eleventh EDITION Exploring Marketing Research Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it eleventh EDITION Exploring Marketing Research Barry J Babin Louisiana Tech University William G Zikmund Australia • Brazil • Japan • Korea • Mexico • Singapore • Spain • United Kingdom • United States Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it This is an electronic version of the print textbook Due to electronic rights restrictions, some third party content may be suppressed Editorial review has deemed that any suppressed content does not materially affect the overall learning experience The publisher reserves the right to remove content from this title at any time if subsequent rights restrictions require it For valuable information on pricing, previous editions, changes to current editions, and alternate formats, please visit www.cengage.com/highered to search by ISBN#, author, title, or keyword for materials in your areas of interest Important Notice: Media content referenced within the product description or the product text may not be available in the eBook version Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it Exploring Marketing Research, 11th Edition Barry J Babin, William G Zikmund © 2016, 2010 Cengage Learning Vice President, General Manager, Social Science & Qualitative Business: Erin Joyner ALL RIGHTS RESERVED No part of this work covered by the copyright herein may be reproduced, transmitted, stored, or used in any form or by any means graphic, electronic, or mechanical, including but not limited to photocopying, recording, scanning, digitizing, taping, Web distribution, information networks, or information storage and retrieval systems, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without the prior written permission of the publisher Product Director: Jason Fremder Senior Product Manager: Michael Roche Senior Content Developer: Elizabeth Lowry Senior Content Developer: John Rich WCN: 02-200-202 Product Assistant: Jamie Mack Marketing Manager: Jeff Tousignant Marketing Coordinator: Christopher P Walz Manufacturing Planner: Ron Montgomery Art and Cover Direction, Production Management and Composition: Lumina Datamatics, Inc Cover Image: © Dimitri Otis/Photographer’s Choice RF/Getty Images Intellectual Property Analyst: 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the United States of America Print Number: 01 Print Year: 2015 Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it First, to my wonderful family and second, to my colleagues and students who continue to be a source of inspiration Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it Brief contents Preface, xix Part one Introduction, 1 Part two Designing Research Studies, 107 Part three The Role of Marketing Research, Harnessing Big Data into Better Decisions, 25 The Marketing Research Process, 49 The Human Side of Marketing Research: Organizational and Ethical Issues, 75 Qualitative Research Tools, 108 Secondary Data Research in a Digital Age, 142 Survey Research, 166 Observation, 207 Conducting Marketing Experiments, 233 Measurement, 267 Measurement and Attitude Scaling, 268 11 Questionnaire Design, 303 Part four Sampling and Statistical Theory, 335 12 Sampling Designs and Sampling Procedures, 336 13 Big Data Basics: Describing Samples and Populations, 361 Part five Basic Data Analytics, 391 Basic Data Analysis, 392 15 Testing for Differences between Groups and for Predictive Relationships, 412 16 Communicating Research Results, 443 Part six Marketing 17 18 19 20 21 22 Part seven Analytics Tools, 465 Beyond the Basics in Basic Data Analysis, 466 Advanced Topics in Linear Analytics, 489 Testing Hypotheses with GLM Procedures, 510 Introducing Multivariate Data Analysis, 528 Multivariate Data Analysis: Analytics with Interdependence Techniques, 549 Primer on Structural Equations Modeling, 569 Comprehensive Cases with Computerized Databases, 585 Comprehensive Cases, 586 Appendix: Statistical Tables, Endnotes, 597 Index, 609 vii Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it 608 Endnotes 10 The LISREL results are nearly identical, x2 value of 158 with 63 df 11 Pounders, K R., B J Babin and A G Close (2015) “All the Same to Me: Outcomes of Aesthetic Labor Performed by Frontline Service Providers.” Journal of the Academy of Marketing Science, DOI 10.1007/s11747-014-0407-4, in press; Tobacyk, J J., B J Babin, J S Attaway, S Socha, D Shows, and K James (2011) “Materialism through the Eyes of Polish and American Consumers.” Journal of Business Research, 64(9), 944–950; Delgado-Ballester, E., M HernandezEspallardo, and A Rodriguez-Orejuela (2014) “Store Image Influences in Consumers’ Perceptions of Store Brands: The Moderating Role of Value Consciousness.” European Journal of Marketing, 48(9/10), 1850–1869; Chang, W., G R Franke, T D Butler, C F Musgrove, and A E Ellinger (2014) “Differential Mediating Effects of Radical and Incremental Innovation on Market Orientation-Performance Relationship: A Meta-Analysis.” The Journal of Marketing Theory and Practice, 22(3), 235–250 12 Sarstedt, M., C M Ringle, J Henseler, & J F Hair (2014) “On the Emancipation of PLS-SEM: A Commentary on Rigdon (2012).” Long Range Planning, 47(3), 154–160 Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it Dimitri Otis/Getty Images Index A Absolute causality, 58 Accuracy, questionnaire, 305–306 Acquiescence bias, 172 ACSI See American Consumer Satisfaction Index Active research, 90 Adjusted R2, 498 Administrative error, 174 Advocacy research, 95 Aided-recall, 317 Alexa.com, 223e Ambiguity, 52 American Consumer Satisfaction Index (ACSI), 148, 278 AMOS (Analysis of Moment Structures), 570 Analysis