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Submitted To :

Prof. Sarika Tandon

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INTRODUCTIONProblem Statement:

New Car Buyer Behaviour - Quantifying Key Stages & Activities in theConsumer Buying Process.

Research Objectives: Managing demand.

Understanding influences on timing

of purchase decisions.

Validate current positions on consumer

behaviour.

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Questionnaire Design

To design the buying behaviour of consumer.

The respondents were asked to give the preferenceabout the brand they want.

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Sample Characteristics

Sample consisted of the customers of five CAR companies in Indiaviz. VW,Maruti, Hyundai, Tata, Mahindra

These cars were selected, as they are representative of the majorsegments in the car industry from full fare to low priced cars.

Targeted sample size was 40 per car, and achieved sizes were as follows.

Table 1

Car (Brand) wise Composition of Sample

NO Company Obtained numberof samples

1 VW 39

2 Maruti 40

3 Hyundai 35

4 Tata 38

5 Mahindra 36

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DATA ANALYSIS & RESULTS

The statistical analyses used were ANOVA, Regressionanalysis, Factor analysis.

Analysis of research data used the level of significance, a =

0.05.

The objective of this study was to examine customerperception of service quality.

ANOVA was performed and the result showed a significant

difference among the five car companies in India viz. VW,

Maruti, Hyundai, Tata, Mahindra

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Testing for Significance: FTest

The Ftest is used to determine whether a significantrelationship exists between the dependent variable and theset of all the independent variables.

The Ftest is referred to as the test for overall significance.

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Testing for Significance: FTest

Hypotheses

H0:1 =2 = . . . =p = 0

Ha: One or more of the parameters

is not equal to zero.

Rejection Rule

Reject H0 ifF > F

where F is based on an F distribution withp d.f. in

the numerator and n -p - 1 d.f. in the denominator.

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As adjusted square is 0.004, it implies that 0.4% of variance ofthe dependent variable is explained by independent variable.

As R= 0.182, it explains a very weak correlation.

H0:1 =2 = . . . =p = 0

Ha: One or more of the parameters

is not equal to zero.

p = 0.285p= .05

Since p > p we accept the null hypothesis and our model isnot good.

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Testing for Significance: tTest

Hypotheses

H0:i = 0

Ha:i = 0

Rejection RuleReject H0 ift < t or t > t

where tis based on a t distribution with

n -p - 1 degrees of freedom.

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H0:i = 0Ha:i = 0

p = 0.000

p < .05

Since p < 0.05, we reject the null hypothesis.

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K.M.O Test

If two variables share a common factor with othervariables, their partial correlation (aij) will be small,indicating the unique variance they share.

This index is used to measure the appropriateness of thetest .

High values (.5 1) means factor analysis is adequate.

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Interpretation of the KMO as characterized by

Kaiser, Meyer, and Olkin

KMO Value Degree of Common Variance

0.90 to 1.00 Marvelous

0.80 to 0.89 Meritorious

0.70 to 0.79 Middling

0.60 to 0.69 Mediocre

0.50 to 0.59 Miserable

0.00 to 0.49 Don't Factor

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Kaiser-Meyer-Olkin Measure of Sampling adequacy 0.524

Barletts Test of Sphericity Approx. Chi Square 79.957

df 28

Significance 0.0000

KMO and Bartletts Test

Since the value of KMO is 0.524, therefore it implies that

the degree of variance is very bad, in fact the variables do

not factor with the other variables.

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Limitations

The findings of this study are limited to the behaviour of the consumer

towards car in India.

This study has not considered industry measures to measure service quality.

We have measured only the customer perception of service quality.

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Conclusion

Timing of orders & delivery bias towards weekends

Fridays for collectionSaturdays for order

supports dealer research

Differences between men & women

females less willing to wait

reference growth in female motorists & change in

relative influence & role

Information Sources

Dealer still critical

Friend, Brochure, Magazine4 different sources of information

growth of internet now nearly 20%

Research suggests that the consumer demand for a Car would bestrong

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Welcome message from author
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