perfect fit model

(Joreskog&Sorbom, 1984). Root-Mean square error approximation (RMSEA) ranges

from 0 to 1 with a smaller value indicating a better model (Browne&Cudeek 1993).

Expected Cross Validation Index (ECVI) is an estimate of how well the result

obtained from one sample can be generalized to other samples. This measure always

remains positive and closer to zero indicating a better model (Browne&Cudeek 1993).

Chi square is sensitive to larger sample size and power of the test. Therefore it is

suggested the use of ratio of Chi square to degree of freedom. Carmines&Mclver

(1981) suggest that 2 to 1 or 3to 1 is indicative of acceptable model between

hypothetical model and sample data. Ratio approximately five or less is considered to

be reasonable (Wheaton, Muthen, Alwin& Summers 1977). The results of

Confirmatory factor analysis carried out for above said factors are displayed in the

table 4.18.

158

Table 4.18

Confirmatory factor analysis

Factors GFI AGFI RMSEA ECVI χ 2 d.f

Experiencing conflict at family side .891 .874 .068 2.748 3.236

Experiencing conflict at work

environment .901 .884 .086 2.349 4.157

Managing work- life conflict at family

side .903 .884 .093 1.083 3.214

Managing work- life conflict at work

environment .912 .902 .087 1.058 3.215

Betterment of Managing work- life

conflict at family and work environment .941 .915 .057 0.928 1.257

Feeling about present family life .901 .891 .078 0.978 2.587

Feeling about present work environment .921 .909 .098 1.001 2.214

The GFI for Experiencing at family side is .891 and the AGFI value is .874,

indicating a reasonably good fit, the RMSEA value is .068 which is within the range,

indicating a better model fit, the ECVI value is 2.748, which is positive and within the

limit, the Chi-square ratio value of this model is 3.236 indicating reasonably good fit.

(Refer Appendix I Figure 1)

The GFI value for Experiencing at work environment is .901 and AGFI value

is .884, indicating good fit, RMSEA value is .086 a smaller value indicating a better

model and ECVI is 2.349, which are within the acceptable range indicating a better

model fit, the Chi-square ratio value is 4.157 indicating reasonably good fit. (Refer

Appendix I Figure 2)

The GFI value for Managing work- life conflict at family side is .903 and

AGFI value is .884, indicating good fit, RMSEA value is .093, a smaller value

indicating a better model and ECVI is 1.083, which is positive and closer to zero

indicating a better model, the Chi-square ratio value is 3.214 indicating reasonably

good fit. (Refer Appendix I Figure 3)

159

The GFI for Managing work- life conflict at work environment is .912 and the

AGFI value is .902, indicating a reasonably good fit, the RMSEA value is .087 which

is within the range, indicating a better model fit, the ECVI value is 1.058, which is

positive and within the limit, the Chi-square ratio value of this model is 3.215

indicating reasonably good fit. (Refer Appendix I Figure 4)

The GFI value for Betterment of Managing work- life conflict at family and

work environment is .941 and AGFI value is .915, indicating good fit, RMSEA value

is .057 a smaller value indicating a better model and ECVI is .928, which are within

the acceptable range indicating a better model fit, the Chi-square ratio value is 1.257

indicating reasonably good fit. (Refer Appendix I Figure 5)

The GFI value for Feeling about present family life is .901 and AGFI value is

.891, indicating good fit, RMSEA value is .078, a smaller value indicating a better

model and ECVI is .978, which is positive and closer to zero indicating a better

model, the Chi-square ratio value is 2.587 indicating reasonably good fit. (Refer

Appendix I Figure 6)

The GFI for Feeling about present work environment is .921 and the AGFI

value is .909, indicating a reasonably good fit, the RMSEA value is .098 which is

within the range, indicating a better model fit, the ECVI value is 1.001, which is

positive and within the limit, the Chi-square ratio value of this model is 2.214

indicating reasonably good fit. (Refer Appendix I Figure 7)

4.4 Assessing the experience of conflict at family side of women

employees working in software industry in Chennai

One sample t-test is used to test the experience of conflict at family side of

selected women employees of software companies in Chennai. Experience level of

conflict of the employees were measured by eleven variables in various aspects. To

test the significant difference between the mean value of the variables measured under

experience level of conflict at family side of women employees in current

organization against the test average response of 3 (mean score). The following null

hypothesis was framed:

160

H01 (a): The experience level of conflict at family side of women employees

working in software industry do not differ with the average score.

Table 4.19 shows the results of t-test for variables measured to assess the

experience of conflict at family side of the women employees and average score.

Table 4.19

t-test for variables measured for assessing the experience level of

conflict at family side and average score

Statements Mean SD t-value

Away from family 3.75 .774 21.71**

Emotionally drained 3.90 .737 27.31**

Taking care of children 3.98 .791 27.83**

Time off 4.12 .868 28.94**

Long working hours 4.04 .872 26.78**

Difficult to fulfil responsibilities 3.83 .917 20.13**

Changes in family activities 3.49 1.031 10.53**

Taking care of elders 3.46 1.044 9.89**

Transport facilities 3.25 1.045 5.43**

Cooperation from my family 3.44 .879 11.19**

Working hours interferes with leisure hours 3.34 .889 8.55**

** Significant at 1% level

From table 4.19 significant difference is observed at 1% level between average

score and all the variables considered to assess the experience level of conflict at

161

family side of the women employees working in software industry. On observing the

mean values in table 4.19 women employees of software industry are experiencing

conflict at family side which is more than the average level.

4.5 Assessing the experience of conflict at work environment of

women employees working in software industry in Chennai

One sample t-test is used to test the experience of conflict at work environment

of selected women employees of software industry in Chennai. Experience level of

conflict of the employees were measured by fifteen variables in various aspects. To

test the significant difference between the mean value of the variables measured under

experience level at work environment of women employees in current organizations

against the test average response of 3 (mean score). The following null hypothesis

was framed:

H01 (b): The experience level of conflict at work environment of women

employees working in software industry do not differ with the average score.

Table 4.20 shows the results of t-test for variables measured to assess the

experience level of conflict at work environment of the women employees and

average score.

162

Table 4.20

t-test for variables measured for assessing the experience of conflict

at work environment and average score

Statements Mean SD t-value

Working hours Vs. standard hours 3.61 .881 15.49**

To adapt myself to shift work timing 3.70 .863 18.03**

Time owing to transport facilities 3.86 .918 20.95**

Manager support 3.78 1.037 16.78**

Cooperation of team members 3.63 .976 14.34**

Deadlines 3.44 .978 10.01**

Prepared to go onsite 3.53 .873 13.57**

Favourable of HR policies 3.56 .805 15.61**

Traveling time 3.64 .927 15.43**

Working environment 3.65 .952 15.22**

Health insurance 3.63 1.017 13.84**

Leave benefits 3.52 1.154 10.07**

Compensation benefits 3.59 .898 14.73**

Able to climb up in my career 3.56 .928 13.45**

Canteen facilities 3.39 .882 9.78**

Entertainment facilities 3.51 .944 12.02**

** Significant at 1% level

From table 4.20 significant difference is observed at 1% level between average

score and all the variables to assess the experience of conflict at work environment of

163

the women employees working in software companies. On observing the mean

values in table 4.20 women employees of software industry are experiencing conflict

at work environment which is more than the average level.

4.6 Important aspects of managing work- life conflict at family side

Women employees of software industry in Chennai experience conflict both at

family and work environment. Selected women employees working in software

industry in Chennai expressed their satisfaction level towards managing work- life

conflict at family side. Testing the significance of various aspects of managing work-

life conflict at family side, Friedman’s test for k-related samples was applied to study

the relationship between various aspects of managing work- life conflict at family

side.

Null hypothesis H0 2: All the aspects of managing work- life conflict at family

side gives equal satisfaction to the women employees.

164

Table 4.21

Friedman test for managing work- life conflict at family side

Mean

Rank

Chi square

Value

Happy with work 6.98

53.426**

(p<.001)

Physical and emotional satisfaction 7.29

Satisfaction level of children studies 7.05

To assist during morning hours 6.82

Able to spend time 7.01

Working hours does not interfere with spend at home 6.67

Able to fulfill my family responsibilities 6.58

Able to plan for family commitments 6.52

Able to take care my elders at home 6.63

Don’t have any hassles regarding transport facilities 7.15

Receive fullest cooperation from family 7.55

Able to have leisure hours to take children 7.53

Don’t have financial strain 7.23

** Significant at 1% level

The results in the table 4.21 shows that the null hypothesis H02is rejected at

1% level. All the aspects of managing work life conflict at family side do not give

equal satisfaction to the women employees.

Further the mean ranks in the table 4.21 shows clearly that “Receive fullest

cooperation from family” “Able to have leisure hours to take children” and “Physical

and emotional satisfaction” are the main aspects which brings good satisfaction to the

software professionals towards managing work- life conflict at family side. “Able to

plan for family commitments” “Able to fulfil my family responsibilities” and “Able

165

to take care my elders at home” are the factors that brings less satisfaction to the

software professionals towards managing work- life conflict at family side.

4.7 Important Aspects of Managing Work- Life Conflict at Work

Environment

Women employees of software industry in Chennai experience conflict both at

family and work environment. Selected women employees working in software

industry in Chennai expressed their satisfaction level towards managing work- life

conflict at work environment. Testing the significance of various aspects of

managing work- life conflict at work environment, Friedman’s test for k-related

samples was applied to study the relationship between various aspects of managing

work- life conflict at work environment.

Null hypothesis H03: All the aspects of managing work- life conflict at work

environment gives equal satisfaction to the women employees.

166

Table 4.22

Friedman test for managing work- life conflict at work environment

Mean

Rank

Chi square

value

Working hours are flexible 8.81

53.103**

(p<.001)

Shift timing are comfortable 8.30

Reach work spot in time 8.36

Support from manager 8.25

Able to work at ease with my team 8.08

Able to meet up with deadlines 9.05

Willing to go onsite 9.53

Happy with HR policies 9.73

Don’t have difficulty with traveling time 10.03

Working environment is comfortable 9.63

Insurance benefits 9.00

Job security 9.85

Able to avail leave benefits 9.86

Compensation is good 9.00

Recognition and promotion 8.26

Canteen facility 8.47

Relax in my job 8.77

** Significant at 1% level

The result in the table 4.22 shows that the null hypothesis H03is rejected at 1%

level. All the aspects of managing work life conflict at work environment do not give

equal satisfaction to the women employees.

167

Further the mean ranks in the table 4.22 shows clearly that “Don’t have

difficulty with traveling time”, “Able to avail leave benefits” and “Job security” are

the main aspects which brings good satisfaction to the software professionals towards

managing work- life conflict at work environment. “Able to work at ease with my

team”, “Support from manager” and “Recognition and promotion” are the aspect that

brings less satisfaction to the software professionals towards managing work- life

conflict at work environment.

4.8 Important Aspects of assessing the expectation of Women

Employees towards the betterment of Managing Work- Life

Conflict at family and work environment

Women employees of software industry in Chennai experience conflict both at

family and work environment. Selected women employees working in software

industry in Chennai expressed their expectation level towards betterment of managing

work- life conflict at family and work environment. Testing the significance of

various aspects of expectation for the betterment of work- life conflict at family and

work environment, Friedman’s test for k-related samples was applied to study the

relationship between various aspects of expectation for the betterment of managing

work- life conflict at family and work environment.

Null hypothesis H04: All the aspects considered for the betterment of managing

work- life conflict at work environment carry equal expectation among women

employees.

168

Table 4.23

Friedman test for betterment of managing- work life conflict at

family and work environment

Mean

Rank

Chi square

value

Demand of work never interfere with family life 4.90

49.015**

(p<.001)

Work time to fulfill family responsibility 5.69

No physical or mental strain 5.95

To expect support from managers 5.65

Part of organization because of culture and policies 5.50

Expect job security 5.38

Demands at home never interfere with job 5.52

Family strain never interfere with job 5.48

Never expect physical and financial strain 5.74

Sufficient time to spend with children 5.19

** Significant at 1% level

The results in the table4.23 shows that the null hypothesis H04 is rejected at

1% level. All the aspects considered for the betterment of managing work- life

conflict at work environment do not carry equal expectations among the women

employees.

Further the mean ranks in the table 4.23 shows clearly that “No physical or

mental strain”, “Never expect physical and financial strain” and “Work time to fulfil

family responsibility” are the main aspects which brings more expectation to the

software professionals towards betterment of managing work- life conflict at work

environment. “Demand of work never interferes with family life”, “Sufficient time to

spend with children” and “Expect job security” are the aspects that brings less

169

expectation to the software professionals towards betterment of managing work- life

conflict at family and work environment.

4.9 Assessing the Feeling about their present family life of women

Employees working in software industry in Chennai

One sample t-test is used to test the feeling about their present family life of

selected women employees of software industry in Chennai. The assessment of their

present life and their feeling towards it were measured by six variables in various

aspects. To test the significant difference between the mean value of the variables

measured with regard to their present family life of women employees in software

industry against the test average response of 3 (mean score). The following null

hypothesis was framed:

H05: The feeling of women employees in software industry with regard to their

present family life do not differ with the average score.

Table 4.24 shows the results of t-test for variables measured to assess the

feeling of women employees with regard to their present family life and average

score.

