advanced analysis and presentation approaches

1 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, 2003.

Learning Objectives:

1. Understand how to use cluster analysis with

discriminant analysis.

2. Understand how to use factor analysis with

regression.

3. Explain the use of summated scores instead of

factor scores.

4. Clarify the visual impact of Importance-

Performance Analysis.

Advanced Analysis and Advanced Analysis and Presentation Presentation ApproachesApproaches

Chapter 14


Relationship Variables from Customer Relationship Variables from Customer SurveySurvey

17. How satisfied are you

with Samouel’s restaurant? Not Satisfied Very

At All Satisfied

1 2 3 4 5 6 7

18. How likely are you to return to

Samouel’s restaurant in

the future? Definitely Will Definitely Will

Not Return Return

1 2 3 4 5 6 7

19. How likely are you to recommend

Samouel’s restaurant to a friend? Definitely Will Not Definitely Will

Recommend Recommend

1 2 3 4 5 6 7

20. How often do you patronize

Samouel’s restaurant? 1 = Occasionally (Less than once a month)

2 = Frequently (1 – 3 times a month)

3 = Very Frequently (4 or more times a month)

21. How long have you been a customer of Samouel’s restaurant?

1 = Less than One Year

2 = One year to three years

3 = More than three years


Cluster Analysis Research Cluster Analysis Research QuestionsQuestions

Research Question One:

“Can clusters be identified?”

Research Question Two:

“Are the clusters valid?”

Research Question Three:

“Do the perceptions variables predict the clusters?”


Exhibit 14-2 Error Coefficients Exhibit 14-2 Error Coefficients and Error Reduction for and Error Reduction for

Satisfaction Variables’ Cluster Satisfaction Variables’ Cluster SolutionsSolutions

Error Coefficients Error Reduction

Four Clusters = 140.865 3 – 4 Clusters = 42.013

Three Clusters = 182.878 2 – 3 Clusters = 99.972

Two Clusters = 282.850 1 – 2 Clusters =

551.405

One Cluster = 834.255


Exhibit 14-3 Means Exhibit 14-3 Means for Two-Cluster for Two-Cluster

SolutionSolutionVariables Groups N Mean

X17 – Satisfaction

1 80 4.14

2 120 6.19

Total 200 5.37

X18 – Return in Future

1 80 3.83

2 120 5.72

Total 200 4.96

X19 – Recommend to Friend

1 80 3.61

2 120 5.53

Total 200 4.76


Exhibit 14-3 Means Plots Exhibit 14-3 Means Plots for Two-Cluster Solutionfor Two-Cluster Solution

Ward Method

21

Mea

n of

X17

-- S

atis

fact

ion

6.5

6.0

5.5

5.0

4.5

4.0

Ward Method

21

Mea

n of

X18

-- R

etur

n in

Fut

ure

6.0

5.5

5.0

4.5

4.0

3.5

Ward Method

21M

ean

of X

19 --

Rec

omm

end

to F

riend

6.0

5.5

5.0

4.5

4.0

3.5


Exhibit 14-4 Means Exhibit 14-4 Means for Three-Cluster for Three-Cluster

SolutionSolutionVariables Groups N Mean

X17 – Satisfaction

1 80 4.14

2 75 6.53

3 45 5.62

Total 200 5.37

X18 – Return in Future

1 80 3.83

2 75 6.20

3 45 4.91

Total 200 4.96

X19 – Recommend to Friend

1 80 3.61

2 75 5.92

3 45 4.89

Total 200 4.76


Exhibit 14-4 Means Exhibit 14-4 Means Plots for Three-Plots for Three-Cluster SolutionCluster Solution

Ward Method

321

Mea

n of

X17

--

Sat

isfa

ctio

n

7.0

6.5

6.0

5.5

5.0

4.5

4.0

Ward Method

321

Me

an

of

X1

8 -

- R

etu

rn in

Fu

ture

6.5

6.0

5.5

5.0

4.5

4.0

3.5

Ward Method

321

Mea

n of

X19

--

Rec

omm

end

to F

riend

6.5

6.0

5.5

5.0

4.5

4.0

3.5

3.0


Exhibit 14-5 ANOVA Results for Exhibit 14-5 ANOVA Results for Two-Cluster Solution of Two-Cluster Solution of Satisfaction VariablesSatisfaction Variables

Variables F Sig.

