Decison Science-Ver 4 21 OCT-4.1

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What drives mobile telephony adoption in Rural India? Anempirical evaluation.

ABSTRACT

Mobile telephony has become one of the major factors driving the social and economic

development of a country. It has diffused differently in diverse economies with different factors

affecting the process. Mobile telephony has penetrated markets throughout India. The ratio of

mobile penetration in urban to rural India is 4:1 which clearly indicates that different social

systems adopt the same technology in different ways. An understanding of the factors affecting

the choice is essential both for economists studying the determinants of growth and for the

providers of such technologies. Whilst most of current studies on mobile telephony are based onurban users, this paper focuses on users living in rural India. The objective of this paper is to

understand and identify factors for adoption of mobile telephony in rural India and their impact

on its adoption.

This study employs a mixed approach to examine the factors affecting the intention to adopt

mobile telephony in rural India. The results highlight that mobility, social influence, perceived

usefulness, cost of handset, lack of ease of service accessibility and lack of understanding of

mobile service offerings are the key factors affecting the rural people decision to adopt mobile

telephony. This study is useful for researchers willing to highlight the factors that motivate users

mobile telephony adoption in rural India. It also has implications for government and service

providers seeking to enhance its adoption in India. For practitioners, our findings suggest that in

order to facilitate adoption of mobile telephony and its related services, it is crucial to strengthen

user perception on the potential benefits and to create transparency of the services.

.

KeywordsMobile telephony, adoption, rural, India


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INTRODUCTION

In recent years, there is increasing evidence from both academic researchers and policymakers

that the use of mobile telephony is the important base for economic growth and social

development of a country. Studies at country level have shown that wireless phones have a

positive and significant impact on economic growth (Waverman, Meschi, & Fuss, 2005). A

study by Abraham (2007) found that the widespread use of mobile telephony by Kerala

fishermen has increased the efficiency of markets by decreasing risk and uncertainty. But

adopting a technology is a complex process and involves a mix of social, technological,

economical and political factors influencing its adoption decision. Even though the growth of

mobile telephony is a global story, there are important regional differences in how the mobile

telephony has evolved and diffused in different countries. Indian Telecom sector has undergone amajor transformation during recent years and is now the second-largest telecom market, just after

china. Figure 1 presents the penetration of mobile telephony in India since 1997. The ratio of

mobile penetration in urban to rural India is 4:1. Also, the urban to rural subscribers are in the

ratio of 2:1. These numbers indicates that different social systems adopt the same technology in

different ways.

Figure 1: Growth of Mobile telephony in India


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A deeper insight is required to understand the underlying motivations that lead to

adoption of mobile telephony in rural India. While most of current studies on mobile telephony

are based on urban users, this paper focuses on users living in rural India. The objective of this

paper is to understand and identify factors for adoption of mobile telephony in rural India and

their impact on adoption. Our findings will provide valuable managerial insights for service

providers and policymakers. The mixed approach is adopted in this study as a research

methodology. The study was conducted in two phases (phase 1 being qualitative and phase 2

being quantitative)

LITERATURE REVIEW ON ADOPTION AND DIFFUSION APPROACH

Adoption relates to consumers individual decision making process with regard to the purchase

and use of new products and services. Diffusion equals the sum of consumer adoptions in a

market over time (Gatignon & Robertson, 1985). Studies on diffusion describe and predict the

cumulative response of consumers to a new technology/product/service in a market. Thus,

research on adoption is directly linked to research on diffusion. Also Gatignon and Robertson

(1985) stated that: adoption lies at the heart of diffusion. The literature on adoption and diffusion

includes two major streams: econometric models and explanatory models. Econometric

approaches study epidemic models, which describe the phenomenon at country level. Gatignonand Robertson's (1985) consumer diffusion paradigm is an example of an explanatory model

which links individual characteristics and experience to adopt an innovation. The research about

adoption decision mainly studies the factors influencing individual adoption from the angle of

individual. Such research from individual perspective compensates the lack of study from overall

angle, and considers individual heterogeneity. There are various theories relating to the adoption

of new services or technologies that exist in the literature such as innovation diffusion

theory/DOI (Rogers, 1962), theory of reasoned action/TRA (Ajzen & Fishbein, 1977), theory of

planned behavior/TBP (Ajzen, 1991) and technology acceptance model TAM (Davis, 1989).