170

Table 4.24

t-test for variables measured for assessing the feeling about their

present family life and average score

Statements Mean SD t-value

Life close to ideal 3.49 .934 11.83**

Balance life and work 3.46 .979 10.55**

Physical and mental health is perfect 3.59 .848 15.66**

Stable financial position 3.62 1.031 13.48**

Adapt myself with family 3.62 .964 14.43**

Satisfied as a parent 3.67 .930 16.21**

** Significant at 1% level

From table 4.24 significant difference is observed at 1% level between average

score and all the variables considered to assess the feeling about their present family

life of women employees working in software industry. On observing the mean

values in table 4.24 women employees of software industry are having more

expectation with regard to their present family life which is more than the average

level.

4.10 Assessing the feeling about their present work environment of

women employees working in Software Industry in Chennai

One sample t-test is used to test the feeling of the women employees with

regard to their present work environment in software industry in Chennai. The

employees and their feeling about their present work environment were measured by

five variables in various aspects. To test the significant difference between the mean

171

value of the variables measured to assess the feeling of women employees with regard

to their present work environment in current organization against the test average

response of 3 (mean score). The following null hypothesis was framed:

H06: The feeling of women employees in their present work environment in

software industry do not differ with the average score.

Table 4.25 shows the results of t-test for variables measured to assess the

feeling of women employees in their present work environment and average score.

Table 4.25

t-test for variables measured to assess the feeling about their present

work environment and average score

Statements Mean SD t-value

Feel nervous and stressed in work 3.69 .949 16.15**

Depressed mood in work 3.67 .929 16.12**

Feel burn out at the end of the day in work 3.75 .935 17.88**

Never felt an intention to leave the company 3.71 .937 17.03**

Absented myself 3.75 .920 18.12**

** Significant at 1% level

From table 4.25 significant difference is observed at 1% level between average

score and all the variables considered to assess the feeling about their present work

environment of women employees working in software industry. On observing the

mean values in table 4.25 women employees of software industry are having more

expectation level in their present work environment which is more than the average

level.

172

4.11 Influence of Women Employees’ Demographics on Family Life

and Work Environment

4.11.1 Influence of women employees’ demographics on experiencing

Conflict in their family life

Testing the significant influence of women employees’ demographics (Age,

Marital status, Category of Job, Work experience, Educational qualification, Monthly

income and Working hours per week) on experiencing conflict in their family life.

Independent samples t-test was applied to ascertain if there is any significant

influence of women employees’ marital status on experiencing their family life. One

way ANOVA is applied to ascertain if there is any significant influence of women

employees’ age, category of job, work experience, educational qualification, monthly

income and working hours per week on experiencing conflict in their family life.

The following null hypotheses were framed:

H07: There is no significant influence of women employees’ demographics (a)

Age (b) Marital status (c) Category of Job (d) Work experience (e) Educational

qualification (f) Monthly income (g) Working hours per week on experiencing

conflict in their family life.

Table 4.26 shows the results of influence of women employees’ demographics

on experiencing conflict in their family life.

173

Table 4.26

Influence of women employees’ demographics on experiencing

conflict in their family life

N Mean S D t/ F values

Age

Below 25 years 134 26.55 4.282

F=5.290**

(p=.001)

25-35 years 140 25.15 3.909

36-45 years 132 24.90 3.709

Above 45 years 94 24.73 4.421

Marital status Single 125 25.21 4.069 t=0.539

(p=.590) Married 375 25.44 4.133

Category of job

Professional 254 25.63 4.912

F=0.978

(p=.377) Non professional 102 25.05 3.595

Others 144 25.18 2.648

Work experience

Less than 5 years 109 25.03 4.887

F=2.401

(p=.067)

5-10 years 267 25.70 3.570

11-15 years 72 25.62 3.303

Above 15 years 52 24.17 5.565

Educational

qualification

Graduate 213 25.93 4.323

F=5.681**

(p=.004) Post graduate 197 25.33 3.599

Professional degree 90 24.21 4.440

Monthly income

Less than Rs.20,000 132 26.18 4.693

F=3.031*

(p=.029)

Rs.20,001-40,000 199 25.37 3.646

Rs.40,001-50,000 113 24.92 3.319

Above Rs.50,000 56 24.50 5.294

Working hours

per week

35-39 hours 42 22.90 2.592

F=6.578**

(p<.001)

40-44 hours 259 25.35 4.156

45-49 hours 182 25.95 4.234

Above 50 hours 17 25.94 3.009

** Significant at 1% level * significant at 5% level

174

Age

The obtained 'F' value is 5.290 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ age on experiencing conflict

in their family life.

Further, the mean table 4.26 indicates that the employees having age below 25

years have scored higher mean value of 26.55 and the lowest mean was scored by the

employees having age above 45 years (24.73). This shows that the employees having

age below 25 years are experiencing more conflict and the employees with age above

45 years are experiencing lesser conflict in their family side.

Therefore, the formulated hypothesis H0 7(a) that “there is no significant

influence of employees’ age on experiencing their family life” is rejected.

Marital Status

The obtained’t’ value is 0.539 and it is not significant at 5% level. The value

indicates that there is no significant influence of employees’ marital status on

experiencing conflict in their family life.

Therefore, the formulated hypothesis H0 7(b) that “there is no significant

influence of employees’ marital status on experiencing conflict in their family life” is

accepted.

Category of job

The obtained 'F' value is 0.978 and it is not significant at 5% level. The value

indicates that there is no significant influence of employees’ category of job on

experiencing conflict in their family life.

Therefore, the formulated hypothesis H0 7(c) that “there is no significant

influence of employees’ category of job on experiencing conflict in their family life”

is accepted.

175

Work experience

The obtained 'F' value is 2.401 and it is not significant at 5% level. The value

indicates that there is no significant influence of employees’ work experience on

experiencing conflict in their family life.

Therefore, the formulated hypothesis H0 7(d) that “there is no significant

influence of employees’ work experience on experiencing conflict in their family life”

is accepted.

Educational Qualification

The obtained 'F' value is 5.681 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ educational qualification on

experiencing conflict in their family life.

Further, the mean table 4.26 indicates that the Graduates have scored higher

mean value of 25.93 and the lowest mean was scored by the employees possessing

professional degree in their educational qualification (24.21). This shows that the

employees possessing graduation are experiencing more conflict and the employees

with professional degree are experiencing lesser conflict in their family side.

Therefore, the formulated hypothesis H0 7(e) that “there is no significant

influence of employees’ qualification on experiencing their family life” is rejected.

Monthly income

The obtained 'F' value is 3.031 and it is significant at 5% level. The value

indicates that there is significant influence of employees’ monthly income on

experiencing conflict in their family life.

Further, the mean table 4.26 indicates that the employees earning monthly

income less than Rs. 20,000 have scored higher mean value of 26.18 and the lowest

mean was scored by the employees earning monthly income above Rs.50,000 (24.50).

This shows that the employees earning monthly income less than Rs. 20,000 are

experiencing conflict more in the family side than the employees earning monthly

income more than Rs. 50,000.

176

Therefore, the formulated hypothesis H0 7(f) that “there is no significant

influence of employees’ monthly income on experiencing their family life” is

rejected.

Working hours per week

The obtained 'F' value is 6.578 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ working hours per week on

experiencing conflict in their family life.

Further, the mean table 4.26 indicates that the employees working 45-49 hours

per week have scored higher mean value of 25.95 and the lowest mean was scored by

the employees working 35-39 hours per week (22.90). This shows that the employees

working 45-49 hours per week are more affected and experience conflict and the

employees working 35-39 hours per week are less affected and experience lesser

conflict towards their family side.

Therefore, the formulated hypothesis H0 7(g) that “there is no significant

influence of employees’ working hours per week on experiencing their family life” is

rejected.

177

4.11.2 Influence of women employees’ demographics on experiencing

conflict in their work environment

Testing the significant influence of women employees’ demographics (Age,

Marital status, Category of Job, Work experience, Educational qualification, Monthly

income and Working hours per week) on experiencing conflict in their work

environment. Independent samples t-test was applied to ascertain if there is any

significant influence of women employees’ marital status on experiencing conflict in

their work environment. One way ANOVA is applied to ascertain if there is any

significant influence of women employees’ age, category of job, work experience,

educational qualification, monthly income and working hours per week on

experiencing conflict in their work environment. The following null hypotheses were

framed:

H0 8: There is no significant influence of women employees’ demographics (a)

Age (b) Marital status (c) Category of Job (d) Work experience (e) Educational

qualification (f) Monthly income (g) Working hours per week on experiencing

conflict in the work environment.

Table 4.27 shows the results of influence of women employees’ demographics

on experiencing conflict in their work environment.

178

Table 4.27

Influence of women employees’ demographics on experiencing

conflict in their work environment

N Mean S D t/ F values

Age

Below 25 years 134 58.30 3.261

F=19.041**

(p<.001)

25-35 years 140 58.47 4.620

36-45 years 132 58.34 5.230

Above 45 years 94 54.15 6.414

Marital status Single 125 56.62 5.841 t=2.421*

(p=.016) Married 375 57.90 4.841

Category of job

Professional 254 57.55 5.691

F=0.532

(p=.588) Non professional 102 57.21 4.888

Others 144 57.89 4.190

Work experience

Less than 5 years 109 59.83 4.155

F=35.292**

(p<.001)

5-10 years 267 58.00 4.226

11-15 years 72 56.68 4.755

Above 15 years 52 51.94 7.160

Educational

qualification

Graduate 213 58.53 4.137

F=11.611**

(p<.001) Post graduate 197 57.49 4.666

Professional degree 90 55.50 7.241

Monthly income

Less than Rs.20,000 132 58.36 3.931

F=12.165**

(p<.001)

Rs.20,001-40,000 199 58.04 4.689

Rs.40,001-50,000 113 57.70 5.311

Above Rs.50,000 56 53.85 7.020

Working hours per

week

35-39 hours 42 61.71 3.351

F=17.435**

(p<.001)

40-44 hours 259 57.73 4.461

45-49 hours 182 56.89 5.529

Above 50 hours 17 52.47 6.911

** Significant at 1% level * significant at 5% level

179

Age

The obtained 'F' value is 19.041 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ age on experiencing conflict

in their work environment.

Further, the mean table 4.27 indicates that the employees having age of 25 - 35

years have scored higher mean value of 58.47 and the lowest mean was scored by the

employees having age of above 45 years (54.15). This shows that the employees

having age of 25 - 35 years are more affected and experience conflict and the

employees with age above 45 years are less affected and experience lesser conflict

towards their work environment in software industry in Chennai.

Therefore, the formulated hypothesis H0 8(a) that “there is no significant

influence of employees’ age on experiencing their work environment” is rejected.

Marital Status

The obtained’t’ value is 2.421 and it is significant at 5% level. The value

indicates that there is significant influence of employees’ marital status on

experiencing conflict in their work environment.

Further, the mean table 4.27 indicates that the married employees have scored

higher mean value of 57.90 than the employees living as single (56.62). This shows

that the married employees are more affected and experience more conflict and the

employees with marital status as single are less affected and experience lesser conflict

towards their work environment in software industry in Chennai.

Therefore, the formulated hypothesis H0 8(b) that “there is no significant

influence of employees’ marital status on experiencing conflict in their work

environment” is rejected.

Category of job

The obtained 'F' value is 0.532 and it is not significant at 5% level. The value

indicates that there is no significant influence of employees’ category of job on

experiencing conflict in their work environment.

180

Therefore, the formulated hypothesis H0 8(c) that “there is no significant

influence of employees’ category of job on experiencing conflict in their work

environment” is accepted.

Work experience

The obtained 'F' value is 35.292 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ work experience on

experiencing conflict in their work environment.

Further, the mean table 4.27 indicates that the employees with work

experience less than 5 years have scored higher mean value of 59.83 and the lowest

mean was scored by the employees with work experience more than 15 years (51.94).

This shows that the employees having work experience less than 5 years are more

affected and experience more conflict and the employees with work experience more

than 15 years are less affected and experience lesser conflict towards the work

environment in software industry in Chennai.

Therefore, the formulated hypothesis H08 (d) that “there is no significant

influence of employees’ work experience on experiencing conflict in their work

environment” is rejected.

Educational Qualification

The obtained 'F' value is 11.611 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ educational qualification on

experiencing conflict in their work environment.

Further, the mean table 4.27 indicates that the Graduates have scored higher

mean value of 58.53 and the lowest mean was scored by the employees possessing

professional degree (55.50). This shows that the graduates are more affected and

experience more conflict and the employees possessing professional degree are less

affected towards their work environment and experience lesser conflict in software

industry in Chennai.

Therefore, the formulated hypothesis H08 (e) that “there is no significant

influence of employees’ qualification on experiencing conflict in their work

environment” is rejected.

181

Monthly income

The obtained 'F' value is 12.165 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ monthly income on

experiencing conflict in their work environment.

Further, the mean table 4.27 indicates that the employees earning monthly

income less than Rs. 20,000 have scored higher mean value of 58.36 and the lowest

mean was scored by the employees earning monthly income more than Rs.50,000

(53.85). This shows that the employees earning monthly income less than Rs.20, 000

are more affected and experience more conflict and the employees earning monthly

income above Rs. 50,000 are less affected and experience lesser conflict towards the

work environment in software industry in Chennai.

Therefore, the formulated hypothesis H08 (f) that “there is no significant

influence of employees’ monthly income on experiencing conflict in their work

environment” is rejected.

