Studying the Consumer Buying Behavior while buying a laptop

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Studying the Consumer Buying Behavior while buying a laptop at SIC Marketing Research Project SUBMITTED BY: YATEESH HOBLIDAR 2009A02 PURAV SHAH 2009A04 TUSHAR ALVA2009A06

description

Laptop Questionnaire and the research on the various brands that can be purchased and the various features.

Transcript of Studying the Consumer Buying Behavior while buying a laptop

Page 1: Studying the Consumer Buying Behavior while buying a laptop

Studying the Consumer Buying Behavior

while buying a laptop at SIC

Marketing Research Project

SUBMITTED BY:

YATEESH HOBLIDAR – 2009A02

PURAV SHAH – 2009A04

TUSHAR ALVA– 2009A06

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Contents Executive Summary ........................................................................................................................... 4

Background ....................................................................................................................................... 4

Objectives: ........................................................................................................................................ 5

Primary Research Objective: .......................................................................................................... 5

Secondary Research Objective: ...................................................................................................... 5

Research Approach............................................................................................................................ 6

Data collection method ................................................................................................................. 6

Measurement technique ............................................................................................................... 6

Sample .......................................................................................................................................... 6

Analytical approach ....................................................................................................................... 7

Cost and Time requirement: .......................................................................................................... 7

Exploratory Research – Questionnaire ............................................................................................... 9

Secondary Data ............................................................................................................................... 10

Primary Questionnaire .................................................................................................................... 12

Respondent Profile .......................................................................................................................... 17

Chi-Square ....................................................................................................................................... 19

ANOVA ............................................................................................................................................ 21

Factorial Design: .......................................................................................................................... 22

Factor Analysis ................................................................................................................................ 24

Cluster Analysis ............................................................................................................................... 27

Multidimensional Scaling ................................................................................................................. 30

Attribute Based Perceptual Mapping ............................................................................................... 32

Recommendations .......................................................................................................................... 36

Appendix A – Anova (Factorial Design)............................................................................................. 38

Appendix B - Hierarchical Clustering Data ........................................................................................ 39

ICICLE PLOT ................................................................................................................................. 41

Appendix C – K-Means Cluster Analysis............................................................................................ 42

Appendix D - Attribute based Perceptual Mapping .......................................................................... 44

References: ..................................................................................................................................... 47

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Executive Summary

Laptops are an integral part of today’s management student’s study kit. And with a

plethora of brands inundating the market, each trying to differentiate itself from the other in

terms of features, style, etc and trying to entice the buyer with attractive offers, the decision

of zeroing on the laptop has become a gruesome exercise for the student. The very nature

of the product encourages the prospective buyer to go through all the stages of a typical

buying process. That is the reason that we have taken up to study the consumer buying

behavior for laptop buying.

The primary objective of the project can be satisfied progressively by satisfying the

secondary research objectives which are determining the factors, mapping the customer

profile & perceptual mapping. A primary research based on questionnaires and analytical

processing of the response will be conducted to fulfill the research objectives wherever the

secondary data is not available.

The student community of the IC campus will form the sample for the research and

the research is expected to take about 20 days and cost around Rs 210.

Background

The computers have come a long way from their birth as complex mechanical

calculating machines available only to a few large institutions to being ubiquitous complex

electronic systems capable of handling large amount of data and executing complex

calculation in the today’s world. Their power and performance has been growing at an

incredible pace which has made them a must-have for every business from a retail shop to

airlines. The ever decreasing price of the computer systems has only added to the trend. All

these factors have increased the importance of computers in the business world and

otherwise at a phenomenal rate especially over the past few years.

As the requirement for better, powerful, compact, faster & higher memory computer

systems grew, smaller & portable computer systems called laptops was introduced. These

wonderful machines are a great help to the user owing to their compactness and capabilities.

In the present age of information, laptops have proved to be an executive ’s best friend. Their

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feature of compactness over desktop PCs gives the user the convenience to work, share

and stay connected while on the go.

The B-Schools of the day have taken cognizance of the developing situation and are

training the future managers to be well versed and comfortable in using the

computers/laptops. The B-Schools across the globe have been introducing computer

enabled analysis, reporting decision support, management, etc as an integral part of their

curriculum.

Following the trends taking shape in the business world, the three colleges, SCMHRD, SCIT

and SIIB at the Symbiosis Infotech Campus, Hinjewadi, Pune have made it compulsory for

the students to use laptops for academic purposes. Every year around 600 students enrol for

the regular MBA course offered by these institutions. The students coming to the institutes

belong to different social, cultural and economical background. Hence, the study of

preferences for a laptop at SIC can help understand what the youth sees while buying

laptop.

Objectives:

Primary Research Objective:

To study the consumer behaviour while buying a laptop at Symbiosis Infotech Campus.

Secondary Research Objective:

1. To study the influence of various variables like sex, educational background, family

annual income, work experience, etc on the choice of laptop brand.

2. To probe if the interactions between the above mentioned variables have any effect on

the choice of laptop bought.

3. To group the huge number of attributes into major factors (Factor Analysis).

4. To map the profile of the students in terms of lifestyle, attitude & perception

(Segmentation).

5. To evaluate the student preferences about laptops of different brands available in the

market. (Attribute based perceptual mapping).

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Research Approach

Data collection method

For exploratory research, the following techniques were used:

a. Open-ended questionnaire – These questions were used to know what are the

different attributes which a student at SIC looks for while selecting a laptop.

b. Focused group discussions – Here, a discussion among a group of students was

arranged to bring out the attributes that are evaluated by the students while selecting

a laptop.

For secondary research, the following sources were used:

a. Websites of different laptop brands to know their unique selling propositions.

b. Other journals and tech magazines available online and at SCMHRD library.

Based on the attributes found out in the exploratory research and the secondary research,

the information gap was identified and hence it was decided to conduct primary research to

fill the gap. The research was conducted by administering questionnaire on the students of

the SIC campus. For primary data collection, Questionnaire administration was done

personally and through online questionnaires.

Measurement technique

Questionnaire was used to collect data from respondents. Questionnaire was given

to the respondents in hard copy or emailed to them. Direct Response Attitude Scales was

used to understand the perceptions of consumers about attributes of various products.

Suitable scale was used based on the number of options available for measuring responses

on multiple dimensions

Sample

A sample size of 104 students from SIC was used for the purpose of research.

Students from both the batches (08-10 and 09-11) were surveyed spanning both the boy and

girl populations to obtain a representative sample. The sampling technique used was area

sampling so that students from all the hostels – A, B and D are surveyed.

