Consumer Choice Models With Endogenous Network Effects
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Consumer Choice Models with Endogenous Network Effects
Network externality arises when the utility of a product depends not only on its attributes, but also on the number of consumers who purchase the same product. In this paper, we propose and analyze consumer choice models that endogenize such network externality. We first characterize the choice probabilities under such models and conduct studies on comparative statics. Then we investigate the assortment optimization problem under such choice models. Although the problem is generally NP-hard, we show that a new class of assortments, called quasi-revenue-ordered assortments, which consist of a revenue-ordered assortment plus at most one additional item, are optimal under mild conditions. We also propose an iterative estimation method to calibrate such choice models, for both uncensored and censored data cases. An empirical study on a mobile game dataset shows that our proposed model can provide better fits for the data, increase the prediction accuracy for consumer choices and potentially increase revenue.
Revenue Management and Pricing Analytics
“There is no strategic investment that has a higher return than investing in good pricing, and the text by Gallego and Topaloghu provides the best technical treatment of pricing strategy and tactics available.” Preston McAfee, the J. Stanley Johnson Professor, California Institute of Technology and Chief Economist and Corp VP, Microsoft. “The book by Gallego and Topaloglu provides a fresh, up-to-date and in depth treatment of revenue management and pricing. It fills an important gap as it covers not only traditional revenue management topics also new and important topics such as revenue management under customer choice as well as pricing under competition and online learning. The book can be used for different audiences that range from advanced undergraduate students to masters and PhD students. It provides an in-depth treatment covering recent state of the art topics in an interesting and innovative way. I highly recommend it." Professor Georgia Perakis, the William F. Pounds Professor of Operations Research and Operations Management at the Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts. “This book is an important and timely addition to the pricing analytics literature by two authors who have made major contributions to the field. It covers traditional revenue management as well as assortment optimization and dynamic pricing. The comprehensive treatment of choice models in each application is particularly welcome. It is mathematically rigorous but accessible to students at the advanced undergraduate or graduate levels with a rich set of exercises at the end of each chapter. This book is highly recommended for Masters or PhD level courses on the topic and is a necessity for researchers with an interest in the field.” Robert L. Phillips, Director of Pricing Research at Amazon “At last, a serious and comprehensive treatment of modern revenue management and assortment optimization integrated with choice modeling. In this book, Gallego and Topaloglu provide the underlying model derivations together with a wide range of applications and examples; all of these facets will better equip students for handling real-world problems. For mathematically inclined researchers and practitioners, it will doubtless prove to be thought-provoking and an invaluable reference.” Richard Ratliff, Research Scientist at Sabre “This book, written by two of the leading researchers in the area, brings together in one place most of the recent research on revenue management and pricing analytics. New industries (ride sharing, cloud computing, restaurants) and new developments in the airline and hotel industries make this book very timely and relevant, and will serve as a critical reference for researchers.” Professor Kalyan Talluri, the Munjal Chair in Global Business and Operations, Imperial College, London, UK.
History Of Marketing Science, The (Second Edition)
The field of marketing science has evolved significantly in the last 70 years. Throughout its rich history, developments in this field have always been anchored on marketing phenomena that drew on economics, statistics, operations research, and related disciplines. This book reviews the accomplishments of notable marketing scientists in several research areas. It emphasizes both the role and the importance that pioneers in marketing science have had in the rapid development of this field and honors those contributions.This second edition of the book offers updates of the former chapters and six new chapters on emerging areas of marketing science including machine learning, field experimentation methods, and internet marketing. Combined with older areas of research like endogeneity, services, and market segmentation, this book provides a road map for the development of 22 areas of marketing science, which not only is useful from a historical perspective but also identifies important gaps in the literature which can provide an impetus for future research. As such, it provides an important resource for the main consumers of the academic marketing research literature: doctoral students, faculty, and marketing science practitioners in consulting firms and companies.