Verfügbarkeit: Marketing research

Marketing research: approaches, methods and applications in europe

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Bibliographische Detailangaben
1. Verfasser:	Kent, Ray 1944- (VerfasserIn)
Format:	Buch
Sprache:	English
Veröffentlicht:	London [u.a.] Thomson Learning 2007
Schlagworte:	Marketing Onderzoeksmethoden Marketing research Marketingforschung
Online-Zugang:	Inhaltsverzeichnis
Beschreibung:	XIX, 592 S. Ill., graph. Darst.
ISBN:	9781844803279 1844803279

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adam_text	Contents Walk-through tour xi Accompanying website xiii Preface xv Part I Contexts ι 1 Client-based market research 2 Learning objectives 2 Introduction 3 Internet activity з What is client-based market research? 4 Why do organizations need market research? 7 Types of client-based marketing research 9 Online marketing research 11 The process of designing research for clients 11 Diagnosing the problem 12 Strengths and weaknesses of the company 14 Decisions and action standards 15 The information required 15 The type of research envisaged 16 The objectives of the research 17 The research brief 18 The research proposal 19 Buying and selling research 29 Buying research - the client perspective 29 Selling research - the agency perspective 31 The European market research industry 33 The suppliers of research services 34 The research buyers 34 The profession 35 Trends 36 The changing role of the market researcher 37 Ethical issues 38 Data protection 39 Summary 41 Questions for discussion 41 Case study Flymo 42 Further reading 42 2 Academic research in marketing 43 Learning objectives 43 Introduction 43 Internet activity 44 The nature of academic, scholarly research 44 Philosophical underpinnings 47 The marketing physicist 51 The marketing physician 52 The marketing psychiatrist 53 So, who is correct? 53 The nature and role of theories and models 55 Theory 55 The role of theory 56 Models 56 Designing academic research 57 The research background 59 The literature review 60 Theories and models 60 The research objectives 60 Research methods and techniques 61 Data analysis 62 Ethical issues 62 Summary 64 Questions for discussion 65 Case study Young people and tobacco marketing 66 Further reading 66 Part II Accessing and constructing good-quality data 67 3 Accessing secondary data 68 Learning objectives 68 Introduction 68 Ľ. VI ì CONTENTS Internet activity 69 What are "data"? 69 Sources of secondary data 72 Published sources 72 Commerciai sources 74 Internal data 75 Evaluating secondary data 77 Doing desk research 78 Secondary research and secondary data analysis 79 Marketing intelligence 80 Desk research for academic projects 81 Ethical issues 83 Summary 83 Questions for discussion 84 Case study Vodafone 84 Further reading 84 4 Constructing qualitative data 85 Learning objectives 85 Introduction 86 Internet activity 86 What are "qualitative data"? 86 Client-based qualitative market research 88 Interviewing groups and individuals 91 Focus groups 91 Planning focus groups Ш Depth interviews 99 Planning depth interviews 100 Groups or depths; the choice of method 102 Alternative to interview methods 105 Observation 103 Ethnography 107 Consultation 108 The impact of the internet no Online focus groups 110 Bulletin boards 111 Moderated e-maii groups 111 Academic qualitative research 112 Summary 113 Questions for discussion 114 Case study Fox Kids Europe 114 Further reading 115 5 Constructing quantitative data Structuring data and measuring variables m Learning objectives 116 Introduction 117 Internet activity 117 What are "quantitative data"? 117 Qualitative and quantitative data 118 The structure of data 119 Cases 119 Variables 120 Values 123 Categorical scales 124 Metric scales 127 The process of measurement 132 Direct measurement 133 Indirect measurement 134 Derived measurement 134 Multidimensional measurement 139 Measurement error 141 Ethical issues 146 Summary 146 Questions for discussion 147 Case study The rise of the free daily newspaper 149 Further reading 149 6 Constructing quantitative data Developing the instruments of data capture 150 Learning objectives 150 Introduction 151 internet activity 151 Questionnaire design 151 Specify the information needed 152 Decide on the method of questionnaire administration 153 