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Analytical approach

The data collected from the exploratory research provided us with the different

attributes that a student looks for in a laptop. Based on these responses, another

questionnaire was used to do factor analysis to reduce the number of attributes handled into

fewer attributes, so that handling of factors becomes easier for subsequent analysis.

To determine the profile of various students at SIC so that we can know more about

their lifestyle, attitudes and preferences so as to gain an insight on what kind of laptop they

are likely to choose, we have used cluster analysis, a segmentation technique.

Finally to evaluate the student perceptions about laptops of different brands, we have

used attribute based perceptual mapping using Discriminant analysis and also Multi-

Dimensional Scaling.

Apart from using these three major techniques, we have also used chi square

analysis with cross tab to evaluate whether the preferences are different for boys and girls

and other such one dimensional analysis. We have also used ANOVA technique to analyze

if the effect of various independent variables on the choice of the brand of laptop and also

the interaction effect that these variables have on the laptop choice of the population.

Cost and Time requirement:

The cost involved with research was only the printing and photocopying cost of the

questionnaire. 40 questionnaires were photocopied for the exploratory research while

around 50 were done for the primary research. Rest of the responses was collected from

respondents online. In addition, the final report submission, assuming it to be of about 50

pages, will cost about Rs 50 more. Thus, the total cost for the research will be approximately

Rs. 140.

The project began on 21-12-09 and took about 40 days for completion. the duration

take by each task in the project, their start and end date are mentioned clearly in the Gantt

chart given below.

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Exploratory Research – Questionnaire Name:

Age:

Annual Income:

1. Do you own a laptop? If YES which brand is it?

2. What are the various brands of laptops that you are aware of?

3. What are the various attributes that you look at while purchasing a laptop?

4. What is the purpose of you purchasing a laptop?

5. What are the various features that you would like to have in your laptop?

6. How much would you spend on purchasing the laptop of your choice?

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Secondary Data

The secondary data has been obtained from a project done in the first semester whose Pro was to

determine the factors affecting sales position of the Notebook PC for Dell Corporation India.

The conclusions obtained from the same are as below:

Awareness is a very important factor that leads to increase in sales of the newly developed Netbook PC Segment.

People prefer to buy Notebooks from Authorised retailers more than that from any other form of outlet.

The existing Customer Service practices of Dell Corporation in India are not effective. There is scope for improvement in the delivery time and repair time.

Dell is equally competitive in features and benefits offered as its competitors.

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Primary Questionnaire 1. Name : ______________________________________________

2. Gender : a. Male b. Female

3. Indicate the age group you fall into

a. < 20 years

b. 20-22 years

c. 22-25 years

d. > 25 years

4. Indicate your educational qualification

a. BE/BTech

b. MBBS/BDS

c. B.Com

d. BSc

e. BA

f. Other (specify): ______________

5. Indicate your work experience

a. 0-1 years

b. 1-2 years

c. 2-4 years

d. > 4 years

6. Which brand of laptop are you currently using

a. Dell

b. Lenovo

c. HP

d. Toshiba

e. Apple

f. Acer

g. Vaio

h. Other ________

7. Indicate your agreement to the below statements on a 7 point Likert scale where

1- Strongly Agree

2- Moderately Agree

3- Mildly Agree

4- Neither agree nor disagree

5- Mildly Disagree

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6- Moderately Disagree

7- Strongly Disagree

I want a laptop which attracts attention of colleagues 1 2 3 4 5 6 7

I don’t mind buying products based on recent (not-proven,

yet) technologies.

1 2 3 4 5 6 7

I feel utility matters and not the looks of any product. 1 2 3 4 5 6 7

I feel family plays an important role in my purchasing

decision.

1 2 3 4 5 6 7

I prefer a foreign made product to Indian made products. 1 2 3 4 5 6 7

I use email as a major source of communication. 1 2 3 4 5 6 7

I use laptop for entertainment more than for any other

purpose.

1 2 3 4 5 6 7

Owning a computer in today's world is very important. 1 2 3 4 5 6 7

I think borrowing money even during times of need is not a

good idea.

1 2 3 4 5 6 7

I feel everyone should enjoy the present without worrying too

much about the future.

1 2 3 4 5 6 7

I am a very fashion conscious person. 1 2 3 4 5 6 7

I feel good quality means more price 1 2 3 4 5 6 7

I prefer branded products 1 2 3 4 5 6 7

8. Indicate your preferences for laptop based on the following attributes.

I bought my laptop because it had a great display. 1 2 3 4 5 6 7

Bigger memory in a laptop is a must. 1 2 3 4 5 6 7

My laptop works on the best available processor. 1 2 3 4 5 6 7

I use my laptop to make a style statement. 1 2 3 4 5 6 7

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My friends are jealous of my laptop because it is exclusive. 1 2 3 4 5 6 7

I bought my laptop because it had a great texture. 1 2 3 4 5 6 7

I bought my laptop because it was affordable. 1 2 3 4 5 6 7

Wi-Fi connection is the growing trend in internet connection. 1 2 3 4 5 6 7

Laptops can be used as an alternative to digital cameras. 1 2 3 4 5 6 7

High quality audio is very important for watching movies on

laptops.

1 2 3 4 5 6 7

I feel that the data kept in my laptop is always secure. 1 2 3 4 5 6 7

Bulky laptops are an important reason for their owner’s back

aches.

1 2 3 4 5 6 7

The battery backup of a laptop depends on the usage and not

on the brand.

1 2 3 4 5 6 7

I am aware of the features and weaknesses of different OS

versions.

1 2 3 4 5 6 7

I like to show off my laptop’s features in front of thers. 1 2 3 4 5 6 7

I like to try newer and better versions (heavier) of computer

games.

1 2 3 4 5 6 7

I believe that heat dissipaters of the laptops have to be

complimented with extra devices for optimal operation.

1 2 3 4 5 6 7

Laptops can serve as an important storage medium for all the

data from the mobile devices.

1 2 3 4 5 6 7

I liked my friend’s laptop that had a larger keyboard to

accommodate the additional functional keys.

1 2 3 4 5 6 7

My girlfriend/boyfriend/bestfriend uses the same model. 1 2 3 4 5 6 7

My laptop has attractive accessories. 1 2 3 4 5 6 7

Add-on software packages with laptops are a must. 1 2 3 4 5 6 7

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I always shop when a new scheme or offer is on. 1 2 3 4 5 6 7

Extended service warranty is a redundant offer with a good

laptop.

