Marketing research with SPSS

457 Pages·2008·55.848 MB·English

by  Wim Janssens, et al

Marketing Research
Wim Janssens
with SPSS
Wim Janssens Katrien Wijnen
Katrien Wijnen Patrick De Pelsmacker
Patrick De Pelsmacker J Patrick Van Kenhove
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Patrick Van Kenhove s
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s

In the past, there have been Marketing Research W
books and there have been SPSS guide books. This ij M
book combines the two, providing a step-by-step n
e
treatment of the major choices facing marketing
n a
researchers when using SPSS. The authors offer a

D r
concise approach to analysing quantitative marketing Marketing Research
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research data in practice.
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Whether at undergraduate or graduate level, students ls t
are often required to analyse data, in methodology m i with SPSS
and marketing research courses, in a thesis, or a n
c
in project work. Although they may have a basic k g
e
understanding of how SPSS works, they may not
r
understand the statistics behind the method. This
V R
book bridges the gap by offering an introduction to
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marketing research techniques, whilst simultaneously n e
explaining how to use SPSS to apply them. K
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n e
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About the authors o a
v
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Wim Janssens is professor of marketing at the c
University of Hasselt, Belgium.
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Katrien Wijnen obtained her doctoral degree on
w
consumer decision making from Ghent University,
Belgium. She is currently employed at an i
t
international media company as a research analyst. h

Patrick De Pelsmacker is professor of marketing S
at Ghent University and part-time professor of P
marketing at FUCAM, Mons, Belgium. S
S
Patrick Van Kenhove is professor of marketing at
the University of Ghent, Belgium.
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MARR_A01.QXD 2/20/08 1:04 PM Page i
MARKETING
RESEARCH WITH
SPSS
MARR_A01.QXD 2/20/08 1:04 PM Page ii
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MARKETING
RESEARCH WITH SPSS
Wim Janssens
Katrien Wijnen
Patrick De Pelsmacker
Patrick Van Kenhove
MARR_A01.QXD 2/20/08 1:04 PM Page iv
Pearson Education Limited
Edinburgh Gate
Harlow
Essex CM20 2JE
England
and Associated Companies throughout the world
Visit us on the World Wide Web at:
www.pearsoned.co.uk
First published 2008
© Pearson Education Limited 2008
The rights of Wim Janssens, Katrien Wijnen, Patrick De Pelsmacker and Patrick Van Kenhove
to be identified as authors of this work have been asserted by them in accordance with the
Copyright, Designs and Patents Act 1988.
All rights reserved. No part of this publication may be reproduced, stored in a retrieval
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All trademarks used herein are the property of their respective owners. The use of any
trademark in this text does not vest in the author or publisher any trademark ownership rights
in such trademarks, nor does the use of such trademarks imply any affiliation with or
endorsement of this book by such owners.
ISBN: 978-0-273-70383-9
British Library Cataloguing-in-Publication Data
A catalogue record for this book is available from the British Library
Library of Congress Cataloging-in-Publication Data
Marketing research with SPSS / Wim Janssens . . . [et al.].
p. cm.
Includes bibliographical references and index.
ISBN 978-0-273-70383-9 (pbk. : alk. paper) 1. Marketing research. 2. SPSS for
Windows. I. Janssens, Wim.
HF5415.2.M35842 2008
658.8'30285555—dc22 2007045264