DOI theory suggests that an individuals adoption decision is influenced by the five

perceived characteristics of innovation - relative advantage, complexity, compatibility,

trialability, and observability. Moore and Benbasat (1991) have expanded DOI theory and

suggested seven innovation characteristics (relative advantage, ease of use, compatibility, image,


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visibility, result demonstrability and trialability) that influence the adoption decision. Davis

(1989) has proposed a model that provides an explanation toward the acceptance of technology

which explains users behavior on accepting new information technology and analyzes the

factors that influence their intention toward its adoption. This model is popularly known as

Technology Acceptance Model (TAM) and contained three factors affecting behavioral intention

(IA) to adopt: (1) Perceived ease of use (2) Perceived Usefulness (3) Attitude. TAM has been

highly praised for its parsimony and predictive power (Mathieson, 1991) which makes it easy to

apply to different situations. The model has been continuously studied, modified and expanded

by researchers. Davis , Bagozzi and warshaw (1989) used the original TAM model and found

strong and significant correlation between PU, PEOU and intention to use the system thus

eliminating the need for the attitude construct from the model. This can be explained in that if a

system is perceived to be useful, people may have a high behavioral intention to adopt eventhough they do not have a positive attitude toward it (Davis et al., 1989). The resultant model is

presented in Figure 2. Venkatesh and Davis (1996) also removed attitude from their revised

model because attitude did not appear to mediate fully the effect of perceived usefulness and

perceived ease of use on behavioral intention as originally anticipated.

Figure 2: TAM (Source: Davis, Bagozzi and Warshaw (1989))

The widely followed Davis and Rogers models are complementary. Specifically,

usefulness and ease of use in Davis model is similar to relative advantage and complexity in

Rogers model respectively. Constructs employed in TAM are fundamentally a subset of the

perceived innovation characteristics and, if integrated, could provide an effective model than


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either standing alone. The TAM has been used in various information and communication

technology adoption studies like V-mail and customer dial up system (Subramanian, 1994),

spreadsheet and word processor (Jackson, Chow & Leitch, 1997), world wide web (Lederer,

Maupin, Sena & Zhuang, 2000), internet banking (Suh & Han, 2002), wireless internet (Lu , Yu,

Chang & Yao, 2003) .

Only recently the TAM is being applied to mobile services in urban environment of

developed nations. Kuo and Yen (2008) applied TAM to understand the intention to use 3G

value added services in Taiwan. The study of advanced mobile services was done by Lpez-

Nicols (2008) to assess its acceptance by Dutch consumers. It was found that traditional

antecedents of behavioral intention, ease of use and perceived usefulness, can be linked to

variables, such as social influence and perceived benefits. Kim and Garrison (2009) extended the

TAM model to investigate the mobile wireless technology adoption in Korea. Yongqing,Jinlong, Jianhua, and Yuanyuan (2011) also extended the model to understand the adoption of

mobile instant messaging in china.

The studies have shown strong empirical findings which have encouraged the models

use in our study. A key research opportunity emerges to apply and extend these models in rural

context of developing nation, in our case India for investigating the adoption and diffusion of

mobile telephony. Pursuing this would address the theoretical gap highlighted in sections above

and will offer a fresh theoretical perspective for explaining mobile telephony adoption in rural

India, a developing nation. Further, these factors that shape ones intentions will also help

service providers to leverage optimally and control those factors in order to promote adoption

and diffusion. And, therefore the first logical step is to understand and find how and why users

adopt mobile telephony in rural India.

CONCEPTUAL MODEL AND HYPOTHESIS

Phase 1 of the study was conducted to find new factors in Indian rural context and to come up

with a conceptual model. Open ended questions were asked to the owners and users of mobile

telephony (basic voice service). The data collected helped to give a broad picture of users

perception and provided new insights. Most of the factors explored were in line with those

concluded from literatures. Perceived health hazard, lack of service quality, lack of ease of


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service accessibility, cost of service, cost of handset and lack of understanding of mobile service

offerings came out as new factors. Direct and indirect linkages between variables were also

identified.