Determine the content, format and wording of each question 153 Create a draft of the complete questionnaire 153 Test the questionnaire 154 Question formats 155 Question content 157 Question wording 161 Screening 162 Routing 163 Sequencing 163 Questionnaire length 164 Self-completed and interviewer-completed questionnaires 166 Questionnaire layout 1б7 Using computer software 169 Diaries 170 Diary design 173 CONTENTS I vii Recording devices 175 Ethical issues 178 Summary 178 Questions for discussion 179 Case study eBay 179 Further reading 180 7 Constructing quantitative data Selecting methods isi Learning objectives 181 Introduction 182 Internet activity 182 Survey research 182 Interview surveys 184 Telephone surveys 189 Postal surveys 191 Online surveys 192 Mixed techniques 194 Error in survey design and execution 195 Experimental research 203 Experimental design 204 Types of experiment 206 Experimental validity 212 Continuous research 213 Panel research 214 Regular interval surveys 219 Client-based and academic quantitative research 222 Ethical issues 223 Summary 224 Questions for discussion 224 Case study Levi Strauss 225 Further reading 225 б Constructing quantitative data Selecting cases 226 Learning objectives 226 Introduction 226 Internet activity 227 The research population 227 When samples are needed 229 Sample selection 229 Sample design 232 Sample size 236 Sampling in practice 237 Online sampling techniques 240 Sampling errors 241 Systematic error 241 Random error 242 Total survey error 243 Controlling error 244 Ethical issues 245 Summary 246 Questions for discussion 246 Case study Egg pic 247 Further reading 247 9 Mixed research designs 24s Learning objectives 248 Introduction 249 Internet activity 249 Qualitative and quantitative research 249 The nature of research design 251 Mixed methods and mixed designs 253 Types of mixtures 255 Sequential mixed designs 255 Concurrent mixed designs 255 Eclectic designs 256 Research rationales and mixed designs 257 Summary 258 Questions for discussion 258 Case study SMA Nutrition and the segmentation of the baby milk market 259 Further reading 259 Part 111 Data analysis 261 10 Analyzing qualitative data 262 Learning objectives 262 Introduction 262 Internet activity 263 Analyzing qualitative data for clients 263 Describing 264 Commenting 265 Theorizing 266 Reflecting 266 Applying 267 Academic approaches 267 Content analysis 268 Ethnography 268 Grounded theory 270 Phenomenology 272 Discourse analysis 273 Semiotics 275 Vílí I CONTENTS Validity in the analysis of qualitative data 277 Using computer-assisted qualitative data analysis software (CAQDAS) 278 Summary 282 Questions for discussion 282 Case study Living 24/7 283 Further reading 283 11 Analyzing quantitative data Essential descriptive summaries of single variables 284 Learning objectives 284 Introduction 285 internet activity 285 Preparing data for analysis 286 Checking 286 Editing 287 Coding 288 Assembly 289 Data entry 291 Choosing the right data analysis techniques 296 What does the researcher want to do with the data? 296 On what type of scale are the variables recorded? 297 How many variables are to be entered into the calculation? 298 Univariate data display: categorical variables 300 Univariate frequency tables 300 Simple bar charts and pie charts 304 Univariate data display: metric variables 306 Univariate frequency tables 306 Metric tables 306 Histograms and line graphs 308 Data summaries: categorical variables 309 Data summaries; metric variables 310 Central tendency 310 Dispersion 311 Distribution shape 313 The normal distribution 314 Percentile values 315 Data transformations 316 Upgrading or downgrading scales 316 Collapsing categories 317 Class intervals 318 Computing totals 318 Multiple response questions 318 "Don't know" responses and missing values 319 Open-ended questions 321 Analyzing summated rating scales 323 Using SPSS 328 Frequency tables 328 Graphs and charts 330 Histograms and line graphs 330 Data summaries 331 Using Recode 333 Using Compute 334 Using Define Variable/Missing Values Using Multiple Response 336 Summary 337 Questions for discussion 337 SPSS exercises 338 Further reading 338 12 Analyzing relationships between two variables 339 Learning objectives 339 Introduction 340 Internet activity З4о Bivariate data display 340 Bivariate data