1 2 3 4 5 6 7

I can travel any distance to buy my favourite laptop. 1 2 3 4 5 6 7

I believe that a good laptop (from a reliable brand) hardly

encounters any glitch.

1 2 3 4 5 6 7

I do not mind paying extra for a good service. 1 2 3 4 5 6 7

I need to have freedom of choosing the features in my laptop

even if that comes at a price.

1 2 3 4 5 6 7

9. Rank your current laptop on the following attributes

Rank on the scale of 1 to 5. Rank 1 if you find your laptop very bad on the attribute

and 5 if you find your laptop very good on the attribute and so on.

Brand Image 1 2 3 4 5

Features Configuration 1 2 3 4 5

Style 1 2 3 4 5

Audio/Video Quality 1 2 3 4 5

Price 1 2 3 4 5

Convenience of service 1 2 3 4 5

10. Please indicate the distance (1to 10) between the following brands in the cells below.

Brands which are similar are indicated as 1 and those far apart as 10.

DELL

DELL

DELL

DELL

DELL

DELL

LENOVO

HP

TOSHIBA

APPLE

ACER

VAIO

LENOVO

LENOVO

LENOVO

LENOVO

LENOVO

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HP

TOSHIBA

APPLE

ACER

VAIO

HP

HP

HP

HP

TOSHIBA

APPLE

ACER

VAIO

TOSHIBA

TOSHIBA

TOSHIBA

APPLE

ACER

VAIO

APPLE

APPLE

ACER

VAIO

ACER

VAIO

11. Place the brands in the cells below in terms of their performance in the given

attributes

VERY GOOD

VERY BAD

BRAND IMAGE

FEATURES

CONFIGURATION

STYLE

AUDIO/VIDEO QUALITY

PRICE

CONVENIENCE OF SERVICE

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Respondent Profile Primary research was conducted in online as well as personal interview form. The

questionnaire was created using Google forms and distributed to respondents in the SIC

campus. The main purpose behind doing this was to get data from respondent which varied

demographically and geographically. A total of 104 respondents filled in the questionnaire.

The internet link of the questionnaire is

https://spreadsheets.google.com/viewform?formkey=dFJ2YmcyVUdjWS1UY2liRXlHTkVtV2c6MA

The respondents profile can be seen in the following graphs:

64%

36%

Sex Ratio among respondents

Male

Female

36%

23%

39%

2%

Work Experience of respondents

0-1 years

1-2 years

2-4 years

> 4 years

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43%

4%

37%

13%

3%

Educational Qualification break-up

BE/B.Tech

MBBS/BDS/B.Pharma

B.Com

B.Sc

B.A

6%

39%

31%

24%

Annual Family Income of respondents

< 2 Lacs

2-4 Lacs

4-7 Lacs

> 7 Lacs

33%

11%34%

7%

2% 8%5%

Laptops Owned by respondents

Dell

Lenovo

HP

Toshiba

Apple

Acer

Vaio

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Chi-Square

1. To find out whether the choice of laptop depends on the gender of the individual, we

did a cross tabulation of the data and a chi-square analysis of the laptop choice w.r.t

gender at 95% confidence level.

Hypothesis:

H0 : There is no significant relationship/correlation between the laptop choice and gender at

95% confidence level.

H1: There exists a significant relationship between choice of laptop and the gender of the

person at 95% confidence level.

From the analysis, the following results were obtained:

Case Processing Summary

Cases

Valid Missing Total

N Percent N Percent N Percent

Laptop * Gender 104 100.0% 0 .0% 104 100.0%

Laptop * Gender Crosstabulation

Gender Total

Female Male Female

Laptop Lenovo Count 3 7 10

Expected Count 3.6 6.4 10.0

Dell Count 14 20 34

Expected Count 12.1 21.9 34.0

HP Count 11 25 36

Expected Count 12.8 23.2 36.0

Acer Count 5 3 8

Expected Count 2.8 5.2 8.0

Toshiba Count 2 5 7

Expected Count 2.5 4.5 7.0

Vaio Count 0 5 5

Expected Count 1.8 3.2 5.0

IBM Count 0 2 2

Expected Count .7 1.3 2.0

Apple Count 2 0 2

Expected Count .7 1.3 2.0

Total Count 37 67 104

Expected Count 37.0 67.0 104.0

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Chi-Square Tests

Value df Asymp. Sig.

(2-sided)

Pearson Chi-Square 11.164(a) 7 .132

Likelihood Ratio 13.833 7 .054 Linear-by-Linear Association

.034 1 .855

N of Valid Cases 104

The chi square value comes out to be 11.64 for 7 degree of freedom. The p value is

0.132. If we check at 95% confidence level since p observed > p critical, we cannot reject

the hypothesis. Thus, there is no significant relationship between the laptop choice and the

gender of the buyer.

2. To find whether there is a relationship between the graduation degree and the laptop

choice of students. For this too, we do a cross tabulation analysis using chi-square.

We test the laptop brand choice w.r.t the degree obtained by the respondent.

Hypothesis:

H0: There is no significant relation between the laptop choice and the graduation degree of

respondent at 95% confidence level.

H1 : There is a significant relationship between the laptop choice and the graduation degree

of respondent at 95% confidence level.

Chi-Square Tests

Value Df Asymp. Sig.

(2-sided)

Pearson Chi-Square 68.740(a) 49 .033

Likelihood Ratio 76.774 49 .007 Linear-by-Linear Association

2.260 1 .133

N of Valid Cases 103

From the table above, it can be seen that the chisquare value is very high while the p

value is low abolut 3.3%. At 95% confidence level, we will have to reject the null hypotheses

since the p value (observed) < p value critical. Thus, we reject the null hypothesis and

conclude that there is a significant relation between the degree and the kind of laptop

selected.

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Laptop * Degree Cross tabulation

C

Degree

Total B.E/B.Tech BSc. MBBS/BDS B.Com B.A BBA M.Sc BBM

Laptop Lenovo 7 3 0 0 0 0 0 0 10

Dell 12 3 5 6 3 3 2 0 34

Vaio 5 0 0 0 0 0 0 0 5

HP 22 2 0 8 0 0 0 3 35

Acer 0 3 3 2 0 0 0 0 8

Toshiba 7 0 0 0 0 0 0 0 7

IBM 2 0 0 0 0 0 0 0 2

Apple 2 0 0 0 0 0 0 0 2

Total 57 11 8 16 3 3 2 3 103

It can be seen from the cross tabulation that while Dell is chosen by almost all

students, brands like Acer are popular among the MBBS students and B.E/B.Tech students

tend to use more of HP computers. The B.Com students use HP, Acer and Dell. Thus, there

is a relationship between the degree obtained by the respondent and the laptop brand used

by him.

