Consumer Buying Behavior Towards Maruti Swift and Ford Figo.
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Research Project
on
Consumer Buying Behavior Towards
Maruti Swift and Ford Figo.
in
In Partial fulfillment of the Masters of Business Administration
Submitted To: Submitted By:
Dr. Gurdeep Singh Gur Gaurav Singh
Munish kumar
Abhinav Gupta
th
Dated: 28 April, 2014
UIET,Panjab University, ChandigarhCERTIFICATE OF APPROVAL
This is to certify that Mr.Gur Gaurav Singh,Mr. Munish Kumar, Mr. Abhinav
th
Gupta students of BE-MBA (10 Semester) UIET,Panjab University have done a
research project titled “Consumer Buying Behavior Towards Maruti Swift and
Ford Figo”, under my supervision in partial fulfilment of the Masters in Business
Administration.
Their work is original and up to my satisfaction. This project has not been
submitted anywhere else for the award of any degree or diploma.
Mr. Rahul KanwarAcknowledgement We avail this opportunity to acknowledge the academic interaction, exchange of views and participation of all those who directly or indirectly contributed towards the completion of this project. We wish to express my heartfelt thanks to my project guide Mr Rahul Kanwar for his continuous guidance, helpful criticism and supervision through course of this project. We thank and sincerely acknowledge the support of all the people who have given contribution to this research.
INTRODUCTION TO THE TOPIC Last decade witnessed a fast growth in Indian automobile. According to the Indian automobile Manufacturers (SIAM, 2008), the Indian automobile industry has maintained a steady growth of 20% till 2005. The automobile industry contributes to about 5% of the GDP of Indian economy and it is targeted to grown fivefold by the year 2016. The 1200 cc passenger car segment There are many car companies which provide the 1200 cc car variants in to the market. Maruti Suzuki dominates in this segment; Tata Motors is at the second place, while Hyundai and many other car companies provide their 1200 cc car variants in the market, the details of which are as given below: 1. Maruti Suzuki: Eeco, Ritz, Swift, Swift Dzire. 2. Tata Motors: Indica, Indica Vista, Indigo. 3. Hyundai: i10, i20. 4. Chevrolet: Beat, U-VA, Aveo. 5. Fiat: Grande Punto. 6. Honda: Jazz. 7. Nissan: Micra. 8. Skoda: Fabia. 9. Volkswagen: Polo. 10. Ford: Figo.
RESEARCH OBJECTIVE
To understand consumer purchasing behaviour and perspective towards Global
brands vs. local brands : The Indian car industry.
The objective of the research is to find whether the customers have faith in Indian
manufacturers or they prefer multinationals while purchasing a car. Here, are trying
to compare one car of Indian origin i.e. Maruti Suzuki Swift to that of Ford Ford(
German Manufacturer).Both of the cars are 1200 cc/compact cars having the same
price range and both cars belong to the Hatch back class of cars.
We are preferring Maruti Suzuki to other Indian brands like Tata motors and
Mahindra because of the price difference of the cars like Tata vista and Mahindra
Verito than that of Ford Figo and all cars don‟t belongs to the same category.
Vista and Verito belongs to the Sedan class while figo belongs to the Hatch back
class.
Henceforth, we narrowed down our research to Maruti Swift and Ford Figo.
The sub objectives of our research will be illustrated as:
1. To find out the major variables of consumer‟s purchase decision.
2. To determine the contribution of these variables in the
consumer‟s purchase decision.
3. To carry out the factor analysis to understand the perception of consumer.2.2 Research Design: An exploratory study was conducted in the tri-city (Chandigarh, Mohali and Panchkula) in which detailed face to face structured interviews were conducted with the people which helped us to uncover individual‟s covert feelings and emotions towards purchasing behavior and perspective of global brands vs. local brands. Sampling Design: The systematic sampling technique used was to identify 53 respondents as our sample. Understanding of the problem and linkages of variables When the consumer is taking a purchasing decision whether to go for Indian manufacturers or to go for German manufacturer various factors influences his/her mind like reliability, fuel economy, price, safety features, warranty and service facility. But, any addition in these features many create a significant utility. However, looking to the complexity to deal with large number of variables, their reduction in the form of few factors shall follow the analysis for data summation. The variables considered for conducting the proposed study are Styling and appearance, Price and discounting policy, Passenger comfort, Driving pleasure and ride quality, Reliability, Manufacturer‟s Reputation, Engine Performance and its stability at higher speed, Fuel Efficiency, Boot space, Vehicle durability, Presence of safety features, Warranty period, Resale value, Additional features, Previous experience, Opinion of opinion leaders, Opinion of family members, Availability of spare parts and economy of maintenance of car, Impact of advertising and Environmental friendliness
Development of Hypotheses
1. Economic Issues (like price and discounting policy, fuel efficiency,
warranty, availability of spare parts etc ).