Working hours per week

The obtained 'F' value is 17.435 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ working hours per week on

experiencing conflict in their work environment.

Further, the mean table 4.27 indicates that the employees working 35-39 hours

per week have scored higher mean value of 61.71 and the lowest mean was scored by

the employees working above 50 hours per week (52.47). This shows that the

employees working 35-39 hours per week are more affected and experience more

conflict and the employees working above 50 hours per week are less affected and

experience less conflict towards the work environment in software industry in

Chennai.

Therefore, the formulated hypothesis H08 (g) that “there is no significant

influence of employees’ working hours per week on experiencing conflict in their

work environment” is rejected.

182

4.11.3 Influence of women employees’ demographics on managing

work-life conflict at family side

Testing the significant influence of women employees’ demographics (Age,

Marital status, Category of Job, Work experience, Educational qualification, Monthly

income and Working hours per week) on managing work-life conflict at family side.

Independent samples t-test was applied to ascertain if there is any significant

influence of women employees’ marital status on managing work-life conflict at

family side. One way ANOVA is applied to ascertain if there is any significant

influence of women employees’ age, category of job, work experience, educational

qualification, monthly income and working hours per week on managing work-life

conflict at family side.

The following null hypotheses were framed:

H0 9: There is no significant influence of women employees’ demographics (a)

Age (b) Marital status (c) Category of Job (d) Work experience (e) Educational

qualification (f) Monthly income (g) Working hours per week on managing

work-life conflict at family side.

Table 4.28 shows the results of influence of women employees’ demographics

on managing work-life conflict at family side.

183

Table 4.28

Influence of women employees’ demographics on managing work-life

conflict at family side

N Mean S D t/ F values

Age

Below 25 years 134 46.75 5.477

F=3.365*

(p=.019)

25-35 years 140 46.96 4.050

36-45 years 132 47.03 4.069

Above 45 years 94 45.25 4.841

Marital status Single 125 46.64 4.680 t=0.122

(p=.903) Married 375 46.58 4.659

Category of job

Professional 254 47.46 5.563

F=4.904**

(p=.008) Non professional 102 45.99 3.361

Others 144 46.90 3.402

Work experience

Less than 5 years 109 47.88 4.983

F=11.339**

(p<.001)

5-10 years 267 46.68 4.321

11-15 years 72 46.62 3.901

Above 15 years 52 43.46 5.259

Educational

qualification

Graduate 213 46.70 5.095

F=2.465

(p=.086) Post graduate 197 46.93 3.747

Professional degree 90 45.64 5.273

Monthly income

Less than Rs.20,000 132 46.38 5.539

F=2.122

(p=.096)

Rs.20,001-40,000 199 46.94 4.176

Rs.40,001-50,000 113 46.91 3.379

Above Rs.50,000 56 45.28 5.950

Working hours

per week

35-39 hours 42 48.23 3.627

F=4.434**

(p=.004)

40-44 hours 259 46.96 4.029

45-49 hours 182 45.81 5.559

Above 50 hours 17 45.41 3.792

** Significant at 1% level

184

Age

The obtained 'F' value is 3.365 and it is significant at 5% level. The value

indicates that there is significant influence of employees’ age on managing work-life

conflict at family side.

Further, the mean table 4.28 indicates that the employees having age of 36 - 45

years have scored higher mean value of 47.03 and the lowest mean was scored by the

employees having age above 45 years (45.25). This shows that the employees having

age of 36 - 45 years are more able to manage the work-life conflict at family side and

the employees having age above 45 years are less able to manage the work-life

conflict at family side.

Therefore, the formulated hypothesis H0 9(a) that “there is no significant

influence of employees’ age on managing work-life conflict at family side” is

rejected.

Marital Status

The obtained 't' value is 0.122 and it is not significant at 5% level. The value

indicates that there is no significant influence of employees’ marital status on

managing work-life conflict at family side.

Therefore, the formulated hypothesis H0 9(b) that “there is no significant

influence of employees’ marital status on managing work-life conflict at family side”

is accepted.

Category of job

The obtained 'F' value is 4.904 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ category of job on managing

work-life conflict at family side.

Further, the mean table 4.28 indicates that the professionals have scored

higher mean value of 47.46 and the lowest mean was scored by the non-professionals

(45.99). This shows that the professionals are more able to manage the work-life

conflict at family side and the non-professionals are less able to manage the work-life

conflict at family side.

185

Therefore, the formulated hypothesis H0 9(c) that “there is no significant

influence of employees’ category of job on managing work-life conflict at family

side” is rejected.

Work experience

The obtained 'F' value is 11.339 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ work experience on

managing work-life conflict at family side.

Further, the mean table 4.28 indicates that the employees having work

experience less than 5 years have scored higher mean value of 47.88 and the lowest

mean was scored by the employees having work experience above 15 years (43.46).

This shows that the employees having work experience less than 5 years are more

able to manage the work-life conflict at family side and the employees with work

experience of above 15 years are less able to manage the work-life conflict at family

side.

Therefore, the formulated hypothesis H0 9(d) that “there is no significant

influence of employees’ work experience on managing work-life conflict at family

side” is rejected.

Educational Qualification

The obtained 'F' value is 2.465 and it is not significant at 5% level. The value

indicates that there is no significant influence of employees’ educational qualification

on managing work- life conflict at family side.

Therefore, the formulated hypothesis H0 9(e) that “there is no significant

influence of employees’ qualification on managing work-life conflict at family side”

is accepted.

Monthly income

The obtained 'F' value is 2.122 and it is not significant at 5% level. The value

indicates that there is no significant influence of employees’ monthly income on

managing work-life conflict at family side.

186

Therefore, the formulated hypothesis H0 9(f) that “there is no significant

influence of employees’ monthly income on managing work-life conflict at family

side” is accepted.

Working hours per week

The obtained 'F' value is 4.434 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ working hours per week on

managing work-life conflict at family side.

Further, the mean table 4.28 indicates that the employees working 35-39 hours

per week have scored higher mean value of 48.23 and the lowest mean was scored by

the employees working above 50 hours per week (45.41). This shows that the

employees working 35-39 hours per week are more able to manage the work-life

conflict at family side and the employees working more than 50 hours per week are

less able to manage the work-life conflict at family side.

Therefore, the formulated hypothesis H0 9(g) that “there is no significant

influence of employees’ working hours per week on managing work-life conflict at

family side” is rejected.

4.11.4 Influence of women employees’ demographics on managing

work-life conflict at work environment

Testing the significant influence of women employees’ demographics (Age,

Marital status, Category of Job, Work experience, Educational qualification, Monthly

income and Working hours per week) on managing work life conflict at work

environment. Independent samples t-test was applied to ascertain if there is any

significant influence of women employees’ marital status on managing work-life

conflict at work environment. One way ANOVA is applied to ascertain if there is any

significant influence of women employees’ age, category of job, work experience,

educational qualification, monthly income and working hours per week on managing

work-life conflict at work environment.

187

The following null hypotheses were framed:

H010: There is no significant influence of women employees’ demographics (a)

Age (b) Marital status (c) Category of Job (d) Work experience (e) Educational

qualification (f) Monthly income (g) Working hours per week on managing

work-life conflict at work environment.

Table 4.29 shows the results of influence of women employees’ demographics

on managing work-life conflict at work environment.

188

Table 4.29

Influence of women employees’ demographics on managing work-life

conflict at work environment

N Mean S D t/ F values

Age

Below 25 years 134 59.39 4.039

F=22.841**

(p<.001)

25-35 years 140 61.89 4.981

36-45 years 132 61.36 5.135

Above 45 years 94 56.91 5.759

Marital status Single 125 59.34 4.902 t=1.977*

(p=.049) Married 375 60.41 5.361

Category of job

Professional 254 59.68 6.054

F=2.245

(p=.107) Non professional 102 60.90 5.262

Others 144 60.43 3.392

Work experience

Less than 5 years 109 61.64 4.657

F=26.185**

(p<.001)

5-10 years 267 60.71 4.969

11-15 years 72 59.70 3.123

Above 15 years 52 54.69 6.775

Educational

qualification

Graduate 213 60.56 4.946

F=15.562**

(p<.001) Post graduate 197 60.92 4.536

Professional degree 90 57.44 6.537

Monthly income

Less than Rs.20,000 132 59.85 4.745

F=26.766**

(p<.001)

Rs.20,001-40,000 199 61.48 4.604

Rs.40,001-50,000 113 60.72 4.470

Above Rs.50,000 56 54.92 6.773

Working hours per

week

35-39 hours 42 63.71 4.019

F=8.006**

(p<.001)

40-44 hours 259 59.84 4.801

45-49 hours 182 59.95 6.009

Above 50 hours 17 58.05 1.819

** Significant at 1% level * significant at 1% level

189

Age

The obtained 'F' value is 22.841 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ age on managing work-life

conflict at work environment.

Further, the mean table 4.29 indicates that the employees having age of 25 - 35

years have scored higher mean value of 61.89 and the lowest mean was scored by the

employees having age above 45 years (56.91). This shows that the employees having

age of 25 - 35 years are more able to manage the work-life conflict at work

environment and the employees with age above 45 years are less able to manage the

work-life conflict at work environment.

Therefore, the formulated hypothesis H010 (a) that “there is no significant

influence of employees’ age on managing work-life conflict at work environment” is

rejected.

Marital Status

The obtained 't' value is 1.977 and it is significant at 5% level. The value

indicates that there is significant influence of employees’ marital status on managing

work-life conflict at work environment.

Further, the mean table 4.29 indicates that the married employees have scored

higher mean value of 60.41 than the employees living as single (59.34). This shows

that the married employees are more able to manage the work-life conflict at work

environment than the employees living as single.

Therefore, the formulated hypothesis H010 (b) that “there is no significant

influence of employees’ marital status on managing work-life conflict at work

environment” is rejected.

Category of job

The obtained 'F' value is 2.245 and it is not significant at 5% level. The value

indicates that there is no significant influence of employees’ category of job on

managing work-life conflict at work environment.

190

Therefore, the formulated hypothesis H010(c) that “there is no significant

influence of employees’ category of job on managing work-life conflict at work

environment” is accepted.

Work experience

The obtained 'F' value is 26.185 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ work experience on

managing work-life conflict at work environment.

Further, the mean table 4.29 indicates that the employees having work

experience less than 5 years have scored higher mean value of 61.64 and the lowest

mean was scored by the employees with work experience of above 15 years (54.69).

This shows that the employees with work experience less than 5 years are more able

to manage the work life conflict at work environment and the employees with work

experience above 15 years are less able to manage the work-life conflict at work

environment.

Therefore, the formulated hypothesis H010 (d) that “there is no significant

influence of employees’ work experience on managing work-life conflict at work

environment” is rejected.

Educational Qualification

The obtained 'F' value is 15.562 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ educational qualification on

managing work-life conflict at work environment.

Further, the mean table 4.29 indicates that the employees possessing post-

graduation have scored higher mean value of 60.92 and the lowest mean was scored

by the employees possessing professional degree as their educational qualification

(57.44). This shows that the employees possessing post-graduation are more able to

manage the work-life conflict at work environment and the employees possessing

professional degree are less able to manage the work-life conflict at work

environment.

191

Therefore, the formulated hypothesis H010 (e) that “there is no significant

influence of employees’ qualification on managing work-life conflict at work

environment” is rejected.

Monthly income

The obtained 'F' value is 26.766 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ monthly income on

managing work-life conflict at work environment.

Further, the mean table 4.29 indicates that the employees earning monthly

income of Rs. 20,001 - Rs. 40,000 have scored higher mean value of 61.48 and the

lowest mean was scored by the employees earning monthly income above Rs. 50,000

(54.92). This shows that the employees earning monthly income of Rs. 20,001 to Rs.

40,000 are more able to manage the work life conflict at work environment and the

employees earning monthly income of above Rs. 50,000 are less able to manage the

work-life conflict at work environment.

Therefore, the formulated hypothesis H010 (f) that “there is no significant

influence of employees’ monthly income on managing work-life conflict at work

environment” is rejected.

Working hours per week

The obtained 'F' value is 8.006 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ working hours per week on

managing work-life conflict at work environment.

Further, the mean table 4.29 indicates that the employees working 35-39 hours

per week have scored higher mean value of 63.71 and the lowest mean was scored by

the employees working above 50 hours per week (58.05). This shows that the

employees working 35-39 hours per week are more able to manage the work-life

conflict at work environment and the employees working above 50 hours per week

are less able to manage the work-life conflict at work environment.

Therefore, the formulated hypothesis H010 (g) that “there is no significant

influence of employees’ working hours per week on managing work-life conflict at

work environment” is rejected.

192

4.11.5 Influence of women employees’ demographics on betterment

of managing work-life conflict at family and work

environment

Testing the significant influence of women employees’ demographics (Age,

Marital status, Category of Job, Work experience, Educational qualification, Monthly

income and Working hours per week) on betterment of managing work-life conflict at

family and work environment. Independent samples t-test was applied to ascertain if

there is any significant influence of women employees’ marital status on betterment

of managing work-life conflict at family and work environment. One way ANOVA is

applied to ascertain if there is any significant influence of women employees’ age,

category of job, work experience, educational qualification, monthly income and

working hours per week on betterment of managing work-life conflict at family and

work environment.

The following null hypotheses were framed:

H011: There is no significant influence of women employees’ demographics (a)

Age (b) Marital status (c) Category of Job (d) Work experience (e) Educational

qualification (f) Monthly income (g) Working hours per week on betterment of

managing work-life conflict at family and work environment.

