A decision support framework for evaluating revenue performance in sequential purchase contexts
O. Cem Ozturk and
Selçuk Karabatı
European Journal of Operational Research, 2017, vol. 263, issue 3, 922-934
Abstract:
This paper studies the product ordering problem in sequential purchase contexts where sellers aim to maximize their revenue faced with budget constrained buyers. We propose a multi-layered decision support framework that combines empirical data with simulation, optimization, and econometric methods to address this problem. Our framework allows sellers to: (i) compare revenue performances of limited information sequencing strategies, (ii) quantify benchmark revenue levels that can be achieved via the optimal sequence based on detailed buyer information, (iii) determine the costs of limited information and strategic buyers to the seller, and (iv) identify the moderators of sequencing strategy performance. We illustrate our framework through two applications in a business-to-business used-car auction setting. Contrary to previous studies reporting practitioners’ tendency to sequence items from the lowest value to the highest, our results suggest that the best-performing limited information sequencing strategy depends on buyers’ bidding behavior. We also find that the revenue difference between the optimal sequence and a limited information sequencing strategy can be substantial. Our results show that a significant portion of this revenue difference is associated with the seller’s limited information on buyers’ budgets and product valuations. Our applications also provide various sensitivity analyses and develop new propositions on the moderators of the relationship between the seller’s revenue and sequencing strategies.
Keywords: Decision support systems; Multi-item sequential auctions; Optimization; Simulation (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221717305684
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:263:y:2017:i:3:p:922-934
DOI: 10.1016/j.ejor.2017.06.029
Access Statistics for this article
European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati
More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().