X17 – Satisfaction Between Groups 426.270 .000

X18 – Return in Future Between Groups 340.375 .000

X19 – Recommend to Friend Between Groups 394.646 .000

ANOVA


Exhibit 14-6 Validation Exhibit 14-6 Validation Statistics for Two-Group Statistics for Two-Group

Satisfaction ClustersSatisfaction Clusters

Variables Groups N Mean

X20 – Frequency of Patronage

1 80 1.53

2 120 2.63

Total 200 2.19

X21 – How Long a Customer

1 80 1.40

2 120 2.63

Total 200 2.14

Descriptives

Variables F Sig.

X20 – Frequency of Patronage Between Groups 139.289 .000

X21 – How Long a Customer Between Groups 178.330 .000

ANOVA


Exhibit 14-7 Prediction of Exhibit 14-7 Prediction of Customer Satisfaction Customer Satisfaction

ClustersClusters

Test of Function(s) Wilks’ Lambda Chi- Square Sig.

1 .671 77.795 .000

Wilks’ Lambda

*79.0% of original grouped cases correctly classified.

Predicted Group Membership Total

Dependent Variables 1 2

Original Count 1 53 27 80

2 15 105 120

% 1 66.3 33.8 100.0

2 12.5 87.5 100.0

Classification Results*


Exhibit 14-8 Structure Exhibit 14-8 Structure Matrix for Matrix for

Two-Cluster SolutionTwo-Cluster SolutionVariables Function 1

X6 – Friendly Employees .777

X12 – Competent Employees .752

X1 – Excellent Food Quality .510

X4 – Excellent Food Taste .387

X11 – Courteous Employees .384

X9 – Wide Variety of Menu Items .189


Exhibit 14-9 Group Means for Exhibit 14-9 Group Means for Food and Employee Independent Food and Employee Independent

VariablesVariables

Variables Mean Mean

Group 1 Group 2

X1 – Excellent Food Quality 5.01 5.87

X4 – Excellent Food Taste 5.06 5.70

X6 – Friendly Employees 2.93 4.14

X9 – Wide Variety of Menu Items 5.31 5.63

X11 – Courteous Employees 2.10 2.60

X12 – Competent Employees 1.64 2.55

Group Statistics


Exhibit 14-10 Rotated Factor Solution for 12 Exhibit 14-10 Rotated Factor Solution for 12 Perceptions Variables on the Customer SurveyPerceptions Variables on the Customer Survey

Variables Components (Factors)

1 2 3 4

X4 – Excellent Food Taste .912

X9 – Wide Variety of Menu Items .901

X4 – Excellent Food Quality .883

X6 – Friendly Employees .892

X11 – Courteous Employees .850

X12 – Competent Employees .800

X8 – Fun Place to Go .869

X2 – Attractive Interior .854

X7 – Appears Clean and Neat .751

X3 – Generous Portions .896

X5 – Good Value for Money .775

X10 – Reasonable Prices .754


Exhibit 14-10 Rotated Factor Solution Exhibit 14-10 Rotated Factor Solution for 12 Perceptions Variables on the for 12 Perceptions Variables on the

Customer Survey ContinuedCustomer Survey Continued

ComponentRotation Sums of Squared Loadings

% of Variance Cumulative %

Total

1 2.543 21.188 21.188

2 2.251 18.758 39.946

3 2.100 17.498 57.444

4 2.060 17.170 74.614


. . . are composite

scores calculated for

each respondent on

each of the derived

factors..