ANOVA ANOVA stands for Analysis Of Variance, the generic name given to a set of

techniques for studying cause-and-effect of one or more factors (independent variables) on a

single dependant variable. ANOVA is used when the independent variable are of nominal

scale (categorical) and the dependant variable is metric (continuous). The application areas

in marketing research for experiments using ANOVA as the analytical method are wide.

Whenever a marketing mix variable such as price, a specific promotion or type of

distribution, even specific elements like shelf space, or color of packaging and so on is

change, we would want to know its effect. Under proper conditions, an experiment can tell us

the effects of specific variations in one or more elements of the marketing mix.

In our project ANOVA has been used to study the effect of multiple factors on the

choice of laptop simultaneously and also the interaction effect between the independent

factors (factorial design with 3 factors).

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Factorial Design:

Null Hypothesis

There is no significance difference in the choice of the laptop brand between

respondents of different educational background.

There is no significance difference in the choice of the laptop brand between

respondents of with varied annual family income.

There is no significance difference in the choice of the laptop brand between

respondents of varied amount of work experience.

There is no significant impact on the choice of laptop brand when both

educational background and the family income interact with each other.

There is no significant impact on the choice of laptop brand when both

educational background and years of work experience interact with each other.

There is no significant impact on the choice of laptop brand when both annual

family income and years of work experience interact with each other.

There is no significant impact on the choice of laptop brand when annual family

income, work experience and educational background of the respondent interact

with each other.

Findings:

The significance of the F-test with respect to the variable educational qualification

is 0.037.

The significance of the F-test with respect to the variable annual family income is

0.004.

The significance of the F-test with respect to the variable years of work

experience is 0.126.

The significance of the F-test with respect to the interaction of the variables

educational qualification and annual family income is 0.000.

The significance of the F-test with respect to the interaction of the variables

educational qualification and work experience is 0.336.

The significance of the F-test with respect to the interaction of the variables

annual family income and tears of work experience is 0.038.

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The significance of the F-test with respect to the interaction of the variables

educational qualification and annual family income and work experience is 0.605.

Inference:

As 0.037 < 0.05, we reject the null hypothesis and infer that educational

qualification has a significant impact on the choice of laptop brand.

As 0.004 < 0.05, we reject the null hypothesis and infer that annual family has a

significant impact on the choice of laptop brand.

As 0.126 > 0.05, we do not reject the null hypothesis and infer that educational

qualification does not have a significant impact on the choice of laptop brand.

As 0.000 < 0.05, we reject the null hypothesis and infer that the interaction of the

variables educational qualification and family income has a significant impact on

the choice of laptop brand.

As 0.336 > 0.05, we do not reject the null hypothesis and infer that the interaction

of the variables educational qualification and family income does not have a

significant impact on the choice of laptop brand.

As 0.038 < 0.05, we reject the null hypothesis and infer that the interaction of the

variables family income and work experience has a significant impact on the

choice of laptop brand.

As 0.605 > 0.05, we do not reject the null hypothesis and infer that the interaction

of the variables educational qualification, family income and work experience

does not have a significant impact on the choice of laptop brand.

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Factor Analysis Factor Analysis is a general name denoting a class of procedures primarily used for

data reduction and summarization. In marketing Research, there may be a large number of

variables most of which are correlated and which must be reduced to a manageable level.

Relationships among sets of many interrelated variables are examined and represented in

terms of a few underlying factors. Factor Analysis is an independent technique in that an

entire set of independent relationships is examined.

Factor analysis is used in the following circumstances:

1. To identify underlying dimensions or factors that explains the correlation among a

set of variables. For ex, a set of lifestyle statements may be used to measure the

psychographic profiles of consumers. These statements may be factor analyzed

to identify the underlying psychographic factors.

2. To identify a new, smaller set of uncorrelated variables to replace the original set

of correlated variables in subsequent multivariate analyses.

3. To identify a smaller set of salient variables from a larger set for use in

subsequent multivariate analysis. For example, a few of the original lifestyle

statements that correlate highly with the identified factors may be used as

independent variables to explain the differences between the loyal and normal

users.

In the exploratory research, we obtained 28 attributes which respondents find important

while buying a laptop. Factor analysis was used to club similar attributes into factors so as to

know what exactly the consumers look for while choosing a laptop.

The total variance explained is shown in the table below along with the eigen value at each

stage. When the eigen value drops below 1, we stop the factor analysis process. Since at

the 6th stage, the eigen value became < 1, we stopped the process and concluded that

there are 6 factors as per the respondents.

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We obtained the following 6 factors after doing factor analysis:

Factor 1 Convenience features

Factor 2 Heavy usage features

Factor 3 Style features

Factor 4 Gaming features

Factor 5 Easy movability features

Factor 6 Security features

By the main questionnaire, we tried to measure people’s attitude towards various attributes

that directly or indirectly affect the buying behaviors of people towards buying of snacks

food. Please refer to questionnaire in the appendix. Respondents were asked questions like

if they prefer foreign brands, if they watch TV during leisure time, If people around them

affect their buying decisions.

Respondents were asked to rate their attitude towards on a Likert scale of 1 to 7, where 1

stands for Strongly agree and 7 stands for strongly disagree.

The data collected was analysed using SPSS for identifying the significant factors. Factors

with eigen values more than 1 were considered and it explained 70% of the total variation.

Factors identified are Brand Image, taste, price, quality and advertisement & promotions.

