A utility theoretic approach to determining optimal wait times in distributed information retrieval
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Design of a shopbot and recommender system for bundle purchases
Decision Support Systems
An Experimental and Analytical Study of On-Line Digital Music Sampling Strategies
International Journal of Electronic Commerce
Shopbot 2.0: Integrating recommendations and promotions with comparison shopping
Decision Support Systems
A Temporary Monopolist: Taking Advantage of Information Transparency on the Web
Journal of Management Information Systems
A Pooling Analysis of Two Simultaneous Online Auctions
Manufacturing & Service Operations Management
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Journal of Theoretical and Applied Electronic Commerce Research
Assessing Screening and Evaluation Decision Support Systems: A Resource-Matching Approach
Information Systems Research
Designing a cross-language comparison-shopping agent
Decision Support Systems
Optimizing queries to remote resources
Journal of Intelligent Information Systems
Usercentric Operational Decision Making in Distributed Information Retrieval
Information Systems Research
Comparison shopping agents and online price dispersion: a search cost based explanation
Journal of Theoretical and Applied Electronic Commerce Research
Online loyalty programs viewed from a searchability perspective
Proceedings of the 14th Annual International Conference on Electronic Commerce
Competitive Shopbots-Mediated Markets
ACM Transactions on Economics and Computation
Introducing spatial context in comparative pricing and product search
Proceedings of the Fifth International Conference on Management of Emergent Digital EcoSystems
Hi-index | 0.01 |
A primary tool that consumers have for comparative shopping is the shopbot, which is short for shopping robot. These shopbots automatically search a large number of vendors for price and availability. Typically a shopbot searches a predefined set of vendors and reports all results, which can result in time-consuming searches that provide redundant or dominated alternatives. Our research demonstrates analytically how shopbot designs can be improved by developing a utility model of consumer purchasing behavior. This utility model considers the intrinsic value of the product and its attributes, the disutility from waiting, and the cognitive costs associated with evaluating the offers retrieved. We focus on the operational decisions made by the shopbot: which stores to search, how long to wait, and which offers to present to the user. To illustrate our model we calibrate the model to price and response time data collected at online bookstores over a six-month period. Using prior expectations about price and response time, we show how shopbots can substantially increase consumer utility by searching more intelligently and then selectively presenting offers.