of data, 11–12, 70 diagnostic, 56 forecast, 83 market-basket, 152 site analysis techniques, 150 Analysis of variance (ANOVA), 470e, 472e, 506, 522 See also One-way analysis of variance (ANOVA) for complex experimental designs, 470–472 for factorial experiment, 472–473 Anonymity, 91 ANOVA See Analysis of variance Appendix (research report), 449 Applied marketing research, scientific method in, Arbitron, 160 Artifacts, 218 Attention filters, 253 Attitude, 284 Attitudinal rating scales balanced/unbalanced rating scale, 295 behavioral intention, 298 category scales, 287, 288e constant-sum scale, 290–291 direct assessment, 294 face scale, 292e forced-choice scales, 295–296 graphic rating scale, 291–292, 292e Likert scale, 287–289 measuring affect component, 286 multi-attribute attitude score, 297–298 paired comparison, 293–294 physiological measures, 285 ranking, 293 response position, 294–295 self-report scales, 285–292 semantic differential, 289–290, 289e Auto-correlation, 504 Automatic interaction detection, 483 Auxiliary variables, 385 Average variance, explanation, 555 B Balanced experimental design, 477 Balanced rating scale, 295 Bar charts, 454–455 Basic experimental designs, 247 Basic marketing research, scientific method in, Behavioral intention, 298 Behavioral tracking, 33 Benefits vs costs, 19 Best Buy and integrated marketing, 17–18 Between-groups variance, 429 609 Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it 610 Index Between-subjects design, 249 Bias, 5, 7–8 acquiescence, 172 coverage, 182 experimenter, 244–245 extremity, 173 interviewer, 173 nonresponse, 385–386 observer, 214 order, 318–322 response, 171–173 sample, 170 self-selection, 171 social desirability, 173 sources, 349–350 Big data, 26 Big data mining, 483–486 Bimodal distribution, 400e Bivariate hypotheses, 414e Bivariate statistical analysis, 403 “Blind” experimental administrator, 246 Blocking variables, 236 Body (research report), 448–449 Body language, 212e Bootstrapping, 520 Bottom-box score, 365 Branching, 320 Breakoff, 320 Business orientations, 9e understanding, and marketing research, 4–5 C Calibration, neurological devices, 228 Callbacks, 180, 196 Camera surveillance, 224–225 CART (classification and regression technique), 485 Case studies, 119–120 Category scale, 287, 288e CATI, 180 Causal inference, 57 Causality, 57–58, 497–501 degrees of, 58–59 Causal research, 57–59 Cause-and-effect relationships, 57 Census, 337 Central-limit theorem, 375, 375–376 Central location interviewing, 186 Central tendency metrics mean, 365–366, 365e median, 366 mode, 366–367 Certainty, 51 Charts (research reports) bar charts, 454–455 line graphs, 454 pie charts, 454 use of, 451–455 Checklist question, 309 x2 test, 572–573 for goodness-of-fit, 416–420 Children, interviewing, 92–93 Children’s Online Privacy Protection Act (COPPA), 92 Chi-square automatic interaction detection (CHAID), 483, 484 Choice, 286 CIA Factbook, 36 Class coding, 394 Click rate, 198 Click-through rate (CTR) definition, 221 online advertisement and, 223–224 Click-through response rate, 197 Cloud storage, 31 Cluster analysis, 560 applications of, 561–563 interpreting, output, 563–564 of test-market cities, 562, 562e Cluster sampling, 354–355, 355e Codes, 393 Coding, 393 Coefficient alpha (a), 280 Coefficient of determination, 494, 495, 506 Coffee industry, 3–4 Cohort effect, 251 Collages, 128 Commercial sources, marketing, 159 Common factor analysis approach, 556 Communality, 555 Communication nonverbal, 212, 212e smartphones, 166 technology, 20 telephone interviews, 181–183 Comparative fit index (CFI), 573–574 Complete mediation, 518 Complex experimental designs ANOVA for, 470–472 unbalanced designs, 477–478 within-subject designs, 475–477, 476e Complimentary evidence, 215–216 Composite factor scores, 552 Composite scales, 278, 279e, 554–556 CompuStat, 36, 148 Computer-assisted telephone interviewing (CATI), 180 Concept, 271 Concept testing, 114 Conclusions and recommendations selection, 449 Concomitant variation, 57 Conditional causality, 59 Confidence interval estimate, 377 Confidence level, 378, 381 Confidentiality, 91, 99–100 Confirmatory factor analysis (CFA), 552, 574, 574–575, 576e estimation of, 575 interpretation of results, 576–577 Confirmatory research, 113 Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it Index Conflict of interest, 101 between marketing management and marketing research, 84–87 reducing, between management and research, 87 reducing two-way communication, 87e Confounds, 243 Constancy of conditions, 247 Constant-sum scale, 290–291 Construct reliability, 576, 576e Construct, 272 Construct validity, 283, 576, 577e Consumer attitude research, 159 Consumer data, 160 Consumption behavior data, 159–160 Content analysis, 219–220 Content providers, 39 Context variable, 522 Contingency table, 396 Continuous measures, 277 Contrast, 481 Contributory causality, 59 Contrived observation, 214 Control group, 239 Control variables, 497, 498 Convenience sampling, 348 Convenient subjects, 252–253 Convergent validity, 283 Conversations, 127 Conversation volume, 222 Cookies, 42 COPPA (Children’s Online Privacy Protection Act), 92 Correlation, 57 Correlation coefficient, 491, 492–494 calculation of, 494 Correlation matrix, 497 Correspondence rules, 271 Cost, test-marketing, 258 Counterbalancing, 247 Counterbiasing statement, 313 Covariance, 490, 491, 491e Covariance matrix, 495, 497 moments in, 570e Covariate, 236 Coverage bias, 182 Cover letter, 190, 191e Criterion validity, 282 Cross-checks, 145 Cross-functional teams, 83–84 Cross (split)-loadings, 558 Cross-tabulation biological sex and target patronage, 397e consumer