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Marketing Research

Marketing Research

Naresh K. Malhotra | Dan Nunan | David F. Birks

(2017)

Additional Information

Book Details

Abstract

Offering a clear explanation and discussion of concepts and valued for its comprehensive nature, the European version of this text is much valued for its wealth of European and International case material, which is why we see strong sales of this title in both the UK as well as Europe.


Table of Contents

Section Title Page Action Price
Cover Cover
Title Page iii
Copyright Page iv
Brief contents v
Contents vii
Preface xiii
Publisher’s acknowledgements xv
About the authors xvii
1 Introduction to marketing research 1
Objectives 2
Overview 2
What does ‘marketing research’ mean? 3
A brief history of marketing research 6
Definition of marketing research 6
The marketing research process 9
A classification of marketing research 12
The global marketing research industry 15
Justifying the investment in marketing research 19
The future – addressing the marketing research skills gap 22
Summary 25
Questions 26
Exercises 26
Notes 27
2 Defining the marketing research problem and developing a research approach 29
Objectives 30
Overview 30
Importance of defining the problem 31
The marketing research brief 32
Components of the marketing research brief 33
The marketing research proposal 36
The process of defining the problem and developing a research approach 39
Environmental context of the problem 42
Discussions with decision makers 42
Interviews with industry experts 44
Initial secondary data analyses 45
Marketing decision problem and marketing research problem 46
Defining the marketing research problem 49
Components of the research approach 50
Objective/theoretical framework 51
Analytical model 52
Research questions 53
Hypothesis 54
Summary 54
Questions 55
Exercises 56
Notes 57
3 Research design 59
Objectives 60
Overview 60
Research design definition 61
Research design from the decision makers’ perspective 62
Research design from the participants’ perspective 63
Research design classification 69
Descriptive research 73
Causal research 79
Relationships between exploratory, descriptive and causal research 80
Potential sources of error in research designs 82
Summary 85
Questions 86
Exercises 86
Notes 87
4 Secondary data collection and analysis 90
Objectives 91
Overview 91
Defining primary data, secondary data and marketing intelligence 92
Advantages and uses of secondary data 94
Disadvantages of secondary data 96
Criteria for evaluating secondary data 96
Classification of secondary data 99
Published external secondary sources 100
Databases 104
Classification of online databases 104
Syndicated sources of secondary data 106
Syndicated data from households 109
Syndicated data from institutions 115
Summary 117
Questions 118
Exercises 119
Notes 119
5 Internal secondary data and analytics 121
Objectives 122
Overview 122
Internal secondary data 125
Geodemographic data analyses 128
Customer relationship management 132
Big data 134
Web analytics 136
Linking different types of data 139
Summary 144
Questions 144
Exercises 145
Notes 146
6 Qualitative research: its nature and approaches 147
Objectives 148
Overview 148
Primary data: qualitative versus quantitative research 150
Rationale for using qualitative research 152
Philosophy and qualitative research 155
Ethnographic research 162
Grounded theory 168
Action research 171
Summary 174
Questions 176
Exercises 176
Notes 177
7 Qualitative research: focus group discussions 179
Objectives 180
Overview 180
Classifying qualitative research techniques 182
Focus group discussion 183
Planning and conducting focus groups 188
The moderator 193
Other variations of focus groups 194
Other types of qualitative group discussions 195
Misconceptions about focus groups 196
Online focus groups 198
Advantages of online focus groups 200
Disadvantages of online focus groups 201
Summary 202
Questions 203
Exercises 204
Notes 205
8 Qualitative research: in-depth interviewing and projective techniques 207
Objectives 208
Overview 208
In-depth interviews 209
Projective techniques 221
Comparison between qualitative techniques 227
Summary 228
Questions 229
Exercises 230
Notes 230
9 Qualitative research: data analysis 233
Objectives 234
Overview 234
The qualitative researcher 235
The process of qualitative data analysis 239
Grounded theory 251
Content analysis 254
Semiotics 256
Qualitative data analysis software 259
Summary 262
Questions 263
Exercises 264
Notes 264
10 Survey and quantitative observation techniques 267
Objectives 268
Overview 268
Survey methods 269
Online surveys 271
Telephone surveys 275
Face-to-face surveys 276
A comparative evaluation of survey methods 279
Other survey methods 288
Mixed-mode surveys 289
Observation techniques 289
Observation techniques classified by mode of administration 292
A comparative evaluation of the observation techniques 295
Advantages and disadvantages of observation techniques 296