Table 4.30 shows the results of influence of women employees’ demographics

on betterment of managing work-life conflict at family and work environment.

193

Table 4.30

Influence of women employees’ demographics on betterment of

managing work-life conflict at family and work environment

N Mean S D t/ F values

Age

Below 25 years 134 37.46 3.910

F=14.254**

(p<.001)

25-35 years 140 36.63 3.656

36-45 years 132 35.74 3.533

Above 45 years 94 34.42 3.300

Marital status Single 125 34.72 3.278 t=5.187**

(p<.001) Married 375 36.69 3.802

Category of job

Professional 254 36.96 3.930

F=5.929**

(p=.003) Non professional 102 35.31 3.092

Others 144 36.13 3.798

Work experience

Less than 5 years 109 37.30 4.001

F=16.197**

(p<.001)

5-10 years 267 36.64 3.557

11-15 years 72 34.26 3.305

Above 15 years 52 34.34 3.423

Educational

qualification

Graduate 213 37.09 3.921

F=11.545**

(p<.001) Post graduate 197 35.72 3.698

Professional degree 90 35.15 3.082

Monthly income

Less than Rs.20,000 132 37.32 3.880

F=7.191**

(p<.001)

Rs.20,001-40,000 199 36.19 3.941

Rs.40,001-50,000 113 35.48 3.705

Above Rs.50,000 56 35.07 1.998

Working hours

per week

35-39 hours 42 38.76 3.274

F=17.949**

(p<.001)

40-44 hours 259 36.54 3.305

45-49 hours 182 35.53 3.848

Above 50 hours 17 31.94 5.413

** Significant at 1% level

194

Age

The obtained 'F' value is 14.254 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ age on betterment of

managing work-life conflict at family and work environment.

Further, the mean table 4.30 indicates that the employees having age below 25

years have scored higher mean value of 37.46 and the lowest mean was scored by the

employees having age above 45 years (34.42). This shows that the employees having

age below 25 years are expecting more betterment in managing work-life conflict and

employees having age above 45 years are expecting less betterment in managing

work-life conflict.

Therefore, the formulated hypothesis H011 (a) that “there is no significant

influence of employees’ age on betterment of managing work-life conflict at family

and work environment” is rejected.

Marital Status

The obtained 't' value is 5.187 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ marital status on betterment

of managing work-life conflict at family and work environment.

Further, the mean table 4.30 indicates that the married employees have scored

higher mean value of 36.69 than the employees living as single (34.72). This shows

that the married employees are expecting more betterment in managing work-life

conflict than the employees living as single.

Therefore, the formulated hypothesis H0 11(b) that “there is no significant

influence of employees’ marital status on betterment of managing work-life conflict at

family and work environment” is rejected.

Category of job

The obtained 'F' value is 5.929 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ category of job on

betterment of managing work-life conflict at family and work environment.

Further, the mean table 4.30 indicates that the employees working in

Professional category have scored higher mean value of 36.96 and the lowest mean

195

was scored by the employees working in non-professional category (35.31). This

shows that the employees working in professional category are expecting more

betterment in managing work-life conflict and the employees working in

nonprofessional category are expecting less betterment in managing work-life

conflict.

Therefore, the formulated hypothesis H0 11(c) that “there is no significant

influence of employees’ category of job on betterment of managing work-life conflict

at family and work environment” is rejected.

Work experience

The obtained 'F' value is 16.197 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ work experience on

betterment of managing work- life conflict at family and work environment.

Further, the mean table 4.30 indicates that the employees having work

experience less than 5 years have scored higher mean value of 37.30 and the lowest

mean was scored by the employees with work experience of 11 - 15 years (34.26).

This shows that the employees having work experience less than 5 years are expecting

more betterment in managing work-life conflict and the employees with work

experience of 11 - 15 years are expecting less betterment in managing work-life

conflict.

Therefore, the formulated hypothesis H0 11(d) that “there is no significant

influence of employees’ work experience on betterment of managing work-life

conflict at family and work environment” is rejected.

Educational Qualification

The obtained 'F' value is 11.545 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ educational qualification on

betterment of managing work-life conflict at family and work environment.

Further, the mean table 4.30 indicates that the graduates have scored higher

mean value of 37.09 and the lowest mean was scored by the employees possessing

professional degree as their educational qualification (35.15). This shows that the

graduates are expecting more betterment in managing work-life conflict and the

196

employees possessing professional degree as their educational qualification are

expecting less betterment in managing work-life conflict.

Therefore, the formulated hypothesis H0 11(e) that “there is no significant

influence of employees’ qualification on betterment of managing work-life conflict at

family and work environment” is rejected.

Monthly income

The obtained 'F' value is 7.191 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ monthly income on

betterment of managing work- life conflict at family and work environment.

Further, the mean table 4.30 indicates that the employees earning monthly

income less than Rs. 20,000 have scored higher mean value of 37.32 and the lowest

mean was scored by the employees earning monthly income of above Rs. 50,000

(35.07). This shows that the employees earning monthly income less than Rs. 20,000

are expecting more betterment in managing work- life conflict and the employees

earning monthly income of above Rs. 50,000 are expecting more betterment in

managing work-life conflict.

Therefore, the formulated hypothesis H0 11(f) that “there is no significant

influence of employees’ monthly income on betterment of managing work life

conflict at family and work environment” is rejected.

Working hours per week

The obtained 'F' value is 17.949 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ working hours per week on

betterment of managing work life conflict at family and work environment.

Further, the mean table 4.30 indicates that the employees working 35-39 hours

per week have scored higher mean value of 38.76 and the lowest mean was scored by

the employees working more than 50 hours per week (31.94). This shows that the

employees working 35-39 hours per week are expecting more betterment in managing

work-life conflict and the employees working above 50 hours per week are expecting

less betterment in managing work-life conflict.

197

Therefore, the formulated hypothesis H011 (g) that “there is no significant

influence of employees’ working hours per week on betterment of managing work-

life conflict at family and work environment” is rejected.

4.11.6 Influence of women employees’ demographics on feeling

about their present family life

Testing the significant influence of women employees’ demographics (Age,

Marital status, Category of Job, Work experience, Educational qualification, Monthly

income and Working hours per week) on feeling about their present family life.

Independent samples t-test was applied to ascertain if there is any significant

influence of women employees’ marital status on feeling about their present family

life. One way ANOVA is applied to ascertain if there is any significant influence of

women employees’ age, category of job, work experience, educational qualification,

monthly income and working hours per week on feeling about their present family

life. The following null hypotheses were framed:

H012: There is no significant influence of women employees’ demographics (a)

Age (b) Marital status (c) Category of Job (d) Work experience (e) Educational

qualification (f) Monthly income (g) Working hours per week on feeling about

their present family life.

Table 4.31 shows the results of influence of women employees’ demographics

on feeling about their present family life.

198

Table 4.31

Influence of women employees’ demographics on feeling about their present

family life

N Mean S D t/ F values

Age

Below 25 years 134 20.56 2.984

F=0.445

(p=.722)

25-35 years 140 21.82 2.428

36-45 years 132 22.12 2.450

Above 45 years 94 21.26 2.333

Marital status Single 125 21.28 2.535 t=0.899

(p=.369) Married 375 21.52 2.678

Category of job

Professional 254 21.58 2.656

F=2.568

(p=.078) Non professional 102 21.74 2.841

Others 144 21.05 2.437

Work experience

Less than 5 years 109 22.09 2.110

F=2.836*

(p=.038)

5-10 years 267 21.29 2.837

11-15 years 72 21.12 2.787

Above 15 years 52 21.48 2.227

Educational

qualification

Graduate 213 21.52 2.802

F=0.421

(p=.657) Post graduate 197 21.50 2.621

Professional degree 90 21.23 2.293

Monthly income

Less than Rs.20,000 132 21.09 3.125

F=1.245

(p=.293)

Rs.20,001-40,000 199 21.52 2.637

Rs.40,001-50,000 113 21.65 2.313

Above Rs.50,000 56 21.71 1.923

Working hours

per week

35-39 hours 42 22.59 2.142

F=3.048*

(p=.028)

40-44 hours 259 21.37 2.729

45-49 hours 182 21.29 2.608

Above 50 hours 17 21.82 2.242

*significant 5% level

199

Age

The obtained 'F' value is 0.445 and it is not significant at 5% level. The value

indicates that there is no significant influence of employees’ age on feeling about their

present family life.

Therefore, the formulated hypothesis H012 (a) that “there is no significant

influence of employees’ age on feeling about their present family life” is accepted.

Marital Status

The obtained 't' value is 0.899 and it is not significant at 5% level. The value

indicates that there is no significant influence of employees’ marital status on feeling

about their present family life.

Therefore, the formulated hypothesis H012 (b) that “there is no significant

influence of employees’ marital status on feeling about their present family life” is

accepted.

Category of job

The obtained 'F' value is 2.568 and it is not significant at 5% level. The value

indicates that there is no significant influence of employees’ category of job on

feeling about their present family life.

Therefore, the formulated hypothesis H012(c) that “there is no significant

influence of employees’ category of job on feeling about their present family life” is

accepted.

Work experience

The obtained 'F' value is 2.836 and it is significant at 5% level. The value

indicates that there is significant influence of employees’ work experience on feeling

about their present family life.

Further, the mean table 4.31 indicates that the women employees having work

experience less than 5 years have scored higher mean value of 22.09 and the lowest

mean was scored by the employees with work experience of 11 – 15 years (21.12).

This shows that the employees having work experience less than 5 years are more

comfortable and the employees with work experience of 11 – 15 years are less

200

comfortable towards the present family life of women employees working in software

companies in Chennai.

Therefore, the formulated hypothesis H012 (d) that “there is no significant

influence of employees’ work experience on feeling about their present family life” is

rejected.

Educational Qualification

The obtained 'F' value is 0.421 and it is not significant at 5% level. The value

indicates that there is no significant influence of employees’ educational qualification

on feeling about their present family life.

Therefore, the formulated hypothesis H012 (e) that “there is no significant

influence of employees’ qualification on feeling about their present family life” is

accepted.

Monthly income

The obtained 'F' value is 1.245 and it is not significant at 5% level. The value

indicates that there is no significant influence of employees’ monthly income on

feeling about their present family life.

Therefore, the formulated hypothesis H012 (f) that “there is no significant

influence of employees’ monthly income on feeling about their present family life” is

accepted.

Working hours per week

The obtained 'F' value is 3.048 and it is significant at 5% level. The value

indicates that there is significant influence of employees’ working hours per week on

feeling about their present family life.

Further, the mean table 4.31 indicates that the employees working 35-39 hours

per week have scored higher mean value of 22.59 and the lowest mean was scored by

the employees working 45-49 hours per week (21.29). This shows that the employees

working 35-39 hours per week are more comfortable and the employees working 45-

201

49 hours per week are less comfortable towards their present family life of women

employees working in software companies in Chennai.

Therefore, the formulated hypothesis H012 (g) that “there is no significant

influence of employees’ working hours per week on feeling about their present family

life” is rejected.

4.11.7 Influence of women employees’ demographics on feeling

about their present work environment

Testing the significant influence of women employees’ demographics (Age,

Marital status, Category of Job, Work experience, Educational qualification, Monthly

income and Working hours per week) on feeling about their present work

environment. Independent samples t-test was applied to ascertain if there is any

significant influence of women employees’ marital status on feeling about their

present work environment. One way ANOVA is applied to ascertain if there is any

significant influence of women employees’ age, category of job, work experience,

educational qualification, monthly income and working hours per week on feeling

about their present work environment. The following null hypotheses were framed:

H013: There is no significant influence of women employees’ demographics (a)

Age (b) Marital status (c) Category of Job (d) Work experience (e) Educational

qualification (f) Monthly income (g) Working hours per week on feeling about

their present work environment.

Table 4.32 shows the results of influence of women employees’ demographics

on feeling about their present work environment.

202

Table 4.32

Influence of women employees’ demographics on feeling about their

present work environment

N Mean S D t/ F values

Age

Below 25 years 134 18.88 1.839

F=2.077

(p=.102)

25-35 years 140 18.64 2.234

36-45 years 132 18.18 2.455

Above 45 years 94 18.53 2.834

Marital status Single 125 18.17 2.511 t=2.155*

(p=.032) Married 375 18.69 2.258

Category of job

Professional 254 18.59 2.283

F=0.560

(p=.572) Non professional 102 18.35 2.403

Others 144 18.65 2.374

Work experience

Less than 5 years 109 18.65 1.959

F=1.830

(p=.141)

5-10 years 267 18.52 2.187

11-15 years 72 18.97 2.483

Above 15 years 52 18.00 3.313

Educational

qualification

Graduate 213 18.76 2.035

F=1.450

(p=.235) Post graduate 197 18.38 2.384

Professional degree 90 18.48 2.817

Monthly income

Less than Rs.20,000 132 21.09 3.125

F=1.245

(p=.293)

Rs.20,001-40,000 199 21.52 2.637

Rs.40,001-50,000 113 21.65 2.313

Above Rs.50,000 56 21.71 1.923

Working hours per

week

35-39 hours 42 19.21 1.457

F=15.758**

(p<.001)

40-44 hours 259 18.27 2.360

45-49 hours 182 19.09 2.205

Above 50 hours 17 15.64 2.148

** Significant at 1% level * significant at 5% level

203

Age

The obtained 'F' value is 2.077 and it is not significant at 5% level. The value

indicates that there is no significant influence of employees’ age on feeling about their

present work environment.

