Mm3 project ppt group 1_section a

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Section – A group – 1

UM14001 ABHIJEET DASH

UM14014 ANUPRAS JAIN

UM14017 AYUSHI GILRA

UM14042 PRITAM RANJAN ROUL

UM14053 SUBHAM MEHRA

UM14060 VIJENDRA KUMAR

Work-life Balance : Ironical isn’t it for a MBA student???

• This App performs 3 major functions

• Build a daily expected timeline that is customized according to

your choices

• Prepare a daily schedule syncing Gmail, WhatsApp, Intranet

notice board

• Gives a weekly report gauging your target achievement

based on time spent on all activities in the entire week.

Why should you install this app??

• Responds swiftly to changing circumstances throughout the day.

• Actively encourages a balance among work, home and play.

• Helps you prioritize your work

Profile Operating

System

Customizability Resolution

1 Windows Medium 1080p

2 Android Low 1080p

3 Android Medium 720p

4 iOS Medium 480p

5 Windows Low 480p

6 iOS Low 720p

7 iOS High 1080p

8 Android High 480p

9 Windows High 720p

Conjoint Profiles

4.80

4.85

4.90

4.95

5.00

5.05

5.10

5.15

5.20

5.25

0

50

100

150

200

250

300

350

400

Grp1 Grp2 Grp3 Grp4 Grp5 Grp6 Grp7 Grp8 Grp9 Grp10

Overall Rating

Count1 Count2 Count3 Count4 Count5 Count6 Count7 Mean

Univariate Analysis

0.00

1.00

2.00

3.00

4.00

5.00

6.00

0

50

100

150

200

250

300

350

400


Relevance


4.60

4.65

4.70

4.75

4.80

4.85

4.90

4.95

5.00

5.05

0

50

100

150

200

250

300

350

400


Credibility


4.30

4.40

4.50

4.60

4.70

4.80

4.90

5.00

5.10

0

50

100

150

200

250

300

350

400


Uniqueness


4.00

4.20

4.40

4.60

4.80

5.00

5.20

0

50

100

150

200

250

300

350

400


Intention To Try


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate1 .418a .175 .167 .83736

a. Predictors: (Constant), Uniqueness,

Relevance, Credibility

Coefficients

Model

Unstandardized

Coefficients

Standardize

d

Coefficients

t Sig.B

Std.

Error Beta1 (Constant)

2.688 0.310 8.682 0.000

Relevance0.294 0.048 0.313 6.095 0.000

Credibility 0.144 0.041 0.184 3.512 0.001

Uniqueness

0.055 0.039 0.071 1.408 0.160

a. Dependent Variable: Overall Rating

So, the equation is –

OR = 2.688 + (Uniqueness*0.055) + (Credibility*0.144) +

(Relevance*0.294)

So, the equation is –

ITT = 3.070 + (Uniqueness*0.174) + (Credibility*-0.010) + (Relevance*0.396)

Model Summary

Model R R Square

Adjusted

R Square

Std. Error

of the

Estimate1 0.328a 0.107 0.100 1.28427

a. Predictors: (Constant), Relevance, Uniqueness,

Credibility

Coefficients

Model

Unstandardized

Coefficients

Standardize

d

Coefficients

t Sig.B

Std.

Error Beta1 (Constant) 2.222 0.475 4.680 0.000

Relevance 0.396 0.074 0.287 5.366 0.000

Credibility -0.010 0.063 0.009 -0.158 0.875

Uniqueness

0.174 0.060 0.153 2.913 0.004

a. Dependent Variable: Intention to try

intention to tryTotal

1.00 2.00 3.00 4.00 5.00 6.00 7.00

gender

1.00 5 6 13 38 76 41 29 221

2.00 2 3 6 17 38 26 14 108

3.00 0 1 0 0 0 0 0 1

4.00 0 0 0 1 1 0 0 2

6.00 0 0 0 1 0 1 0 2

Total 7 10 19 57 115 68 43 334


1.00 2.00 3.00 4.00 5.00 6.00 7.00

btech/n

on

btech

1.00 4 8 14 48 98 55 34 261

2.00 0 2 6 4 12 10 7 41

3.00 0 0 0 1 0 0 0 1

5.00 0 0 0 1 0 1 0 2

Total 4 10 20 54 111 66 41 305

1 – Male

2 – Female

Others – Neglected

• Maximum no of

males and females

gave us the rating

above 5

1 – B.Tech

2 – Non B.Tech

Others – Neglected

• Engineers as well

as non engineers

found our app

suitable


1.00 2.00 3.00 4.00 5.00 6.00 7.00

income

1.00 1 4 4 10 21 13 11 64

2.00 0 2 2 4 16 10 2 36

3.00 1 3 8 25 36 21 15 109

4.00 1 0 4 9 23 16 9 62

Total 3 9 18 48 96 60 37 271


1.00 2.00 3.00 4.00 5.00 6.00 7.00

age

1.00 0 0 0 0 5 2 2 9

2.00 3 9 15 45 78 47 32 229

3.00 2 0 4 9 25 15 8 63

4.00 0 0 0 0 3 2 1 6

Total 5 9 19 54 111 66 43 307

1 – Less than 7 Lakhs

2 – 7-10 lakhs

3 – 10-15 Lakhs

4 – More than 15 Lakhs

• Income level of less than

7 Lakhs and More than

10 Lakhs intent to try our

app.