ethics survey, 396e contingency table, 396–397 definition, 396 elaboration analysis, 398–399 marital status, sex, and responses, 398e number of, 399 percentage, 398 refinement, 399 Cross-tabulation tables, 416–420 Crowdsourcing, 195 CTR See Click-through rate Cultural cross-validation, 22 Culture, 118 Customer discovery, 152 Customer orientation, 8–9 Customer relationship management (CRM), 30, 82, 152 Custom research, 80–81 Cutting score, 538 D Data characteristics of, 28e conversion, 145 definition of, 26 external, 154 internal, 153–154 proprietary, 153–154 qualitative, 113 quantitative, 113 reliability and validity of, 145 scanner, 33 secondary See Secondary data secondary data sources, 154–160 single-source, 160 Data analysis, 11–12, 70 Data archives data retailers, 35 data wholesalers, 35 financial databases, 36–37 statistical databases, 36 video databases, 37–38 Database, 31, 38e Database marketing, 152 Data-collection, 69–70 Data conversion, 145, 399 See also Data transformation Data interchange, electronic, 34 Data mining, 151e, 152 Data Monitor, 149 Data processing error, 174 Data quality, 28–29 Data reduction, 552, 553 parts of variance involved in, 556, 556e Data reduction technique, 554 Data retailers, 35 Data technology, ethics of, 43–45 Data transformation, 145 definition, 399 definition of, 145 index numbers, 401–402 problems, 400–401 simple transformations, 399–400 tabular and graphic methods, 402 Data warehouse, 31 Data warehousing, 31 Data wholesalers, 35 Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it 611 612 Index Davie-Brown Index, 13 Debriefing, 93 Deception, in research, 93 Decision making, 50–51 decision situations, classification of, 52, 53e Decision statements, 66e Decision support system (DSS) characteristics of, 29–31 databases and data warehousing, 31 input management, 31–34 and intelligence, 31e sources of marketing, 32e Decision-tree, 483, 485–486 Degrees of freedom, 572–573 Deliverables, 62 Delivery information acquisition devices (DIADs), 29 Demand artifacts, 475 Demand characteristics “blind” experimental administrator, 246 definition of, 244 experimental disguise, 245–246 experimental treatment condition, 246 isolate experimental subjects, 246 paying for performance, 247 Demand effect, 244 Demographic concepts, 271 Dependence analysis, 531 measurement scales, influence of, 530–531 methods/techniques, 530 Dependence techniques, 530 Dependent variables, 240, 415e Depth interview, 125–126, 126e Descriptive analysis, 394–395, 395e Descriptive research, 54–57 Determination, coefficient of See Coefficient of determination Deviation scores, 368 Diagnostic analysis, 56 DIALOG catalog, 36 Dichotomous-alternative question, 309 Digital monitoring, 220–221 Dimensions, 550 Direct effect, 513 Direct observation definition, 213 errors with, 214 reasons for using, 213–214 Director of marketing research, 82, 83 Discrete measures, 276–277 Discriminant analysis, 538 illustration of, 538–539 Discriminant score, 538 Discriminant validity, 283 Discussion guide, 130 Dispersion deviation scores, 368 low vs high, 368e range, 367–368, 367e–368e standard deviation, 368–370, 369e Disproportional stratified sample, 354, 354e Distribution frequency, 363, 363e mean, 375e normal, 370–373, 371e–372e percentage, 363, 364e population, 373, 376e sampling, 374 standardized normal, 371 Distribution research, sample, 16–17 Divisibility, 314 Do-not-call legislation, 90 Door-to-door interviews, 179 Double-barreled question, 315 Drop-off method, 192 Dummy coding, 393 Dummy variables, 393–394 E E-cigarettes, 15 Effects coding, 393 Eigenvalues, 556 Elaboration analysis, 398 Electronic data interchange (EDI), 34 E-mail surveys, 193–194 Emotion, and research, 137 Empirical testing, 66 Endogenous constructs, 578 Enterprise search, 154 Entrap, 217 Entropy (pseudo) R2, 543 Environmental scanning, 36, 39, 40, 147–148 Ethical dilemma, 88 Ethical issues See also Rights and obligations and client sponsor, 94–95 conflicts of interest, 101 data technology, 40–43 in experimentation, 260–261 human observation, 216–217, 216e idealism, 88 and online research, 134 and participant, 89–94 privacy, 89–91, 96 relativism, 88 and the researcher, 96–100 of society at large, 100 and surveys, 201 Ethics, data technology, 40–43, 91 Ethnography, 118 Executive summary (research report), 448 Exogenous constructs, 578 Experimental condition color and lighting experiment, 235–236, 236e consumer average patronage, 236–237, 237e definition, 235 Experimental design basic vs factorial, 247 experimental and control groups, 239 Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it Index experimental confounds, 243 experimental treatment, 239–240 extraneous variables, 243–244 manipulation, independent variable, 238–240 matching, 242–243 randomization, 242 repeated measures, 243 sample selection and random sampling errors, 241–242 selection and measurement, dependent variable, 240 Experimental disguise, 245–246 Experimental group, 239 Experimental manipulations, 59e Experimental treatment, 239–240 Experimental validity between-subjects design, 249 control establishments, 247 demand characteristics and, 244–247 experimenter bias, 244–245 external, 252–254 field experiments, 248 internal, 250–252 internal vs external, 250–252 laboratory experiments, 248 test-marketing, 254–260 Experimental variable, 59 Experimenter bias, 244–245 Experiments See also Field experiments and consent, 93 definition of, 59 experimental conditions, 235–236 interaction effect, 237–238 main effect, 236–237 and small sample research, 112 subjects, 235 Exploratory factor analysis (EFA), 552 Exploratory research, 54, 112–114, 135–137 Exponential