Factor ScoresFactor Scores


Exhibit 14-11 Factor Exhibit 14-11 Factor Scores for Five Scores for Five

Respondents in Customer Respondents in Customer SurveySurvey

Factors

1 2 3 4

Respondents

#1 -.89212 1.24493 .84853 -.38169

#2 -2.33246 -1.01861 .21274 .65610

#3 -.55517 -1.14659 -.90178 -.91886

#4 -.22994 -1.91237 .23862 -.20539

#5 -.03014 .19599 1.30175 -.53036


Exhibit 14-12 Descriptive Exhibit 14-12 Descriptive Statistics for Multiple Regression Statistics for Multiple Regression

Using Factor ScoresUsing Factor Scores

X25 – Competitor Variables Mean

Samouel’s

X17 – Satisfaction 4.78

Food Factor – .153

Employees Factor – .626

Atmosphere Factor .262

Value Factor – .076

Gino’s

X17 – Satisfaction 5.96

Food Factor .153

Employees Factor .626

Atmosphere Factor – .262

Value Factor .076


Exhibit 14-13 Multiple Exhibit 14-13 Multiple Regression Regression

Using Factor ScoresUsing Factor Scores

X25 – Competitor

Model R R Square

Samouel’s 1 .604 .365

Gino’s 1 .548 .300

Model Summary

*Predictors: (Constant), Food Factor, Employees

Factor, Atmosphere Factor, Value Factor


Exhibit 14-13 Multiple Exhibit 14-13 Multiple Regression Regression

Using Factor Scores Using Factor Scores ContinuedContinued

X25 – Competitor

Model Sum of Squares

Mean Square

F Sig.

Samouel’s

1 Regression 48.583 12.146 13.643 .000

Residual 84.577 .890

Total 133.160

Gino’s

1 Regression 28.130 7.032 10.167 .000

Residual 65.710 .692

Total 93.840

*Predictors: (Constant), Dependent Variable: X17 – Satisfaction

ANOVA


Exhibit 14-14 Regression Coefficients for Exhibit 14-14 Regression Coefficients for Regression ModelsRegression Models

X25 – Competitor

Standardized Coefficients

t Sig.

Model Beta

Samouel’s 1

(Constant) 39.221 .000

Food Factor .433 5.155 .000

Employees Factor .319 3.736 .000

Atmosphere Factor .137 1.564 .121

Value Factor .162 1.951 .054

Gino’s 1

(Constant) 45.521 .000

Food Factor .421 4.673 .000

Employees Factor .480 5.305 .000

Atmosphere Factor .028 .318 .752

Value Factor .091 1.052 .296

Coefficients*

*Dependent Variable: X17 – Satisfaction


Exhibit 14-15 Raw Data for 12 Exhibit 14-15 Raw Data for 12 Perceptions Variables on Perceptions Variables on

Customer SurveyCustomer Survey

Perceptions Variables

ID X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12

1 6 4 1 6 4 4 4 3 6 3 3 2

2 6 5 3 4 4 4 5 4 4 4 4 3

3 7 4 4 7 6 4 4 3 7 4 3 4

4 3 4 5 3 3 2 5 4 3 5 2 1

5 5 4 5 5 5 5 3 3 5 4 3 2


. . . . are calculated by adding the

original scale responses together and

determining the mean value.

Summated Summated

ScoresScores


Exhibit 14-16 Summated Exhibit 14-16 Summated Scores for Five Customer Scores for Five Customer

Survey RespondentsSurvey Respondents

New Summated Scores Variables

food_s employ_s atmos_s value_s

Respondent ID

#1 6.00 3.00 3.67 2.67

#2 5.33 3.67 4.67 3.67

#3 7.00 3.67 3.67 4.67

#4 3.00 1.67 4.33 4.33

#5 5.00 3.33 3.33 4.67


Exhibit 14-17 Discriminant Analysis with Exhibit 14-17 Discriminant Analysis with Summated ScoresSummated Scores

Test of Function(s) Wilks’ Lambda Sig.