Therefore, the formulated hypothesis H013 (a) that “there is no significant

influence of employees’ age on feeling about their present work environment” is

accepted.

Marital Status

The obtained 't' value is 2.155 and it is significant at 5% level. The value

indicates that there is significant influence of employees’ marital status on feeling

about their present work environment.

Further, the mean table 4.32 indicates that the married employees have scored

higher mean value of 18.69 than the employees living as single (18.17). This shows

that the married employees are more comfortable than the employees living as single

are less comfortable towards the present work environment in software companies in

Chennai.

Therefore, the formulated hypothesis H013 (b) that “there is no significant

influence of employees’ marital status on feeling about their present work

environment” is rejected.

Category of job

The obtained 'F' value is 0.560 and it is not significant at 5% level. The value

indicates that there is no significant influence of employees’ category of job on

feeling about their present work environment.

Therefore, the formulated hypothesis H013(c) that “there is no significant

influence of employees’ category of job on feeling about their present work

environment” is accepted.

204

Work experience

The obtained 'F' value is 1.830 and it is not significant at 5% level. The value

indicates that there is no significant influence of employees’ work experience on

feeling about their present work environment.

Therefore, the formulated hypothesis H0 13(d) that “there is no significant

influence of employees’ work experience on feeling about their present work

environment” is accepted.

Educational Qualification

The obtained 'F' value is 1.450 and it is not significant at 5% level. The value

indicates that there is no significant influence of employees’ educational qualification

on feeling about their present work environment.

Therefore, the formulated hypothesis H013 (e) that “there is no significant

influence of employees’ qualification on feeling about their present work

environment” is accepted.

Monthly income

The obtained 'F' value is 1.245 and it is not significant at 5% level. The value

indicates that there is no significant influence of employees’ monthly income on

feeling about their present work environment.

Therefore, the formulated hypothesis H013 (f) that “there is no significant

influence of employees’ monthly income on feeling about their present work

environment” is accepted.

Working hours per week

The obtained 'F' value is 15.758 and it is significant at 1% level. The value

indicates that there is significant influence of employees’ working hours per week on

feeling about their present work environment.

Further, the mean table 4.32 indicates that the employees working 35-39 hours

per week have scored higher mean value of 19.21 and the lowest mean was scored by

the employees working more than 50 hours per week (15.64). This shows that the

employees working 35-39 hours per week are more comfortable and the employees

205

working more than 50 hours per week are less comfortable towards the present work

environment in software companies in Chennai.

Therefore, the formulated hypothesis H013 (g) that “there is no significant

influence of employees’ working hours per week on feeling about their present work

environment” is rejected.

4.12 FRUSTRATION IN JOB IN SOFTWARE INDUSTRY

4.12.1 Association between family support and frustration in job.

Null hypothesis H014: There is no significant relationship between family

support and frustration in job

To assess the relationship between family support and frustration in job, Chi-

square test was performed to identify the relationship between family support and

frustration in job. The results are shown in table 4.33

206

Table 4.33

Association between family support and frustration in job

Frustration in job

Total Chi-square

Value Yes No

Family

support

Almost

always

N 174 8 182

16.684**

(p < .001)

% 34.80 1.60 36.40

Frequently N 233 30 263

% 46.60 6.00 52.60

Sometimes N 50 5 55

% 10.00 1.00 11.00

Total N 457 48 500

% 91.40 8.60 100.00

** Significant at 1% level

From the table 4.33 it is observed that there is significant association between

family support and frustration in job. Chi-square value (16.684) shows that the null

hypothesis is rejected at 1% level. It is found from the analysis that there is a close

association between family support and frustration in job. From the table 4.34 it is

evident that most of the women employees (46.60%) having frequent support from

the family are frustrated in the job.

4.12.2 Association between feel about company support and

frustration in job.

Null hypothesis H015: There is no significant relationship between organization

support and frustration in job

To assess the relationship between organization support and frustration in job,

Chi-square test was performed to identify the relationship between feel organization

support and frustration in job. The results are shown in table 4.34

207

Table 4.34

Association between organization support and frustration in job

Frustrated in job

Total Chi-square

Value Yes No

Feel about

company

support

Almost

always

N 163 7 170

12.151**

(p = .002)

% 32.60 1.40 34.00

Frequently N 242 30 282

% 48.40 6.00 56.40

Sometimes N 42 6 48

% 8.40 1.20 9.60

Total N 457 43 500

% 91.40 8.60 100.00

** Significant at 1% level

From the table 4.34 it is observed that there is significant association between

feel about company support and frustration in job. Chi-square value (12.151) shows

that the null hypothesis is rejected at 1% level. It is found from the analysis that there

is a close association between organization support and frustration in job. From the

table 4.34 it is evident that most of the women employees (48.40%) having

organization support are still frustrated in their job.

4.12.3 Association between retaining in same company and

frustration in job.

Null hypothesis H016: There is no significant relationship between the intention

to retain in the same organization and frustration in job

To assess the relationship between the intention to retain in the same

organization and frustration in job, Chi-square test was performed to identify the

relationship between intention to retain in the same organization and frustration in

job. The results are shown in table 4.35

208

Table 4.35

Association between the intention to retain in the same organization

and frustration in job

Frustrated in job

Total Chi-square

Value Yes No

Retaining in

same company

Certainly N 196 29 225

10.431**

(p = .005)

% 39.20 5.80 45.00

Probably N 215 7 222

% 43.00 1.40 44.40

Not at all N 46 7 53

% 9.20 1.40 10.60

Total N 457 43 500

% 91.40 8.60 100.00

** Significant at 1% level

From the table 4.35 it is observed that there is significant association between

the intention to retain in the same organization and frustration in job. Chi- square

value (10.431) shows that the null hypothesis is rejected at 1% level. It is found from

the analysis that there is a close association between the intention to retain in the same

organization and frustration in job. From the table 4.35 it is evident that most of the

women employees (43.00%) who are frustrated in job probably possess the intention

to retain in the same organization.

4.12.4 Association between experiencing conflict at family and

frustration in job.

Null hypothesis H017: There is no significant relationship between experiencing

conflict at family and frustration in job

209

To assess the relationship between experiencing conflict at family and

frustration in job, Chi-square test was performed to identify the relationship between

experiencing conflict at family and frustration in job. The results are shown in table

4.36

Table 4.36

Association between experiencing conflict at family and

Frustration in job

Frustrated in job

Total Chi-square

value Yes No

Experiencing

conflict at

family

Poor N 161 6 167

15.174**

(p = .001)

% 32.20 1.20 33.40

Fair N 133 9 142

% 26.60 1.80 28.40

Good N 163 28 191

% 32.60 5.60 38.20

Total N 457 43 500

% 91.40 8.60 100.00

** Significant at 1% level

From the table 4.36 it is observed that there is significant association between

experiencing conflict at family and frustration in job. Chi- square value (15.174)

shows that the null hypothesis is rejected at 1% level. It is found from the analysis

that there is a close association between experiencing conflict at family and frustration

in job. From the table 4.36 it is evident that most of the women employees (32.60%)

having good experience of conflict in family are frustrated in job.

210

4.12.5 Association between experiencing conflict at Work

environment and frustration in job.

Null hypothesis H018: There is no significant relationship between experiencing

conflict at Work environment and frustration in job

To assess the relationship between experiencing conflict at Work environment

and frustration in job, Chi-square test was performed to identify the relationship

between experiencing conflict at Work environment and frustration in job. The results

are shown in table 4.37

Table 4.37

Association between experiencing conflict at Work environment and

frustration in job

Frustrated in job

Total Chi-square

value Yes No

Experiencing

conflict at

Work

environment

Poor N 143 7 150

17.354**

(p < .001)

% 28.60 1.40 30.00

Fair N 165 17 182

% 33.00 3.40 36.40

Good N 149 19 168

% 29.80 3.80 33.60

Total N 457 43 500

% 91.40 8.60 100.00

** Significant at 1% level

211

From the table 4.37 it is observed that there is significant association between

experiencing conflict at Work environment and frustration in job. Chi- square value

(17.354) shows that the null hypothesis is rejected at 1% level. It is found from the

analysis that there is a close association between experiencing conflict at Work

environment and frustration in job. From the table 4.37 it is evident that most of the

women employees (33.00%) having fair experience of conflict at work environment

are frustrated in job.

4.12.6 Association between Work-life conflict at family side and

frustration in job.

Null hypothesis H019: There is no significant relationship between Work-life

conflict at family side and frustration in job

To assess the relationship between Work-life conflict at family side and

frustration in job, Chi-square test was performed to identify the relationship between

Work-life conflict at family side and frustration in job. The results are shown in table

4.38

Table 4.38

Association between Work-life conflict at family side and

Frustration in job

Frustrated in job

Total Chi-square

value Yes No

Work- life conflict

at family side

High N 201 8 209

31.864**

(p < .001)

% 40.20 1.60 41.80

Medium N 108 7 115

% 21.60 1.40 23.00

Low N 148 28 176

% 29.60 5.60 35.20

Total N 457 43 500

% 91.40 8.60 100.00

** Significant at 1% level

212

From the table 4.38 it is observed that there is significant association between

Work-life conflict at family side and frustration in job. Chi- square value (31.864)

shows that the null hypothesis is rejected at 1% level. It is found from the analysis

that there is a close association between Work-life conflict at family side and

frustration in job. From the table 4.38 it is evident that most of the women employees

(40.20%) having high conflict at family side are frustrated in job.

4.12.7 Association between Work-life conflict at Work

environment and frustration in job.

Null hypothesis H020: There is no significant relationship between Work-life

conflict at Work environment and frustration in job

To assess the relationship between Work-life conflict at Work environment

and frustration in job, Chi-square test was performed to identify the relationship

between Work-life conflict at Work environment and frustration in job. The results

are shown in table 4.39

Table 4.39

Association between Work-life conflict at Work environment and

frustration in job

Particulars Frustrated in job

Total Chi-square

value Yes No

Work-life conflict

at Work

environment

Low N 127 8 135

10.461**

(p = .005)

% 25.4 1.60 27.00

Medium N 158 11 169

% 31.6 2.2 33.80

High N 172 24 196

% 34.40 4.80 39.20

Total N 457 43 500

% 91.40 8.60 100.00

** Significant at 1% level

213

From the table 4.39 it is observed that there is significant association between

Work-life conflict at Work environment and frustration in job. Chi- square value

(10.461) shows that the null hypothesis is rejected at 1% level. It is found from the

analysis that there is a close association between Work-life conflict at Work

environment and frustration in job. From the table 4.39 it is evident that most of the

women employees (34.40%) having high conflict at Work environment are having

frustration at job.

4.12.8 Association between age and frustration in job.

Null hypothesis H021: There is no significant relationship between age and

frustration in job

To assess the relationship between age and frustration in job, Chi-square test

was performed to identify the relationship between age and frustration in job. The

results are shown in table 4.40

Table 4.40

Association between age and frustration in job

Particulars Frustrated in job

Total Chi-square

value Yes No

Age

Below 25 years N 120 14 134

3.812

(p = .283)

% 24.00 2.80 26.80

25-35 years N 125 15 140

% 25.00 3.00 28.00

36-45 years N 124 8 132

% 24.80 1.60 26.40

Above 45

years

N 88 6 94

% 17.6 1.20 18.80

Total N 457 43 500

% 91.40 8.60 100.00

214

From the table 4.40 it is observed that there is no significant association

between age and frustration in job. Chi- square value (3.812) shows that the null

hypothesis is accepted at 5% level. It is found from the analysis that there is no

relationship between age and frustration in job.

4.12.9 Association between marital status and frustration in job.

Null hypothesis H022: There is no significant relationship between marital status

and frustration in job

To assess the relationship between marital status and frustration in job, Chi-

square test was performed to identify the relationship between marital status and

frustration in job. The results are shown in table4.41.

Table 4.41

Association between marital status and frustration in job

Particulars Frustrated in job

Total Chi-square

value Yes No

Marital

status

Single N 119 6 125

3.062

(p = .080)

% 23.80 1.20 25.00

Married N 338 37 375

% 67.60 7.40 75.00

Total N 457 43 500

% 91.40 8.60 100.00

From the table 4.41 it is observed that there is no significant association

between marital status and frustration in job. Chi- square value (3.062) shows that the

null hypothesis is accepted at 5% level. It is found from the analysis that there is no

relationship between marital status and frustration in job.

215

4.12.10 Association between Category of job and frustration in job.

Null hypothesis H023: There is no significant relationship between Category of

job and frustration in job

To assess the relationship between Category of job and frustration in job, Chi-

square test was performed to identify the relationship between Category of job and

frustration in job. The results are shown in table 4.42

Table 4.42

Association between Category of job and frustration in job

Frustrated in job

Total Chi-square

Value Yes No

Category

of

job

Professional N 235 19 254

4.150

(p = .126)

% 47.00 3.80 50.80

Non professional N 96 6 102

0 19.20 1.20 20.40

Others N 126 18 144

% 25.20 3.60 28.80

Total N 457 43 500

% 91.40 8.60 100.00

From the table 4.42 it is observed that there is no significant association

between Category of job and frustration in job. Chi- square value (4.150) shows that

the null hypothesis is accepted at 5% level. It is found from the analysis that there is

no relationship between Category of job and frustration in job.