summaries: categorical variables 345 Coefficients appropriate for binary or nominal variables 349 Coefficients appropriate for ordinal variables 355 Coefficients appropriate for two ranked variables 358 Coefficients appropriate for mixed variables 359 Selecting the appropriate statistic 359 Bivariate data summaries: metric variables 361 Correlation and regression compared 363 Pearson's r and Spearman's rho 364 Using SPSS 366 Crosstabulation 366 Measures of association 366 Correlation and regression 366 Summary 368 Questions for discussion 369 SPSS exercises 369 Further reading 371 13 Making statistical inferences 372 Learning objectives 372 Introduction 373 Internet activity 373 CONTENTS Estimation 374 Estimation for categorical variables 374 Estimation for metric variables 376 Testing hypotheses for statistical significance 377 Testing univariate hypotheses for categorical variables 378 Testing univariate hypotheses for metric variables 380 Testing bivariate hypotheses 383 Testing bivariate hypotheses for categorical variables 383 Testing bivariate hypotheses for metric variables 384 Testing metric differences for categories 385 Statistical inference and bivariate data summaries 388 The significance test controversy 389 Using SPSS 392 Summary 395 Questions for discussion 396 SPSS exercises 396 Further reading 397 14 Multivariate analysis 39s Learning objectives 398 Introduction 399 Internet activity 399 The limitations of bivariate analysis 399 What is multivariate analysis? 402 Looking for patterns 402 Multivariate analysis for categorical variables 404 Three-way and η -way tables 404 Loglinear analysis 405 Multivariate analysis for metric variables: dependence techniques 409 Multiple regression 410 Logistic regression 413 Discriminant analysis 414 Multivariate analysis of variance 417 Multivariate analysis for metric variables: interdependence techniques 420 Factor analysis 420 Cluster analysis 422 Multidimensional scaling 426 Explaining relationships between variables 428 What is an "explanation"? 428 Causal analysis 429 Providing understanding 431 Dialectical analysis 432 Using SPSS 432 Three-way and η -way tabular analysis 432 Loglinear analysis 432 Multiple regression 434 Binary logistic regression 434 Discriminant analysis 435 Multivariate analysis of variance 435 Factor analysis 435 Cluster analysis 435 Summary 436 Questions for discussion 437 SPSS exercises 437 Further reading 437 15 Alternative methods of data analysis 438 Learning objectives 438 Introduction 439 internet activity 439 The origins of mainstream statistics 440 The limitations of mainstream statistics 442 The focus on variables 442 The focus on covariation 444 Causality and linear relationships 444 Nonlinear variable analysis alternatives 449 Neural network analysis 450 Data mining 453 Bayesian statistics 455 Case-based analysis and combinatorial logic 455 Fuzzy set analysis 459 Using Fuzzy-Set/Qualitative Comparative Analysis (FS/QCA) 461 Holistic approaches to the analysis of data 463 Summary 464 Questions for discussion 464 Case study Fuzzy set analysis of the results of an e-mail survey in Norway 465 Further reading 468 Part IV Applications 1 б Commercial proprietary techniques 470 Learning objectives 470 Introduction 470 Internet activity 471 Diagnostic techniques 471 χ CONTENTS Market measurement 472 Mťdia audience measurement 479 Single-source data 491 Osagt; and attitude studies 496 Customer satistaction and relationship management research 498 Advertising tracking studies 504 Predictive techniques 510 'testing products and product concepts 511 Advertising pretesting 517 Volume and brand share prediction 519 Summary 527 Questions for discussion 527 Further reading 528 1 ? Cross-national research 529 Learning objectives 529 Introduction 529 internet activity 530 National and cross-national research 530 The design of cross-national research 532 Identifying market opportunities 533 Building »«formation systems 534 Carrying out primary research 536 Academic cross-national research 543 Ethical issues 543 Summary 544 Questions for discussion 544 Case study Making the Compass Group a preferred employer 545 Further reading 546 18 Communicating the results 547 Learning objectives 547 Introduction 548 Internet activity 548 The research report 548 Report content 549 The presentation 552 Research follow-up 554 Reporting cross-national research 554 Academic articles 555 The academic review process 558 Summary 560 Questions for discussion 561 Further reading 561 Glossary 562 Appendix I: The Table Tennis Questionnaire 573 References 577 Index 585