2. Comfort issues (like passenger comfort, driving pleasure and ride quality,
reliability, engine performance and stability at higher speed, boot space).
3. Safety and additional features issues (like presence of safety features,
additional features, styling and appearance).
4. Advertising and manufacturer‟s reputation.
5. Service and maintenance
6. Self-assessment issues (like previous experience, opinion of family
member, opinion of opinion leader).
Need and importance of the study:
The Indian market, one of the most promising in the world, is fast evolving. So is
the Indian consumer, across all socioeconomic strata, regions and town classes.
Rising incomes, multiple income households, exposure to international lifestyles
and media, easier financial credit and an upbeat economy are enhancing
aspirations and consumption.
The study will help in determining the factors which have a major influence on
consumer buying behaviour for domestic cars over multinational cars. This study
will help companies to project their car products according to the factor which
have a major influence on consumer buying behaviour.70
60
50
40
frequency
30 percentage
20
10
0
Indian Multinational
Figure 3 Frequency distribution of the respondents having Indian and multinational cars in the sample
Table 1 Frequency distribution Table of the respondents having Indian and multinational cars in
the sample
Frequency percentage Cumulative
percentage
Indian 34 64.1509434 64.1509434
Multinational 19 35.8490566 100
Total 53 100Satisfaction level of the people who own Indian and multinational cars in
the sample
100
90
80
70
60
50 frequency
percentage
40
30
20
10
0
Indian multinational
Figure 4 Frequency distribution of the satisfaction level of people having Indian and multinational
cars in the sample
Table 2 Frequency distribution Table of the satisfaction level of people having Indian and multinational
cars in the sample
Frequency percentage Cumulative
percentage
Indian 49 92.452 92.45
Multinational 4 7.5471 100
Total 53 100People willing to switch their cars from Indian to multinational or vice versa.
Some people have a versatile personality always prefer or welcome
change whole heartedly.
70
60
50
40
Frequency
30 percentage
20
10
0 willing to switch from Indian to global willing to switch from global to Indian
Figure 5 Frequency distribution of the satisfaction level of people having Indian and
multinational cars in the sample
Table 3 Frequency distribution Table of the satisfaction level of people having Indian and
multinational cars in the sample
Frequency percentage Cumulative
percentage
Willing to switch from 18 33.96 33.96
Indian to global
Willing to switch from 35 66.03 100
global to Indian
Total 53 100MOST IMPORTANT FACTORS DEFINING THE VARIABLES Once we understand the relative importance of the variables, we need to identify what are the main factors/ traits that define them. So, a focus group interview was conducted where we asked 53 respondents to discuss the traits they think define the desired economic issues, safety , self- assessment, advertising and manufacturers reputation, comfort and service and maintenance . We collected the main factors discussed in this discussion forum along with those taken from theories to make a list of factors to be considered in our tool (questionnaire). Following 4 factors were considered for Economic issues: 1. Discounting policy 2. Warranty 3. Availability of spare parts 4. Fuel efficiency Following 6 factors were considered for Comfort issues: 1. Passenger comfort 2. Driving pleasure and ride quality 3. Reliability, 4. Engine performance 5. Stability at higher speed 6. Leg space Following 4 factors were considered for Safety issues 1. Presence of safety features 2. Additional features 3. Styling 4. Appearance
Following 2 factors were considered for Service and maintenance
1. Sales person
2. availability of spare parts
Advertising and manufacturer‟s reputation was also considered as a factor
Following 2 factors were considered for Self-assessment issues
1. Previous experience
2. Opinion of family member
3. Opinion of Sales person.
Since, all the factors won‟t be equally important in the definition of the desired
variables, so we applied factor analysis tool to identify the most important of
these factors.
5.1 Identifying key factors/ traits defining desired Economic issues
Table 10 ; KMO and Bartlett’s test for the model
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .845
Bartlett's Test of Sphericity Approx. Chi-Square 382.344
Df 190
Sig. .001
The KMO coefficient value of 0.845 (greater than 0.7), signifies that our model explains
84.5 % of the variance.