216

4.12.11 Association between work experience and frustration in job

Null hypothesis H024: There is no significant relationship between work

experience and frustration in job

To assess the relationship between work experience and frustration in job,

Chi-square test was performed to identify the relationship between work experience

and frustration in job. The results are shown in table 4.43.

Table 4.43

Association between work experience and frustration in job

Frustrated in job

Total Chi-square

Value Yes No

Work

experience

Less than 5

years

N 94 15 109

24.846**

(p < .001)

% 18.8 3.00 21.8

5-10 years N 250 17 267

% 50.00 3.40 53.40

11-15 years N 67 5 72

% 13.40 1.00 14.40

Above 15 years N 46 6 52

% 9.20 1.20 10.40

Total N 457 43 500

% 91.40 8.60 100.00

** Significant at 1% level

From the table 4.43 it is observed that there is significant association between

work experience and frustration in job. Chi- square value (24.846) shows that the null

hypothesis is rejected at 1% level. It is found from the analysis that there is a close

association between work experience and frustration in job. From the table 4.43 it is

evident that most of the women employees (50.00%) with work experience of 5-10

years are frustrated in job.

217

4.12.12 Association between Educational qualification and

frustration in job

Null hypothesis H025: There is no significant relationship between Educational

qualification and frustration in job

To assess the relationship between Educational qualification and frustration in

job, Chi-square test was performed to identify the relationship between Educational

qualification and frustration in job. The results are shown in table 4.44

Table 4.44

Association between Educational qualification and frustration in job

Frustrated in job

Total Chi-square

Value Yes No

Educational

qualification

Graduate N 186 27 213

9.675**

(p = .008)

% 37.20 5.40 42.60

Post graduate N 189 8 197

% 37.80 1.60 39.40

Professional

degree

N 82 8 90

% 16.40 1.60 18.00

Total N 457 43 500

% 91.40 8.60 100.00

** Significant at 1% level

From the table 4.44 it is observed that there is significant association between

Educational qualification and frustration in job. Chi- square value (9.675) shows that

the null hypothesis is rejected at 1% level. It is found from the analysis that there is a

close association between Educational qualification and frustration in job. From the

table 4.44 it is evident that most of the women employees (37.80%) having non-

professional degree are frustrated in job.

218

4.12.13 Association between monthly income and frustration in job

Null hypothesis H026: There is no significant relationship between monthly

income and frustration in job

To assess the relationship between monthly income and frustration in job, Chi-

square test was performed to identify the relationship between monthly income and

frustration in job. The results are shown in table 4.45

Table 4.45

Association between monthly income and frustration in job

Frustrated in job

Total Chi-square

Value Yes No

Monthly

income

Less than

Rs.20,000

N 108 18 132

13.424**

(p = .004)

% 21.60 4.8 26.40

Rs.20,001-

40,000

N 185 14 199

% 37.00 2.80 39.80

Rs.40,001-

50,000

N 108 5 113

% 21.6 1.00 22.60

Above

Rs.50,000

N 50 6 56

% 10.00 1.20 11.20

Total N 457 43 500

% 91.40 8.60 100.00

** Significant at 1% level

219

From the table 4.45 it is observed that there is significant association between

monthly income and frustration in job. Chi- square value (13.424) shows that the null

hypothesis is rejected at 1% level. It is found from the analysis that there is a close

association between monthly income and frustration in job. From the table 4.45 it is

evident that most of the women employees (37.00%) earning Rs.20, 001-40,000 are

frustrated in job.

4.12.14 Association between working hours per week and

frustration in job

Null hypothesis H027: There is no significant relationship between working

hours per week and frustration in job

To assess the relationship between working hours per week and frustration in

job, Chi-square test was performed to identify the relationship between working hours

per week and frustration in job. The results are shown in table 4.46

220

Table 4.46

Association between working hours per week and frustration in job

Frustrated in job

Total Chi-square

Value Yes No

Working hours

per week

35-39 hours N 28 14 42

42.364**

(p < .001)

% 5.60 2.80 8.40

40-44 hours N 241 18 259

% 48.20 3.60 51.80

45-49 hours N 177 5 182

% 35.40 1.00 36.40

Above 50 hours N 11 6 17

% 2.20 1.20 3.40

Total N 457 43 500

% 91.40 8.60 100.00

** Significant at 1% level

From the table 4.46 it is observed that there is significant association between

working hours per week and frustration in job. Chi- square value (42.364) shows that

the null hypothesis is rejected at 1% level. It is found from the analysis that there is a

close association between working hours per week and frustration in job. From the

table 4.46 it is evident that most of the women employees (48.20%) working 40-44

hours per week are frustrated in job.

4.12.15 Association between working in shift and frustration in job

Null hypothesis H028: There is no significant relationship between working in

shift and frustration in job

To assess the relationship between working in shift and frustration in job, Chi-

square test was performed to identify the relationship between working in shift and

frustration in job. The results are shown in table 4.47.

221

Table 4.47

Association between working in shift and frustration in job

Frustrated in job

Total Chi-square

value Yes No

Working in

shift

Yes N 362 37 399

1.139

(p = .286)

% 72.40 7.40 79.80

No N 95 6 101

% 19.00 1.20 20.20

Total N 457 43 500

% 91.40 8.60 100.00

From the table 4.47 it is observed that there is no significant association

between working in shift and frustration in job. Chi- square value (1.139) shows that

the null hypothesis is accepted at 5% level. It is found from the analysis that there is

no relationship between working in shift and frustration in job.

4.12.16 Association between job related travel and frustration in job

Null hypothesis H029: There is no significant relationship between job related

travel and frustration in job

To assess the relationship between job related travel and frustration in job,

Chi-square test was performed to identify the relationship between job related travel

and frustration in job. The results are shown in table 4.48.

222

Table 4.48

Association between job related travel and frustration in job

Frustrated in job

Total Chi-square

value Yes No

Job related

travel

Yes N 289 30 319

0.725

(p = .394)

% 57.80 6.00 63.80

No N 168 13 181

% 33.60 2.60 36.20

Total N 457 43 500

% 91.40 8.60 100.00

From the table 4.48 it is observed that there is no significant association

between job related travel and frustration in job. Chi- square value (0.725) shows that

the null hypothesis is accepted at 5% level. It is found from the analysis that there is

no relationship between job related travel and frustration in job.

4.12.17 Association between full time employee and frustration in

job

Null hypothesis H030: There is no significant relationship between full time

employee and frustration in job

To assess the relationship between full time employee and frustration in job,

Chi-square test was performed to identify the relationship between full time employee

and frustration in job. The results are shown in table 4.49.

223

Table 4.49

Association between full time employee and frustration in job

Frustrated in job

Total Chi-square

value Yes No

Full time

employee

Yes N 404 19 423

59.979**

(p < .001)

% 80.80 3.80 84.60

No N 53 24 77

% 10.60 4.80 15.40

Total N 457 43 500

% 91.40 8.60 100.00

** Significant at 1% level

From the table 4.49 it is observed that there is significant association between

full time employee and frustration in job. Chi- square value (59.979) shows that the

null hypothesis is rejected at 1% level. It is found from the analysis that there is a

close association between full time employee and frustration in job. From the table

4.49 it is evident that most of the women employees (80.80) working as full time

employees are frustrated in job.

4.13 Correlation Analysis for Family Life and Work Life

4.13.1 Correlation analysis for family life

224

Table 4.50

Correlation analysis for family life

Experiencing

conflict at

Family side

Managing Work life

conflict at family side

Managing Work-life conflict at

family side

r =.566**

1

p < .001

Betterment of managing work-life

conflict at family and work

environment

r =.554**

r =.424**

p < .001 p < .001

** Significant at 1% level

Positive significant correlation was observed between Experiencing conflict

at Family side and Managing Work-life conflict at family side (r = .566), which is

good relationship and it shows that management of work-life conflict at family side

has improved women employees’ family life by 56.6% in software industry in

Chennai.

Significant correlation was observed between Experiencing conflict at Family

side and Betterment of managing work- life conflict at family and work environment

(r = .554), which is a positive relationship and it shows that Betterment of managing

work-life conflict at family and work environment will improve women employees’

family life by 55.4% in software industry in Chennai.

Positive significant correlation was observed between Managing Work-life

conflict at family side and Betterment of managing work-life conflict at family and

work environment (r = .424), which shows that Betterment of managing work-life

conflict at family and work environment will help women employees to manage

work-life conflict at family side by 42.4% in software industry in Chennai.

225

4.13.2 Correlation analysis for work life

Table 4.51

Correlation analysis for work life

Experiencing

conflict at Work

environment

Managing Work life

conflict at Work

environment

Managing Work life conflict at

Work environment

r =.688**

1

p < .001

Betterment of managing work

life conflict at family and work

environment

r =.487**

r =.433**

p < .001 p < .001

** Significant at 1% level

Positive significant correlation was observed between Experiencing conflict

at work environment and Managing Work-life conflict at work environment (r =

.688), which is good relationship and it shows that management of work-life conflict

at work environment has improved women employees’ work life by 68.8% in

software industry in Chennai.

Significant correlation was observed between Experiencing conflict at work

environment and Betterment of managing work-life conflict at family and work

environment (r = .487), which is a positive relationship and it shows that Betterment

of managing work-life conflict at family and work environment will improve women

employees’ work life by 48.7% in software industry in Chennai.

Positive significant correlation was observed between Managing Work-life

conflict at work environment and Betterment of work-life conflict at family and work

environment (r = .433), which shows that Betterment of managing work-life conflict

at family and work environment will help women employees to manage work-life

conflict at work environment by 43.3% in software industry in Chennai.

226

4.14 Assessing the predictor variable for rating of Organization

Multiple regression analysis was conducted by taking rating of organization in

software industry as dependent variable and experiencing conflict at family,

experiencing conflict at work environment, managing work-life conflict at family

side, managing work-life conflict at work environment, betterment of managing work-

life conflict at family and work environment, retaining in same company and working

hours per week were taken as independent variable (shown in the table 4.52)

Table 4.52

Regression analysis for rating of organization in software industry

R2

Standard

Beta

F

t- value

Experiencing conflict at family

Experiencing conflict at work environment

Managing work-life conflict at family side

Managing work-life conflict at work

environment

Betterment of managing work-life conflict at

family and work environment

Retaining in same company

Working hours per week

0.389

0.057

-0.327

0.358

0.314

0.412

0.514

-0.324

31.391**

1.643

3.134**

3.876**

4.258**

3.587**

3.147**

2.147*

Adjusted

R2

0.371

** significant at 1% level * significant at 1% level

It is observed from the table 4.52, the regression model’s F value is 31.391

and it is significant at 1% level. The regression model’s coefficient of determination

(R2) is 0.389 and its adjusted R

2is 0.371, which is a healthy coefficient. One unit

decrease in experiencing at work environment leads to 0.389 unit decrease in rating of

organization. This shows that experiencing conflict at work environment serves as a

significant predictor for rating of organization. One unit increase in managing work-

life conflict at family side increases 0.358 units in rating of organization. This shows

227

that managing work-life conflict at family side serves as a significant predictor for

ratting of organization. One unit increase in managing work-life conflict at work

environment increases 0.314 units in rating of organization. This shows that

managing work-life conflict at work environment serves as a significant predictor for

rating of organization. Betterment of managing work-life conflict at family and work

environment serves as a significant predictor and improves rating the organization by

0.412 units. Retaining themselves in the same organization serves as a significant

predictor and improves rating of organization by 0.514 units and working hours per

week serves as a significant predictor for rating of organization and decreases rating

of organization by 0.371 units. Experiencing conflict at family is not serving as

significant predictor for rating of organization in software industry.

The regression equation of rating of organization in software industry

Rating of organization in software industry = 3.457 – 0.327 (Experiencing at work

environment) + 0.358 (Managing work-life conflict at family side) + 0.314 (Managing

work-life conflict at work environment) + 0.412 (Betterment of managing work-life

conflict at family and work environment) + 0.514 (Retaining in same company) -

0.324 (Working hours per week)

Hence experiencing at work environment, managing work-life conflict at

family side, managing work-life conflict at work environment, betterment of

managing work-life conflict at family and work environment, Retaining in same

company and Working hours per week serves as significant predictors.

228

4.15 Model for Managing Work-Life Conflict in Software Industry

Structural equation modeling (SEM) is a statistical technique for testing and

estimating causal relations using a combination of statistical data and qualitative

causal assumptions. This definition of SEM was articulated by the geneticist Sewall

Wright (1921), the economist TrygveHaavelmo (1943) and the cognitive scientist

Herbert Simon (1953), and formally defined by Judea Pearl (2000) using a calculus of

counterfactuals.

SEM allows both confirmatory and exploratory modeling, meaning they are

suited to both theory testing and theory development. Confirmatory modeling usually

starts out with a hypothesis that gets represented in a causal model. The concepts used

in the model must then be operationalized to allow testing of the relationships

between the concepts in the model. The model is tested against the obtained

measurement data to determine how well the model fits the data. The causal

assumptions embedded in the model often have falsifiable implications which can be

tested against the data.

With an initial theory SEM can be used inductively by specifying a

corresponding model and using data to estimate the values of free parameters. Often

the initial hypothesis requires adjustment in light of model evidence. When SEM is

used purely for exploration, this is usually in the context of exploratory factor analysis

as in psychometric design.