adam_txt	Contents Walk-through tour xi Accompanying website xiii Preface xv Part I Contexts ι 1 Client-based market research 2 Learning objectives 2 Introduction 3 Internet activity з What is client-based market research? 4 Why do organizations need market research? 7 Types of client-based marketing research 9 Online marketing research 11 The process of designing research for clients 11 Diagnosing the problem 12 Strengths and weaknesses of the company 14 Decisions and action standards 15 The information required 15 The type of research envisaged 16 The objectives of the research 17 The research brief 18 The research proposal 19 Buying and selling research 29 Buying research - the client perspective 29 Selling research - the agency perspective 31 The European market research industry 33 The suppliers of research services 34 The research buyers 34 The profession 35 Trends 36 The changing role of the market researcher 37 Ethical issues 38 Data protection 39 Summary 41 Questions for discussion 41 Case study Flymo 42 Further reading 42 2 Academic research in marketing 43 Learning objectives 43 Introduction 43 Internet activity 44 The nature of academic, scholarly research 44 Philosophical underpinnings 47 The marketing physicist 51 The marketing physician 52 The marketing psychiatrist 53 So, who is correct? 53 The nature and role of theories and models 55 Theory 55 The role of theory 56 Models 56 Designing academic research 57 The research background 59 The literature review 60 Theories and models 60 The research objectives 60 Research methods and techniques 61 Data analysis 62 Ethical issues 62 Summary 64 Questions for discussion 65 Case study Young people and tobacco marketing 66 Further reading 66 Part II Accessing and constructing good-quality data 67 3 Accessing secondary data 68 Learning objectives 68 Introduction 68 Ľ. VI ì CONTENTS Internet activity 69 What are "data"? 69 Sources of secondary data 72 Published sources 72 Commerciai sources 74 Internal data 75 Evaluating secondary data 77 Doing desk research 78 Secondary research and secondary data analysis 79 Marketing intelligence 80 Desk research for academic projects 81 Ethical issues 83 Summary 83 Questions for discussion 84 Case study Vodafone 84 Further reading 84 4 Constructing qualitative data 85 Learning objectives 85 Introduction 86 Internet activity 86 What are "qualitative data"? 86 Client-based qualitative market research 88 Interviewing groups and individuals 91 Focus groups 91 Planning focus groups Ш Depth interviews 99 Planning depth interviews 100 Groups or depths; the choice of method 102 Alternative to interview methods 105 Observation 103 Ethnography 107 Consultation 108 The impact of the internet no Online focus groups 110 Bulletin boards 111 Moderated e-maii groups 111 Academic qualitative research 112 Summary 113 Questions for discussion 114 Case study Fox Kids Europe 114 Further reading 115 5 Constructing quantitative data Structuring data and measuring variables m Learning objectives 116 Introduction 117 Internet activity 117 What are "quantitative data"? 117 Qualitative and quantitative data 118 The structure of data 119 Cases 119 Variables 120 Values 123 Categorical scales 124 Metric scales 127 The process of measurement 132 Direct measurement 133 Indirect measurement 134 Derived measurement 134 Multidimensional measurement 139 Measurement error 141 Ethical issues 146 Summary 146 Questions for discussion 147 Case study The rise of the free daily newspaper 149 Further reading 149 6 Constructing quantitative data Developing the instruments of data capture 150 Learning objectives 150 Introduction 151 internet activity 151 Questionnaire design 151 Specify the information needed 152 Decide on the method of questionnaire administration 153 Determine the content, format and wording of each question 153 Create a draft of the complete questionnaire 153 Test the questionnaire 154 Question formats 155 Question content 157 Question wording 161 Screening 162 Routing 163 Sequencing 163 Questionnaire length 164 Self-completed and interviewer-completed