INVESTIGATION OF DIRECT AND INDIRECT EFFECTS OF VARIABLES IN MARKETING DISSERTATION Presented in Partial Fulfillment of Requirements for the Degree in Doctor of Philosophy in the Graduate School at The Ohio State University By Sandeep Rao Chandukala * * * * * The Ohio State University 2008 Dissertation Committee: Dr. Greg M. Allenby, Adviser Dr. H. Rao Unnava Dr. Robert E. Burnkrant Approved by ___________________________________ Adviser Business Administration Graduate Program ii ABSTRACT The idea of hierarchical, sequential, or intermediate effects has long been posited in textbooks and academic literature. Hierarchical effects occur when relationships among variables are mediated through other variables. Despite the attractive theoretical properties of these models, their practical existence has been difficult to show in empirical studies. This thesis comprises of three essays where we demonstrate the presence of hierarchical effects and propose methods for detecting and measuring these effects. The first two essays use empirical data to demonstrate our methodology and its extensions, while the third essay uses three experimental studies to demonstrate the hierarchical effects and role of memory associations impacting consideration sets. In the first essay, we propose an approach to studying hierarchical effects using sets of conditional relationships among affected variables while allowing for heterogeneous response segments, and using Bayesian variable selection to deal with the high dimensional parameter space often resulting in applied empirical studies. Cross- sectional data from a national brand-tracking study is used to illustrate our model, where we find empirical support for a hierarchical relationship among media recall, brand beliefs, and intended actions. We find these effects to be insignificant when measured with standard models and analyses. The proposed model is useful for understanding the iii influence of variables that lead to intermediate, as opposed to direct effects on brand choice. The second essay proposes a methodological extension to the first essay by extending it to panel data. We investigate through a series of quantitative models the role played by customer wait times at a teller and its relationship with the overall satisfaction in a retail banking environment. We demonstrate that accounting for heterogeneous segments of branches provides a better understanding of the drivers of overall satisfaction. Customer wait times impact the drivers of customer satisfaction that result in impacting overall satisfaction. We provide managerial insights by incorporating a threshold parameter in the model that determines average time that a customer is willing to spend waiting at a bank and its impact on overall satisfaction. The third essay incorporates the benefits sought by consumers into network models of memory. Prior consumer research in network models of memory has primarily focused on the association between brands and attributes. The concept of benefits sought by consumers has not been integrated into these models. We propose a model of memory organization that explicitly recognizes the distinction between brand attributes and desired benefits and study the impact of advertising on this proposed network. The model we advance includes nodes representing benefits sought by consumers that are linked to brand attributes and brand names. We demonstrate, using three studies, that advertising effectiveness increases when the advertising message taps into an individual's desired iv benefits. Understanding the cognitive associations between desired benefits and brand attributes can help marketers design more effective communications. This thesis contributes new methodological approaches for exploring hierarchical effects among variables in marketing. Essay one proposes a Bayesian approach for analyzing hierarchical effects in cross-sectional data which can easily be extended and applied to mediation analysis. Essay two demonstrates the importance of our proposed modeling approaches with application in services literature. Essay three contributes to the existing literature on associative networks by incorporating an additional layer that accounts for desired benefits and demonstrates the significant role played by the associations in a hierarchical memory network on forming consumer consideration sets. v ACKNOWLEDGMENTS I wish to express sincere thanks to my adviser, Dr. Greg M. Allenby, for the time and effort he put into my doctoral education. I truly believe that I have benefited both academically and personally from my association with Greg. He has instilled in me something he truly believes in, to be rigorous in research. I would also like to thank Dr. H. Rao Unnava for his invaluable help and patience in guiding me through entire experimental design research. I am grateful to Dr. Robert E. Burnkrant for his insightful comments that helped fine tune my research. I would also like to thank Dr. Thomas Otter for his encouragement during my doctoral program. I could not have completed my doctoral studies without the consistent support of my family and friends and I am indebted to them. I would also like to thank all the current and past doctoral students who helped me through my research work. Finally, I would like to thank Cindy Coykendale and Lisa Gang for their help in navigating through all the administrative details. vi VITA October 16, 1975 Born – Hyderabad, India 1997 B.E., Instrumentation Engineering Osmania University, Hyderabad, India 1999 M.S., Computer Engineering University of Minnesota, Twin Cities, MN, USA 2002 M.B.A, University of Texas, Dallas, TX, USA 2003 M.S., M.A.S University of Texas, Dallas, TX, USA 2003-present Graduate Teaching and Research Associate, The Ohio State University FIELDS OF STUDY Major Field: Business Administration Specialization: Marketing vii TABLE OF CONTENTS Page Abstract ii Acknowledgements v Vita vi List of Tables ix List of Figures xi Chapters: 1. Introduction 1 2. Essay 1: Bayesian Analysis of Hierarchical Effects 5 2.1 Introduction 5 2.2 Model 9 2.3 Simulation Study 17 2.4 Data 19 2.5 Results 20 2.6 Discussion 25 2.7 Conclusion 29 3. Essay 2: Bayesian Investigation of Service Wait Times 48 3.1 Introduction 48 3.2 Data 50 3.3 Model Specifications 