A model was developed by using analysis of moment structure (AMOS 16.1).

A model is fit to manage work-life conflict in software companies in Chennai. In the

model factors such as experiencing conflict at family, experiencing conflict at work

environment, managing work-life conflict at family side, managing work-life conflict

at work environment, betterment of managing work-life conflict and employee’s well-

being are taken as observed variables. e1, e2, e3, e4, e5 and e6 are error terms

(residuals) for observed variables.

229

Null Hypothesis H031: The model fitted for managing work-life conflict in

software industry in Chennai is good.

Figure 4.1: Model for managing work-life conflict in software industry in

Chennai

Model fit Summary

The model fit Chi-square 2 = 2.103 and the model’s p-value is .127 which is

insignificant at 5% level, which shows that the null hypothesis “The model fitted for

managing work life conflict in software companies in Chennai is good” is

accepted. The goodness of fit index (GFI) is .921 of the model, shows reasonably

good fit, and its adjusted goodness of fit (AGFI) is .903. The Root Mean Square Error

of Approximation (RMSEA) is .071, a smaller value indicates better model, and

Expected Cross Validation Index (ECVI) is .091, which are within the acceptable

range indicating a better model fit.

230

Figure 4.2: Experiencing conflict at family side

231

231: Experiencing conflict at work environment

232

Figure 4.3 : Managing work-life conflict at family side

233

Figure 4.5: Managing work- life conflict at work environment

234

Figure 4.6: Betterment of managing work life conflict at family and work environment

235

Figure 4.7: Present family life

236

Figure 4.8: Present work environment

237

CHAPTER V

FINDINGS, SUGGESTIONS AND CONCLUSION

Women employees working in software industry in Chennai city were selected

for the study. Experiencing conflict in their family life and work life, management of

work-life conflict in family life and work-life conflict in work life, betterment of

managing work-life conflict and family-life conflict, present family life and present

work life were analyzed in detail in the previous chapter. The study includes 500

selected women employees working in software industry in Chennai who have

participated and expressed their views on work-family conflict. Women entrepreneurs

were selected and the responses were collected in the form of well-structured

questionnaire and personal interviews were conducted to get their opinions. The

results found in the previous chapter are displayed in this chapter.

5.1 Findings

5.1.1 Profile of women employees

Most of the women employees (28.00%) working in software industry in

Chennai are in the age group of 25 - 35 years.

Majority of the selected women employees (75.00%) working in software

industry in Chennai were married.

Most of the women employees (50.80%) working in software industry in

Chennai are working in the professional category.

Majority of the women employees (53.40%) working in software industry

in Chennai are having work experience of 5 – 10 years.

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Majority of the women employees (42.60%) working in software industry

in Chennai are graduates.

Majority of the women employees (39.80%) in software industry in

Chennai are earning Rs. 20,001 - Rs. 40,000 per month.

Most of the women employees (51.80%) working in software industry in

Chennai are working 40-44 hours per week.

Majority of the women employees’ spouse (71.20%) are employed in

organizations.

Most of the women employees (99.00%) are having children.

Most of the women employees (44.40%) are having children with age of

5-10 years.

69.00% of the women employees working in software industry are having

dependents at home.

84.20% of the women employees working in software industry are getting

domestic help at home.

84.60% of the women employees are working as full time employees.

79.80% of the women employees in software industry are working in

shifts.

63.80% of the women employees are engaged with job related travelling in

software industry.

91.40% of the women employees expressed that they are frustrated in job

in software industry in Chennai.

Most of women employees (19.25%) are frustrated due to work pressure in

software companies in Chennai.

47.20% of the women employees have left their company twice.

16.20 % of the women employees have left their previous organizations

for better corporate image.

52.60% of the women employees expressed that they are getting frequent

family support.

56.40% of the women employees expressed that they are getting frequent

support from organization.

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52.40% of the women employees rated that their organization as one of the

best in the industry.

45.00% of the women employees expressed that they are certainly

interested to retain themselves in the same company and they are not

interested in quitting the company.

5.1.2 Confirmatory Factor Analysis

The GFI for experiencing conflict at family side is .891 and the AGFI value is

.874, indicating a good fit.

The GFI value for experiencing conflict at work environment is .901 and

AGFI value is .884, shows the fit is good.

The GFI value for managing work-life conflict at family side is .903 and AGFI

value is .884, indicating a good fit.

The GFI for managing work-life conflict at work environment is .912 and the

AGFI value is .902, which shows good fit.

The GFI value for Betterment of Managing work-life conflict at family and

work environment is .941 and AGFI value is .915, indicating a good fit.

The GFI value for Feeling about present family life is .901 and AGFI value is

.891, indicating good fit, RMSEA value is .078, a smaller value indicating a

better fit.

The GFI for Feeling about present work environment is .921 and the AGFI

value is .909, indicating the fit is good.

5.1.3 Family side and work environment

Women employees of software industry are experiencing conflict at family

side which is more than the average level.

Women employees of software industry are experiencing conflict at work

environment which is more than the average level.

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“Receive fullest cooperation from family”, “Able to have leisure hours to take

children” and “Physical and emotional satisfaction” are the main aspects

which brings good satisfaction to the software professionals towards managing

work-life conflict at family side. “Able to plan for family commitments”,

“Able to fulfil my family responsibilities” and “Able to take care my elders at

home” are the factors that bring less satisfaction to the software professionals

towards managing work-life conflict at family side.

“Don’t have difficulty with traveling time”, “Able to avail leave benefits” and

“Job security” are the main aspects which brings good satisfaction to the

software professionals towards managing work-life conflict at work

environment. “Able to work at ease with my team”, “Support from manager”

and “Recognition and promotion” are the aspect that brings less satisfaction to

the software professionals towards managing work-life conflict at work

environment.

“No physical or mental strain”, “Never expect physical and financial strain”

and “Work time to fulfil family responsibility” are the main aspects which

brings more expectation to the software professionals towards betterment of

managing work-life conflict at work environment. “Demand of work never

interferes with family life”, “Sufficient time to spend with children” and

“Expect job security” are the aspect that brings less expectation to the software

professionals towards betterment of managing work-life conflict at family and

work environment.

Women employees of software industry are having more expectation level in

present family life which is more than the average level.

Women employees of software industry are having more expectation level in

present work environment which is more than the average level.

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5.1.4 Influence of Women employees’ demographics on Family life

and work environment

5.1.4.1 Experiencing conflict in their family life

Significant influence of employees’ age on experiencing conflict in their

family life is observed. Employees having age below 25 years are more

affected and experience more conflict and the employees with age above 45

years are less affected and experience less conflict towards their family side.

Significant influence of employees’ marital status on experiencing conflict in

their family life is not observed.

Significant influence of employees’ category of job on experiencing conflict in

their family life is not observed.

Significant influence of employees’ work experience on experiencing conflict

in their family life is not observed.

Significant influence of employees’ educational qualification on experiencing

conflict in their family life is observed. Employees possessing graduation are

more affected and experience more conflict and the employees with

professional degree are less affected and experience lesser conflict towards

their family side.

Significant influence of employees’ monthly income on experiencing conflict

in their family life is observed. Employees earning monthly income less than

Rest. 20,000 are more affected and experience more conflict and the

employees earning monthly income more than Rs. 50,000 are less affected and

experience lesser conflict towards their family side.

Significant influence of employees’ working hours per week on experiencing

their family life is observed. Employees working 45-49 hours per week are

more affected and experience more conflict and the employees working 35-39

hours per week are less affected and experience lesser conflict towards their

family side.

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5.1.4.2 Experiencing conflict in their work environment

Significant influence of employees’ age on experiencing conflict in their work

environment is observed. Employees having age of 25 - 35 years are more

affected and experience more conflict in their work and the employees with

age above 45 years are less affected and experience lesser conflict towards

their work environment in software industry in Chennai.

Significant influence of employees’ marital status on experiencing conflict in

their work environment is observed. Married employees are more affected and

experience more conflict and the employees with marital status as single are

less affected towards their work environment in software industry in Chennai.

Significant influence of employees’ category of job on experiencing their

work environment is not observed.

Significant influence of employees’ work experience on experiencing conflict

in their work environment is observed. Employees having work experience

less than 5 years are more affected and experience more conflict and the

employees with work experience more than 15 years are less affected and

experience lesser conflict towards the work environment in software industry

in Chennai.

Significant influence of employees’ educational qualification on experiencing

their work environment is observed. Graduates are more affected and

experience more conflict and the employees possessing professional degree

are less affected and experience lesser conflict towards their work

environment in software industry in Chennai.

Significant influence of employees’ monthly income on experiencing conflict

in their work environment is observed. Employees earning monthly income

less than Rs.20, 000 are more affected and experience more conflict and the

employees earning monthly income above Rs. 50,000 are less affected and

experience lesser conflict towards the work environment in software industry

in Chennai.

Significant influence of employees’ working hours per week on experiencing

conflict in their work environment is observed. Employees working 35-39

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hours per week are more affected and experience more conflict and the

employees working above 50 hours per week are less affected and experience

lesser conflict towards the work environment in software industry in Chennai.

5.1.4.3 Managing work-life conflict at family side

Significant influence of employees’ age on managing work-life conflict at

family side is observed. Employees having age of 36 - 45 years are more able

to manage the work-life conflict at family side and the employees having age

above 45 years are less able to manage the work-life conflict at family side.

Significant influence of employees’ marital status on managing work-life

conflict at family side is not observed.

Significant influence of employees’ category of job on managing work-life

conflict at family side is observed. Professionals are more able to manage the

work-life conflict at family side and the non-professionals are less able to

manage the work-life conflict at family side.

Significant influence of employees’ work experience on managing work-life

conflict at family side is observed. Employees having work experience less

than 5 years are more able to manage the work-life conflict at family side and

the employees with work experience of above 15 years are less able to manage

the work-life conflict at family side.

Significant influence of employees’ educational qualification on managing

work life conflict at family side is not observed.

Significant influence of employees’ monthly income on managing work-life

conflict at family side is not observed.

Significant influence of employees’ working hours per week on managing

work-life conflict at family side is observed. Employees working 35-39 hours

per week are more able to manage the work-life conflict at family side and the

employees working more than 50 hours per week are less able to manage the

work-life conflict at family side.

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5.1.4.4 Managing work life conflict at work environment

Significant influence of employees’ age on managing work-life conflict at

work environment is observed. Employees having age of 25 - 35 years are

more able to manage the work-life conflict at work environment and the

employees with age above 45 years are less able to manage the work-life

conflict at work environment.

Significant influence of employees’ marital status on managing work-life

conflict at work environment is observed. Married employees are more able to

manage the work-life conflict at work environment than the employees living

as single.

Significant influence of employees’ category of job on managing work-life

conflict at work environment is not observed.

Significant influence of employees’ work experience on managing work-life

conflict at work environment is observed. Employees with work experience

less than 5 years are more able to manage the work-life conflict at work

environment and the employees with work experience above 15 years are less

able to manage the work-life conflict at work environment.

Significant influence of employees’ educational qualification on managing

work-life conflict at work environment is observed. Employees possessing

post-graduation are more able to manage the work-life conflict at work

environment and the employees possessing professional degree are less able to

manage the work-life conflict at work environment.

Significant influence of employees’ monthly income on managing work-life

conflict at work environment is observed. Employees earning monthly income

of Rs. 20,001 to Rs. 40,000 are more able to manage the work--life conflict at

work environment and the employees earning monthly income of above Rs.

50,000 are less able to manage the work-life conflict at work environment.

Significant influence of employees’ working hours per week on managing

work-life conflict at work environment is observed. Employees working 35-39

hours per week are more able to manage the work-life conflict at work

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environment and the employees working above 50 hours per week are less

able to manage the work-life conflict at work environment.

5.1.4.5 Betterment of managing work-life conflict at family and work

environment

Significant influence of employees’ age on betterment of managing work-life

conflict at family and work environment is observed. Employees having age

below 25 years are expecting more in the betterment of managing work-life

conflict and employees having age above 45 years are expecting lesser in the

betterment of managing work-life conflict.

Significant influence of employees’ marital status on betterment of managing

work life conflict at family and work environment is observed. Married

employees are expecting more in the betterment of managing work-life

conflict than the employees living as single.

Significant influence of employees’ category of job on betterment of

managing work-life conflict at family and work environment is observed.

Employees working in professional category are expecting more in the

betterment of managing work-life conflict and the employees working in non-

professional category are expecting less betterment in managing work-life

conflict.

Significant influence of employees’ work experience on betterment of

managing work- life conflict at family and work environment is observed.

Employees having work experience less than 5 years are expecting more in the

betterment of managing work-life conflict and the employees with work

experience of 11 - 15 years are expecting lesser in the betterment of managing

work-life conflict.

Significant influence of employees’ educational qualification on betterment of

managing work-life conflict at family and work environment is observed.

Graduates are expecting more in the betterment of managing work-life conflict

and the employees possessing professional degree as their educational

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qualification are expecting lesser in the betterment of managing work-life

conflict.

Significant influence of employees’ monthly income on betterment of

managing work- life conflict at family and work environment is observed.

Employees earning monthly income less than Rs. 20,000 are expecting more

in the betterment of managing work-life conflict and the employees earning

monthly income of above Rs. 50,000 are expecting lesser in the betterment of

managing work-life conflict.

