Executive Summary
As products grow more complex, understanding consumer preferences among numerous attributes is a critical task for marketers. The authors develop a Web-based upgrading method for eliciting consumer preferences for complex products. The method builds on upgrading, a real-life task with which most people are familiar. Respondents under this method will upgrade from a “bare-bones” product, one attribute at a time, to a most-preferred configuration, given a budget constraint. The task is incentive-aligned to ensure that researchers obtain the true amount that the respondents are willing to pay for a given product upgrade. The authors improve the benchmark self-explicated approach, which directly asks people about their preferences.
To test the validity of the upgrading method empirically, they conduct a within-subject experiment that compares the upgrading method and the self-explicated approach (the state-of-the-art method used for complex products) using digital cameras (with 11 attributes and 60 levels in all). Each of 88 study participants completed a self-explicated task, an upgrading task, an external validity task, and a brief survey.
The preference structure uncovered in the Web-based upgrading method has superior external validity to that uncovered in the self-explicated method. Specifically, the upgrading method leads to significantly better predictive performance: The percentage of matches between the actual choices (from the external validity task) and the top predicted option were 42% for the upgrading method versus 27% for the self-explicated method, compared with the baseline prediction of 6% in a naive model (i.e., random selection of 1 in 17 choices).
The upgrading method also takes less time to complete than the self-explicated approach, and respondents appeared to enjoy the upgrading method more than the self-explicated approach and were much more involved. Overall, this study provides strong empirical evidences for the validity and managerial usefulness of the proposed upgrading method in understanding preferences for complex products.
Biography
Young-Hoon Park is Assistant Professor of Marketing in the Johnson Graduate School of Management at Cornell University. He earned a PhD in Marketing from the Wharton School of Business at the University of Pennsylvania. His research interests focus on customer value analysis, database marketing, online auctions, and marketing–operations interfaces. His research has appeared in leading marketing journals, such as Journal of Marketing Research, Management Science, and Marketing Science, among others. He currently serves on the editorial board of Marketing Science.
Min Ding is Associate Professor of Marketing in the Smeal College of Business at Pennsylvania State University. He received his PhD in Molecular, Cellular, and Developmental Biology from Ohio State University and PhD in Marketing from Wharton School of Business at University of Pennsylvania. His current research includes designing incentive-aligned data collection methods, product development in high-risk/high-reward industries (e.g., pharmaceutical), and arational decision theory (e.g., theory of intraperson games). His work has appeared in journals such as Journal of Marketing Research, Management Science, and Journal of Marketing, among others.
Vithala R. Rao is Deane Malott Professor of Management and Professor of Marketing and Quantitative Methods in the Johnson Graduate School of Management at Cornell University. He received his PhD in Applied Economics/Marketing from the Wharton School of Business at the University of Pennsylvania. He has published more than 100 articles on several topics including conjoint analysis and multidimensional scaling, promotions, pricing, market structure, and brand equity. His current work focuses on bundle design and pricing, preannouncement strategies, and the link between branding strategies to financial performance. His research has been published in Journal of Marketing Research, Journal of Marketing, Journal of Consumer Research, Management Science, Marketing Letters, International Journal of Research in Marketing, and Marketing Science. He is the coauthor of four books: Applied Multidimensional Scaling, Decision Criteria for New Product Acceptance and Success, New Science of Marketing, and Analysis for Strategic Marketing. He is a member of the editorial boards of various marketing journals.
J Marketing Research, Volume 45, Number 5, October 2008
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