Figure 3. Conceptual Model

Based on the literature review and phase 1 of the study conceptual model for adoption of mobile

telephony in rural India is proposed as shown in Figure 3. To study at end user level, Intention to

Adopt (IA) is used as the dependent variable. IA is defined as the strength of the adopters

intention to support the adoption decision (Ajzen & Fishbein, 1977). The operational definition

and description of the variables identified and there hypothesis are described as under

Perceived usefulness (PU)is defined as the degree to which a person believes that using

mobile telephony would enhance his or her personal communication performance or

effectiveness (Davis 1989). Prior research has found that perceived usefulness is the strongest


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predictor of intention to adopt (Venkatesh, Morris & Davis, 2003). The relation between

usefulness and adoption intention was also confirmed by Lopez-Nicoas (2008) for advanced

mobile service in Netherlands. Phase 1 of our study also supported the persistence of its

influence in the current context. Perceived ease of use (PEOU)is defined the degree to which a

person believes that using mobile telephony would be free of effort (Davis, 1989). It has also

been found to be an important factor for various technologies (Davis, Bagozzi & Warshaw

1989). In addition, perceived ease of use has been found to indirectly influence intention through

perceived usefulness (Davis et al. 1989). PEOU has shown a significant effect on PU in the

majority of studies but the effect of PEOU on intention has shown inconsistent results. In the

study of Kuo and Yen (2009), ease of use was found to have an indirect effect on intention to

adopt 3G service. Relationship of perceived ease of use on adoption intention was confirmed by

Kim and Garrison (2008) for mobile wireless technology in Korea. Therefore, the hypothesis isH1: PU has a positive effect on intention to adopt mobile telephony in rural India.

H2a: PEOU has a positive effect on intention to adopt mobile telephony in rural India.

H2b: PEOU has a positive effect on perceived usefulness.

Previous researchers have studied the diffusion of technology with respect to culture and

have found that in individualistic culture diffusion of technology happens at a faster rate. Highly

individualistic cultures are those in which individual is the most important unit, while highly

collectivistic cultures believe that the group is the most important unit. In collectivistic

environment one act conforms the norms of the group. As collectivistic cultures are characterized

by collective decisions, it results in delay in the adoption decision process. Because collective

culture emphasize on conformity to social norms and group behavior, the adopters of technology

in this culture will be socially influenced while making any adoption decision (Yaveroglu &

Donthu ,2002; Bulte & Stremersch,2004). On similar grounds, the culture in metropolitan cities

and urban India can be considered to have less collective culture as compared to rural India. This

can be one of the reasons of slow diffusion of mobile telephony in rural area. It also lays

importance of social influence (SI) in the context of the study (rural India). In the current context

social influence is defined as the degree to which individuals believed that others thought they

should adopt mobile telephony. On the other side, mass media (MM) influence is defined as the

degree to which people had the impression that mass media reports encouraged them to adopt

mobile telephony. Social influence is generally interdependent with mass media and seems to


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be more important in the earlier phases of adoption, rather than late. However when conflict

occurs, social influence is found to have a greater impact (Gatignon and Robertson's, 1985). It is

because, opinions and pressures from the peer group reduces the perceived risk associated with

adoption. Potential users may feel that adopting mobile telephony does not require much effort

and is useful if others in their social surroundings say that the system is easy to use. Thus

individuals beliefs are socially framed through interactions with other members and it will have

significant impact on the individual perceived usefulness and perceived ease of use over the

characteristics of mobile telephony.

In Innovation diffusion theory image is also included as an important aspect of relative

advantage. Personal Image is defined as the degree to which use of an innovation is perceived

to enhance ones image or status in ones social system. Research of Van den Bulte and

Stremersch (2004) indicates that the competition for status is an important growth driver,sometimes more important than interpersonal ties, and that the speed of diffusion increases in

societies that are more sensitive to status differences. In some parts of rural India, adopting a

mobile telephony is still a luxury. When an individual adopts a mobile telephony, his or her

relationship to their immediate social context is considerably transformed and raised. Users

perceive that they have entered the modern and urban spheres. They regard it as fashion and

decide to adopt it to symbolize their social progress. It is also believed that social influence will

affect image because if important members in an individuals social group believe that a person

should have mobile telephony then adopting it will raise the standing of the individual within the

group. Hence based on the above discussion, the hypothesis is

H3a: MM has a positive effect on intention to adopt mobile telephony in rural India

H3b: MM has a positive effect on SI.

