Find us on Facebook Find us on LinkedIn Follow us on Twitter Subscribe to our YouTube channel

Operations Management and Econometrics and Marketing

Incentive Aligned Data Collection

Professor Min Ding, Smeal College of Business The Pennsylvania State University

27th May 2011  11:00 am - MLR6, Merewether Building (H04)

Incentive alignment aims to motivate participants to reveal truthfully their preferences, and it has been used in a variety of contexts such as conjoint analysis (Ding, Grewal and Liechty 2005; Ding 2007). Incentive alignment also makes it more feasible for researchers/managers to design new data collection methods, and one of such new methods is discussed in this presentation. Extant preference measurement research, including conjoint analysis, is done in the isolation of one¹s own mind. That is, it remains completely silent on the explicit influence of others in the formation of consumer preferences. This paper proposes a holistic framework of preference, PIE, as well as a measurement method to remedy this problem. The new paradigm posits that consumers evaluate product attributes using (potentially) three perspectives which are determined by some combinations of the product¹s physical profile (P), the focal customer¹s idiosyncratic attributes (I), and an external target group¹s value system (E), the last factor allowing for influences from others. To provide an empirically feasible method to collect information consistent with this framework, we propose and test an incentive-aligned approach, a group-sourced mechanism, which mimics a real life consultation of a customer with her ³friends² in purchase decision making. The results provide support for the PIE framework, including superior predictive power.