Summary 297
Questions 297
Exercises 298
Notes 299
11 Causal research design: experimentation 302
Objectives 303
Overview 303
Concept of causality 304
Conditions for causality 305
Definitions and concepts 308
Definition of symbols 310
Validity in experimentation 310
Extraneous variables 311
Controlling extraneous variables 313
A classification of experimental designs 315
Pre-experimental designs 316
True experimental designs 317
Quasi-experimental designs 318
Statistical designs 320
Laboratory versus field experiments 323
Experimental versus non-experimental designs 325
Application: test marketing 326
Summary 328
Questions 329
Exercises 330
Notes 330
12 Measurement and scaling: fundamentals, comparative and non-comparative scaling 333
Objectives 334
Overview 334
Measurement and scaling 335
Scale characteristics and levels of measurement 336
Primary scales of measurement 337
A comparison of scaling techniques 342
Comparative scaling techniques 343
Non-comparative scaling techniques 347
Itemised rating scales 349
Itemised rating scale decisions 352
Multi-item scales 356
Scale evaluation 358
Choosing a scaling technique 363
Mathematically derived scales 364
Summary 364
Questions 365
Exercises 366
Notes 367
13 Questionnaire design 371
Objectives 372
Overview 372
Questionnaire definition 374
Questionnaire design process 375
Specify the information needed 378
Specify the type of interviewing method 379
Determine the content of individual questions 380
Overcoming the participant’s inability and unwillingness to answer 381
Choose question structure 385
Choose question wording 389
Arrange the questions in proper order 394
Identify the form and layout 396
Reproduce the questionnaire 397
Eliminate problems by pilot-testing 398
Summarising the questionnaire design process 400
Designing surveys across cultures and countries 402
Summary 403
Questions 404
Exercises 405
Notes 405
14 Sampling: design and procedures 409
Objectives 410
Overview 410
Sample or census 412
The sampling design process 414
A classification of sampling techniques 419
Non-probability sampling techniques 420
Probability sampling techniques 425
Choosing non-probability versus probability sampling 433
Summary of sampling techniques 434
Issues in sampling across countries and cultures 436
Summary 437
Questions 438
Exercises 439
Notes 439
15 Sampling: determining sample size 442
Objectives 443
Overview 443
Definitions and symbols 445
The sampling distribution 446
Statistical approaches to determining sample size 447
The confidence interval approach 448
Multiple characteristics and parameters 454
Other probability sampling techniques 454
Adjusting the statistically determined sample size 455
Calculation of response rates 456
Non-response issues in sampling 457
Summary 464
Questions 464
Exercises 465
Appendix: The normal distribution 466
Notes 468
16 Survey fieldwork 471
Objectives 472
Overview 472
The nature of survey fieldwork 474
Survey fieldwork and the data-collection process 475
Selecting survey fieldworkers 475
Training survey fieldworkers 476
Recording the answers 479
Supervising survey fieldworkers 481
Evaluating survey fieldworkers 482
Fieldwork and online research 483
Fieldwork across countries and cultures 485
Summary 487
Questions 487
Exercises 488
Notes 489
17 Social media research 491
Objectives 492
Overview 492
What do we mean by ‘social media’? 492
The emergence of social media research 494
Approaches to social media research 495
Accessing social media data 497
Social media research methods 499
Research with image and video data 508
Limitations of social media research 509
Summary 510
Questions 510
Exercises 511
Notes 511
18 Mobile research 513
Objectives 514
Overview 514
What is a mobile device? 514
Approaches to mobile research 516
Guidelines specific to mobile marketing research 518
Key challenges in mobile research 522
Summary 525
Questions 526
Exercises 526
Notes 526
19 Data integrity 528
Objectives 529
Overview 529
The data integrity process 530
Checking the questionnaire 531
Editing 532
Coding 533
Transcribing 539
Cleaning the data 541
Statistically adjusting the data 543
Selecting a data analysis strategy 545
Data integrity across countries and cultures 548
Practise data analysis with SPSS 549
Summary 552
Questions 552
Exercises 553
Notes 554
20 Frequency distribution, crosstabulation and hypothesis testing 556
Objectives 557
Overview 557
Frequency distribution 560
Statistics associated with frequency distribution 562
A general procedure for hypothesis testing 565
Cross-tabulations 570
Statistics associated with cross-tabulation 576
Hypothesis testing related to differences 580
Parametric tests 582
Non-parametric tests 588
Practise data analysis with SPSS 593
Summary 596
Questions 596
Exercises 597
Notes 598
21 Analysis of variance and covariance 601
Objectives 602
Overview 602
Relationship among techniques 604
One-way ANOVA 605
Statistics associated with one-way ANOVA 606
Conducting one-way ANOVA 606
Illustrative applications of one-way ANOVA 610