1 – Less than 22 Years

2 – 22-25 Years

3 – 26-28 Years

4 – More than 29 Years

• People having age

between 22 to 25 years

intent to try the app.


1.00 2.00 3.00 4.00 5.00 6.00 7.00

work ex

1.00 0 7 7 20 33 24 14 105

2.00 0 2 2 11 20 16 11 62

3.00 3 1 10 15 42 11 10 92

4.00 1 0 0 7 13 13 7 41

Total 4 10 19 53 108 64 42 300

1 – less than 12 months

2 – 12-24 months

3 – 24-36 months

4 – More than 36 months

• People with work experience less

than 12 months and 24-36 months

found our app worth trying.

Here are the facts about the responses –

• Out of 334 responses, 221 were male & 108 female.

• 261 are Engineers & 44 are others.

Age Group Frequency

Less than 22 9

22-25 229

26-28 63

More than 28 6

Work Experience (in

Months)

Frequency

Less than 12 105

12-24 62

24-36 92

More than 36 41

Household Income Frequency

Less than 7 Lakhs 64

7-10 Lakhs 36

10-15 Lakhs 109

More than 15 Lakhs 62

RegionNo of Respondents Belonging to

that region

East 170

West 27

North 54

South 22

Central 15

Utility and importance of features winner concept of Section A

The interpretation of results for Conjoint Analysis of Group 3 are-

Conjoint Analysis

Regression Eqn-

Preference = 4.75 – 0.11DP1+ 0.11DP2+ 0.13DL1 + 0.07DL2 + 0.11DA1+ 0.01DA2

PRICE Life Support Features Academic Support

Features

α60 – α20 = -0.11 αL2 – αL1 = 0.13 αA2 – αA1 = 0.11

α95 – α20 =0.11 αL3 – αL1 = 0.07 αA3 – αA1 = 0.01

α20 + α60 + α95=0 αL1 + αL2 + αL3=0 αA1 + αA2 + αA3=0

Equations for calculating part worth

LEVEL

ATTRIBUTE Level Description Utility ImportancePRICE 1 20 (Basic) ( P1) -0.111

0.48062 60 (Standard) (P2) 0.109

3 95 (Premium) 0.002

LIFE SUPPORT

FEATURES1 Insta services +Expense

Tracker (L1) 0.061630.282

2 NewsCenter (L2) 0.00600

3 Health and Fitness -0.06763

ACADEMIC

SUPPORT

FEATURES

1 Interview Preparation (A1) 0.069

0.2372 Academic & Committee

Planner (A2) -0.028

3 Insta services +Expense

Tracker -0.040

N=366*9 = 3294 data points

Utility and importance of features of our App

Our conjoint analysis is used for the purpose of app- product development research. We have taken the

operating system, customizability of the app and the resolution supported by the app

The regression equation:

Preference= 4.791+0.037*DO1+0.203DO2-0.080DC1-0.160DC2+0.172DR1-0.069DR2

• When operating system changes from android to windows, preference decreases by 0.033

• When resolution is increased from 480p to 720p, it goes down by 0.027

• Customization is the most important feature of the app.

Operating System Customizability Resolution Supported by

App

αI-αA = 0.037 αM-αH = -0.080 α720-α480 = 0.172

αW- αA= 0.203 αL- αH = -0.160 α1080 - α480 = -0.069

αI+αA+ αW = 0 αM+αH+ αL = 0 α720 + α480+ α1080 = 0

Levels

Attribute No. Description Utility Range Importance

Operating

System

1 Android -0.08 0.203 32.27%

2 iOS -0.043

3 Windows 0.123

Customizability 1 High 0.080 0.16 25.43%

2 Medium 0.000

3 Low -0.080

Resolution

Supported by

App

1 480p -0.051 0.266 42.28%

2 720p 0.146

3 1080p -0.12

Sum of part worth 0.629 100%

N=366*9 = 3294 data points

The following factors were identified and explained 65.62 % of variance –

• Factor 1 – Incomplete life without luxury (0.656), incomplete life without International Travel (0.712) and Exotic Food (0.650) . Factor name is Luxury

• Factor 2 – Spouse (0.559) , Social Work (0.780) , India’s Development (0.803). So the factor can be named as Networking.

