Focus On Authors
Greg M. Allenby (“Explaining Preference Heterogeneity with Mixed Membership Modeling”) is the Kurtz Chair in Marketing at the Ohio State University. He is a fellow of the INFORMS Society for Marketing Science and the American Statistical Association. He was also the 2012 recipient of the American Marketing Association’s Charles Coolidge Parlin Marketing Research Award and a recipient of the INFORMS Society for Marketing Science Long Term Impact Award. He is a past editor of Quantitative Marketing and Economics and past area/associate editor for Marketing Science, the Journal of Marketing Research, and the Journal of Business and Economic Statistics.
Ron Berman (“Curation Algorithms and Filter Bubbles in Social Networks”) is an assistant professor of marketing at the Wharton School. He focuses his research on online marketing, marketing analytics, and the marketing actions of startup firms. Ron holds a PhD and MSc in business administration (marketing) from the University of California, Berkeley, an MBA and MSc in computer science from Tel-Aviv University, and a BSc in computer science, physics and mathematics from the Hebrew University in Jerusalem.
Bart J. Bronnenberg (“Consumer Misinformation and the Brand Premium: A Private Label Blind Taste Test”) is a professor of marketing at the Tilburg School of Economics and Management (on unpaid leave from Stanford University) and a research fellow of the Centre for Economic Policy Research (CEPR). His current research covers convenience and retailing, branding, and search behavior. His publications on these topics have appeared in leading academic journals in business and economics and have won various best paper awards. He has received several grants from the NSF, Dutch Science Foundation, and the ERC.
Joachim Büschken (“Explaining Preference Heterogeneity with Mixed Membership Modeling”) is a professor of marketing at Katholische Universität Eichstätt-Ingolstadt (Germany).
Yuxin Chen (“Frontiers: In-Consumption Social Listening with Moment-to-Moment Unstructured Data: The Case of Movie Appreciation and Live Comments”) is the Distinguished Global Professor of Business at New York University Shanghai, and is affiliated with New York University Stern School of Business. His primary research areas include data-driven marketing, internet marketing, pricing, retailing, competitive strategies, structural empirical models, Bayesian econometric methods, behavioral economics, and marketing in emerging markets. He serves as a senior editor of Marketing Science.
Marc R. Dotson (“Explaining Preference Heterogeneity with Mixed Membership Modeling”) is an assistant professor of marketing at the Brigham Young University Marriott School of Business. He graduated with an MS from the London School of Economics and Political Science in 2009, and with a PhD from the Ohio State University in 2016. His research interests include Bayesian inference, predictive modeling, consumer preference heterogeneity, and unstructured data.
Jean-Pierre Dubé (“Consumer Misinformation and the Brand Premium: A Private Label Blind Taste Test”) is the Sigmund E. Edelstone Professor of Marketing at the University of Chicago Booth School of Business, director of the Kilts Center for Marketing and a Faculty Research Fellow at the NBER. He earned his PhD from Northwestern University in 2000. His current research interests span pricing, advertising, branding, and digital marketing. His research has been published in the leading journals in marketing and economics and has won or been nominated for best-paper awards.
Xiao Huang (“Service Product Design and Consumer Refund Policies”) is an associate professor and the Concordia University Research Chair in Supply Chain Management at the John Molson School of Business, Concordia University. She received her PhD and MS from the University of Southern California and BEng from Tsinghua University. Her work has appeared in leading journals including Management Science and Manufacturing & Service Operations Management.
P. K. Kannan (“Modeling Dynamics in Crowdfunding”) is dean's chair in marketing science at the Smith School of Business, University of Maryland. His expertise is in marketing modeling, applying statistical, econometric, machine learning, and AI methods to marketing data. His current research stream focuses on digital marketing - mobile marketing, attribution modeling, and media mix modeling. His research has won the Little Award, ISMS Lilien Practice Prize Award, Root Award, and Lehmann Award. He is the editor-in-chief of the International Journal of Research in Marketing.
Zsolt Katona (“Curation Algorithms and Filter Bubbles in Social Networks”) is Cheryl and Christian Valentine Associate Professor at the Haas School of Business, UC Berkeley. His research focuses on online marketing strategy, networks and social media. He studies how firms can better take advantage of new digital technologies and how they can integrate them into their marketing mix. Before joining Berkeley-Haas in 2008, Zsolt received his PhD in management from INSEAD. He also holds a PhD in computer science from the Eotvos Lorand University, Hungary.
Chul Kim (“Modeling Dynamics in Crowdfunding”) is an assistant professor of marketing at Baruch College, City University of New York (CUNY). His research priority is to provide counterfactual insights regarding social media and digital marketing. He also has professional experience as a data scientist at Samsung.