logistic coefficient, 543 Expressive behavior, 210e External data, 154 sources, 154–160 External validity convenient subjects, 252–253 definition, 252 internal validity and, trade-offs, 253–254 Extraneous variables, 243–244 Extremity bias, 173 Eye activity, 212e Eye-tracking monitor, 226 F Face scale, 292e Face-to-face focus group techniques vs online techniques, 133 Face-to-face interview, 90, 133 Face (content) validity, 282 Facial expressions, 212e Fact-finding, research data, 146–148 Factor, 551 Factor analysis, 551–552, 552 approaches of, 552–553 conducting, 557–558, 559 illustrations of, 551, 551e, 553 interpreting, 558–560 steps in conducting, 557, 557e Factorial designs, 472, 472–475 Factorial experimental designs, 247 Factor loading, 551, 554 Factor rotation, 556 Federal Trade Commission (FTC), 97, 219 Field experiments artificiality of laboratory vs., 249e definition, 248 Field notes, 128 Filter question, 320 Financial databases, 36–37 Fit, 571, 571–574 comparative fit index, 573–574 fixed and free parameters, 573 illustration of, 571–572, 572e validity, 283 Fixed-alternative questions, 306 Fixed parameters, 573 Focus blog, 133 Focus group interview advantages of, 122–123 definition of, 120 as diagnostic tools, 125 disadvantages of, 131 environmental concerns, 124–125 illustration of, 123–124 moderator for, 125 outline for, 130–131 respondents to, 124 Focus groups, 65 Food and Drug Administration (FDA), Forced-choice rating scale, 295–296 Forecast analysis, 82 Fortune, 314 F-ratios, 430–431 Free-association techniques, 128 Free parameters, 573 Frequency-determination question, 309 Frequency distribution, 363, 363e Frequency table, 395 F-statistic, 430, 467 computing, 467–472 for one-way ANOVA, 467–470 F-test, 430, 506 Funnel technique, 319 G Gallup, 67 Galvanic skin response (GSR), 227 General linear model (GLM), 433, 467, 510–525, 531 Geodemographics, 15, 160 Geographical databases, 36 Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it 613 614 Index Geographical information, 210e Geolocation technologies, 43 Gestures, 212e GLM See General linear model Global marketing information, 161e Global marketing research, 20–22, 29 GoodBuy, theory for, 574e Government sources, marketing, 157 Grand mean, 428 Graphic aids, 450 Graphic rating scale, 291–292, 292e Graphs, scree plot, 557 Grounded theory, 119 GSR See Galvanic skin response H Harley-Davidson, 12, 128 Harm, protection from, 93–94 Harris Interactive, 67, 159 Health Insurance Portability and Accountability Act (HIPAA), 42–43 Heat map question, 325, 325e Hermeneutics, 116 Hermeneutic unit, 116 Heteroscedasticity, 501, 501e Hidden observation, 211 Hierarchical regression, 522, 523 illustration of, 524 interaction effect, depicting, 524–525 Histogram, 395 History effect, 250 History sniffing, 45 Homoscedasticity, 501, 501e Honesty, 99 Human subjects review committee, 94 Hypotheses testing direct effect, 513–517 with multiple regression, 513 procedure, 403 with regression analysis, 510–521 Hypothesis, 66, 511–512 I Idea generation, 113 Idealism, 88 Implicit consent, 91 Incentives, use of, 185–186 Incomplete experimental design, 478 Independent samples t-test, 420, 423e Independent variables, 238–240, 415e, 543 Index measure, 278 Index numbers, 401 Index of retail saturation, 151 Indirect effect, 517 Inferential statistics, 362 Information, 27 Information, characteristics of, 27–29 Information completeness, 28 Information Resources Inc (IRI), 224 Information technology, 40–43 Informed consent, 90 INFOSCAN, 159 In-house research, 76–78 Input management behavioral tracking, 33 internal records, 32 outside vendors, 35–36 proprietary marketing research, 32–33 salesperson input, 33 web tracking, 33–34, 39–40 Institutional Review Board (IRB), 94, 216 Instrumentation effect, 251 Integrated marketing communication, 17 Integrated marketing mix, 17–18 Interaction effect, 237–238 Interactive survey approaches, 175 Interdependence methods, 530 Interdependence techniques, 550 vs dependence techniques, 550 Interest, conflicts in, 101 Internal consistency, 280 Internal data, 153–154 Internal validity, 250 external validity and, trade-offs, 253–254 Internet, 38–40, 155–156 activities, 210e privacy, 90 surveys, 194–198 Interpretation, 178 Interpretative software, 134–135 Interval scale, 273e–274e, 275–276 Interviewer bias, 173 Interviewer cheating, 174 Interviewer error, 174 Interviews and children, 92–93 face-to-face, 90 push pull, 98 Interview techniques conversational tools, 115, 127 conversations, 127 depth procedure, 126–127 focus group See Focus groups free-association and sentence completion, 128 probing, 114 projective techniques, 129–130 semi-structured interviews, 127 technology for, 132–135 Intranet, 42–43 Introduction section, 448 Inventories, 219 IRB See Institutional Review Board IRI See Information Resources Inc Isolation vs cross-functionality of marketing, 11e Item nonresponse, 177 Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it Index J J.D Power, 79 Joint Advertising, Market Research & Studies (JAMRS), 155 Judgment (purposive) sampling, 349 Junior analyst, 82 K Keying mail with codes, 192 Keyword search, 39–40 K-means, 563, 564 L Laboratory experiment, 248 Laddering, 126 Landline vs mobile phones, 184e Latent construct, 552 Leading question, 312 Letter of authorization, 448 Letter of transmittal, 447–448 Likelihood value, 542 Likert scale, 287–289 Limited research service companies, 80–81 Line graphs, 454 LISREL, 569 Literature review, 64 Loaded question, 312 Logistic regression, 541 See also Regression illustration of, 543–546, 545e interpreting, 539–546 logit in, 541 prediction in, 542–543 Logit, 541 Low dispersion