questionnaires 166 Questionnaire layout 1б7 Using computer software 169 Diaries 170 Diary design 173 CONTENTS I vii Recording devices 175 Ethical issues 178 Summary 178 Questions for discussion 179 Case study eBay 179 Further reading 180 7 Constructing quantitative data Selecting methods isi Learning objectives 181 Introduction 182 Internet activity 182 Survey research 182 Interview surveys 184 Telephone surveys 189 Postal surveys 191 Online surveys 192 Mixed techniques 194 Error in survey design and execution 195 Experimental research 203 Experimental design 204 Types of experiment 206 Experimental validity 212 Continuous research 213 Panel research 214 Regular interval surveys 219 Client-based and academic quantitative research 222 Ethical issues 223 Summary 224 Questions for discussion 224 Case study Levi Strauss 225 Further reading 225 б Constructing quantitative data Selecting cases 226 Learning objectives 226 Introduction 226 Internet activity 227 The research population 227 When samples are needed 229 Sample selection 229 Sample design 232 Sample size 236 Sampling in practice 237 Online sampling techniques 240 Sampling errors 241 Systematic error 241 Random error 242 Total survey error 243 Controlling error 244 Ethical issues 245 Summary 246 Questions for discussion 246 Case study Egg pic 247 Further reading 247 9 Mixed research designs 24s Learning objectives 248 Introduction 249 Internet activity 249 Qualitative and quantitative research 249 The nature of research design 251 Mixed methods and mixed designs 253 Types of mixtures 255 Sequential mixed designs 255 Concurrent mixed designs 255 Eclectic designs 256 Research rationales and mixed designs 257 Summary 258 Questions for discussion 258 Case study SMA Nutrition and the segmentation of the baby milk market 259 Further reading 259 Part 111 Data analysis 261 10 Analyzing qualitative data 262 Learning objectives 262 Introduction 262 Internet activity 263 Analyzing qualitative data for clients 263 Describing 264 Commenting 265 Theorizing 266 Reflecting 266 Applying 267 Academic approaches 267 Content analysis 268 Ethnography 268 Grounded theory 270 Phenomenology 272 Discourse analysis 273 Semiotics 275 Vílí I CONTENTS Validity in the analysis of qualitative data 277 Using computer-assisted qualitative data analysis software (CAQDAS) 278 Summary 282 Questions for discussion 282 Case study Living 24/7 283 Further reading 283 11 Analyzing quantitative data Essential descriptive summaries of single variables 284 Learning objectives 284 Introduction 285 internet activity 285 Preparing data for analysis 286 Checking 286 Editing 287 Coding 288 Assembly 289 Data entry 291 Choosing the right data analysis techniques 296 What does the researcher want to do with the data? 296 On what type of scale are the variables recorded? 297 How many variables are to be entered into the calculation? 298 Univariate data display: categorical variables 300 Univariate frequency tables 300 Simple bar charts and pie charts 304 Univariate data display: metric variables 306 Univariate frequency tables 306 Metric tables 306 Histograms and line graphs 308 Data summaries: categorical variables 309 Data summaries; metric variables 310 Central tendency 310 Dispersion 311 Distribution shape 313 The normal distribution 314 Percentile values 315 Data transformations 316 Upgrading or downgrading scales 316 Collapsing categories 317 Class intervals 318 Computing totals 318 Multiple response questions 318 "Don't know" responses and missing values 319 Open-ended questions 321 Analyzing summated rating scales 323 Using SPSS 328 Frequency tables 328 Graphs and charts 330 Histograms and line graphs 330 Data summaries 331 Using Recode 333 Using Compute 334 Using Define Variable/Missing Values Using Multiple Response 336 Summary 337 Questions for discussion 337 SPSS exercises 338 Further reading 338 12 Analyzing relationships between two variables 339 Learning objectives 339 Introduction 340 Internet activity З4о Bivariate data display 340 Bivariate data summaries: categorical variables 345 Coefficients appropriate for binary or nominal variables 349 Coefficients appropriate for ordinal variables 355 Coefficients appropriate for two ranked variables 358 Coefficients appropriate for mixed variables 359 Selecting the appropriate statistic 359 Bivariate data