H4a: SI has a positive effect on intention to adopt mobile telephony in rural India.

H4b: SI has a positive effect on PU.

H4c: SI has a positive effect on PEOU.

H4d: SI has a positive effect on PI.

H4e: SI has a positive effect on mobility.

H5a: PI has a positive effect on intention to adopt mobile telephony in rural India.

H5b: PI has a positive effect on PU.


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Mobility is perceived to be the most significant feature of mobile telephony. Mobility

(MOB) is defined as the degree to which one can use the innovation anytime and anywhere.

Dholakia and Kshetri (2004)found mobility refereeing to anytime, anywhere capability to be

one of the factor influencing the diffusion of mobile telephony. Looney, Jessup and Valacich

(2004) stated that the capability of communicating from virtually anywhere at any time offers

convenience which can influence adoption intention. Therefore, the hypothesis is

H6a: MOB has a positive effect on intention to adopt mobile telephony in rural India.

H6b: MOB has a positive effect on perceived usefulness.

People in India are price sensitive and avoid over expenditure, the other influencing

factor is the technology cost. Technology cost includes two aspects: the running cost which is

defined as the cost of service (mobile call charges (CS)) and the onetime cost defined as the cost

of the handset (CH). A mobile call was priced at rupee 16 per minute in 1994, it is now aboutrupee 0.50 per minute. A STD calls was priced at rupee 36 per minute in 1994, today it is rupee

0.40 per minute. The mobile handset was costing over Rs. 8000 in 1994. It is now about less than

Rs. 1500 (Chowdhary, 2006). These innovations are providing relative advantage to the users

which they assess while adopting the mobile telephony. As over expenditure and loans are not

encouraged among Indian society especially in rural India, we believe that technology cost can

act as barrier towards adoption decision, thus delaying the diffusion process. Therefore, the

hypothesis is

H7a: CS has a negative effect on intention to adopt mobile telephony in rural India.

H7b: CS has a negative effect on perceived usefulness.

H8a: CH has a negative effect on intention to adopt mobile telephony in rural India.

H8b: CH has a negative effect on perceived usefulness.

One of the limitations of TAM is that it assumes that the service is accessible. We believe

that constrained access influences the perceptions of potential adopters about the mobile

telephonys true usefulness and hence the adoption decision resulting in slow diffusion in rural

India. Explored in Phase 1of the study, ease of service accessibility (EOSA) is defined as the

degree to which product, service or related environment is easily available to get benefit from

the service. More than 90% of Indian mobile subscribers hold prepaid account and recharge

through prepaid coupons. In the prepaid account the subscriber has the direct control /

monitoring of his expenditure and can regulate his expenditure limits with respect to priorities.


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Also consumer is free of doubts related to bills as he is continuously informed and updated about

his expenditure. Lack of easy access of mobile innovations- like prepaid calling cards and low

cost handset in the area and availability of electricity for recharging handset can act as external

controls and hindrance in the adoption environment leading to retardation of diffusion of mobile

telephony. Therefore, the hypothesis is

H9a: Lack of ease of service accessibility (LEOSA) has a negative effect on intention to adopt

mobile telephony in rural India.

H9b: LEOSA has a negative effect on perceived usefulness.

During phase 1 of the study, the factor perceived health hazard was explored. PHH is

defined as an unknown and unpredictable phenomenon that adversely affects ones health. It

can be an important barrier in the diffusion of mobile telephony in rural India. In the study of

Cocosila Turel, Archer and Yuan (2007) in Canada, health hazard was found to have smallnegative indirect influence on the intention to adopt 3G cell phones. It had a diminishing effect

on PU. The main conclusion drawn from their analysis was that PHH perceptions affect the PU

of 3G cell phones, which in turn influences user IA. Therefore, the hypothesis is

H10a: PHH has a negative effect on intention to adopt mobile telephony in rural India.