51 3.4 Results 58 3.5 Discussion 62 3.6 Summary 65 4. Essay 3: Incorporating Desired Benefits into Network Models of Memory 74 4.1 Introduction 74 4.2 Product attributes and benefits 75 4.3 Proposed memory network 77 4.4 Study 1 81 4.5 Study 2 91 viii 4.6 Study 3 96 4.7 Discussion 100 5. Conclusions and Future Research 111 Appendices 117 Appendix A: Estimation algorithm for Essay1 117 Appendix B: Estimation algorithm for HB threshold model 122 Appendix C: Ad for Study 1 125 Appendix D: List of statements and response scales (Study 1 and Study 2) 126 Appendix E: Ad for Study 2 129 List of references 130 ix LIST OF TABLES Table Page 2.1 Model Description 35 2.2 Coefficient Estimates for Homogeneous Regression Model Simulated Data 36 2.3 Coefficient Estimates for Normal Mixture Model Simulated Data 37 2.4 Coefficient Estimates for Finite Mixture Model Simulated Data 38 2.5 Descriptive Statistics for Automobile Data (N = 6178) 39 2.6 Aggregate Regression Coefficient Estimates Automobile Data 40 2.7 Naïve Segment Regression Estimates 41 2.8 Coefficient Estimates for Naïve Aggregate Model using Multivariate Regression 42 2.9 Model Fit 43 2.10 Sub-model model Fit 43 2.11 Direct Effects of Media Exposure, Brand Beliefs and Intended Actions on Purchase Intention {β k } 44 2.12 Effects of Brand Beliefs on Intended Actions {Γ k } 45 2.13 Effects of Media Exposure on Brand Beliefs {∆ k } 46 2.14 Aggregate Effect of Media Exposure (Z) on Purchase Intention (y) 47 3.1 Branch level Descriptive Statistics for Retail Banking Data (N = 1748 branches) 70 3.2 Correlation matrix for the variables in retail banking data 70 [...]... underlying finding in all the essays is: not accounting for indirect effects of variables can mask the true impact and underestimate the effects of commonly encountered variables in marketing The remainder of this thesis is organized as follows In chapter 2, the first essay “Bayesian Investigation of Hierarchical Effects is discussed The second essay, an extension to essay 1, “Bayesian Investigation of. .. communications The implications of such a representation of brand information in memory are studied in two experiments This thesis is geared toward understanding and developing models for measuring direct and indirect effects of variables In: essay 1, impact of media exposure on purchase intention, essay 2: impact of wait times on overall satisfaction and essay 3: impact of attribute efficacy associations... model 3 capture the direct effects of brand beliefs and media on purchase intent and indirect effects through auxiliary multivariate regressions Our approach thus identifies direct and indirect effects of media and brand beliefs on consumer actions and purchase intent after accounting for heterogeneous segments Models that attempt to draw a direct relationship between media exposure and purchase likelihood... intention (y), and indirect through the influence of media on brand beliefs, and brand beliefs on intended actions (see also Orth and Marchi, 2007) Measuring the influence of media on purchase intentions must account for both direct and indirect effects Parameter estimates for our best-fitting model, model 4, are displayed in tables 2.11 – 2.13 We report parameter estimates that have more than 95% of posterior... X, B and Z The results of this search across various sub-models that allow for the presence of direct effects are reported in Table 2.10 The fit statistics indicate that the joint distribution of X, B, and Z is best factored hierarchically: [X,B,Z] = [X|B][B|Z][Z] Thus, we find evidence for both direct and indirect media effects – direct in the sense that media (Z) directly influences purchase intention... Thus, attempting to explore a direct link between purchase intention (y) and media exposure (Z) may result in a finding of no effect, even when media do affect some aspects of intermediate beliefs and behavior Our model can reflect intermediate effects through the coefficient matrices Γk and ∆k 14 Our approach to studying hierarchical effects involves comparison of the joint distribution of the data,... attempting to initiate purchase Possible variables include the use of electronic and direct postal mail These variables may also influence a set of intended actions, such as dealer visits, and may influence the formation of brand beliefs, all of which may precede actual vehicle purchase 6 Our approach to analyzing hierarchical effects in extended models of behavior is to employ three known aspects of modern... better understand and develop models for measuring the direct and indirect or intermediate effects of commonly encountered variables in marketing data There are two main themes to this dissertation First, to propose a methodology to capture hierarchical effects between various variables, extend this methodology and demonstrate using empirical applications the relevance and significance of the proposed... consumers 3 along with attributes and brands into a network model of memory We propose and test the presence of a memory structure linking benefits with attributes and brands, and show that advertising effectiveness increases when the advertising message taps into an individual's desired benefits or concerns Understanding the cognitive associations between benefits and brand attributes can help marketers... hierarchical model of essay 1 to panel data in a retail banking environment We propose three different model 2 specifications to understand the impact of customer waiting times on drivers of satisfaction and overall satisfaction in the context of retail banking The first model, Standard HB model, investigates the moderating effect of mean waiting time before and after reaching a teller on drivers of satisfaction . INVESTIGATION OF DIRECT AND INDIRECT EFFECTS OF VARIABLES IN MARKETING DISSERTATION Presented in Partial Fulfillment of Requirements for the Degree in Doctor of Philosophy in the. underlying finding in all the essays is: not accounting for indirect effects of variables can mask the true impact and underestimate the effects of commonly encountered variables in marketing. . of such a representation of brand information in memory are studied in two experiments. This thesis is geared toward understanding and developing models for measuring direct and indirect effects