Publication Type
Journal Article
Version
submittedVersion
Publication Date
1-2019
Abstract
Online entertainment shopping, normally supported by the pay-to-bid auction mechanism, represents an innovative business model in e-commerce. Because the unique selling mechanism combines features of shopping and online auction, consumers expect both monetary return and entertainment value from their participation. We propose a dynamic structural model to analyze consumer behaviors on entertainment shopping websites. The model captures the consumer learning process, based both on individual participation experiences and also on observational learning of historical auction information. We estimate the model using a large data set from an online entertainment shopping website. Results show that consumers’ initial participation incentives mainly come from a significant overestimation of the entertainment value and an obvious underestimation of the auction competition. Both types of learning contribute to a general decreasing participation trend among consumers over time. Our model provides both a theoretical explanation and empirical evidence of the consumer churn issue. It further identifies two groups of consumers with different risk characteristics: One group is risk-averse and quits using the website before effective learning takes place, while the other group exhibits risk-seeking behavior and overly commits to the auction games. Based on the estimated parameters of the model, we perform counterfactual analyses to evaluate the effects of policy changes on consumers’ participation behaviors. We discuss several important design implications and recommend strategies for building a sustainable business model in the entertainment shopping industry.
Keywords
Bayesian statistics, Consumer learning, Dynamic structural model, Maximum likelihood estimation, Pay-to-bid auction
Discipline
Databases and Information Systems | E-Commerce
Research Areas
Information Systems and Management
Publication
Journal of the Association for Information Systems
Volume
20
Issue
4
First Page
285
Last Page
316
ISSN
1536-9323
Identifier
10.17705/1.jais.00536
Publisher
Association for Information Systems
Citation
LI, Jin; GUO, Zhiling; and TSO, Geoffrey K.F..
An economic analysis of consumer learning on entertainment shopping websites. (2019). Journal of the Association for Information Systems. 20, (4), 285-316.
Available at: https://ink.library.smu.edu.sg/sis_research/4404
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://aisel.aisnet.org/jais/vol20/iss4/6/
Comments
https://doi.org/10.17705/1.jais.00536