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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.

    Used to measure sampling adequacy.

    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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