Also since the p value for the model is 0.001, this means that the model is significant at
99% level of confidence interval.Using factor analysis, we extracted the following 2 set of components:
1. Discounting policy.
2. Fuel efficiency.
Please find the factor loadings from Table A.1 and correlation among the 2 components
from Table A.2 of Appendix A.
The components are extracted on the basis of the value of individual factor loadings of
the 4 variables considered on the 2 components extracted.
Table 11 : Total Variance Explained by the extracted components
Extraction Sums of Squared Rotation Sums of Squared
Initial Eigenvalues Loadings Loadings
% of Cumulative % of Cumulative % of Cumulative
Component Total Variance % Total Variance % Total Variance %
1 2.671 36.709 36.709 2.671 36.709 36.709 1.839 28.709 28.709
2 1.425 24.254 60.963 1.425 24.254 60.963 1.737 27.254 55.963
3 1.230 12.302 73.265 1.230 12.302 73.265 1.643 16.302 72.265
4 1.038 10.383 83.648 1.038 10.383 83.648 1.146 11.383 83.648
Extraction Method: Principal Component Analysis.
From table , we conclude that the two components extracted explain 83.648% of
the variance in the data which is significantly high and acceptable.5.2 Identifying key factors/ traits defining desired comfort:
Table 12 : : KMO and Bartlett’s test for the model
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .780
Bartlett's Test of Sphericity Approx. Chi-Square 336.182
Df 105
Sig. .001
The KMO coefficient value of 0.780 (greater than 0.7), signifies that our model explains
78.0 % of the variance.
Also since the p value for the model is 0.001, this means that the model is significant at
99% level of confidence interval.
Using factor analysis, we extracted the following 4 set of components:
1. Driving pleasure and ride quality
2. Reliability
3. Engine performance
4. Stability at higher speed
Please find the factor loadings from Table A.3 and correlation among the 4 components
from Table A.4 of Appendix A.
The components are extracted on the basis of the value of individual factor loadings of all
the 6 variables considered on the 4 components extracted.Table 13 : Total Variance Explained by the extracted components
Extraction Sums of Squared Rotation Sums of Squared
Initial Eigenvalues Loadings Loadings
% of Cumulative % of Cumulative % of Cumulative
Component Total Variance % Total Variance % Total Variance %
1 4.047 26.98 26.98 4.047 26.98 26.98 2.741 24.273 24.273
2 2.351 20.672 47.652 2.351 20.672 47.652 2.599 16.329 40.602
3 1.524 12.158 59.81 1.524 12.158 59.81 2.052 13.677 54.279
4. 1.068 7.122 77.495 1.068 7.122 77.495 1.315 10.768 77.495
5 1.134 10.563 70.373 1.134 10.563 70.373 1.417 12.448 66.727
6.
.843 6.427 90.075
Extraction Method: Principal Component Analysis.
From table , we conclude that the five components extracted explain 77.495% of the
variance in the data which is significantly high and acceptable.
5.3 Identifying key factors/ traits defining desired safety
Table 14 KMO and Bartlett’s test for the model
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .850
Bartlett's Test of Sphericity Approx. Chi-Square 135.357
Df 28
Sig. .001
The KMO coefficient value of 0.850 (greater than 0.7), signifies that our model explains
85.0 % of the variance.Also since the p value for the model is 0.001, this means that the model is significant at
99% level of confidence interval.
Using factor analysis, we extracted the following 2 set of components:
1. Presence of safety features
2. Appearance
Please find the factor loadings from Table A.5 and correlation among the 5 components
from Table A.6 of Appendix A.
The components are extracted on the basis of the value of individual factor loadings of
the 4 variables considered on the 2 components extracted
Table 15 : Total Variance Explained by the extracted components
Total Variance Explained
Extraction Sums of Rotation Sums of Squared
Initial Eigenvalues Squared Loadings Loadings
% of Cumulative % of Cumulative % of Cumulative
Component Total Variance % Total Variance % Total Variance %
1 2.246 28.079 28.079 2.246 28.079 28.079 1.748 21.844 21.844
2. .778 9.720 86.564 .778 9.720 86.564 1.063 13.282 86.564
3 .533 6.662 93.226
4 .336 4.202 97.428
5 .206 2.572 100.000
Extraction Method: Principal Component Analysis.
From table 15, we conclude that the 2 components extracted explain 86.564% of the
variance in the data which is significantly high and acceptable.5.4 Identifying key factors/ traits defining Service and maintenance:
Table 16 : KMO and Bartlett’s test for the model
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .845
Bartlett's Test of Sphericity Approx. Chi-Square 382.344
Df 190
Sig. .001
The KMO coefficient value of 0.845 (greater than 0.7), signifies that our model explains
84.5 % of the variance.