vs high dispersion, 368e M Magnetic resonance imaging (MRI), 227 Mail survey, 187–189 characteristics of, 187–189 costs of snail mail vs courier surveys, 188e definition of, 187 increasing response rates, 190–192 response rates, 189–190 Main effect, 236–237 Mall-intercept interviews, 179 Managerial decision situation, 62–64 Manager of decision support systems, 82 MANCOVA, 532 Manipulation, 59 Manipulation check, 250 Manners, 212e MANOVA See Multivariate analysis of variance Marginals, 397 Market-basket analysis, 152 Market dynamism, 29 Marketing analytics, 43 Marketing channel, 16 Marketing concept, 9, 13-14, Marketing ethics, 88 Marketing management, and marketing research, 84–87 Marketing metrics, 18, 489, 490 Marketing mix integrated, 17–18 planning and implementing, 15–18 Marketing orientation, Marketing performance, 18 Marketing research See also Research applied, 7, basic, 7, business and, 4–5 characteristics of different types of, 60e conducting vs not conducting, 20e and decision making, 50–52 and decision risk, 13e defined, 5–6 function of, global, 20–22 and marketing management, 84–87 need for, 18–20, 20e overview, 3–4 rights and obligations of, 89e scientific method, 7–8, 7e strategic management orientations, 8–15 Market intelligence, 27 Market opportunity, 51 Market potentials, 149e Market problem, 51 Market-share data, 159 Market tracking, 147 Maturation effect, 251 McCann-Erickson, 136 Mean, 365–366, 365e Mean distribution, 375e Mean squares, 469 Measurement concept, 271 definition, 269 indexes and composites, 278–281 operational definitions, 271–272 scale measurements See Scale measurements validity, 270e, 281–283 Measures of association, 490 Mechanical observation camera surveillance, 224–225 click-through rate, 221, 223–224 online advertising, 223–224 scanner-based research, 224 smartphones, 225 television, radio and digital monitoring, 220–221 web traffic and buzz monitoring, 221–222 Median, 366 Median split, 400, 401e Media sources, marketing, 158 Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it 615 616 Index Mediation basics of testing, 517 conditions of, 518 details of, 519–520 illustration of, 518–519 macro output, 521, 521e PROCESS macro, using, 520, 520e terminology, 521 Mediator variable, 517 Metric data, 531 Metrics, 362 Misrepresented in report, 100e Mistakes, avoiding (questionnaires), 318e ambiguity, 314–315 assumptions, 316 double-barreled items, 315–316 leading and loaded questions, 312–314 and memory taxing, 316–317 simpler is better, 311–312 Mobile phones, landline vs., 184e Mode, 366–367 Model building advertising response, 151–152 analysis of trade sites, 150–151 definition of, 148 and estimating market potential, 148–149 and sales forecasting, 149–150 Moderation, 521, 521–522 Moderator, 125 Moderator variable, 398 Moment, 570 Moral standards, 88 Mortality effect, 251 MRI See Magnetic resonance imaging Multi-attribute attitude score, 297–298 Multi-attribute model, 296 Multicollinearity, 498 Multidimensional scaling, 579 Multiple-choice question, 309 Multiple regression, hypotheses testing with, 513 Multiple regression analysis definition, 434 interpretation, 434–435, 435e Multistage area sampling, 356 Multivariate analysis of variance (MANOVA), 532 illustrating, 533–537, 534e, 535e interpreting, steps, 532–533, 533e Multivariate data analysis, 529 Multivariate dependence analyses, summarizing steps in, 532 Multivariate dependence techniques, 530, 531, 531e, 532 Multivariate result, 533 Multivariate statistical analysis, 403 Multivariate statistical methods, 529 Mystery shoppers, 68 N National Eating Trends (NET), 159 National Family Opinion (NFO), 160 National Trade Data Bank (NTDB), 161 Negative (inverse) relationship, 494 Netnography, 118 Neural network, 152 Neurological activities, 210e Neurological devices, 227–228 NFC (near-field-communication), 41–42 Nielsen Company, 160, 185 Nielsen People Meter, 220 No contracts, 171 Nominal scale, 272–274, 273e–274e Non-forced-choice scale, 296 Noninteractive survey approaches, 175 Nonmetric data, 531 Nonprobability sampling, 348 Nonrespondents, 171 Nonresponse bias, 385–386 Nonresponse errors, 171 Nonsampling errors, 170 Nonspurious association, 58 Nonverbal communication, 212 observing and interpreting, 212e Normal distribution, 370–373, 371e–372e Null model, 542 O Objectives, for research database and CRM management, 152–153 data mining, 152 Objectives, secondary data fact-finding, 146–148 model building, 148–152 Observable behaviors, 210e Observation contrived, 214 definition, 208 direct, 213–214 ethical issues, human, 216–217, 216e of human behavior, 212 nature of studies, 211 physical objects, 217–220 physiological reactions, 225–228 technological advances and, 208–209 types of, 210 Observational data prediction, 209 Observer bias, 214 Odds of success, 541 One-way analysis of variance (ANOVA), 427, 431e between-groups variance, 429 computing F-ratios, 430–431 definition, 427 different but equivalent representation, 431 F-test, 430 interpretation, 430e simple illustration, 427–428, 428e total variability, 428–429 Online advertising, 223–224 Online focus group, 132 Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it Index Online panels, 343 Online sentiment analysis, 10 Open data partnership, 44 Open-ended response questions, 306 Open source information, 34 Open-source innovation, 154 Operationalization, 271 Opting in, 346–347 Oral presentation, 455, 455–457 Order bias, 318–322 Ordinal scale, 273e–274e, 274–275 Ordinary least squares (OLS) illustration of, 504–506 using squared deviations, 504–506 Outside agency, 76–78, 78e Overattention, 257 P Paired comparison, 293–294 Paired-samples