H10b: PHH has a negative effect on PU.

Service quality (SQ) is defined as the extent to which a service meets the users

requirements or expectation. In this study ease of subscribing, customer support

(responsiveness) and network (coverage aspect) are taken as three dimensions of service quality

as examined during phase 1 of the study. Based on the previous literature, the hypothesis can be

stated as:

H11a: Lack of SQ (LSQ) has a negative effect on intention to adopt mobile telephony in rural

India.

H11b: LSQ has a negative effect on PU.

H11c: LSQ has a negative effect on PEOU.

During phase 1 of the study, the factor understanding of mobile service offering

(UMSO) was explored. It is defined as ones ability to clearly visualize the mobile telephony

benefits in thought and understanding. It relates to the transparency of the services that are on

offer and the ease of being able to differentiate between these services. Thus the hypothesis can

be stated as:


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H12a: Lack of UMSO (LUMSO) has a negative effect on intention to adopt mobile telephony in

rural India.

H12b: LUMSO has a negative effect on PU.

H12c: LUMSO has a negative effect on PEOU.

RESEARCH DESIGN

The methodology used is both qualitative and quantitative, the mixed methodology. Phase 1 of

the study was qualitative in nature to find new factors in Indian context and to derive the

conceptual model. Phase 2 of the research is quantitative in nature to find factors that affect

adoption in rural India. This combination of qualitative and quantitative approaches helped to

ensure the sufficiency and quality of obtained evidence.

Based on the conceptual model presented in Figure 3, the survey instrumentaquestionnairewas developed to measure the effect of factors that were thought to influence an

intention to adopt mobile telephony. All the items were measured on five point likert scale.

Questionnaire was given to some of the experts in the field to assess the face validity to eliminate

ambiguity in questions. Modifications were made accordingly without affecting the intended

meanings. Prior to the main study, a pilot test using 20 people (age range from 18-45) from the

rural area of India was conducted to validate the relevance, accuracy and wording of content of

the questionnaire. Reliability of measures was assessed through Cronbach Alpha. It shows that

that all alpha value exceeds or nearly meets the minimum of 0.6 (Hair, Black, Babin, Anderson

and Tatham, 2006). The questionnaire had undergone 2 revisions before the main study and then

was distributed in Hindi as it was the language understood by 95% of the people in the area.

Initially people willing to participate were asked whether they had any experience with mobile

telephony. Final questionnaire was distributed amongst 180 people in the rural state of India-

Chhattisgarh. Rationale for selecting the state was the increasing growth rate of subscribers and

low mobile density. Also, the state is primarily a rural state with only 20% of population

residing in urban areas. 170 responded back and only 148 were found usable.

ANALYSIS AND RESULTS

Sample Characteristics.


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The data used was collected in the November 2010 from rural part of the Indian state

Chhattisgarh. Table 1 presents the characteristics of the sample. Out of 148 respondents, 141

were prepaid users. 59% of the users were the subscribers (owners of subscriber identity module

(SIM)). 55 % of the respondents have less than 3 years of experience in using mobile. It was

found that only 21% of the household have fixed line telephony. The mean age of the

respondents was 23 years and mean of the experience of the respondents with mobile telephony

was 2.8 years.

Table 1. Sample Characteristics

Measurement model evaluation

Exploratory factor analysis was done to identify latent factor. Appropriateness of factor analysis

was done by examining sampling adequacy through Kaiser- Meyer-Olkin (KMO) statistic which


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came out as 0.60. Indicators which have loadings below 0.5 were removed and then again

exploratory factor analysis was performed. The measurement model was then tested by

performing validity and reliability analyses on each of the items of the model, in order to ensure

that only reliable and valid items of the constructs are used before conclusions about the nature

of the relationships between construct are drawn. Table 2 presents the reliability measures of the

factors. Model is also evaluated using three criteria suggested by Fornell and Larcker (1981).

