Focus On Authors

Ron N. Borkovsky (“Measuring and Understanding Brand Value in a Dynamic Model of Brand Management”) is an assistant professor of marketing at the Rotman School of Management, University of Toronto. He received a Ph.D. in managerial economics and strategy from the Kellogg School of Management, Northwestern University. His research focuses on dynamic models of industry equilibrium and their applications in marketing and industrial organization.

Eric T. Bradlow (“Customer Acquisition via Display Advertising Using Multi-Armed Bandit Experiments”) is the K.P. Chao Professor, professor of marketing, economics, statistics and education, Vice-Dean and Director of Wharton Doctoral Programs, Co-Director of the Wharton Customer Analytics Initiative, and Chairperson of the Marketing Department at the Wharton School of the University of Pennsylvania. An applied statistician, he uses high-powered statistical models to solve problems on everything from Internet search engines to product assortment issues. Specifically, his research interests include Bayesian modeling, statistical computing, and developing new methodology for unique data structures with application to business problems.

Babur De los Santos (“Optimizing Click-Through in Online Rankings with Endogenous Search Refinement”) is an assistant professor of economics at the College of Business, Clemson University; he previously taught at the Kelley School of Business, Indiana University. He received his Ph.D. in economics at the University of Chicago. His research on consumer search lies at the intersection of marketing and industrial organization, with an emphasis on informational frictions faced by consumers in online markets. His work has generated new insights on consumer search on the Internet, product customization in online platforms, and search engine optimization, among others. His work has appeared in the American Economic Review, Journal of Economics & Management Strategy, and Information Economics and Policy.

Peter S. Fader (“Customer Acquisition via Display Advertising Using Multi-Armed Bandit Experiments”) is the Frances and Pei-Yuan Chia Professor of Marketing at the Wharton School of the University of Pennsylvania. His expertise centers around the analysis of behavioral data to understand and forecast customer shopping/purchasing activities. He works with firms from a wide range of industries, such as consumer packaged goods, interactive media, financial services, and pharmaceuticals. Managerial applications focus on topics such as customer relationship management, lifetime value of the customer, and sales forecasting for new products. Much of his research highlights the consistent (but often surprising) behavioral patterns that exist across these industries and other seemingly different domains.

Richard Friberg (“The Effect of Retail Distribution on Sales of Alcoholic Beverages”) is the Jacob Wallenberg Professor of Economics at the Stockholm School of Economics. His research interests straddle the fields of industrial organization and risk management. He has published in leading journals such as American Economic Review and Journal of Finance. His most recent book, Managing Risk and Uncertainty: A Strategic Approach, was published in 2015.

Avi Goldfarb (“Measuring and Understanding Brand Value in a Dynamic Model of Brand Management”) is the Ellison Professor of Marketing at the Rotman School of Management, University of Toronto. He received his Ph.D. in economics from Northwestern University. His research explores brand value, behavioral modeling in industrial organization, and on understanding the opportunities and challenges of the digital economy. He is Chief Data Scientist of the Creative Destruction Lab, a research associate at the National Bureau of Economic Research, and a senior editor at Marketing Science.

Avery Haviv (“Measuring and Understanding Brand Value in a Dynamic Model of Brand Management”) is an assistant professor of marketing at the Simon School of Business, University of Rochester. He received a Ph.D. in marketing from the Rotman School of Management, University of Toronto. His research examines empirical industrial organization, and the application of flexible structural dynamic models.

Sergei Koulayev (“Optimizing Click-Through in Online Rankings with Endogenous Search Refinement”) is an economist at the Consumer Financial Protection Bureau. At his day job, he works on policy issues in the residential mortgage market, analyzing the effectiveness of government regulations in this area. His academic interests including modeling of consumer search, identification of search costs, and the interaction of search and purchase decisions. In a recent study, he examines limited consumer search for mortgages, arguing that every year U.S. consumers leave billions of dollars on the table by not shopping enough for this important purchase.

Song Lin (“Add-on Policies Under Vertical Differentiation: Why Do Luxury Hotels Charge for Internet While Economy Hotels Do Not?”) is an assistant professor of marketing in the Department of Marketing, Hong Kong University of Science and Technology. He studies product and pricing policies, consumer learning and search, new products, and advertising. He has won the 2013 INFORMS Society for Marketing Science (ISMS) Doctoral Dissertation Proposal Competition, and was a finalist for the 2015 John D. C. Little Award for the best marketing paper.

Sridhar Moorthy (“Measuring and Understanding Brand Value in a Dynamic Model of Brand Management”) is the Manny Rotman Professor of Marketing at the Rotman School of Management and is a Senior Consultant at Charles River Associates. His expertise is in bringing economic perspectives to bear on marketing problems. His research focuses on strategic issues in advertising, branding, and brand extension, product differentiation, vertical relations between manufacturers and retailers, and the impact of the Internet on marketing. He is an associate editor (and past co-editor) of Quantitative Marketing and Economics, associate editor of Management Science, member of the editorial board of the Journal of Marketing Research, and coauthor of the textbook Marketing Models. He has served as a vice president (education) of the INFORMS Society for Marketing Science, and provided expert testimony in a number of legal cases.

Donald Ngwe (“Why Outlet Stores Exist: Averting Cannibalization in Product Line Extensions”) is an assistant professor in the Marketing Unit of Harvard Business School. He holds a Ph.D. in economics from Columbia University and a Bachelor’s degree in economics from the University of the Philippines. His research interests include pricing, product design, retailing, and structural modeling.

Mitsukuni Nishida (“First-Mover Advantage Through Distribution: A Decomposition Approach”) is an assistant professor at the Johns Hopkins Carey Business School. He received a Bachelor’s in international relations from Kyoto University and a Ph.D. in economics from the University of Chicago. His research fields are empirical industrial organization and quantitative marketing, covering such topics as retail chains’ entry, expansion, and franchising, search costs, pricing, and productivity decompositions. His research has been published in Marketing Science, International Journal of Industrial Organization, Journal of Regulatory Economics, and Journal of Productivity Analysis.

Fabio Pinna (“Estimating Search Benefits from Path-Tracking Data: Measurement and Determinants”) is an associate at Deutsche Asset Management where he works as a data scientist in the development of quantitative and systematic investments. He received his Ph.D. from the London School of Economics. He is particularly interested in uncovering patterns from companies’ and consumers’ behavior.

Mark Sanctuary (“The Effect of Retail Distribution on Sales of Alcoholic Beverages”) is the Wallander Postdoctoral Researcher at the Stockholm School of Economics. His research interests lie at the intersection of international economics and environmental economics.

Stephan Seiler (“Estimating Search Benefits from Path-Tracking Data: Measurement and Determinants”) is an associate professor of marketing at the Stanford Graduate School of Business. He received his Ph.D. from the London School of Economics and has published in leading journals in both marketing and economics. He is particularly interested in studying consumer search and its consequences for firm conduct and market outcomes. His paper “The Impact of Search Costs on Consumer Behavior: A Dynamic Approach” received the 2014 Dick Wittink Best Paper Award from the Quantitative Marketing and Economics journal.

Eric M. Schwartz (“Customer Acquisition via Display Advertising Using Multi-Armed Bandit Experiments”) is an assistant professor of marketing at the Stephen M. Ross School of Business at the University of Michigan. His expertise focuses on predicting customer behavior, understanding its drivers, and examining how firms actively manage their customer relationships through interactive marketing. His research in customer analytics stretches managerial applications, including online advertising, email marketing, digital media consumption, and word-of-mouth. The quantitative methods he uses are primarily statistical machine learning, Bayesian statistics, dynamic programming, and adaptive field experiments.