t-Test, 425–426, 425e Panel samples, 346 Parsimony, 551 Partial least squares (PLS), 579, 579–580 Partial mediation, 518 Participant-observations, 118 Passive research, 91 Percentage distribution, 363, 364e Performance-monitoring research, 18 Periodicals, marketing, 157 Personal interviews advantages of, 176–177 callbacks, 180, 196 central location interviewing, 186 characteristics of phone interviews, 183–186 definition of, 175 disadvantages of, 178–179 door-to-door, 179–180 mobile phones, 182–183 telephone interviews, 181–183 Personal space, 212e Phenomenology, 115–116 Physical distribution, 210e Physical movements, 210e Physical objects, 210e artifacts, 218 content analysis, 219–220 inventories, 219 Physiological measures, attitudinal rating scales, 285 Physiological reactions, 210e eye-tracking monitor, 226 neurological devices, 227–228 psychogalvanometer, 227 pupilometer, 226–227 voice-pitch analysis, 227 Pictorial records, 210e Picture frustration, 129 Pie charts, 454 Piggyback, 122 Pilot study, 64 Piping software, 326 Placebo, 93, 246 Placebo effect, 246 Planned comparison, 481, 482–483 Point estimates, 377 Polk Company, 159 Pooled estimate of the standard error, 421 Population (universe), 337 Population distribution, 373, 376e Population element, 337 Population parameters definition, 170, 362 frequency distributions, 363–364, 363e proportions, 364 top-box/bottom-box scores, 364–365 Population size, 382–383 Portable People Meter 366 (PPM366), 220 Post-hoc comparison, 479, 480–481 Predictive analytics, 43 Preliminary tabulation, 327 Pretest, 64 Pretesting, 199 Pricing, 16 Pricing research, 16 Primary sampling unit (PSU), 344 Principal components analysis (PCA), 556 Privacy, 96 internet, 90 rights and, 89–91 PRIZM data, 153, 160 Probability, 364 Probability distribution, 364e Probability sampling, 348 Probing, 114 Production oriented firms, Product oriented firms, Product research, 15–16 Profitability, 10 Projective technique, 129–130 Promax, 556 Promotion, 17 Promotion research, 17 Prompting, 325–326, 326e Proportion, 364 Z-test, 426 Proportional stratified sample, 353 Proportional vs disproportional sampling, 353–354 Proprietary data, 153–154 Proprietary marketing research, 32–33 Pseudo-research, 97 Psychogalvanometer, 227 Public opinion research, 159 Pull technology, 40–41 Pupilometer, 226–227 Push poll, 98 Push technology, 40–41 p-value, 404, 404e Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it 617 618 Index Q Qualitative data, 113 Qualitative marketing research common tools, 121e definition of, 109 exploratory research, 135–137 and exploratory research designs, 112–114 free-association and sentence completion, 128 and idea generation, 113 and probing, 114 vs quantitative marketing research, 110–111, 111e technology for, 132–135 uses of, 109–110 Qualitative research orientations case studies, 119–120 ethnography, 118 grounded theory, 119 phenomenology, 115–116 Qualitative research techniques common tools, 121e conservations, 127 depth interviews, 125–126 and exploratory research designs, 112–114 focus group See Focus groups Quantitative data, 113 Quantitative marketing research, 111, 111e Questionnaire design accuracy, 305–306 basic considerations, 304–306 relevancy, 305 Questionnaire formats fixed-alternative questions, 308–310 open-ended response questions, 306–308 phrasing for, 310–311, 311e Questionnaires avoiding mistakes See Mistakes, avoiding (questionnaires) designing, 329 mail questionnaires See Mail survey order bias, 318–322 pretesting, 327–328 self-administered, 187, 187e survey flow, 320–321, 321e survey technology, 322–326, 323e traditional, 321–322 Quota sampling advantages of, 350 definition, 349 sources of bias, 349–350 R Random digit dialing, 183 Randomization, 242 Randomized block design (RBD), 470 Randomized response techniques, 320 Random sampling error, 344–345 Range, 367–368, 367e–368e Ranking task, 285 Rating, 285, 286e See also Attitudinal rating scales Ratio scale, 273e–274e, 276 Refusals, 171 Registered voters, 341 Regression errors in prediction, 504 for prediction, 502–504 research questions, explanation for, 501 statistical significance of, 505–506 time-series analysis, 504 visual estimation of, 502–503 Regression analysis, 433–435 Relationship marketing, 11 Relativism, 88 Relevance, 28 Relevancy, questionnaire, 305 Reliability construct, 576, 576e definition, 280 vs validity, 283–284, 284e Repeated measures, 243 Replicable, 135 Report format, 444, 445–446 Research analyzing marketing performance, 18 applied, 7, basic, 7, causal, 57–59 children and, 92–93 descriptive, 54–57 distribution, 16–17 ethical issues in See Ethical issues examples of, 3–4 experiments, 59 exploratory research, 54 in-house vs outside agency, 76–77 large market research firm’s organizational chart, 83e marketing concept and, 11–12 marketing management and, 84–87 mispresentation of, 99 need for, 18–20 pricing, 16 product, 15–16 promotion, 17 purpose of, 97–99 scientific method, 7–8, 7e and strategic management orientation, 8–15 and strategic marketing management, 12–15 in twenty-first century, 20–22 types of, 15–18, 52–60 uncertainty, influences of, 60 working in, 78–84 world’s largest research firms, 81e Research analyst, 82 Research assistants, 82 Research design, 67–69 Researcher, 97–99 and conflicts of interest, 101 and purpose of research, 97–99 Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it Index Researcher-dependent, 109 Research firms, size large firms, 82 midsized firms, 82 small firms, 81–82 Research follow-up, 444, 458 Research hypotheses, 66e Research methodology section, 449 Research objectives, 62, 66e and exploratory research, 64–65 and