978-1111826925 Case Values and the Automobile Market

Case Three: Values and the Automobile Market 203

Case 3

Values and the Automobile Market

Database: Students are instructed to download the data sets for this case from the book’s

website or to request them from their instructor.

Objectives: The purpose of this case is to allow students to evaluate an entire research

project. Further, the database allows students to analyze the survey data using statistical or

spreadsheet software.

Summary: During the 1990s, the luxury car segment became one of the most competitive in

the automobile market. Many American consumers who purchased luxury cars preferred

imports from Germany and Japan.

Industry analysts believed it would be important to assess the viability of using personal values

as a basis for explaining ownership of American, German, and Japanese luxury cars. Further

they believed they should also assess whether knowledge of owners’ personal values provided

any additional information that would explain ownership.

A mail survey of 498 consumers containing names of people who had purchased a luxury

American, German or Japanese car received a 32 percent response rate. Several questions

concerned issues that consumers consider when buying luxury automobiles. Respondents also

rated how important twelve car attributes and eight values were to them.

Questions:

1. Is the sampling method adequate? Is the attitude measuring scale sound? Explain.

The sampling frame was from a respected commercial organization. A thirty-two percent

2. Using the computerized database with a statistical software package, calculate the means

of the three automotive groups for the values variables. Do any of the values variables

show significant differences between American, Japanese, and European car owners?

The computer software selected will determine the format of the output. Using SPSS (Analyze

duplicated, or posted to a publicly accessible website, in whole or in part.

204 Part Seven: Comprehensive Cases

Descriptives

N Mean Std. Deviation Std. Error

95% Confidence Interval for Mean

Minimum MaximumLower Bound Upper Bound

fun 1 54 2.9444 1.20403 .16385 2.6158 3.2731 1.00 6.00

belong 1 54 2.8889 1.47516 .20074 2.4862 3.2915 1.00 6.00

respect 1 54 2.3704 1.13763 .15481 2.0599 2.6809 1.00 6.00

selfful 1 54 2.0926 1.06874 .14544 1.8009 2.3843 1.00 7.00

accomp 1 54 1.8889 .92485 .12586 1.6365 2.1413 1.00 6.00

warm 1 54 2.1481 1.20388 .16383 1.8196 2.4767 1.00 7.00

security 1 55 1.9818 .95240 .12842 1.7243 2.2393 1.00 5.00

selfres 1 54 1.6111 .87775 .11945 1.3715 1.8507 1.00 5.00

duplicated, or posted to a publicly accessible website, in whole or in part.

Case Three: Values and the Automobile Market 205

One-way ANOVA reveals only one value—self-fulfillment—with significant differences

among the groups:

ANOVA

Sum of Squares df Mean Square F Sig.

fun Between Groups 6.241 2 3.120 2.592 .078

belong Between Groups 3.570 2 1.785 .795 .454

respect Between Groups .840 2 .420 .298 .743

selfful Between Groups 8.990 2 4.495 3.841 .024

accomp Between Groups 5.046 2 2.523 2.764 .066

warm Between Groups 10.787 2 5.394 2.743 .068

security Between Groups 6.088 2 3.044 1.876 .157

selfres Between Groups 2.602 2 1.301 1.212 .301

While not covered in this textbook, to fully answer the regarding difference among American,

Japanese, and European car owners on the value of self-fulfillment, pos hoc comparisons can

be performed:

duplicated, or posted to a publicly accessible website, in whole or in part.

206 Part Seven: Comprehensive Cases

Multiple Comparisons

selfful

LSD

(I) car (J) car Mean Difference (I-J) Std. Error Sig.

95% Confidence Interval

Lower Bound Upper Bound

1 2 .14974 .23476 .525 -.3144 .6139

3 -.44444*.20820 .035 -.8561 -.0328

*. The mean difference is significant at the 0.05 level.

There is significant difference on this value between owners of Japanese luxury cars (3) and

both American luxury cars owners (1) and European luxury car owners (2). The mean score on

3. Are there any significant differences on importance of attributes?

There are several significant differences at the p < 0.05 level (means are not given here):

duplicated, or posted to a publicly accessible website, in whole or in part.

Case Three: Values and the Automobile Market 207

ANOVA

Sum of Squares df Mean Square F Sig.

comfort Between Groups 1.937 2 .969 3.852 .023

safety Between Groups .453 2 .226 .625 .536

power Between Groups 1.601 2 .800 .631 .533

speed Between Groups 8.021 2 4.011 2.418 .093

styling Between Groups 4.005 2 2.003 3.256 .041

durabil Between Groups 2.154 2 1.077 2.472 .088

lowmc Between Groups 14.312 2 7.156 6.088 .003

rely Between Groups .770 2 .385 1.637 .198

warranty Between Groups .670 2 .335 .429 .652

nonpoll Between Groups 3.161 2 1.580 .698 .499

gasmile Between Groups 2.302 2 1.151 .627 .536

duplicated, or posted to a publicly accessible website, in whole or in part.

208 Part Seven: Comprehensive Cases

Further analysis of the mean differences on the “speed of repairs” attribute reveals that

American car owners rated this attribute significantly more important than European and

Japanese car owners:

Descriptives

repairs

N Mean Std. Deviation Std. Error

95% Confidence Interval for Mean

Minimum MaximumLower Bound Upper Bound

1 57 5.8421 1.62337 .21502 5.4114 6.2728 1.00 7.00

ANOVA

repairs

Sum of Squares df Mean Square F Sig.

Between Groups 123.694 2 61.847 20.410 .000

duplicated, or posted to a publicly accessible website, in whole or in part.

Case Three: Values and the Automobile Market 209

Multiple Comparisons

repairs

LSD

(I) car (J) car Mean Difference (I-J) Std. Error Sig.

95% Confidence Interval

Lower Bound Upper Bound

1 2 1.84211*.36751 .000 1.1159 2.5683

3 1.87659*.32467 .000 1.2350 2.5181

*. The mean difference is significant at the 0.05 level.

4. Write a short statement to interpret the results of this research.

Students’ responses will vary. However, there were several instances of significant differences

Advanced Questions:

5. Are any of the value scale items highly correlated?

Yes. For example, Issue 1 (Having a luxury car is a major part of my fun and excitement.) is

6. Should multivariate analysis be used to understand the data?

In a situation where a researcher wishes to compare groups, multiple discriminate analysis can

be used. A factor analysis of the issues considered when buying would also be of interest.

Although the data of this case have been modified, results of multiple discriminant analysis and

duplicated, or posted to a publicly accessible website, in whole or in part.