Component

Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %

1 11.79 42.11 42.11 11.79 42.11 42.11 8.10 28.91 28.91

2 3.80 13.58 55.69 3.80 13.58 55.69 4.82 17.22 46.13

3 2.90 10.34 66.03 2.90 10.34 66.03 4.26 15.22 61.35

4 2.36 8.44 74.47 2.36 8.44 74.47 2.75 9.83 71.18

5 1.96 7.00 81.47 1.96 7.00 81.47 2.67 9.53 80.71

6 1.39 4.98 86.45 1.39 4.98 86.45 1.61 5.74 86.45

7 0.97 3.46 89.91

8 0.82 2.93 92.84

9 0.57 2.04 94.88

10 0.46 1.63 96.51

11 0.35 1.25 97.76

12 0.29 1.05 98.81

13 0.14 0.48 99.30

14 0.08 0.30 99.60

15 0.06 0.22 99.82

16 0.04 0.15 99.96

17 0.01 0.04 100.00

18 0.00 0.00 100.00

19 0.00 0.00 100.00

20 0.00 0.00 100.00

21 0.00 0.00 100.00

22 0.00 0.00 100.00

23 0.00 0.00 100.00

24 0.00 0.00 100.00

25 0.00 0.00 100.00

26 0.00 0.00 100.00

27 0.00 0.00 100.00

28 0.00 0.00 100.00

Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

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After the factor analysis, perceptual maps were drawn using excel for graphically depicting

the relationship by showing the loadings of various attributes on factors identified. Every

possible combination leading to 6C2 i.e. total fifteen maps are drawn for the factor

combinations. One such perceptual map is as shown below:

Series 1 : F2 v/s F3 i.e Heavy usage v/s Style parameters

Rotated Component Matrix:

Factor No. 1 2 3 4 5 6

DisplayQuality 0.224 0.757 -0.033 0.515 0.031 0.083

Memory 0.208 0.763 -0.403 0.251 -0.047 0.112

Processor 0.438 0.859 -0.072 0.105 -0.091 0.054

Looks -0.171 -0.069 0.861 0.151 -0.232 -0.007

Brand 0.744 0.523 -0.208 0.041 0.131 0.101

Texture 0.135 0.048 0.916 -0.244 0.045 -0.007

Price -0.850 -0.115 0.272 -0.378 0.056 0.005

WiFi 0.248 0.164 -0.807 0.117 0.374 -0.123

Camera -0.534 -0.245 0.347 -0.058 0.477 -0.132

AudiospeakersMic 0.520 0.731 0.172 0.039 0.098 -0.061

FingerprintScan -0.076 -0.029 -0.235 0.327 -0.118 0.719

WeightSize -0.169 -0.129 0.354 0.199 -0.789 -0.059

BatteryLife -0.806 -0.309 0.054 -0.423 -0.008 0.083

Operatingsystempreloaded 0.722 0.253 -0.117 0.355 0.147 -0.195

Manyfeatures -0.155 -0.097 0.835 -0.336 0.334 -0.009

Graphicscard 0.219 0.275 -0.167 0.702 0.019 -0.081

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

-0.2 0 0.2 0.4 0.6 0.8 1 1.2

Series1

Texture

Audio

Display

Porcessor

Customized

Memory

Wi-Fi

Many features

Page 27: Studying the Consumer Buying Behavior while buying a laptop

Heatdissipationefficiency -0.793 -0.221 0.513 0.020 -0.117 -0.062

Bluetooth -0.805 -0.175 0.185 -0.260 0.197 -0.140

FunctionButtons 0.813 0.424 0.108 0.206 0.148 0.016

Othersopinion 0.272 0.098 -0.253 0.760 0.041 0.284

Accessories 0.907 0.192 0.158 0.221 -0.065 0.098

Addonsoftwares 0.421 0.164 0.269 0.532 0.498 0.298

SchemesandOffers -0.027 0.051 0.077 -0.169 -0.839 0.106

Extendedservice 0.185 0.108 0.239 -0.099 0.026 0.858

Easyavailabilityofdealers 0.668 0.559 -0.148 -0.129 -0.164 0.058

Closeaftersalesservice 0.907 0.028 -0.005 -0.146 0.223 0.108

Onsiteservice -0.510 0.422 0.341 0.109 0.553 -0.001

Customisedlaptops 0.121 0.956 -0.038 0.068 0.133 -0.016

The attributes important for each factors have a corelation value of > ±0.7. These have been

shown by the darkened cells in the table above.

Cluster Analysis (Please refer to Appendix B and C)

Cluster Analysis is a class of techniques used to classify objects or cases into relatively

homogenous groups called clusters. Objects in each cluster and tend to be similar to each

other and dissimilar to objects in the other clusters. Cluster analysis is also called

classification analysis or numerical taxonomy. Cluster Analysis is also used for the following:

1. Segmenting the market: For ex: Consumers may be clustered on the basis of

benefits sought from the purchase of a product. Each cluster would consist of

consumers who are relatively homogenous in terms of the benefits they seek. This

approach is called benefit segmentation.

2. Understanding Buyer Behaviors: Cluster Analysis can be used to identify

homogenous groups of buyers. Then the buying behavior of each group can be

examined separately.

3. Identifying new product opportunities: By clustering brands and products, competitive

sets within the market can be determined.

4. Selecting Test Markets:

5. Reducing Data: Clustering analysis can be used as general data reduction tool to

develop clusters or subgroups of data that are more manageable than individual

observations.

Page 28: Studying the Consumer Buying Behavior while buying a laptop

The hierarchical clustering was performed on the sample data using SPSS. The sample

consisted of data from 104 respondents on 13 variables. The agglomeration schedule gives

the stage wise cluster formation. Based on the quantum jump in the coefficients, it was

decided to have 5 clusters. After the subjective decision to have five clusters, K-means

cluster analysis was carried out with number of clusters as 5.

The clusters identified are as given below:

Cluster1 – Lazy Individuals:

They do not feel that quality comes with price.

They prefer branded products.

They are not interested in showing –off their laptops.

They are risk averse.

They value utility of a product more than its attractiveness.

They never involve their families in their purchasing decisions.

They are indifferent to Indian made and foreign products.

They always use email as a major source of communication.

They use laptops more for entertainment purposes than for any other purpose.

They feel computers are very important in today’s world.

They strongly feel that borrowing money even during times of need is improper.

They are cautious about their future.

They are fashion conscious.

Cluster2 – Adventurous:

They feel that quality comes with price.

They prefer branded products.

They are not interested in showing –off their laptops.

They do not mind taking risks while buying products based on unproven

technologies.

They strongly value utility of a product more than its attractiveness.

They involve their families in their purchasing decisions.

They are indifferent to Indian made and foreign products.

They always use email as a major source of communication.

They use laptops equally for entertainment and other purposes.

They feel computers are very important in today’s world.

They strongly feel that borrowing money even during times of need is improper.

Page 29: Studying the Consumer Buying Behavior while buying a laptop

They are indifferent to saving for the future.

They are fashion conscious.

Cluster3 – Flexible:

They feel that quality comes with price.

They prefer branded products.

They are not interested in showing –off their laptops.

They are risk averse.

They are indifferent between utility of a product and its attractiveness.

They involve their families in their purchasing decisions.

They are indifferent to Indian made and foreign products.