hypothesis, 66 literature review, 64 and preliminary research, 62 and previous research, 64 and the research proposal, 64 stating, 65 and theory, 65 Research process alternatives in, 61 analyzing data, 70 collecting data, 69–70 defining objectives of, 62–67 and drawing conclusions, 70 flowchart of, 63e planning a design, 67–69 sampling, 69 stages of, 62e Research program, 71 Research project, 70 Research proposal, 64 Research reports, 444 basic reports, 449–450 follow-up of, 458 format, 444–447 and the internet, 457–458 oral presentation of, 455–457 parts of the report, 447–449 use of charts, 451–455 use of tables, 450–451 Research suppliers definition of, 79 limited research service companies, 80–81 standardized research service, 80 syndicated service, 79 Residuals, 498, 499 Respondent error definition of, 171 nonresponse error, 170–171 response bias, 171–173 Respondents, 167 Response bias, 171–173 types of, 172–173 Response latency, 216 Response rate definition of, 189 mail surveys, 190–192 Results section, 449 Reverse coding, 279 Reverse directory, 343 RFID (radio frequency identification), 41 Rights and obligations of participant, 89–94 and privacy, 89–91, 96 of researcher, 96–100 of society at large, 100 of user (client sponsor), 94–95 Right to privacy, 89–91, 96 active research, 90 passive research, 91 Robocalls, 182 Root mean square error of approximation (RMSEA), 574 Roper Starch Worldwide, 160 Rosetta stone and communication, 443–444 S Sales volume estimation, 256–257 Sample, 337 Sample attrition, 251 Sample bias, 170 Sample design accuracy, 356 advance knowledge of population, 357 national vs local project, 357 resources, 356 time, 356 Sample distribution, 373 Sample selection error, 174 Sample size basis of judgment, 384–385 determining factors, 380–381 estimating questions, 382 population size and, 382–383 proportions, 383–384 random error, 380 required, 382–383 statistical information, 381e Sample statistics, 362 Sample survey, 167 Sampling accurate and reliable results, 338–339, 339e cluster, 354–355, 355e convenience, 348–349 defining target population, 340–341 definition of, 69 destruction of test units, 340 and imperfect samples, 347 international marketing research, 343–344 judgment, 349 multistage area, 356 online panels, 343 planning a sample, 69 pragmatic reasons, 338 probability, 348, 350 probability vs non-probability, 348 proportional vs disproportional, 353–354 Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it 619 620 Index quota, 349–350 random sampling error, 344–345 and sampling frame, 342–343 and sampling units, 344 sequential stages, 340e simple random, 351 snowball, 350 stratified, 353 systematic, 351–353, 352e systematic sampling error, 345–347, 347e Sampling, statistics for central-limit theorem, 375–376 central tendency metrics, 365–367 confidence intervals, 377–380 dispersion metrics, 367–370 normal distribution, 370–373 point estimates, 377 population distribution, 373 population parameters, 363–365 sampling distribution, 374 Sampling distribution, 374 Sampling error, 169 Sampling frame, 342–343 Sampling frame error, 343 Sampling unit, 344 Saturday Evening Post, 218 Scale measurements continuous measures, 277 discrete measures, 276–277 interval scale, 273e–274e, 275–276 levels of, 395e nominal scale, 272–274, 273e–274e ordinal scale, 273e–274e, 274–275 ratio scale, 273e–274e, 276 Scales, 271 See also Attitudinal rating scales Scanner-based consumer panel, 224 Scanner-based mechanical observation, 224 Scanner-based research, 224 Scanner data, 33 Scatter plot, 492, 493e Scientific decision process, 136–137 Scientific method, 7–8, 7e Scientific research, Scree plot, 557 Search-engine optimizer, 34 Secondary data advantages of, 143 data mining, 152 definition of, 143 disadvantages of, 144 fact-finding, 146–148 internet sources for, 156e for major league baseball ticket prices, 150e model building, 148–152 objectives of, 147e to use or not to use, 146e Secondary data sources external, 154–160 government agencies, 161 internal and proprietary data, 153–154 single-source, 160 Secondary sampling unit, 344 Secrecy, loss of, 258–260 Segment, 550 Self-administered questionnaires, 187 Self-contained presentations, 457–458 Self-report scales, 285–292 Self-selection bias, 171 Semantic differentials definition, 289 description, 289–290 example of, 289e scoring, 290 Semantic space, 290 Semi-structured interviews, 127 Sensitivity See Calibration, neurological devices Sequential sampling, 382 Service monitoring, 98–99 Significance level, 404 Simple-dichotomy question, 309 Simple random sampling, 351 Simple regression model, 502–503 See also Regression Simple structure, 558 Single-source data, 160 Site analysis techniques, 150 Slopes test, 525 Smart agent software, 40 Smartphones, 225 Smart poster, 42 Snowball sampling, 350 Social desirability bias, 173 Social networking, 133 Sorting, 285 Spatial tensions and locations, 210e Speeders, 324 Split-ballot technique, 314 Split-half method, 280 Spurious association, 58e Squishing, 317 Stakeholder orientation, Standard deviation, 368–370, 369, 369e Standard error of the mean, 374 Standardized distribution curve, 373e Standardized normal distribution, 371 Standardized regression coefficient (b), 434 Standardized research service, 80 Standardized variables, 492 Statistical Abstract of the United States, 35 Statistical base, 398 Statistical databases, 36 Statistical tests, 404e Statistics central-limit theorem, 375–376 central tendency metrics, 365–367 confidence intervals, 377–380 Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it Index dispersion metrics, 367–370 normal distribution, 370–373 point estimates, 