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The "Great Thinkers in Marketing" series highlights the significant contributions of the most influential scholars to marketing research, theory, and practice. The series and volume editors organize each legend's most impactful articles into several volumes as an anthology set. Volume editors also seek commentaries from other scholars familiar with the legend's work on the articles included in that volume.
This set, comprising six volumes of contributions of Donald Lehmann, covers a broad spectrum of topics relating to customer behavior and decision-making processes, the estimation of stochastic models, empirical replication for theoretical generalization, advertising and branding, new product and innovation diffusion, and performance outcomes of marketing strategy.
This volume, edited by Oded Netzer, synthesizes Lehmann's work on marketing analysis methods. Along with a collection of his related articles, it features an interview with Lehmann himself and three insightful commentaries from frequent co-authors. Showcasing Lehmann's work on mapping brand preference and perceptions relating to consumer choice, as well as stochastic estimation models, this volume will help marketing researchers of all levels of experience understand how marketing analysis methods have developed over the last 50+ years.
Table des matières
1. Set Introduction.- 2. Volume I Introduction.- 3. Judged Similarity and Brand-Switching Data as Similarity Measures.- 4. Some Alternatives to Linear Factor Analysis for Variable Grouping Applied to Buyer Behavior Variables.- 5. Some Empirical Contributions to Buyer Behavior Theory.- 6. Three-Way Multivariate Conjoint Analysis.- 7. Using Fuzzy Set Theoretic Techniques to Identify Preference Rules from Interactions in the Linear Model: An Empirical Study.- 8. Modeling Dynamic Effects in Repeated-Measures Experiments Involving Preference/Choice: An Illustration Involving Stated Preference Analysis.- 9. An Empirically Based Stochastic Model.- 10. A Stochastic Three-Way Unfolding Model for Asymmetric Binary Data.- 11. Hierarchical Representations of Market Structures and Choice Processes Through Preference Trees.- 12. Estimating Probabilistic Choice Models from Sparse Data: A Method and an Application to Groups.- 13. A Paired Comparison Nested Logit Model of Individual Preference Structures.- 14. A Combined Simply Scalable and Tree Based Preference Model.-15. A Stochastic Multidimensional Unfolding Approach for Representing Phased Decision Outcomes.- 16. PACM: A Two-Stage Procedure for Analyzing Structural Models.- 17. Combining Related and Sparse Data in Linear Regression Models.- 18. Longitudinal Patterns of Group Decisions: An Exploratory Analysis.- 19. An Alternative Procedure for Assessing Convergent and Discriminant Validity.- 20. Sophistication in Research in Marketing.- 21. The Evolving World of Research in Marketing and the Blending of Theory and Data.- 22. Coach s First Playbook.- 23. 50+ Years with Don Lehmann.- 24. Five Decades of Marketing Analysis Methods.
A propos de l'auteur
Oded Netzer
is Arthur J. Samberg Professor of Business at Columbia Business School. His expertise is developing quantitative methods that leverage data better to understand customer behavior and guide firms' decisions. He focuses primarily on building statistical and econometric models to measure consumer preferences and understand how customer choices change over time and across contexts. He has developed a framework for managing firms' customer bases through dynamic segmentation. More recently, his research focuses on leveraging unstructured data for business applications. He is the author of
Decisions over Decimals
.