They always use email as a major source of communication.

They use laptops equally for entertainment and other purposes.

They feel computers are very important in today’s world.

They feel that borrowing money during times of need is proper.

They are indifferent to saving for the future.

They are indifferent to fashion.

Cluster4 – Patriotic:

They feel that quality comes with price.

They prefer branded products.

They hate to show –off their laptops.

They are risk averse.

They value utility of a product more than its attractiveness.

They involve their families in their purchasing decisions.

They prefer Indian made to foreign products.

They always use email as a major source of communication.

They use laptops equally for entertainment and other purposes.

They feel computers are very important in today’s world.

They strongly feel that borrowing money even during times of need is improper.

They are indifferent to saving for the future.

They are indifferent to fashion.

Cluster5 – GenY:

They feel that quality comes with price.

They strongly believe in branded products.

Page 30: Studying the Consumer Buying Behavior while buying a laptop

They like to show –off their laptops.

They are indifferent to risk involved in buying a product based on unproven

technology.

They value utility of a product more than its attractiveness.

They involve their families in their purchasing decisions.

They prefer foreign made to Indian products.

They always use email as a major source of communication.

They use laptops for entertainment purposes.

They feel computers are very important in today’s world.

They are indifferent to borrowing money during times of need.

They are a carefree lot who believe in enjoying the present.

They are indifferent to fashion.

Multidimensional Scaling MDS is a class of procedures for representing perceptions and preferences of

respondents spatially by means of a visual display. Perceived or psychological relationships

along stimuli are represented as geometric relationships among points in a multidimensional

space. These geometric representations are often called spatial maps. The axes of the

spatial map are assumed to denote the psychological bases or underlying dimensions

respondents use to form perceptions and preferences for stimuli. MDS is used to identify:

1. The number and nature of dimensions consumers use to perceive different brands in

the market place

2. The positioning of current brands on these dimensions

3. The positioning of consumers’ ideal brand on these dimensions.

In our research we used multidimensional scaling technique for finding the number of

dimensions on which people perceive different leading brands that had come up during

exploratory research.

Out of 104 respondents, we filtered out non-serious responses in the distances we had

asked between brands. Users having given same distances between all the brands were not

considered. Also we applied our own perception to weed out arbitrary and casual responses.

Out of serious responses, we took averages of the distances between various brands given

by the users.

Below is the average distance matrix between top five brands.

Page 31: Studying the Consumer Buying Behavior while buying a laptop

Apple Viao Dell HP Toshiba Lenovo Acer

Apple 0 1.4 6.3 5.8 7 6 10.6

Viao 1.4 0 5 4.47 5.6 5.3 9.2

Dell 6.3 5 0 1.4 3.16 5 5.3

HP 5.8 4.47 1.4 0 2 3.6 5

Toshiba 7 5.6 3.16 2 0 3.16 3.6

Lenovo 6 5.3 5 3.6 3.16 0 5.09

Acer 10.6 9.2 5.3 5 3.6 5 0

We ran SPSS software for multidimensional scaling. We got that above distances between

brands can be explained using two dimensions, with Kruskal’s stress less than 2.75%.

Attached below is the SPSS output.

Page 32: Studying the Consumer Buying Behavior while buying a laptop

Stimulus Coordinates

Stimulus Number

Stimulus Name

Dimension

1 2

1 Apple 2.0575 -0.1803

2 Viao 1.5328 0.0732

3 Dell -0.2741 0.9531

4 HP -0.1932 0.3928

5 Toshiba -0.6936 -0.0418

6 Lenevo -0.3032 -1.0412

7 Acer -2.1263 -0.1559

Attribute Based Perceptual Mapping

In this case there are 7 brands of laptop and we are interested in finding out how customers

perceive these brands. In particular, we would like to know how the brand we are marketing

is perceived in relation to other brands.

Dell

HP

LenovoToshiba

Apple

Acer

Vaio

-6

-4

-2

0

2

4

6

-20 -10 0 10 20

Price,Service

Features,Configuration

Series1

Page 33: Studying the Consumer Buying Behavior while buying a laptop

Thus from the above graphs we can observe that the brands Dell and HP fall in the first

quadrant and hence have great features and are priced well as well. Then in the second

quadrant there is Apple and Vaio and in this it shows that Apple is costly but it is not as good

as Dell with respect to configuration. Here Vaio is also costly but the configuration is better

than Apple. In the third quadrant we have Lenovo and Toshiba. Thus we can see that they

are not as costly as Apple and Dell but their configuration is not that good as well and hence

it is in the negative. Finally in the fourth quadrant we have Acer which is very cheap and its

configuration is not good at all.

Dell

HP

LenovoToshiba

Apple

Acer

Vaio

-6

-4

-2

0

2

4

6

-15 -10 -5 0 5 10 15

Price,Service

Features,Configuration

Series1

Features

Price

Style

AudioVideoQuality

Configuration

Convenienceofservice

BrandImage

Page 34: Studying the Consumer Buying Behavior while buying a laptop

Perceptual mapping:

Features

PriceStyle

Audio Video Quality

Configuration

Conveinence of Service

Brand Image

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

-0.2 0 0.2 0.4 0.6 0.8

Factor 1-2

Series1

Features

Price

StyleAudio Video QualityConfiguration

Conveinence of Service

Brand Image-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

-0.2 0 0.2 0.4 0.6 0.8

Factor 2-3

Series1

Page 35: Studying the Consumer Buying Behavior while buying a laptop

There will be 21 such plots in all that can be plotted from the structure matrix table.

Thus from the structure matrix and the Eigen values and the Wilks lambda we can see that

the factors effecting the purchase of laptops are features and price and these are based on

the factor 1,factor 2,factor 3 and factor 4 as the Eigen values in this case are >1 and as wilks

lambda is <0.5.

Features

Price

Style

Audio Video Quality

Configuration

Convenience of Service

Brand Image

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

-0.6 -0.4 -0.2 0 0.2 0.4 0.6

Factor 3-4

Series1

Page 36: Studying the Consumer Buying Behavior while buying a laptop

Recommendations

1. The secondary research on the laptops makes us aware that people prefer to buy laptops from authorized retailers more than that from any other form of outlet.

2. From the Chi-square tests it is found that there is no significant relationship between

the laptop choice and the gender of the buyer.

3. Also from Chi-square test we found that there is a significant relation between the

degree and the kind of laptop selected.

