Focus on Authors
Stephen J. Anderson (“Frontiers: Breaking the Glass Ceiling: Empowering Female Entrepreneurs Through Female Mentors”) is an empirical researcher who studies management and policy questions at the intersection of marketing and entrepreneurship in developing economies. His research focuses on spurring inclusive, equitable growth and sustainable, green growth in disadvantaged regions. With more than 20 randomized controlled trials (RCTs) launched throughout sub-Saharan Africa, Latin America, and Asia, Steve has been a pioneer in bringing development economics research to the field of marketing over the past decade.
Neeraj Arora (“What Cookie-Based Advertising Effectiveness Fails to Measure”) is the Arthur C. Nielsen, Jr. Chair in Marketing Research and Education at the University of Wisconsin–Madison, where he also serves as the academic director of the Marketing Leadership Institute. He has an undergraduate degree in engineering from Delhi University and an MBA and PhD from the Ohio State University. He currently serves as an associate editor for the Journal of Marketing Research and Quantitative Marketing and Economics.
Noah Castelo (“Frontiers: Determining the Validity of Large Language Models for Automated Perceptual Analysis”) is an assistant professor at the Alberta School of Business, University of Alberta. He received a PhD in marketing from Columbia Business School. His research focuses on the psychology of technology.
Pradeep K. Chintagunta (“Frontiers: Breaking the Glass Ceiling: Empowering Female Entrepreneurs Through Female Mentors”) is interested in empirically studying consumer, agent, and firm behavior. He has studied packaged goods, pharmaceutical, technology, and online markets to answer questions related to pricing, advertising, and channels of distribution. More recently, he has started working in development marketing, studying the role of marketing in economic development. He is interested in studying how marketing practices can impact small businesses and entrepreneurial enterprises.
Ioannis Evangelidis (“Frontiers: Shrinkflation Aversion: When and Why Product Size Decreases Are Seen as More Unfair than Equivalent Price Increases”) is an associate professor of marketing at ESADE, Universitat Ramon Llull. He received his PhD in management and his MS in business administration with a specialization in marketing (both with distinction) from Rotterdam School of Management, Erasmus University Rotterdam. He studies how consumers make decisions, particularly how their purchase behavior can be influenced by changes in the decision environment.
Fred M. Feinberg (“When the Data Are Out: Measuring Behavioral Changes Following a Data Breach”) is Handleman Professor of Marketing at the Ross School of Business and professor of statistics, University of Michigan. He previously taught at the University of Toronto and Duke University, having completed his PhD at the MIT-Sloan School of Management. His research lies primarily in the areas of choice models, Bayesian methodology, and the marketing/engineering design interface. He is departmental editor at Production and Operations Management and co-author, with Tom Kinnear and Jim Taylor, of Modern Marketing Research: Concepts, Methods, and Cases.
Frank Germann (“Frontiers: Breaking the Glass Ceiling: Empowering Female Entrepreneurs Through Female Mentors”) is interested in studying how marketing personnel (e.g., marketing mentors), marketing actions (e.g., the use of analytics), and marketing assets (e.g., brands) influence firm and consumer behavior as well as performance. In recent years, he has started working at the intersection of marketing and development economics, investigating how marketing and marketers can impact small, entrepreneurial firms in emerging markets.
George Z. Gui (“Combining Observational and Experimental Data to Improve Efficiency Using Imperfect Instruments”) is a faculty member in the marketing division at Columbia Business School. His research leverages causal inference techniques and behavioral economics to study consumer behaviors in digital marketplaces, with a primary focus on e-commerce and online grocery platforms. He is also broadly interested in enhancing predictive machine-learning models and generative AIs by integrating causal inference and economic theory into their training and usage.
Paul R. Hoban (“What Cookie-Based Advertising Effectiveness Fails to Measure”) is a senior economist manager for advertising economics at Amazon. Paul was previously a member of the marketing faculty at the University of Wisconsin–Madison. He earned a PhD in management at UCLA and an undergraduate degree in marketing at Michigan State University.
Tingliang Huang (“Erratum on “Competing for Recommendations” Model by Zhou and Zou (2023)”) is the Amazon Distinguished Professor of Business Analytics in the Haslam College of Business, University of Tennessee, Knoxville, and an honorary faculty member at University College London (UCL), UK. He has published extensively in leading academic journals in both operations management and marketing. He received his PhD from the Kellogg School of Management, Northwestern University, MS from University of Minnesota, and BS from University of Science and Technology of China (USTC).
Joseph Johnson (“Unlimited Testing: Let’s Test Your Emails with AI”) is associate professor of marketing at the University of Miami (UM) and member of the big data center at UM’s Institute for Data Science. His current research focuses mainly on applications of deep learning and other computational techniques to marketing management problems. His research has appeared in journals such as the Journal of Consumer Research, Marketing Science, Journal of Marketing, Journal of Retailing, Journal of the Academy of Marketing Science, Journal of International Marketing, Journal of Public Policy and Marketing, Production and Operations Management, and Journal of Optimization Theory and Applications.