Tetyana Kosyakova (“Exact MCMC for Choices from Menus—Measuring Substitution and Complementarity Among Menu Items”) is an assistant professor of marketing at Frankfurt School of Finance & Management. Her research focuses on Bayesian modeling with application to marketing problems. She holds an undergraduate degree in linguistics (Kramatorsk University, Ukraine) and business administration (Goethe University Frankfurt) and a graduate degree in quantitative economics (Goethe University Frankfurt). In 2017, she obtained her PhD degree at Goethe University Frankfurt.
Song Lin (“Two-Sided Price Discrimination by Media Platforms”) is an assistant professor of marketing at the Hong Kong University of Science and Technology. His research interests include pricing, platform design, advertising, consumer learning and search, and new products. He has won the 2013 INFORMS Society for Marketing Science (ISMS) Doctoral Dissertation Proposal Competition and was the finalist for the 2015 John Little Award for the best marketing paper published in Marketing Science and Management Science.
Sanjog Misra (“Exact MCMC for Choices from Menus—Measuring Substitution and Complementarity Among Menu Items”) is the Charles H. Kellstadt Professor of Marketing at the University of Chicago Booth School of Business. His research focuses on the use of structural econometric methods to study consumer and firm decisions. Professor Misra currently serves as co-editor of Quantitative Marketing and Economics. Prior to joining Booth, Misra was professor of marketing at UCLA Anderson School of Management and professor at the Simon School of Business at the University of Rochester.
Christian Neuerburg (“Exact MCMC for Choices from Menus—Measuring Substitution and Complementarity Among Menu Items”) has a professional background in market research, having worked over a decade at GfK’s marketing & data science department. During his time at GfK, He designed and analyzed numerous choice experiments for clients from various industries. He received his PhD from University of Erlangen-Nuremberg for his research on modular choice experiments. In 2018, Christian joined sportswear manufacturer Adidas as director of data science & AI solutions.
Andrea Ordanini (“Modeling Dynamics in Crowdfunding”) is professor of marketing and holder of the BNP Paribas Chair in Marketing & Service Analytics at Bocconi University. He has been visiting researcher at the University of California at Irvine and at the London School of Economics and Political Sciences. His main research interests include the consumption processes of cultural goods (e.g., music) and services marketing. He published various papers in marketing and service journals.
Thomas Otter (“Exact MCMC for Choices from Menus—Measuring Substitution and Complementarity Among Menu Items”) is professor of marketing at Goethe University Frankfurt. His research focuses on Bayesian modeling with application to marketing. He currently serves as vice dean of research for the faculty of economics and business at Goethe University, VP membership & communication for EMAC, co-editor for Quantitative Marketing and Economics, and area editor for International Journal of Research in Marketing.
Robert E. Sanders (“Consumer Misinformation and the Brand Premium: A Private Label Blind Taste Test”) is an assistant professor of marketing at the Rady School of Management at the University of California San Diego. He earned his PhD from the University of Chicago Booth School of Business in 2018. His research covers pricing field studies, dynamic decision-making, sustainability, and the intersection of business economics and public policy. Sanders was named a Clayton Dissertation Proposal Competition winner in 2017 and a finalist in the MSI 2018-2020 Research Priorities Working Paper Competition.
Michael Trusov (“Modeling Dynamics in Crowdfunding”) is associate professor of marketing at the Robert H. Smith School of Business at the University of Maryland. His research interests include social media, search engines, social networks, e-commerce, recommendation systems, user-generated content, text analysis, eye-tracking and machine learning. His research has won several awards, including the O'Dell Award, the Paul Green Award, the Donald Lehmann Award, and the SMA Emerging Scholar Award.
Wenbo Wang (“Frontiers: In-Consumption Social Listening with Moment-to-Moment Unstructured Data: The Case of Movie Appreciation and Live Comments”) is an associate professor of marketing at the Hong Kong University of Science and Technology. He received his PhD in marketing from New York University Stern School of Business. His current research areas include user-generated content, content marketing, advertising, unstructured data, and sustainability. His research has appeared in the Journal of Marketing Research, Marketing Science, and the Journal of Consumer Research.
Dan Zhang (“Service Product Design and Consumer Refund Policies”) is a professor of operations management at the Leeds School of Business, University of Colorado Boulder. He received his PhD from the University of Minnesota and BEng from Chongqing University. His work has appeared in journals such as Management Science, Operations Research, Manufacturing & Service Operations Management, and Production and Operations Management. He has consulted for companies in China, Europe, and North America and has been a frequent speaker at companies and academic institutions.
Qiang Zhang (“Frontiers: In-Consumption Social Listening with Moment-to-Moment Unstructured Data: The Case of Movie Appreciation and Live Comments”) is an assistant professor of marketing at the School of Management and Economics and Shenzhen Finance Institute, Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen). He received his PhD in marketing from the Hong Kong University of Science and Technology. His research interests include unstructured data analysis, online content marketing, consumer search, and online retailing.
