Marketing Science 2011
Focus on Authors
Abstract
Wilfred Amaldoss (“ Competing for Low-End Markets ”) is a professor of marketing at the Fuqua School of Business of Duke University. He holds an M.B.A. from the Indian Institute of Management (Ahmedabad), and an M.A. (applied economics) and a Ph.D. from the Wharton School of the University of Pennsylvania. His research interests include experimental economics, advertising, pricing, new product development, and social effects in consumption. His recent publications have appeared in Marketing Science, Management Science, the Journal of Marketing Research, the Journal of Economic Behavior and Organization, and the Journal of Mathematical Psychology. Michael Braun (“ Modeling Customer Lifetimes with Multiple Causes of Churn ”) is an associate professor of management science in the marketing group of the MIT Sloan School of Management. The core of his research program is in developing probability models to uncover patterns of customer behavior from complex data structures in business and marketing contexts, and in using those models to address practical marketing and management issues. He has written on, spoken on, and taught about applications of probability models to marketing problems as diverse as forecasting, customer retention, marketing returns on investment, social networking models, segmentation and targeting strategies, and real-time customization of website design. He is also involved in developing efficient Bayesian statistical methods for the analysis of large data sets to meet the needs of managers in an increasingly data-driven marketplace. Tat Y. Chan (“ Measuring the Lifetime Value of Customers Acquired from Google Search Advertising ”) is an associate professor of marketing at the Olin Business School, Washington University in St. Louis. He received his doctoral degree in economics from Yale University. His recent research focuses on the empirical studies of consumer choices and firm competition. His research has appeared in journals such as the RAND Journal of Economics, the Journal of Political Economy, Marketing Science, and the Journal of Marketing Research. Pradeep K. Chintagunta (“ Assessing the Effect of Marketing Investments in a Business Marketing Context ”) is the Robert Law Professor of marketing at the Booth School of Business at the University of Chicago. He graduated from Northwestern University and has also served on the faculty of the Johnson School, Cornell University. He is interested in studying the effectiveness of marketing activities in pharmaceutical markets, investigating aspects of technology product markets, studying online and off-line purchase behavior, and studying the analysis of household purchase behavior using scanner data. Peter J. Danaher (“ The Impact of Tariff Structure on Customer Retention, Usage, and Profitability of Access Services ”) is a professor of marketing and econometrics at Monash University in Melbourne, Australia. He has had visiting positions at London Business School, the Wharton School, New York University, and the Massachusetts Institute of Technology. He serves on the editorial boards for the Journal of Marketing, the Journal of Marketing Research, Marketing Science, and the Journal of Service Research, and he is also an area editor for the International Journal of Research in Marketing. His primary research interests are media exposure distributions, advertising effectiveness, television audience measurement and behavior, Internet usage behavior, customer satisfaction measurement, forecasting, and sample surveys, resulting in many publications in journals such as the Journal of Marketing Research, Marketing Science, the Journal of Marketing, the Journal of Advertising Research, the Journal of the American Statistical Association, the Journal of Retailing, the Journal of Business and Economic Statistics, and the American Statistician. Daria Dzyabura (“ Active Machine Learning for Consideration Heuristics ”) is a Ph.D. student at the MIT Sloan School of Management. She received an S.B. in mathematics from the Massachusetts Institute of Technology. Her research interests are machine learning, adaptive experimental design, heuristic decision processes, recommendation systems, selling strategies in the presence of self-reflection learning, and consumer response to recalls (analyzed from online textual data). Her earlier papers on cognitive simplicity and unstructured direct elicitation appeared in the Journal of Marketing Research. Skander Essegaier (“ The Impact of Tariff Structure on Customer Retention, Usage, and Profitability of Access Services ”) is an associate professor of marketing at Koç University in Istanbul, Turkey. He earned a Ph.D. from Columbia University in New York, an M.S. from the London School of Economics, and a B.A. from ENSAE in Paris. His research has focused on pricing, channels and retailing, and