Table 2 shows that construct reliabilities exceed and average variance extracted (AVE) of each

construct exceed 0.7 and 0.5 respectively. Indicator factor loading are significant and exceed 0.5

(Table 3). Table 4 shows that square root of the constructs AVE is greater than the correlation of

the other constructs. The construct PHH was removed from the further analysis due to low

cronbach alpha. Reliability of formative constructs (lack of service quality, lack of ease of

service accessibility) was checked by testing the significance of the weights and the measureswith significant weights were only considered for the analysis.

Table 2. Reliability and Validity for rural India mobile telephony data (n=148)

LUMSO


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Table 3. Factor Loadings

Measures Loadings T Statistics Statements

PU 1 0.71 13.94 Mobile service makes me more efficient.

PU 2 0.70 10.48 Mobile service allows me to do things faster.

PU 3 0.76 16.04 Mobile service allow me to do things better.

PU 4 0.78 15.86 Mobile service allows me to act in an emergency

PU 5 0.67 8.70 Mobile service allows me to contact others in an emergency

PEOU 1 0.74 10.84 I believe that it is easy to get mobile service to do what I want it to do.

PEOU 2 0.86 19.82 I find mobile service easy to use.

PEOU 3 0.82 13.42 My interaction with mobile service is clear and understandable

SI 1 0.85 21.53 People around me find I should use mobile service.

SI 2 0.91 59.36 People around me think it is a good idea for me to use mobile service.

SI 3 0.76 12.22 People around me have stimulated me in using mobile service.

PI 1 0.80 17.14 Using mobile service makes me feel accepted by others.

PI 2 0.89 35.69 Using mobile service makes a good impression on other people.

PI 3 0.85 23.24 Using mobile service improves the way I am perceived by others.

MM 1.00 0.00Advertisements through television, newspapers, radio have stimulated me to buyand use mobile service.

MOB 1 0.82 14.04 I can use mobile service anywhere.

MOB 2 0.92 29.36 I can use mobile service anytime.

PCH 1 0.50 2.05 For me, price of basic handset/phone (INR 1200 ) is still high


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Notes: * weights of the formative indicator

Measures Loadings T Statistics Statements

PCH 2 0.77 3.39 Generally speaking, I cannot accept the current price of the handset.

PCH 3 0.86 3.93 A low price of handset is very important for me to subscribe to a mobile service.

PCS 1 0.82 6.56 I think telecom service providers should reduce the tariff of voice (making calls)

PCS 2 0.70 4.20For me, the current voice tariff (50 paise per minute) is still high (cost of makingcalls is still high)

PCS 3 0.76 4.94Generally speaking, I cannot accept the current tariff of mobile voice (makingcalls) services

LUMSO 1 0.50 1.94 Inability to understand differences in various tariff plans.

LUMSO 2 1.00 4.19 Inability to identify benefits from having mobile connectivity.

LSQ 1 0.97* 7.36There is poor coverage of the mobile network (connection breaks or iscompletely missing in some areas).

LSQ 2 -0.65* 2.66 It is not easy to contact the mobile service customer care at the time of difficulty.

LEOSA 1 0.00Prepaid recharge coupons are not easily available in my area (Poor availabilityof service outlets).

IA 1 0.62 6.70 I intend to use mobile telephone services some day.

IA 2 0.79 14.82 I intend to become a subscriber of a mobile service some day

IA 3 0.83 18.21 I intend to use a mobile data service in future.

IA 4 0.73 12.78 I intend to recommend others to subscribe and use a mobile service


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Table 4: Correlations among variables


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Hypothesis Testing

Conceptual model was tested using Partial Least Squares (PLS), a structural modeling technique

well suited for complex models using software smartPLS. This technique allowed for the

understanding of the relationship between the constructs and was considered appropriate for thisstudy due to its to handle smaller sample sizes and use of less strict distributional assumptions

(Gyau and Spiller, 2009; Ringle et al 2005). A rule of thumb for robust PLS path modeling

estimations suggests that the sample size should be equal to the larger of the following (Barclay,

Higgins, and Thompson, 1995): (1) ten times the number of indicators of the scale with the

largest number of formative indicators, or (2) ten times the largest number of structural paths

directed at a particular construct in the inner path model. Based on these necessities, our model

meets the sample size requirement. The model was able to explain 35 % of variance in intention

to adopt mobile telephony in the rural state of India. Currently available PLS software does not

automatically provide goodness-of-fit measures for the full path model. However, a method to

calculate an overall goodness-of-fit (GoF) measure was proposed by Amato , Esposito and

Tenenhaus (2004). GoF was found to be 0.24 suggesting a moderate fit of the model. Chin

(1998) suggests that path coefficients should exceed 0.1 - 0.2. In this model we see that majority

of path coefficients exceed the lower 0.1 level suggesting that the model adequately fits the data.