10 9 8 7 6 5 4 3 2 1
11 10 09 08 07
Typeset in 10/12.5pt GraphicSabon Roman by 73
Printed and bound in Great Britain by Ashford Colour Press, Gosport, Hants
The publisher’s policy is to use paper manufactured from sustainable forests.
MARR_A01.QXD 2/21/08 4:47 PM Page v
Contents
Preface ix Two independent samples 60
Nominal variables: (cid:1)2test of independence
(cross-table analysis) 60
0 Statistical analyses for marketing
Ordinal variables: Mann-Whitney U test 65
research: when and how to use them 1
Interval scaled variables: t-test for independent
Descriptive statistics 1 samples 66
Univariate statistics 2 K independent samples 68
Multivariate statistics 3 Nominal variables: (cid:1)2test of independence 68
Ordinal variables: Kruskal-Wallis test 68
1 Working with SPSS 7 Interval scaled variables: Analysis of variance 68
K dependent samples 68
Chapter objectives 7
Nominal variables: Cochran Q 68
General 7
Ordinal variables: Friedman test 70
Data input 7
Interval scaled variables: Repeated measures
Typing data directly into SPSS 9
analysis of variance 70
Inputting data from other application programs 11
Further reading 70
Data editing 11
Creating labels 11
Working with missing values 13
4 Analysis of variance 71
Creating/calculating a new variable 14
Chapter objectives 71
Research on a subset of observations 16
Technique 71
Recoding variables 19
Example 1: Analysis of variance as a test
Further reading 22
of difference or one-way ANOVA 72
Managerial problem 72
2 Descriptive statistics 23
Problem 72
Chapter objectives 23 Solution 73
Introduction 23 SPSS commands 73
Frequency tables and graphs 25 Interpretation of the SPSS output 75
Multiple response tables 38 Example 2: Analysis of variance with a
Mean and dispersion 44 covariate (ANCOVA) 77
Further reading 46 Technique: supplement 77
Managerial problem 78
Problem 78
3 Univariate tests 47
Solution 79
Chapter objectives 47 SPSS commands 79
General 47 Interpretation of the SPSS output 82
One sample 48 Example 3: Analysis of variance for a
Nominal variables: Binomial test (z-test for proportion) 48 complete 2 (cid:1)2 (cid:1)2 factorial design 92
Nominal variables: (cid:1)2test 50 Managerial problem 92
Ordinal variables: Kolmogorov-Smirnov test 52 Problem 93
Interval scaled variables: Z-test or t-test for the mean 52 Solution 93
Two dependent samples 54 SPSS commands 93
Nominal variables: McNemar test 54 Interpretation of the SPSS output 96
Ordinal variables: Wilcoxon test 57
Interval scaled variables: t-test for paired observations 58
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vi CONTENTS
Example 4: Multivariate analysis of 6 Logistic regression analysis 184
variance (MANOVA) 108 Chapter objectives 184
Technique: supplement 108 Technique 184
Managerial problem 108 Example 1: Interval-scaled and categorical
Problem 109 independent variables, without interaction
Solution 110
term 187
SPSS commands 110
Managerial problem 187
Interpretation of the SPSS output 113
Problem 187
Example 5: Analysis of variance with
Solution 188
repeated measures 120 SPSS commands 188
Managerial problem 120 Interpretation of the SPSS output 192
Problem 122 Example 2: Interval-scaled and categorical
Solution 122
independent variables, with interaction
SPSS commands 122
term 206
Interpretation of the SPSS output 125
Managerial problem 206
Example 6: Analysis of variance with
Problem 207
repeated measures and between-subjects
Solution 208
factor 129 SPSS commands 210
Managerial problem 129 Interpretation of the SPSS output 220
Problem 129 Important guidelines 229
Solution 129 One last remark 229
SPSS commands 129 Example 3: The ‘stepwise’ method,
Interpretation of the SPSS output 131
in addition to the ‘enter’ method, and
Further reading 136
more than one ‘block’ 230
Endnote 136
Managerial problem 230
Problem 230
5 Linear regression analysis 137 Solution 230
Chapter objectives 137 SPSS commands 230
Interpretation of the SPSS output 233
Technique 137
Example 4: Categorical independent
Example 1: A cross-section analysis 141
variables with more than two categories 237
Managerial problem 141
Problem 142 Managerial problem 237
Solution 142 Problem 237
SPSS commands 142 Solution 238
Interpretation of the SPSS output 150 SPSS commands 238
Interpretation of the SPSS output 241
Example 2: The ‘Stepwise’ method,

