Assessment of uncertainty in bid arrival times: A Bayesian mixture model. Issue 11 (2nd November 2021)

• Record Type: Journal Article
• Authors: Zafari, Babak; Soyer, Refik
• Is Part Of: Journal of the Operational Research Society. Volume 72:Issue 11(2021)
• Page Start: 2517
• Page End: 2528
• Publication Date: 2021-11-02
• Subjects: Arrival time modeling -- auction segmentation -- mixture modeling -- beta regression -- Bayesian model comparison -- risk management; Operations research -- Periodicals; 658.4034
• DOI: 10.1080/01605682.2020.1796539
• Languages: English
• ISSNs: 0160-5682

Abstract

Abstract: In this paper, we propose a Bayesian approach to model uncertainty in the bid arrival time by focusing on the time of the first bid in secondary (retail) market online business-to-business auctions. The proposed model is based on a Bayesian finite mixture of beta distributions. Our main objectives is to study potential heterogeneity of different auctions. In doing so, we incorporate some auction-specific features into the model and analyze their effect on the first bid time. We consider multiple competing models both in terms of fit and predictive performance. We also discuss managerial implications of the study and suggest how auctioneers can benefit from both the explanatory and predictive aspects of the model.