• Factor 3 – Power (0.735), Success (0.820). So the factor can be named as success.

• Factor 4 – Work-life Balance (0.866), Enrich parent’s life (0.754). So this factor can be named as Importance

• Factor 5 – Small Cities (0.832), Career Opportunities in Mega Cities (0.895). So this factor can be named as Lifestyle.

*The brackets show the factor loadings for various variables in a factor.

Rotated Component Matrixa

Component

1 2 3 4 5

To me success means money. 0.820

To me success means that I need to become powerful. 0.735

Without Luxury life doesn’t have any meaning. 0.656

For me work-life balance is the most important thing in life. 0.866

It is important for me that I enrich my parents’ life. 0.754

I want to get all those things in life which I could not get

from my parents.

Without a Luxurious car life is incomplete.

My life will be incomplete if I don’t get a chance for

frequent international travel.0.712

Exotic food is a must for my life. 0.650

My spouse should add glamour to my life. 0.559

Without social work my life does not have any meaning. 0.780

My life will be incomplete if I do not get a chance to work

for India’s development0.803

I can not live in small cities. 0.832

Only Mega cities can give me ample career opportunities. 0.895

Number of Cases in each

Cluster

Cluster

1 173.000

2 95.000

3 57.000

4 33.000

Valid 358.000

Missing 6.000

Distances between Final Cluster Centers

Cluster 1 2 3 4

1 2.984 6.055 3.250

2 2.984 4.149 3.428

3 6.055 4.149 5.666

4 3.250 3.428 5.666

The following clusters were identified and the tables show cluster membership &

distance between cluster centres:

3 discriminant functions were observed with the following data –

Eigenvalues Wilks' Lambda

Function Eigenvalue% of

Variance

Cumulative

%

Canonical

Correlation

Test of

Function

(s)

Wilks'

Lambda

Chi-

squaredf Sig.

1 3.725a 86.4 86.4 0.888

1

through

30.126 728.843 15 .000

2 0.326a 7.6 93.9 0.496

2

through

30.598 181.453 8 .000

3 0.262a 6.1 100.0 0.455 3 0.733 81.951 3 .000

Wilk‘s lambda is low for 1st and 2nd function, so they contribute significantly to group differences.

The coefficients of the 3 functions are shown in the table –

Standardized Canonical Discriminant Function

Coefficients

FactorsFunction

1 2 3

Luxury 0.951 0.435 0.387

Networking 0.756 -0.711 0.290

Success 0.928 0.404 0.047

Importance -0.877 0.333 0.161

Lifestyle 0.658 0.040 -0.823

Structure Matrix

Function

1 2 3

Networking 0.223 -0.748 0.321

Luxury 0.288 0.470 0.439

Success 0.253 0.392 0.048

Importance -0.229 0.310 0.157

Lifestyle 0.184 0.040 -0.862

From the structure matrix –

• Luxury and success are associated with

function 1

• Luxury and success are again associated

with 2nd function

• Luxury and networking are associated

with 3rd function.

Cluster

Number

of Case

Function

1 2 3

1 1.556 -0.096 -0.315

2 -0.845 0.836 0.325

3 -3.773 -0.548 -0.354

4 0.789 -0.959 1.329

Unstandardized canonical discriminant

functions evaluated at group means

The coefficients of discriminant functions at various cluster centres are shown in the

table below –

Inferences –

• Cluster 1 gives more emphasis on

function 1 as compared to others, i.e. the

respondents belonging to cluster one

favoured Luxury & Success.

• Cluster 2 has evaluated Luxury &

Success as most favourable.

• Cluster 3 has evaluated Luxury &

Networking as most favourable.

• Cluster 4 has favoured Luxury &

Networking.

Xquilibrio• Segmentation

• Based upon the conjoint analysis, price is the most significant attribute so we divide our market based

upon the buying power of the consumers into 2 offerings:-

• Standard

• Premium

• Then we segregate the customers based upon the perceived utility into 4 categories:-

• Scholars

• Health conscious students

• News seekers

• Committee members

• In order to cater to customers who want are both price and feature sensitive we would bundle them into

various Combo offers

• Target market

• MBA students of XIMB

• Appeal to different categories of students in a customizable way.ie. tweak the app based upon the type of

students we are targeting

• Involve famous personalities like youth icons so that customers identify themselves with the ambassadors.

• Positioning

• Project as a value added app

• Harness potential work life balance expectations

• Focus on price and quality

• 5 Factors were identified –

o Luxury

o Networking

o Success

o Importance

o Lifestyle

Cluster Size Favoured FactorsDiscrimina

nt Function

1 173 Luxury & Success Function 1

2 95 Luxury & Success Function 2

3 57 Luxury & Networking Function 3

4 33 Luxury & Networking Function 3

The target group, segmentation variables and

positioning strategies were clearly stated.

Mm3 project ppt group 1_section a

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