n-way ANOVA 614
Analysis of covariance (ANCOVA) 619
Issues in interpretation 620
Repeated measures ANOVA 622
Non-metric ANOVA 624
Multivariate ANOVA 624
Practise data analysis with SPSS 625
Summary 626
Questions 627
Exercises 627
Notes 630
22 Correlation and regression 632
Objectives 633
Overview 633
Product moment correlation 634
Partial correlation 638
Non-metric correlation 640
Regression analysis 641
Bivariate regression 641
Statistics associated with bivariate regression analysis 642
Conducting bivariate regression analysis 642
Multiple regression 651
Statistics associated with multiple regression 652
Conducting multiple regression analysis 653
Multicollinearity 661
Relative importance of predictors 662
Cross-validation 662
Regression with dummy variables 663
Analysis of variance and covariance with regression 664
Practise data analysis with SPSS 665
Summary 666
Questions 667
Exercises 667
Notes 670
23 Discriminant and logit analysis 673
Objectives 674
Overview 674
Basic concept of discriminant analysis 675
Relationship of discriminant and logit analysis to ANOVA and regression 676
Discriminant analysis model 676
Statistics associated with discriminant analysis 677
Conducting discriminant analysis 678
Conducting multiple discriminant analysis 688
Stepwise discriminant analysis 696
The logit model 696
Conducting binary logit analysis 696
Practise data analysis with SPSS 702
Summary 703
Questions 704
Exercises 705
Notes 705
24 Factor analysis 707
Objectives 708
Overview 708
Basic concept 709
Factor analysis model 710
Statistics associated with factor analysis 711
Conducting factor analysis 712
Applications of common factor analysis 724
Practise data analysis with SPSS 729
Summary 730
Questions 731
Exercises 731
Notes 733
25 Cluster analysis 735
Objectives 736
Overview 736
Basic concept 737
Statistics associated with cluster analysis 739
Conducting cluster analysis 739
Applications of non-hierarchical clustering 750
Applications of TwoStep clustering 752
Clustering variables 754
Practise data analysis with SPSS 757
Summary 758
Questions 759
Exercises 759
Notes 760
26 Multidimensional scaling and conjoint analysis 762
Objectives 763
Overview 763
Basic concepts in MDS 765
Statistics and terms associated with MDS 765
Conducting MDS 766
Assumptions and limitations of MDS 773
Scaling preference data 773
Correspondence analysis 775
Relationship among MDS, factor analysis and discriminant analysis 776
Basic concepts in conjoint analysis 776
Statistics and terms associated with conjoint analysis 777
Conducting conjoint analysis 778
Assumptions and limitations of conjoint analysis 786
Hybrid conjoint analysis 786
Practise data analysis with SPSS 788
Summary 789
Questions 790
Exercises 790
Notes 791
27 Structural equation modeling and path analysis 795
Objectives 796
Overview 796
Basic concepts in SEM 797
Statistics and terms associated with SEM 798
Foundations of SEM 800
Conducting SEM 802
Higher-order CFA 813
Relationship of SEM to other multivariate techniques 814
Application of SEM: first-order factor model 814
Application of SEM: second-order factor model 817
Path analysis 823
Software to support SEM 826
Summary 826
Questions 828
Exercises 828
Notes 829
28 Communicating research findings 831
Objectives 832
Overview 832
Why does communication of research findings matter? 833
Importance of the report and presentation 835
Preparation and presentation process 836
Report preparation 837
Guidelines for graphs 842
Report distribution 845
Digital dashboards 845
Infographics 847
Oral presentation 847
Research follow-up 849
Summary 850
Questions 851
Exercises 852
Notes 852
29 Business-to-business (b2b) marketing research 854
Objectives 855
Overview 855
What is b2b marketing and why is it important? 856
The distinction between b2b and consumer marketing 857
Concepts underlying b2b marketing research 858
Implications of the differences between business and consumer purchases for researchers 860
The growth of competitive intelligence 873
The future of b2b marketing research 876
Summary 877
Questions 877
Exercises 878
Notes 878
30 Research ethics 881
Objectives 882
Overview 882
Ethics in marketing research 884
Professional ethics codes 884
Ethics in the research process 888
Ethics in data collection 890
Data analysis 896
Ethical communication of research findings 898
Key issues in research ethics: informed consent 898
Key issues in research ethics: maintaining respondent trust 900
Key issues in research ethics: anonymity and privacy 901
Key issues in research ethics: sugging and frugging 905
Summary 905
Questions 906
Exercises 906
Notes 906
Glossary 908
A 908
B 908
C 909
D 911
E 912
F 913
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T 924
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Subject index 926
A 926
B 927
C 928
D 931
E 933
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Name index 952
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Company index 954
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