Significant influence of employees’ working hours per week on betterment of

managing work-life conflict at family and work environment is observed.

Employees working 35-39 hours per week are expecting more in the

betterment of managing work-life conflict and the employees working above

50 hours per week are expecting lesser in the betterment of managing work-

life conflict.

5.1.4.6 Present family life

Significant influence of employees’ age on feeling about their present family

life is not observed.

Significant influence of employees’ marital status on feeling about their

present family life is not observed.

Significant influence of employees’ category of job on feeling about their

present family life is not observed.

Significant influence of employees’ work experience on feeling about their

present family life is observed. Employees having work experience less than 5

years are more comfortable and the employees with work experience of 11 –

15 years are less comfortable towards the present family life of women

employees working in software industry in Chennai.

Significant influence of employees’ educational qualification on feeling about

their present family life is not observed.

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Significant influence of employees’ monthly income on feeling about their

present family life is not observed.

Significant influence of employees’ working hours per week on feeling about

their present family life is observed. Employees working 35-39 hours per

week are more comfortable and the employees working 45-49 hours per week

are less comfortable towards their present family life of women employees

working in software industry in Chennai.

5.1.4.7 Present work environment

Significant influence of employees’ age on feeling about their present work

environment is not observed.

Significant influence of employees’ marital status on feeling about their

present work environment is observed. Married employees are more

comfortable than the employees living as single are less comfortable towards

the present work environment in software industry in Chennai.

Significant influence of employees’ category of job on feeling about their

present work environment is not observed.

Significant influence of employees’ work experience on feeling about their

present work environment is not observed.

Significant influence of employees’ educational qualification on feeling about

their present work environment is not observed.

Significant influence of employees’ monthly income on feeling about their

present work environment is not observed.

Significant influence of employees’ working hours per week on feeling about

their present work environment is observed. Employees working 35-39 hours

per week are more comfortable and the employees working more than 50

hours per week are less comfortable towards the present work environment in

software industry in Chennai.

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5.1.5 Frustration in Job in software industry

Significant association between family support and frustration in job is

observed. Most of the women employees (46.60%) having frequent

support from the family are frustrated in the job.

Significant association between feel about organization support and

frustration in job is observed. Most of the women employees (48.40%)

getting organization support are frustrated in the job.

Significant association between intention to retain in the same

company and frustration in job is observed. Most of the women

employees (43.00%) frustrated in job are probably retained in the same

company.

Significant association between experiencing conflict at family and

frustration in job is observed. Most of the women employees (32.20%)

having poor experience in family and experience more conflict are

frustrated in job.

Significant association between experiencing conflict at Work

environment and frustration in job is observed. Most of the women

employees (33.00%) having fair experience at work environment and

experience moderate conflict are frustrated in job.

Significant association between Work-life conflict at family side and

frustration in job is observed. Most of the women employees (40.20%)

having high conflict at family side are frustrated in job.

Significant association between Work-life conflict at Work

environment and frustration in job is observed. Most of the women

employees (34.40%) having high conflict at Work environment are

frustrated in job.

Significant association between age and frustration in job is not

observed.

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Significant association between marital status and frustration in job is

not observed.

Significant association between Category of job and frustration in job

is not observed.

Significant association between work experience and frustration in job

is observed. Chi- square value (24.846) shows that the null hypothesis

is rejected at 1% level. Most of the women employees (50.00%) with

work experience of 5-10 years are frustrated in job.

Significant association between Educational qualification and

frustration in job is observed. Most of the women employees (37.80%)

having non-professional degree are frustrated in job.

Significant association between monthly income and frustration in job

is observed. Most of the women employees (37.00%) earning Rs.20,

001-40,000 are frustrated in job.

Significant association between working hours per week and

frustration in job is observed. Most of the women employees (48.20%)

working 40-44 hours per week are frustrated in job.

Significant association between working in shift and frustration in job

is not observed.

Significant association between job related travel and frustration in job

is not observed.

Significant association between full time employee and frustration in

job is observed. Most of the women employees (80.80%) working as

full time employees are frustrated in job.

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5.1.6 Correlation analysis for family life and work life

Positive significant correlation was observed between Experiencing conflict

at Family side and Managing Work-life conflict at family side (r = .566),

which is good relationship and it shows that management of work-life

conflict at family side has improved women employees’ family life by 56.6%

in software industry in Chennai.

Significant correlation was observed between Experiencing conflict at Family

side and Betterment of managing work-life conflict at family and work

environment (r = .554), which is a positive relationship and it shows that

Betterment of work-life conflict at family and work environment will

improve women employees’ family life by 55.4% in software industry in

Chennai.

Positive significant correlation was observed between Managing Work-life

conflict at family side and Betterment of work-life conflict at family and

work environment (r = .424), which shows that Betterment of work-life

conflict at family and work environment will help women employees to

manage work-life conflict at family side by 42.4% in software industry in

Chennai.

Positive significant correlation was observed between Experiencing conflict

at work environment and Managing Work-life conflict at work environment

(r = .688), which is good relationship and it shows that management of work-

life conflict at work environment has improved women employees’ work-life

by 68.8% in software industry in Chennai.

Significant correlation was observed between Experiencing conflict at work

environment and Betterment of work-life conflict at family and work

environment (r = .487), which is a positive relationship and it shows that

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Betterment of work-life conflict at family and work environment will

improve women employees’ work life by 48.7% in software industry in

Chennai.

Positive significant correlation was observed between Managing Work-life

conflict at work environment and Betterment of work-life conflict at family

and work environment (r = .433), which shows that Betterment of work-life

conflict at family and work environment will help women employees to

manage work-life conflict at work environment by 43.3% in software

industry in Chennai.

5.1.7 Predictor variables for rating of organization

Experiencing conflict at work environment, managing work-life conflict at

family side, managing work-life conflict at work environment, betterment of

managing work-life conflict at family and work environment, Retaining in the

same company and Working hours per week serves as significant predictors.

Model fit Summary

The model is fitted for managing work life conflict in software companies in

Chennai. The model fit Chi-square 2 = 2.103 and it is insignificant shows the model

is good. The goodness of fit index (GFI) is .921, its adjusted goodness of fit (AGFI) is

.903. The Root Mean Square Error of Approximation (RMSEA) is .071, a smaller

value indicates better model, and Expected Cross Validation Index (ECVI) is .091,

which are within the acceptable range indicating a better model fit.

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5.2 SUGGESTION

Most of the women employees (48.20%) are found to be working for 40-44

hours in a week, so the women employees are frustrated in the job. In this

regard the human resource department has to understand the women

employee’s feelings, working constraints and their physical and mental

support needed for their regular official work and also help them to manage

their family life. Hence, Organization has to reduce the work load of the

employees and also find out means to avoid more work pressure in future.

This may lead to retaining the employees and utilize their skill for further

development in the organization.

Based on the analysis, women employees (50%) who have 5-10 years of

experience are frustrated in the job and also experience more conflict in work-

life. In this regard, the less experienced women employees are not in a

position to manage their professional work front as well as manage their

personal life. Hence the Human resource department has to analyse the less

experienced women employee’s problem and their inability to manage their

work-life which results in frustration in the job. In this respect, the

management has to arrange either orientation programs or motivational

programs to enable them to manage the work-life conflict and provide them

avenues to reduce the job frustration with less experienced period through

some psychological expertise.

Most of the women employees (34-40%) are frequently facing problems from

their family front and this results in frustration in the job in regular working

environment. In this regard, the management has to understand each and every

employee’s family and personal problems and motivate them to resolve their

issues and enhance their contribution for betterment of the organization. The

Human resource manager has to manage the sharing of work load in a team,

assign the project in a fair manner and manage the working shift. This may

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lead to improve women employees’ confidence for managing work-life

conflict.

Women employees who have a fair experience (33%) in the work environment

are found to be frustrated in job .This is due the fact that women feel their job

to be frustrating even if they share a fair experience in the work environment.

Organizations can concentrate on giving a better working environment so that

the women employees may feel happy working for the organization. Human

resource manager can arrange for refresher training courses and arrange for

family meets and parties outside the organization in order to motivate the

employees to have a better perception about the work environment.

Women employees who perceive to be having a poor experience in the family

(32.20%) are found to be frustrated in job. Women employees seem to face

lots of problem in their family life which makes them perform poor in work as

well. In order to make them come out of family issues, the organization can

provide counselling sessions and can provide stress relieving activities inside

the organizations.

Women employees who fall under the age category of less than 25 are found

to expect more betterment in managing the work-life conflict. In order to fulfil

such expectations of the age group of 25 and lesser, organizations can

concentrate on activities which would boost their skills to manage their work-

life conflict better. The activities can include family meets, parties etc. which

can encourage active participation of employees under this age category.

Women employees who are married expect more betterment in managing their

work-life conflict. Organizations can concentrate on family participative

activities which will highlight the importance of working women to the other

family members.

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Most of the women employees are supported by the family members for their

work-life balance, though (46.60%) of women employees are not in a position

to manage work conflict, hence the management has to give proper training to

manage their emotional balance in different project assignment and also tackle

the real time working environment and manage the work-life conflict in the

changing work environment.

5.3 CONCLUSION

The Indian Software Industry is the uncrowned king in the outsourcing of

software services. They have shifted emphasis to off-shore projects since the on-site

software development has virtually come to a standstill. They have started to scout for

newer markets, improve on the per capita efficiency, concentrate on future

technologies and revamp their organizational and marketing structure. The share of

onsite work has come down as most foreign companies prefer to sustain as much of

their own employees rather than outsiders. Companies in India have now shifted gears

doing off-shore development which is much cheaper. They have started looking at the

European and Japanese markets which have not yet been affected by the slowdown.

Other markets which they are tentatively eyeing are the Australian, South American

and Middle East markets. Most companies have decided to tide over the problem of

reduced profits by resorting to layoffs and cutting down heavily on fresh recruitment.

More over in Indian software industry, where around 37% of women employees are in

the work force, most of the employees are found to be struggling to manage family

and work place. The researcher has analysed the work-life conflict of women

employees on software industries and based on the study objectives and

methodologies the inferences are well correlated.

The research insists that work-life conflict of women employees is found to be

high for employees with 5-10 years of experience in software industry, where the

women employees felt that the working hours per week are very tedious and they are

not in a position to manage the work-life. The newly married women employees who

report less experience in managing family are frustrated in job and this leads them to

experience work-life conflict. In the competitive working environment, women

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employees’ contribution in software industry is very remarkable and since their

conflict is found to be very high both in family and working environment, the current

research analysis and findings and suggestions would enable the women employees

improve their confidence, belief and manage the work-life conflict in the competitive

working scenario.

The findings that emerged from the analysis and interpretation highlighted the

pervasive factors that impact the work life conflict of women. The societal role

expectations, women’s career ambitions, and the nature of the software industry

challenges the way they manage their professional and personal lives. While their

self-identities primarily lie in their work, they are strongly influenced to perform the

roles of homemaker and dependent care provider given the societal expectations; this

does require negotiation both at home and at work in terms of how and when work

can be done. An implication is that organizations may not be aware of the conflict and

taking measures to resolve them but implementing HR policies and practices would

facilitate women in pursuing their career goals and dependent care responsibilities.

With an increasing number of women entering the workforce it appears that

understanding the role of work and family in the lives of women professionals will

become an important HR concern. Indian women software professionals can achieve

the work family balance by resolving the conflict and setting priorities in their work

and personal lives and by having support systems both at work, formally through HR

policies and programmes, and informally through supervisor and co-worker support

and at home. The identified dimensions could serve as a platform for further research

on women software professionals and the study on work-life conflict will serve as a

guide for organisations to address the work family issues of working women by

designing and implementing HR policies and practices for facilitating the work-family

balance. This, in turn, would go a long way in enabling women to perform better at

work, be more committed to the organisation, and ultimately contribute to the growth

of the economy and positively impact society as whole.

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5.4 IMPLICATION OF RESEARCH:

The research inferences would able to have implications in software industry,

the Human resource department of the Software Industry, Society and the

Government.

1. The research inferences are more useful to software industry and almost all the

research inferences are more relevant to software women employees since

there are around 50 percent of women employees working in software

industry.

2. The research inferences are more useful to understand the basic reasons for

work-life conflict of women employees and also find various remedial

measures to manage the work-life conflict of women employees in any

situation or context. Hence the research inferences have implications in the

software industry not only in India but in a global context.

3. The Human resource department is one of the most vibrant in software

industry to locate and identify the potential personality for developing

business. The research findings have more implications in human resource

department which helps them to find out the feeling and opinion of women

employees, their perception on working environment, workload, the capacity

of women employees to manage the regular work-life and their various means

adopted to tackle the problems in day to day work-life.

4. In the modern society, there is a visible change and improvement in women

empowerment and there is a due recognition of women and their constant

support for the growth of country, economy, industry and society. The

research findings have more implications to the society at large as it brings out

the problems faced by women employees in their day-to-day work life in

software industry. The various means of managing the work-life conflict in

every situation is also brought out clearly in the research. Hence the study

proves to be useful to the society in terms of the role of women employees in

software industry and their means of managing effectively the work-life

conflict.

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5. The Government role plays a vital role in formulating women employee’s

policies and regulations especially in software industry, because majority of

the Indian workforce are employed in the software industry. Hence the

government could utilize these research inferences for formulating policies,

regulations and guidelines pertaining for the betterment of life of software

employees and contribute to their success of their personal life and

professional work.

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