A further test of model fit is provided by Chin (1998) who suggests that R square of 0.66

indicates substantial model fit, R square 0.35 moderate and R square 0.17 weak model fit. Usingthese criteria it appears that this model fits the data moderately well with R square of 0.35.

Bootstrap analysis was performed to test the statistical significance of path coefficients. Path

coefficients represent the strength of the relationships between dependent and independent

variables and are presented in figure 4. It is found that PU, MOB, CH, LEOSA and LUMSO are

the factors directly affecting the adoption intention and hence are the responsible factors for the

diffusion of mobile telephony in Chhattisgarh. To study how (or the mechanism by which) a

given effect occurs between an independent variable and a dependent variable, mediation effect

is analyzed. Some of the variables are indirectly related to the adoption intention. The effect of

SI on IA is mediated by PU, PEOU, MOB and PI. Also the effect of CH, CS, LEOSA, LSQ and

LUMSO on IA is mediated by PU. To assess these mediation effects Sobel test is performed

(Sobel, 1982). To find the mediating effect of PU on relationship between SI and IA sobel tests

was performed by considering the total effect (i.e., the sum of the direct and indirect effects) of


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SI on PU and the separate effects of PU and IA. PU and MOB fully mediated the relationship

between SI and IA (z = 1.92, p = .053; z=.2.33, p=.019). Mediation effect of PU on the

relationship of remaining above variables and IA was found to be insignificant.

Figure 4: Final Conceptual model with path coefficients

Notes: Indicates the significant relationships

Indicates non-significant relationships


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RESULTS AND DISCUSSION

Based on the qualitative analysis six new factors have been identified affecting the intention to

adopt mobile telephony in rural India. These six factors are perceived health hazard, lack of

service quality, lack of ease of service accessibility, cost of service, cost of handset and lack ofunderstanding of mobile service offerings. A conceptual model was developed incorporating

these factors and was validated and tested. The quantitative analysis has shown that the proposed

factors significantly influence users' intention to adopt mobile telephony.

Results indicate that mobility, perceived usefulness, lack of ease of service accessibility

and lack of understanding of mobile service offerings are the direct antecedents of adoption

intention in rural India. Mobility was found to have highest effect, followed by perceived

usefulness and lack of service quality respectively.

The results of our study indicate that social influence exerts an important influence on

peoples decision to adopt mobile telephony in rural India. The opinions of friends and relatives

have a significant impact. Participants expressed that their awareness of mobile telephony and

related service came from mass media, such as advertisements on television, newspaper, radio

but they rarely consider them as direct influence sources on their adoption making decision.

Users mostly consider them as information sources, and were mainly convinced after the

opinions of their friends and relatives. The findings are in line with the literature.

The finding of positive relation between the lack of ease of service accessibility andintention to adopt is in contrast to the common belief of negative relationship between the two.

This state is due to the users (adopters and potential adopters) having high degree of perceived

usefulness (benefits) and is rushing for adoption in spite of the lack of service accessibility. The

delay in mobile telephony adoption and getting its benefits is not appreciated by the users. This

state may represent a case where demand exceeds the supply. The demand generates shortage of

services resulting into competition among adopters to adopt ahead of others even with

difficulties and partial availability of service and its product. The diffusion of usefulness has

generated a demand to an extent that even the partial service and difficulties in getting them are

being tolerated and ignored by the users (adopters and potential adopters). This shows that

improving and simplifying the mechanisms by which end-users access mobile telephony could

be key to enhance its adoption and usage in the region. Increased access is an important step

towards increasing the mobile penetration in rural India.