summaries: metric variables 361 Correlation and regression compared 363 Pearson's r and Spearman's rho 364 Using SPSS 366 Crosstabulation 366 Measures of association 366 Correlation and regression 366 Summary 368 Questions for discussion 369 SPSS exercises 369 Further reading 371 13 Making statistical inferences 372 Learning objectives 372 Introduction 373 Internet activity 373 CONTENTS Estimation 374 Estimation for categorical variables 374 Estimation for metric variables 376 Testing hypotheses for statistical significance 377 Testing univariate hypotheses for categorical variables 378 Testing univariate hypotheses for metric variables 380 Testing bivariate hypotheses 383 Testing bivariate hypotheses for categorical variables 383 Testing bivariate hypotheses for metric variables 384 Testing metric differences for categories 385 Statistical inference and bivariate data summaries 388 The significance test controversy 389 Using SPSS 392 Summary 395 Questions for discussion 396 SPSS exercises 396 Further reading 397 14 Multivariate analysis 39s Learning objectives 398 Introduction 399 Internet activity 399 The limitations of bivariate analysis 399 What is multivariate analysis? 402 Looking for patterns 402 Multivariate analysis for categorical variables 404 Three-way and η -way tables 404 Loglinear analysis 405 Multivariate analysis for metric variables: dependence techniques 409 Multiple regression 410 Logistic regression 413 Discriminant analysis 414 Multivariate analysis of variance 417 Multivariate analysis for metric variables: interdependence techniques 420 Factor analysis 420 Cluster analysis 422 Multidimensional scaling 426 Explaining relationships between variables 428 What is an "explanation"? 428 Causal analysis 429 Providing understanding 431 Dialectical analysis 432 Using SPSS 432 Three-way and η -way tabular analysis 432 Loglinear analysis 432 Multiple regression 434 Binary logistic regression 434 Discriminant analysis 435 Multivariate analysis of variance 435 Factor analysis 435 Cluster analysis 435 Summary 436 Questions for discussion 437 SPSS exercises 437 Further reading 437 15 Alternative methods of data analysis 438 Learning objectives 438 Introduction 439 internet activity 439 The origins of mainstream statistics 440 The limitations of mainstream statistics 442 The focus on variables 442 The focus on covariation 444 Causality and linear relationships 444 Nonlinear variable analysis alternatives 449 Neural network analysis 450 Data mining 453 Bayesian statistics 455 Case-based analysis and combinatorial logic 455 Fuzzy set analysis 459 Using Fuzzy-Set/Qualitative Comparative Analysis (FS/QCA) 461 Holistic approaches to the analysis of data 463 Summary 464 Questions for discussion 464 Case study Fuzzy set analysis of the results of an e-mail survey in Norway 465 Further reading 468 Part IV Applications 1 б Commercial proprietary techniques 470 Learning objectives 470 Introduction 470 Internet activity 471 Diagnostic techniques 471 χ CONTENTS Market measurement 472 Mťdia audience measurement 479 Single-source data 491 Osagt; and attitude studies 496 Customer satistaction and relationship management research 498 Advertising tracking studies 504 Predictive techniques 510 'testing products and product concepts 511 Advertising pretesting 517 Volume and brand share prediction 519 Summary 527 Questions for discussion 527 Further reading 528 1 ? Cross-national research 529 Learning objectives 529 Introduction 529 internet activity 530 National and cross-national research 530 The design of cross-national research 532 Identifying market opportunities 533 Building »«formation systems 534 Carrying out primary research 536 Academic cross-national research 543 Ethical issues 543 Summary 544 Questions for discussion 544 Case study Making the Compass Group a preferred employer 545 Further reading 546 18 Communicating the results 547 Learning objectives 547 Introduction 548 Internet activity 548 The research report 548 Report content 549 The presentation 552 Research follow-up 554 Reporting cross-national research 554 Academic articles 555 The academic review process 558 Summary 560 Questions for discussion 561 Further reading 561 Glossary 562 Appendix I: The Table Tennis Questionnaire 573 References 577 Index 585
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