1 .716 .000

Classification Results

*79% of original grouped cases correctly classified

Predicted Group Membership Total

Ward Method 1 2

Original Count 1 54 26 80

2 16 104 120

% 1 67.5 32.5 100.0

2 13.3 86.7 100.0


Exhibit 14-18 Significant Exhibit 14-18 Significant Predictors in Discriminant Predictors in Discriminant

FunctionFunction

Variables Function 1

Employees Summated .854

Food Summated .444

Value Summated .438

Atmosphere Summated -.022

Correlations between discriminating variables and the discriminant function.

Variables ordered by absolute size of correlation within function.


Exhibit 14-19 Cluster Means Exhibit 14-19 Cluster Means for Summated Score for Summated Score

VariablesVariables

Ward

Method

Variables Mean

Cluster 1

Moderately Satisfied

Cluster 2

Highly Satisfied

Food Summated 5.1292 5.7333

Employees Summated 2.2200 3.0972

Atmosphere Summated 4.0792 4.0556

Value Summated 3.7375 4.3250


Exhibit 14-20 Rankings of Exhibit 14-20 Rankings of Restaurant Selection Factors Restaurant Selection Factors

for Samouel’s Customersfor Samouel’s Customers

Samouel’s X13 –

Food Quality

Ranking

X14 –

Atmosphere

Ranking

X15 –

Prices Ranking

X16 –

Employees

Ranking

N Valid 100 100 100 100

Missing 0 0 0 0

Median 4.00 3.00 2.00 1.00

Mode 4 3 2 1

Minimum 2 2 1 1

Maximum 4 4 3 4

Multiple modes exist. The smallest value is shown.


Exhibit 14-20 Rankings of Exhibit 14-20 Rankings of Restaurant Selection Factors Restaurant Selection Factors

for Gino’s Customersfor Gino’s Customers

Gino’s X13 –

Food Quality

Ranking

X14 –

Atmosphere

Ranking

X15 –

Prices Ranking

X16 –

Employees

Ranking

N Valid 100 100 100 100

Missing 0 0 0 0

Median 4.00 3.00 1.00 2.00

Mode 4 3 1 2

Minimum 2 2 1 1

Maximum 4 4 2 3

Multiple modes exist. The smallest value is shown.


Exhibit 14-21 Means of Selected Exhibit 14-21 Means of Selected Perceptions Variables on Customer Perceptions Variables on Customer

Survey for Samouel’sSurvey for Samouel’s

Samouel’s X1 –

Excellent

Food Quality

X8 –

Fun Place

To Go

X10 –

Reasonable

Prices

X12 –

Competent Employees

N

Valid 100 100 100 100

Missing 0 0 0 0

Mean 5.24 3.65 4.14 1.62

Minimum 3 1 2 1

Maximum 7 6 6 3


Exhibit 14-21 Means of Selected Exhibit 14-21 Means of Selected Perceptions Variables on Customer Perceptions Variables on Customer

Survey for Gino’sSurvey for Gino’s

Gino’s X1 –

Excellent

Food Quality

X8 –

Fun Place

To Go

X10 –

Reasonable

Prices

X12 –

Competent Employees

N

Valid 100 100 100 100

Missing 0 0 0 0

Mean 5.81 3.12 3.97 2.75

Minimum 3 1 2 1

Maximum 7 5 6 5


. . . . a process used to develop maps

that show the perceptions of a

company, product, service, brand, or

any other object in two dimensions.

Perceptual Perceptual

MappingMapping


Exhibit 14-22 Illustration of Exhibit 14-22 Illustration of Importance/Performance Chart Using Importance/Performance Chart Using

Restaurant Customer Survey DatabaseRestaurant Customer Survey Database Importance

4

Atmosphere

Performance 1 2 3 4 5 6

EmployeesGino’s =

Samouel’s =

Food Quality

3

2

1

Prices


Advanced Analysis and Advanced Analysis and Presentation Presentation ApproachesApproaches

Go On-Line www.yankelovich.com

How can business researchers use the

data from the research reported on this

website?

advanced analysis and presentation approaches

Documents

factor analysis

food factor

factor scoresexhibit

cluster solutionexhibit

atmosphere factor

employees factor

rotated factor solution

clusters valid