EconPapers    
Economics at your fingertips  
 

Managing product value uncertainty: The role of ex ante product value delivery

Zhe Yin and Yujia Fu

Journal of the Operational Research Society, 2022, vol. 73, issue 5, 1053-1072

Abstract: This study investigates how online retailers should solve the problem of product value uncertainty through an ex ante product value delivery policy. We construct an endogenous matching probability model depending on the ex ante strategic choice among various product value delivery measures, such as displaying product information online, opening product reviews, building a virtual showroom, and building a physical showroom. This model is different from the exogenous matching probability assumption in the literature. When the matching probability is exogenously given, the retail price reduction policy is commonly used to mitigate product value uncertainty. In contrast, when retailers can determine the matching probability through the ex ante strategic choice for the product value delivery measures, increasing the retail price to rely more on ex ante value delivery may be optimal in the mitigation of a more serious product value uncertainty. In addition, we examine the interaction between the ex ante product value delivery and the ex post return policy. The results show that the adoption of the ex post mitigation policy may encourage or discourage the adoption of the ex ante mitigation policy depending on the cost input for product value delivery and the customers’ surplus loss caused by a mismatch.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/01605682.2021.1892461 (text/html)
Access to full text is restricted to subscribers.

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:taf:tjorxx:v:73:y:2022:i:5:p:1053-1072

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjor20

DOI: 10.1080/01605682.2021.1892461

Access Statistics for this article

Journal of the Operational Research Society is currently edited by Tom Archibald

More articles in Journal of the Operational Research Society from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:tjorxx:v:73:y:2022:i:5:p:1053-1072