4. From the ANOVA test we could recommend that

o educational qualification has a significant impact on the choice of laptop

brand.

o annual family has a significant impact on the choice of laptop brand.

o annual family income has a significant impact on the choice of laptop brand.

o the interaction of the variables educational qualification and family income

has a significant impact on the choice of laptop brand.

o the interaction of the variables family income and work experience has a

significant impact on the choice of laptop brand.

o the interaction of the variables educational qualification, family income and

work experience does not have a significant impact on the choice of laptop

brand.

5. The major factors form factor analysis are as follows:

Factor 1 Convenience features

Factor 2 Heavy usage features

Factor 3 Style features

Factor 4 Gaming features

Factor 5 Easy movability features

Factor 6 Security features

Page 37: Studying the Consumer Buying Behavior while buying a laptop

6. The clusters obtained from the peoples lifestyle are as follows:

Cluster1 – Lazy Individuals:

Cluster2 – Adventurous:

Cluster3 – Flexible:

Cluster4 – Patriotic:

Cluster5 – GenY

Page 38: Studying the Consumer Buying Behavior while buying a laptop

Appendix A – Anova (Factorial Design)

***************************************************************************************************************** UNIANOVA Laptop BY EdnQual FmlyIncome WorkEx /METHOD = SSTYPE(3) /INTERCEPT = INCLUDE /CRITERIA = ALPHA(.05) /DESIGN = EdnQual FmlyIncome WorkEx EdnQual*FmlyIncome EdnQual*WorkEx FmlyIncome*WorkEx EdnQual*FmlyIncome*WorkEx .

Between-Subjects Factors

Value Label N

Edn Qual

1 BE/B.Tech 45

2 MBBS/BDS 4

3 B.Com 39

4 B.Sc 13

5 B.A 3

Fmly Income

1 < 2Lacs 6

2 2-4Lacs 41

3 4-7Lacs 32

4 >7Lacs 25

Work Ex 1 0-1 years 37

2 1-2years 24

3 2-4years 41

4 >4years 2

Tests of Between-Subjects Effects

Dependent Variable: Laptop

Source Type III Sum of Squares df Mean Square F Sig.

Corrected Model 149.709(a) 25 5.988 2.933 .000

Intercept 187.463 1 187.463 91.801 .000

EdnQual 21.989 4 5.497 2.692 .037

FmlyIncome 29.362 3 9.787 4.793 .004

WorkEx 12.055 3 4.018 1.968 .126

EdnQual * FmlyIncome 67.526 4 16.881 8.267 .000

EdnQual * WorkEx 7.020 3 2.340 1.146 .336

FmlyIncome * WorkEx 21.781 4 5.445 2.667 .038

EdnQual * FmlyIncome * WorkEx 2.064 2 1.032 .505 .605

Error 159.281 78 2.042

Total 1101.000 104

Corrected Total 308.990 103

a R Squared = .485 (Adjusted R Squared = .319)

Page 39: Studying the Consumer Buying Behavior while buying a laptop

Appendix B - Hierarchical Clustering Data

*************************************************************************

CLUSTER Qlty_Price BrandedPdts Attracts_Attn Risk_Loving Utility_Loving

Fmly_involved_prch Frgn_Pdts Email Laptop_Ent Comp_Imp Not_borrow

Enjoy_Present Fashion_Consc

/METHOD BAVERAGE

/MEASURE= SEUCLID

/PRINT SCHEDULE

/PLOT DENDROGRAM VICICLE.

**************************************************************************

Case Processing Summary (a,b)

Cases

Valid Missing Total

N Percent N Percent N Percent

104 100.0 0 .0 104 100.0

a Squared Euclidean Distance used b Average Linkage (Between Groups)

* * * * * * H I E R A R C H I C A L C L U S T E R A N A L Y S I S * * * * * *

Dendrogram using Average Linkage (Between Groups)

Rescaled Distance Cluster Combine

C A S E 0 5 10 15 20 25

Label Num +---------+---------+---------+---------+---------+

15

99

57

1

85

43

11

95

53

17

101

59

16

100

58

3

87

45

10

94

Page 40: Studying the Consumer Buying Behavior while buying a laptop

52

41

83

40

82

39

81

42

84

38

80

8

92

50

2

86

44

6

90

48

7

91

49

5

89

47

12

96

54

27

69

21

63

26

68

23

65

24

66

18

102

60

22

64

20

104

62

25

67

19

103

Page 41: Studying the Consumer Buying Behavior while buying a laptop

61

14

98

56

9

93

51

4

88

46

13

97

55

29

71

35

77

32

74

36

78

34

76

31

73

37

79

28

70

30

72

33

75

ICICLE PLOT

Page 42: Studying the Consumer Buying Behavior while buying a laptop

Appendix C – K-Means Cluster Analysis **************************************************************************************************************** QUICK CLUSTER Qlty_Price BrandedPdts Attracts_Attn Risk_Loving Utility_Loving

Fmly_involved_prch Frgn_Pdts Email Laptop_Ent Comp_Imp Not_borrow

Enjoy_Present Fashion_Consc

/MISSING=LISTWISE

/CRITERIA= CLUSTER(5) MXITER(10) CONVERGE(0)

/METHOD=KMEANS(NOUPDATE)

/PRINT ANOVA CLUSTER DISTAN.

*************************************************************************

Iteration History (a)

Iteration

Change in Cluster Centres

1 2 3 4 5

1 4.010 3.561 3.843 3.285 3.669

2 .191 .582 .402 .728 .958

3 .000 .231 .445 .173 .665

4 .000 .000 .000 .000 .000

a Convergence achieved due to no or small change in cluster centres. The maximum absolute coordinate change for any centre is .000. The current iteration is 4. The minimum distance between initial centres is 8.062.