Also since the p value for the model is 0.001, this means that the model is significant at
99% level of confidence interval.
Using factor analysis, we extracted the following 1 component:
1. Availability of spare parts
Please find the factor loadings from Table A.1 and correlation among the 2 components
from Table A.2 of Appendix A.
The components are extracted on the basis of the value of individual factor loadings of
the 3 variables considered on the 1 component extracted.Table 17 : Total Variance Explained by the extracted components
Extraction Sums of Rotation Sums of Squared
Initial Eigenvalues Squared Loadings Loadings
% of Cumulative % of Cumulative % of Cumulative
Component Total Variance % Total Variance % Total Variance %
1 1.038 10.383 83.648 1.038 10.383 83.648 1.146 11.383 83.648
2 .843 6.427 90.075
3 .791 4.91 94.985
Extraction Method: Principal Component Analysis.
From table 7, we conclude that the four components extracted explain 83.648% of
the variance in the data which is significantly high and acceptable.
Identifying key factors/ traits defining desired self assessment
Table 8: KMO and Bartlett‟s test for the model
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .780
Bartlett's Test of Sphericity Approx. Chi-Square 336.182
Df 105
Sig. .001
The KMO coefficient value of 0.780 (greater than 0.7), signifies that our model explains
78.0 % of the variance.
Also since the p value for the model is 0.001, this means that the model is significant at
99% level of confidence interval.Using factor analysis, we extracted the following 5 set of components:
1. Previous experience
2. Opinion of family member
Please find the factor loadings from Table A.3 and correlation among the 5 components
from Table A.4 of Appendix A.
The components are extracted on the basis of the value of individual factor loadings of all
the 3 variables considered on the 2 components extracted.
Total Variance Explained by the extracted components
Extraction Sums of Rotation Sums of Squared
Initial Eigenvalues Squared Loadings Loadings
% of Cumulative % of Cumulative % of Cumulative
Component Total Variance % Total Variance % Total Variance %
1 1.134 10.563 70.373 1.134 10.563 70.373 1.417 12.448 66.727
2 1.068 7.122 77.495 1.068 7.122 77.495 1.315 10.768 77.495
3 .196 0.254 100
Extraction Method: Principal Component Analysis.
From table , we conclude that the 2 components extracted explain 77.495% of the
variance in the data which is significantly high and acceptableConsumer Buying Behaviour
Which car would you like to own/buy? *
o Maruti Swift
o Ford Figo
o Toyota Etios Liva
o Hyundai i20
o Others
What's your purpose of purchasing a car? *
o Business
o family
o Taxi/cab
o Others
Which variant would you prefer? *
o Diesel
o Petrol
Do you have faith in Indian manufacturers or do you prefer
multinationals? *
o Indian manufacturers
o Multinationals
Rate the factors you pay consideration to, while purchasing a car? *
Strong Strongly
Disagree Neutral Agree
Disagree Agree
Word of
mouth
Advertisement
Status Symbol
Brand Image
Reliability
Availability of
Test drive
Exterior and
LooksSafety and Breaking *
Strongly Strongly
Disagree Neutral Agree
Disagree Agree
Power dock
Locks
Anti-theft
alarm
Seat belt
warning
Defog
Availability
Comfort *
Strongly Strongly
Disagree Neutral Agree
Disagree Agree
Rear
Power
Window
Automatic
climate
control
Bottle
Holder
Sunroof
Foldable
seats
Mileage you are comfortable with(on Highway) *
o 16-18
o 18-20
o 20-22Finance Scheme *
Strongly Strongly
Disagree Neutral Agree
Disagree Agree
Lesser
Cash
Down
Payment
Lesser
EMI
Provision
of full
payment
in cash
Services *
Strongly Strongly
Disagree Neutral Agree
Disagree Agree
Customer
Relationship
Spare parts
availability
Service
Stations
Lesser time
to service
Cost of
Service
Salesperson
Maintenance Required *
o 2-3 times a year
o 3-5 times a year
o 5-7 times a year
Are you satisfied with your car? *
o Yes
o NoBased on above, would you like to switch? *
o Yes
o No
Which one you would prefer if provided for free? *
o Maruti Swift
o Ford Figo
Personal Details
This page contains information about personal details. The information is
only for the academic purpose and will be kept secret
Name
Age *
50
Annual Income *
10,00,000
Not Working
Marital Status *
Single
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