377 population distribution, 373 population parameters, 363–365 sampling distribution, 374 Status bar, 325, 326e Strategic management orientation, 8–11 Stratified sampling, 353 Structural coefficients, 578 Structural equations modeling (SEM), 569 as covariance technique, 570 explanatory tool, 571 fit, concept of, 571–574, 572e structural theory testing in, 577–579 Structural model results interpretation, 578–579 setting up, 578 Structured qualitative responses, 393–394 Subjective results, 112, 112 Subjects, 235 Summated scale, 278 Supply chain, 16 Survey flow, 320–321, 321e Surveys See also Marketing research; Research and administrative error, 174 advantages and disadvantages of, 168–169, 200e choosing best approach, 198–199 definition of, 68 errors that distract from representativeness, 170e ethics of, 201 interactive survey approaches, 175 Internet, 194–198 mail questionnaires See Mail survey non-interactive media, 175 personal interviews See Personal interviews respondent error and, 170–173 sampling errors in, 169 text message, 198 types of information gathered, 167–169 Survey technology, 322, 323e physical features, 325–326 randomized assignment, 324 response quality, 323–324 timing, 324 Symptoms, 51 Syndicated service, 79 Systematic/nonsampling error, 241 Systematic sampling, 351–353, 352e error, 345–347, 347e Systemic error, 170 T Table of contents (research report), 448 Tables cross-tabulation, 416–420 research reports, 450–451 Tabulation, 395 cross-tabulation, 416–420 Tachistoscope, 248 Target markets, 15 Tautology, 512 t-distribution, 406e Technology See also Mechanical observation and communication, 20 DIADs, 29 e-mail surveys, 193–194 ethics of data technology, 40–43 information technology, 40–43 internet, 38–40 internet surveys, 194–198 NFC, 42 for qualitative marketing research, 132–135 RFID tag, 41 smartphones, 166 telephone interviews, 181–183 text message surveys, 198 UPC, 33 Telephone interviews, 181–183 Telescoping, 317 Television monitoring, 220 Temporal patterns, 210e Temporal sequence, 57 Tertiary sampling unit, 344 Testing effects, 251 Testing new product concepts, 115e Test-marketing advantages of, 257 disadvantages of, 258–260 forecasting new product success, 255 product weaknesses, 256 sales volume estimation, 256–257 testing marketing mix, 255–256 test-market results, 256 Test-market sabotage, 257 Test-retest method, 281 Tests of differences, 66 choosing appropriate, 413–415 cross-tabulation tables, 416–420 definition, 413 general linear model, 433–435 one-way analysis of variance, 427–432 statistical software, 433 t-test, 420–426 Test units, 241 Text message surveys, 198 Text mining, 135 Thematic apperception test (TAT), 129, 129e Themes, 120 Theory, 65 Time, test-marketing, 258 Timeliness, 29 Time-series analysis, 504 Title page (research report), 447 Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it 621 622 Index Top-box score, 364 Total value management, 18 Trade associations, marketing, 158 Trade-Offs, 253–254 Traditional questionnaires, 321–322 Traffic cameras, 220 Transcranial magnetic simulation See Magnetic resonance imaging (MRI) Trend analysis, 147 T-test for differences independent samples, 420–422, 423e paired-samples, 425–426, 425e univariate, 405–407 practical uses, 422–424 Z-test, 426 Tukey honestly significant difference (HSD), 480, 481 –2LL, 542 Two-way ANOVA sum of squares, partitioning, 473–475, 474e Type I error, 405 Type II error, 405 U Unaided-recall, 317 Unbalanced rating scale, 295 Uncertainty and research, 60 Underspecification, 499 Uniform resource locator (URL), 39 Univariate statistical analysis, 403 Univariate tests of means, 405–407 Universal product code (UPC), 33, 159 Unobtrusive methods, 69 Unobtrusive observation, 211 U.S Census of Population, 157 V Validity construct, 283 convergent, 283 criterion, 282 data, 145 definition, 281 discriminant, 283 establishing, 282–283 experimental See Experimental validity external See External validity face (content), 282 fit, 283 internal, 250, 253–254 measurement, 270e, 281–283 reliability vs., 283–284, 284e Vans, 108 Variable(s), 271–272 auxiliary, 385 blocking, 236 dependent, 240 dummy, 393–394 experimental, 59 extraneous, 243–244 independent, 238–240, 415e moderator, 398 Variance, 369 Variance inflation factor (VIF), 498 Variate, 529 Varimax, 556 Verbal behavior, 210e Verbal records, 210e Video conferencing, 132 Video databases, 37–38 Viral marketing, Visible observation, 211 Visiontrack, 227 Voice-pitch analysis, 227 W Wald statistic, 543 Website visitors, 345–346 Web tracking, 33–34, 39–40 Web traffic and buzz monitoring, 221–222 statistics, 223e White noise, 499 Wilkes lambda (L), 535 Willingness to pay (WTP), 479–481, 479e Within-group error or variance, 429 Within-subjects designs, 249 data analysis of, 475–477 Within-subjects experimental design, 475 Word cloud, 116–118, 117e World Factbook, 161 W.R Simmons and Associates, 160 Y Yankelovich MONITOR, 159 Z Z-test for differences of proportions, 426 Copyright 2016 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it ... a Marketing Mix, 15 Product Research, 15 Pricing Research, 16 Distribution Research, 16 Promotion Research, 17 The Integrated Marketing Mix, 17 Analyzing Marketing Performance, 18 When Is Marketing. .. Care for Some Horns and Halos?, Applied and Basic Marketing Research, Applied Marketing Research, Basic Marketing Research, The Scientific Method, Marketing Research and Strategic Management Orientation,... Part one Introduction Chapter The Role of Marketing Research, Introduction, Survey This!, What Is Marketing Research?, Business and Marketing Research, Marketing Research Defined, Research Snapshot