Zsolt Katona (“Frontiers: Determining the Validity of Large Language Models for Automated Perceptual Analysis”) is the Cheryl and Christian Valentine professor at the Haas School of Business. His research focuses on online marketing strategy, networks, artificial intelligence, 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. He is faculty director of the Fisher Center for Business Analytics at the Haas School.
Peiyao Li (“Frontiers: Determining the Validity of Large Language Models for Automated Perceptual Analysis”) is a PhD candidate studying quantitative marketing at University of California Berkeley with a particular emphasis on integrating state-of-the-art artificial intelligence (AI) models into business research. His work primarily revolves around the analysis of unstructured data, including texts, images, and networks, using advanced AI tools. He is passionate about bridging the gap between artificial intelligence and marketing, striving to bring more insights to the field.
Kathleen T. Li (“Frontiers: A Simple Forward Difference-in-Differences Method”) is an assistant professor of marketing at the University of Texas at Austin McCombs School of Business. She received her PhD in marketing from the Wharton School at the University of Pennsylvania and a BA from Rice University. She received the John A. Howard/American Marketing Association Dissertation Award and the Saroj and Vithala Young Scholar Award and is a 2022 INFORMS Society for Marketing Scienc Early Career Scholar and a 2023 Marketing Science Institute Young Scholar.
Yunchuan Liu (“Platform Manipulation in Online Retail Marketplace with Sponsored Advertising”) is an accomplished associate professor of business administration at Gies College of Business, University of Illinois at Urbana-Champaign. He has published extensively in top-tier journals such as Marketing Science and Management Science. He is co-foundeder of the Chinese Scholar Marketing Association and developed a pioneering Global Employable PhD training program. He received a PhD from Columbia University and is a highly respected scholar in the field of marketing.
Jinyi Liu (“Erratum on “Competing for Recommendations” Model by Zhou and Zou (2023)”) is a PhD student in business analytics at the Haslam College of Business, University of Tennessee, Knoxville. He earned an MA of economics from the University of Rochester and a BEcon in finance from the University of Science and Technology of China (USTC).
Fei Long (“Platform Manipulation in Online Retail Marketplace with Sponsored Advertising”) is an assistant professor of marketing at Kenan-Flagler Business School at UNC-Chapel Hill. Her research focuses on e-commerce platforms and digital advertising. She is also interested in topics in agency theory and salesforce compensation. She has successfully published her work in top-tier journals, including Marketing Science and the Journal of Marketing Research. Fei received a PhD in business from Columbia Business School and an MS in operations research from Columbia University.
Harikesh S. Nair (“Advertising as Information for Ranking E-Commerce Search Listings”) is director of data science at Google. He leads a data science team powering ads measurement for Google and developing next-generation measurement products that support the privacy-preserving future of digital advertising. Previously, he was the Jonathan B. Lovelace Professor of Marketing at Stanford Graduate School of Business, faculty director of the Stanford Computational Marketing Laboratory, and chief business strategy scientist at JD.com.
Nguyen Nguyen (“Unlimited Testing: Let’s Test Your Emails with AI”) is a PhD student at the Miami Herbert Business School, University of Miami. His research covers topics in deep learning, natural language processing, computer vision, and marketing communications. In his research, he leverages modern machine-learning and deep-learning techniques to help firms optimize their marketing campaigns.
Navdeep S. Sahni (“Advertising as Information for Ranking E-Commerce Search Listings”) is an associate professor of marketing at the Stanford Graduate School of Business. His research focuses on digital markets and studies marketing problems at the intersection of business, economics, and policy. His research employs methodologies ranging from econometric modeling to large-scale experimentation to make data-based inferences.
Robert Evan Sanders (“Dynamic Pricing and Organic Waste Bans: A Study of Grocery Retailers’ Incentives to Reduce Food Waste”) is an assistant professor of marketing at the University of California, San Diego Rady School of Management. He received a BSc in economics from the Wharton School at the University of Pennsylvania in 2012 and earned his PhD from the University of Chicago Booth School of Business in 2018. His research interests include pricing field studies, dynamic decision-making, sustainability, and the intersection of business economics and public policy. He was named a Clayton Dissertation Proposal Competition winner in 2017, a finalist in the MSI 2018–2020 Research Priorities Working Paper Competition, one of four finalists for the Robert D. Buzzell MSI Best Paper Award 2021, and a recipient of a Becker Friedman Institute – Industrial Organization Initiative Award.
