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