personalization. His work has been published in Marketing Science, the Journal of Marketing Research, Management Science, the Journal of Applied Probabilities, and the SIAM Journal on Control and Optimization. Peter S. Fader (“ New Perspectives on Customer ‘Death’ Using a Generalization of the Pareto/NBD Model ”) is the Frances and Pei-Yuan Chia Professor of Marketing and codirector of the Wharton Interactive Media Initiative at the Wharton School of the University of Pennsylvania. He loves messing around with “buy-till-you-die” models, such as the one developed in this issue. He is delighted that this research area is alive and well 25 years after it was first conceptualized by Schmittlein, Morrison, and Colombo; and he hopes that current and future researchers will continue to buy into it for years to come. Bruce G. S. Hardie (“ New Perspectives on Customer ‘Death’ Using a Generalization of the Pareto/NBD Model ”) is a professor of marketing at the London Business School. His primary research interest lies in the development of data-based models to support marketing analysts and decision makers, with a particular interest in models that are easy to implement. Most of his current projects focus on the development of probability models for customer-base analysis. John R. Hauser (“ Active Machine Learning for Consideration Heuristics ”) is the Kirin Professor of Marketing at the MIT Sloan School of Management, where he teaches new product development, marketing management, competitive marketing strategy, and research methodology. His awards include the Converse Award for contributions to the science of marketing and the Parlin Award for contributions to marketing research. He has consulted for a variety of corporations on product development, sales forecasting, marketing research, voice of the customer, defensive strategy, and R&D management. He is a founder and principal at Applied Marketing Science, Inc., is a former trustee of the Marketing Science Institute, is a fellow of INFORMS and of the INFORMS Society of Marketing Science, and serves on many editorial boards. Raghuram Iyengar (“ The Impact of Tariff Structure on Customer Retention, Usage, and Profitability of Access Services ”) is an assistant professor of marketing at the Wharton School of the University of Pennsylvania. He earned his Ph.D. from Columbia University and his B.Tech. from Indian Institute of Technology Kanpur, India. His research focuses on pricing and social networks. His work has been published in Marketing Science, the Journal of Marketing Research, Quantitative Marketing and Economics, and Psychometrika. Kamel Jedidi (“ The Impact of Tariff Structure on Customer Retention, Usage, and Profitability of Access Services ”) is the John A. Howard Professor of Marketing at Columbia Business School, Columbia University, New York. He holds a bachelor's degree in economics from the Faculté des Sciences Economiques de Tunis, Tunisia, and master's and Ph.D. degrees in marketing from the Wharton School of the University of Pennsylvania. His substantive research interests include pricing, product design and positioning, diffusion of innovations, market segmentation, and the long-term impact of advertising and promotions; his methodological interests lie in multidimensional scaling, classification, structural equation modeling, and Bayesian and finite-mixture models. He has published extensively in the leading marketing, statistics, and psychometric journals, the most recent of which include the Journal of Marketing Research, Marketing Science, Management Science, and Psychometrika. Kinshuk Jerath (“ Firm Strategies in the ‘Mid Tail’ of Platform-Based Retailing” ; “ New Perspectives on Customer ‘Death’ Using a Generalization of the Pareto/NBD Model ”) is an assistant professor of marketing at the Tepper School of Business at Carnegie Mellon University. He received a B.Tech. degree in computer science and engineering from the Indian Institute of Technology Bombay and a Ph.D. degree in marketing from the Wharton School of the University of Pennsylvania. His research interests are twofold: theoretical models that help to obtain deeper understanding of marketing phenomena, especially phenomena related to retailing, and applied statistical models that support marketing analysts and decision makers. His research has appeared in top-tier marketing journals such as Marketing Science, Management Science, the Journal of Marketing Research, and the Journal of Interactive Marketing. Baojun Jiang (“ Firm Strategies in the ‘Mid Tail’ of Platform-Based Retailing ”) is an assistant professor of marketing at the Olin Business School at the Washington University in St. Louis. He received a B.A. in economics and physics from Grinnell College, an M.S. in physics and an M.S. in electrical engineering from Stanford University, an M.B.A. from th
- DOI
- 10.1287/mksc.1110.0676
- Sources
- openalex