Further reading 243
in addition to the ‘Enter’ method 174
Endnotes 244
Problem 174
Solution 175
SPSS commands 175 7 Exploratory factor analysis 245
Interpretation of the SPSS output 175 Chapter objectives 245
Example 3: The presence of a nominal
Technique 245
variable in the regression model 179
Example: Exploratory factor analysis 249
Problem 179 Managerial problem 249
Solution 179 Problem 250
SPSS commands 179 Solution 251
Interpretation of the SPSS output 181 SPSS commands 251
Further reading 183 Interpretation of the SPSS output 255
Endnotes 183 Further reading 278
Endnote 278
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CONTENTS vii
8 Confirmatory factor analysis and 10 Multidimensional scaling techniques 363
path analysis using SEM 279 Chapter objectives 363
Chapter objectives 279 Technique 363
Technique 279 The form of the data matrix: the number of
Example 1: Confirmatory factor analysis 281 ways and the number of modes 363
Managerial problem 281 The technique: the measurement level of the input
Problem 282 and output and the representation of the data 366
Solution 282 Data collection method: direct or indirect
AMOS commands 282 measurement 368
Interpretation of the AMOS output 294 Example 1: ‘Two-way, two-mode’
Example 2: Path analysis 311 MDS – correspondence analysis 370
Problem 311 Technique: supplement 370
Solution 311 Managerial problem 370
AMOS commands 311 Problem 373
Interpretation of the AMOS output 312 Solution 373
Further reading 316 SPSS Commands 373
Interpretation of the SPSS output 384
Example 2: ‘Three-way, two-mode’
9 Cluster analysis 317
MDS – ‘two-way, one-mode’ MDS using
Chapter objectives 317
replications in PROXSCAL 398
Technique 317
Managerial problem 398
Example 1: Cluster analysis with binary
Technique: supplement 400
attributes – hierarchical clustering 319 Problem 401
Managerial problem 319 Solution 402
Problem 320 SPSS commands: data specification 402
Solution 320 SPSS commands: dimensionality of the solution 404
SPSS Commands 320 Interpretation of the SPSS output: dimensionality
Interpretation of the SPSS output 324 of the solution 407
Example 2: Cluster analysis with continuous Further reading 415
attributes – hierarchical clustering as input Website reference 415
for K-means clustering 342 Endnotes 416
Managerial problem 342
Problem 342
11 Conjoint analysis 417
Solution 343
SPSS commands: Hierarchical clustering 344 Chapter objectives 417
Interpretation of the SPSS output: Hierarchical Technique 417
clustering 347 Example: Conjoint analysis 418
SPSS commands: K-means clustering 353 Managerial problem 418
Interpretation of the SPSS output: K-means Problem 419
clustering 355 Solution 419
Further reading 362 SPSS commands 419
Endnotes 362 Interpretation of the SPSS output 428
Further reading 433
Index 435
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MARR_A01.QXD 2/20/08 1:04 PM Page ix
Preface
Statistical procedures are a ‘sore point’ in every statistical packages in the marketing research
day marketing research. Usually there is very little world. It is also available at most universities and
knowledge about how the proper statistical pro- colleges of higher education. Additionally, it uses
cedures should be used and even less about how a simple menu system (programming is not neces-
they should be interpreted. In many marketing sary) and is thus very easy to learn how to use.
research reports, the necessary statistical report- The book is based on version 15 of this software
ing is often lacking. Statistics are often left out of package.
the reports so as to avoid scaring off the user. Of Information is drawn from concrete datasets
course this means that the user is no longer cap- which may be found on the website (www.
able of judging whether or not the right proce- pearsoned.co.uk/depelsmacker). The reader sim-
dures have been used and whether or not the ply has to open the dataset in SPSS (not included)
procedures have been used properly. This book and may then – with the book opened to the
has been written for different target audiences. appropriate page – practice the techniques, step
First of all, it is suitable for all marketing by step. Most of the datasets originate from actual
researchers who would like to use these statistical marketing research projects. Each of the datasets
procedures in practice. It is also useful for those was compiled during the course of interviews per-
commissioning and using marketing research. It formed on consumers or students, and were then
allows the procedures used to be followed, under- input into SPSS. The website also contains a num-
stood and most importantly, interpreted. In addi- ber of syntaxes (procedures in program form).
tion, this book can prove beneficial for students in This book is not however a basic manual for
an undergraduate or postgraduate educational SPSS. The topic is marketing research with the aid
programme in marketing, sociology, communica- of SPSS. This means that a basic knowledge of
tion sciences and psychology, as a supplement to SPSS is assumed. For the inexperienced reader,
courses such as marketing research and research the first chapter contains a short introduction
methods. Finally, it is useful for anyone who to SPSS. This book is also not a basic manual
would like to process completed surveys or ques- for marketing research or statistics. The reader

tionnaires statistically. should not expect an elaborate theoretical expla-
This book picks up where the traditional mar- nation on marketing research and/or statistical
keting research handbooks leave off. Its primary procedures. The reader will find this type of infor-
goal is to encourage the use of statistical proce- mation in the relevant literature which is referred
dures in marketing research. On the basis of a to in each chapter. The technique used is described
concrete marketing research problem, the book briefly and explained at the beginning of every
teaches you step by step which statistical proce- chapter under the heading ‘Technique.’ The
dure to use, identifies the options available, and book’s primary purpose is to demonstrate the
most importantly, teaches you how to interpret practical implementation of statistics in market-
the results. In doing so, the book goes far beyond ing research, which does more than simply dis-
what the minimum standard options available in play SPSS input screens and SPSS outputs to show
the software packages have to offer. It opts for the how the analysis should proceed, but also
processing of data using the SPSS package. At provides an indication of the problems which may
present, SPSS is one of the most frequently used crop up and error messages which may appear.