Final Cluster Centres

Cluster

1 2 3 4 5

Qlty_Price 5.8333 2.3571 3.3333 3.8696 2.6316

Branded Pdts 3.2917 2.2143 3.5000 2.4348 1.8421

Attracts_Attn 4.5417 5.0000 4.4583 6.4348 3.4737

Risk_Loving 4.9167 3.1429 5.0833 6.5652 4.1053

Utility_Loving 3.6250 1.9286 3.9167 2.0000 2.6316

Fmly_involved_prch 6.0000 2.4286 2.9583 2.0435 3.0000

Frgn_Pdts 3.9167 3.7143 3.8750 5.2174 2.4211

Email 1.7083 1.7857 2.2917 1.4783 1.7895

Laptop_Ent 1.8750 4.1429 4.0417 4.3913 3.0000

Comp_Imp 1.6250 1.2857 1.9167 1.1304 1.5263

Not_borrow 1.5833 1.8571 4.6250 3.5652 3.5263

Enjoy_Present 4.8750 4.0714 4.1250 4.2174 1.3684

Fashion_Consc 3.0833 3.2857 3.5833 4.3913 3.5263

Distances between Final Cluster Centres

Cluster 1 2 3 4 5

1 6.189 5.554 6.601 6.628

2 6.189 4.398 4.781 4.181

3 5.554 4.398 4.126 4.386

4 6.601 4.781 4.126 6.074

5 6.628 4.181 4.386 6.074

Page 43: Studying the Consumer Buying Behavior while buying a laptop

ANOVA

Cluster Error

F Sig. Mean Square

df Mean

Square df

Qlty_Price 39.8877 4.0 1.1405 99.000 34.97351 0.0000

Branded Pdts 10.6241 4.0 1.1666 99.000 9.106851 0.0000

Attracts_Attn 24.962 4.0 0.791 99.000 31.55891 0.0000

Risk_Loving 29.9266 4.0 1.2406 99.000 24.12202 0.0000

Utility_Loving 17.6442 4.0 1.2405 99.000 14.22361 0.0000

Fmly_involved_prch 56.3733 4.0 0.9429 99.000 59.78948 0.0000

Frgn_Pdts 20.4941 4.0 0.6653 99.000 30.80647 0.0000

Email 2.0895 4.0 0.3351 99.000 6.236225 0.0002

Laptop_Ent 24.7195 4.0 0.8159 99.000 30.29654 0.0000

Comp_Imp 2.0751 4.0 0.3602 99.000 5.760856 0.0003

Not_borrow 35.2634 4.0 0.7026 99.000 50.18686 0.0000

Enjoy_Present 36.9103 4.0 0.9749 99.000 37.86155 0.0000

Fashion_Consc 5.5749 4.0 1.058 99.000 5.269425 0.0007

The F tests should be used only for descriptive purposes because the clusters have been chosen to maximize the differences among cases in different clusters. The observed significance levels are not corrected for this and thus cannot be interpreted as tests of the hypothesis that the cluster means are equal.

Number of Cases in each Cluster

Cluster 1 24.000

2 14.000

3 24.000

4 23.000

5 19.000

Valid 104.000

Missing .000

Page 44: Studying the Consumer Buying Behavior while buying a laptop

Appendix D - Attribute based Perceptual

Mapping

Eigenvalues

Function Eigenvalue % of Variance Cumulative % Canonical Correlation

1 25.839(a) 63.5 63.5 .981

2 11.567(a) 28.4 92.0 .959

3 1.946(a) 4.8 96.7 .813

4 1.283(a) 3.2 99.9 .750

5 .039(a) .1 100.0 .194

6 .002(a) .0 100.0 .049

a First 6 canonical discriminant functions were used in the analysis.

Wilks' Lambda

Test of Function(s) Wilks'

Lambda Chi-square df Sig.

1 through 6 .000 108.748 42 .000

2 through 6 .011 62.689 30 .000

3 through 6 .143 27.254 20 .128

4 through 6 .420 12.129 12 .435

5 through 6 .960 .571 6 .997

6 .998 .034 2 .983

Structure Matrix

Function

1 2 3 4 5 6

Features .624(*) .093 -.397 .568 -.175 .286

Price .038 .750(*) .494 -.225 -.093 -.323

Style .131 .175 .507 .738(*) .323 .204

AudioVideoQuality .030 .145 -.438 .197 .735(*) -.088

Configuration .110 .096 .319 -.146 -.458(*) .386

Convenienceofservice -.032 .521 -.142 -.049 -.349 .755(*)

BrandImage .275 -.140 .249 -.475 .473 .623(*)

Pooled within-groups correlations between discriminating variables and standardized canonical discriminant functions Variables ordered by absolute size of correlation within function. * Largest absolute correlation between each variable and any discriminant function

Page 45: Studying the Consumer Buying Behavior while buying a laptop

Functions at Group Centroids

Brands

Function

1 2 3 4 5 6

Dell 13.066 4.192 .007 -.245 .493 -.017

HP 4.742 1.882 -.139 .593 -.910 .032

Lenovo -.998 -2.382 2.394 -.420 -.131 -.111

Toshiba -.976 -2.953 1.013 .952 .388 .122

Apple -11.240 3.498 .064 -1.019 -.004 .077

Acer 3.715 -5.394 -1.918 -.782 -.047 .007

Vaio -8.308 1.157 -1.421 .921 .211 -.110

Unstandardized canonical discriminant functions evaluated at group means

Function 1

50-5-10

Func

tion

2

5.0

2.5

0.0

-2.5

-5.0

Vaio

Acer

Apple

Toshiba

Lenovo

HP

Dell

Canonical Discriminant Functions

Group Centroid

Vaio

Acer

Apple

Toshiba

Lenovo

HP

Dell

Brands

Page 46: Studying the Consumer Buying Behavior while buying a laptop

Classification Results(a)

a 97.14 % of original grouped cases correctly classified.

Brands

Predicted Group Membership Total

Dell HP Lenovo Toshiba Apple Acer Vaio Dell

Original Count Dell 17 0 0 0 0 0 0 17

HP 0 15 1 1 0 0 0 17

Lenovo 0 0 16 1 0 0 0 17

Toshiba 0 0 0 17 0 0 0 17

Apple 0 0 0 0 17 0 0 17

Acer 0 0 0 0 0 17 0 17

Vaio 0 0 0 0 0 0 17 17

% Dell 100.0 .0 .0 .0 .0 .0 .0 100.0

HP .0 88.24 5.88 5.88 .0 .0 .0 100.0

Lenovo .0 .0 93.75 6.25 .0 .0 .0 100.0

Toshiba .0 .0 .0 100.0 .0 .0 .0 100.0

Apple .0 .0 .0 .0 100.0 .0 .0 100.0

Acer .0 .0 .0 .0 .0 100.0 .0 100.0

Vaio .0 .0 .0 .0 .0 .0 100.0 100.0

Page 47: Studying the Consumer Buying Behavior while buying a laptop

References:

Market Research-Text and Cases- Rajendra Nargundkar.

Marketing Research-Measurement and Methods- Tull and Hawkins.

www.dell.co.in

www.hplaptopsindia.com

www.sonyviaolaptopsindia.com

https://www.toshiba-india.com

www.lenovo.com/in/en

www.acer.co.in

www.apple.com