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Relationship between lack of service quality and ease of use came out to be positive. This

positive relationship is in contrasts to the general findings in previous literature. This typical

situation indicates that the adopters are ready to accept the mobile telephony in spite of

increasing difficulties in getting the service. The adopters perceive that they can derive benefits

by using the service without waiting for service quality improvement to take place.

Cost of mobile service was found to be insignificant. One of the reasons could be the low

affordable tariffs due to competition between the service providers. Most of the people in rural

India use the Missed Call concept which reduces their burden of payment for the service. Thus

it can be stated that cost of service may affect their usage levels and but not the adoption

decision. The cost of handset was found to be positively related to usefulness. Few reasons might

explain this situation. First, the majority of the respondents of this study were made up of ruralstudents (who are the potential adopters), who basically rely on either their parents or

sponsorship to survive. Thus, they might not treat money as serious as the general population in

the country. Also students might feel that handset of higher cost will show off the status thus

helping them to create a unique image.

The lack of understanding of mobile service offerings was found to be negatively

impacting adoption and ease of use of mobile telephony thereby making diffusion slow in the

region. The impact is small but significant. The service providers should take into account and

must clearly differentiate between different services and plans and should communicate the

benefits more clearly to the population

IMPLICATIONS FOR RESEAERCH AND PRACTICE

The study contributes to adoption and diffusion research by using detailed primary data in the

rural context of developing nation. This study has extended the body of knowledge with respect

to understand how and why individuals decide to adopt mobile telephony in rural India. We haveextended the technology acceptance model in a completely new environment where the research

is negligible and have integrated the four new variables- lack of ease of service accessibility, cost

of handset, cost of service, lack of understanding of mobile service offerings that affect the

decision to adopt mobile telephony. We believe that our conceptual model is the contribution to


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the existing knowledge because it adds unexplored dimensions that influence the adoption and

diffusion in rural context of emerging country.

As a result it will help managers to understand what drives adoption in rural context from

social, economic and psychological perspective. A deeper understanding of factors influencing

the adopters to adopt mobile telephony in rural India can assists service providers in addressing

the right issues and making decision. First of all, our study confirms the critical role of perceived

usefulness in making adoption decision. For practitioners, our findings suggest that in order to

facilitate adoption of mobile telephony and its related services, it is crucial to strengthen user

perception on the usefulness and easy accessibility of services. Significant benefits about the

service should be communicated to the existing and potential adopters. It is found that media has

an indirect effect in adoption decision whereas social influence plays an important role in

adopting mobile telephony directly and indirectly both.The findings indicate that the slow diffusion in rural India is due to its collectivistic

culture. In collectivistic culture one act conforms the norms of the group. As collectivistic

cultures are characterized by collective decisions, it results in delay in the adoption decision

process. Findings suggest that early adopters or opinion leaders, in the local community to which

people in specific area (social network) are attached, should be identified to accelerate the speed

of diffusion.

Managers should take into consideration the significant relationship between these

identified factors and adoption intention while finding the most appropriate strategies for specific

adopters. It will help them to review their current polices and strategies to make their current and

future mobile service more successful. The policy makers and service providers should introduce

training programs related to potential benefits of mobile telephony, and transparency of the

upcoming services and service plans, which can help them to overcome the adoption barriers.

Service providers need to better articulate the potential tangible and intangible benefits that can

be achieved by adopting mobile telephony.

CONCLUSIONS AND LIMITATIONS

The study has developed the model on adoption of mobile telephony in rural India and identified

the factors and their effect on adoption of mobile telephony in rural India. The study was


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conducted in two phases and five new factorslack ease of service accessibility, cost of handset,

cost of service, lack of understanding of mobile service offerings and perceived health hazard

were explored. The model establishes the link between the main construct of the TAM i..e PU

and PEOU and the other newly identified variables. The most dominating factors are identified.

They are mobility and usefulness. While this research benefits from rich and focused data

collection on the adoption of mobile telephony, it suffers from few limitations. Majority of the

respondents were in the age group of 25, and this overall profile might limit the generalizability

of research findings. Also the non users of mobile telephony i.e with zero experience were

excluded. The responses of the non users can be significantly different from who responded to

the survey and can give some additional insights. The study on the effect of demographic

variables and experience of the user with mobile telephony on the identified variables is

undergoing.

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