Miklos Sarvary (“Frontiers: Determining the Validity of Large Language Models for Automated Perceptual Analysis”) is the Carson Family Professor of Business at Columbia Business School, where he co-heads the Media and Technology Program. Before Columbia, he was a faculty member at INSEAD, Harvard Business School, and Stanford’s Graduate School of Business. He holds a PhD in management from INSEAD. His research focuses on competitive dynamics in the media and technology sectors.
Ike Silver (“Put Your Mouth Where Your Money Is: A Field Experiment Encouraging Donors to Share About Charity”) is the Donald P. Jacobs Scholar and Assistant Professor of Marketing at the Kellogg Graduate School of Management, Northwestern University. Dr. Silver studies moral and political signaling—more specifically, how companies and individual consumers signal their moral values, how various signaling strategies are interpreted by observers, and how related psychological processes impact people’s judgments and decisions.
Deborah Small (“Put Your Mouth Where Your Money Is: A Field Experiment Encouraging Donors to Share About Charity”) is the Adrian C. Israel Professor of Marketing at the Yale School of Management, Yale University. Dr. Small studies how individuals make choices that affect their own and others’ welfare and what their choices signal to themselves and others about their moral character. Dr. Small’s research focuses on prosocial behavior, moral judgments, emotions, and consumer choice.
Min Tian (“What Cookie-Based Advertising Effectiveness Fails to Measure”) is an assistant professor at the Ohio State University. She obtained her PhD in marketing from the University of Wisconsin–Madison. Her research focuses on how consumers respond to firm-initiated communications using advanced statistical and econometric methods. These communications occur in all stages of the customer purchase funnel, including consideration, purchase, and postpurchase consumption.
Michael Tsiros (“Unlimited Testing: Let’s Test Your Emails with AI”) is Centennial Endowed Chair and Professor of Marketing at the Miami Herbert Business School, University of Miami. He received his PhD from Temple University. His research covers topics in consumer decision making, numeracy, and price promotions and has been published in the Journal of Marketing Research, Journal of Consumer Research, Journal of Marketing, Marketing Science, etc. He serves as an associate editor at Journal of Marketing Research.
Dana Turjeman (“When the Data Are Out: Measuring Behavioral Changes Following a Data Breach”) is an assistant professor of marketing and data science at the Arison School of Business, Reichman University. She holds a BSc in computer science, an MBA from The Hebrew University and a PhD in quantitative marketing from the Ross School of Business, University of Michigan. She was previously a software engineer and a technical team lead at Intel Corporation. Dr. Turjeman’s research examines privacy aspects in customer behavior, such as reactions to data breaches, privacy risks, and privacy controls, as well as development of privacy protection methods to assist in protecting customer data. She integrates and develops methodologies in causal inference, statistics, computer science, and psychology in order to understand and improve human behavior in privacy settings.
Naufel Vilcassim (“Frontiers: Breaking the Glass Ceiling: Empowering Female Entrepreneurs Through Female Mentors”) is an expert in the use of economic theory and econometric techniques to analyze substantive marketing problems. Currently, he is undertaking research, using RCTs that examine the role of managerial capital and access to business information tools in enhancing the business performance among growth-oriented microentrepreneurs in Africa (Uganda and Rwanda).
Qiyuan Wang (“For-Sale-by-Owner Platforms and Intermediation Pricing: Evidence from a Natural Experiment”) is an assistant professor of marketing in the faculty of business at the Hong Kong Polytechnic University. He received his PhD in marketing from Sauder School of Business, University of British Columbia, and BA in management from Wuhan University. His research focuses on digital platforms and marketing analytics.
Xi Xiong (“Advertising as Information for Ranking E-Commerce Search Listings”) is a data scientist from JD.com. Her work and research focus on search, recommendation systems, and online experimentation, in which she adopts causal inference methodologies to measure and continuously improve user experiences. She is currently leading a data science team for Tiktok’s global e-commerce risk and fraud.
Joonhyuk Yang (“Advertising as Information for Ranking E-Commerce Search Listings”) is an assistant professor of marketing at the Mendoza College of Business, University of Notre Dame. His research interests are at the intersection of marketing and technology. He currently focuses on topics related to the digital economy, such as platforms, advertising, and artificial intelligence/machine learning applications to managerial and policy questions.
Bo Zhou (“Rejoinder on “Competing for Recommendations: The Strategic Impact of Personalized Product Recommendations in Online Marketplaces””) is an associate professor of marketing at the University of Maryland, College Park. He received his PhD in marketing from Duke University. He was recognized as a Marketing Science Institute Young Scholar in 2019 and was a finalist of the John D. C. Little Best Paper Award in 2017.
Tianxin Zou (“Rejoinder on “Competing for Recommendations: The Strategic Impact of Personalized Product Recommendations in Online Marketplaces””) is an assistant professor of marketing at Warrington College of Business, University of Florida. He received his PhD in marketing from Washington University in St. Louis. He was the winner of the 2022 AMA-MRSIG Don Lehmann Award.
