Advance Selling Strategy with Return Service: The Impacts of Information Disclosure and Disclosure Methods

Yajing Wang (), Jian Li, Shichao Zhu () and Pei Quan ()
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Yajing Wang: School of Economic and Management, Beijing University of Technology, Beijing 100124, P. R. China
Jian Li: School of Economic and Management, Beijing University of Technology, Beijing 100124, P. R. China
Shichao Zhu: School of Economic and Management, Beijing University of Technology, Beijing 100124, P. R. China
Pei Quan: School of Economic and Management, Beijing University of Technology, Beijing 100124, P. R. China

Asia-Pacific Journal of Operational Research (APJOR), 2024, vol. 41, issue 04, 1-31

Abstract: The return cost burdens both consumers and merchants, leading merchants to emphasize information disclosure during pre-sales of new products. This study analyzes the effects of information disclosure methods on consumer valuation and merchants’ pre-sale strategies across four scenarios: no advance selling, no information disclosure, traditional information disclosure, and blockchain-enabled information disclosure. We examine optimal pricing and inventory strategies under each scenario, assessing the value of information disclosure and the merchant’s optimal advance selling strategy. We find that traditional information disclosure could lead to various pre-sale pricing outcomes based on consumer valuation distribution bounds, trust levels, and merchant return losses. Blockchain-based disclosure influences merchants to implement premium pricing, which may render blockchain unnecessary. Offering pre-orders is beneficial with any information disclosure method. If consumers have varied product understandings, merchants benefit more from using an information disclosure strategy rather than just offering returns; otherwise, the reverse is true. The paper provides theoretical insights into optimal pre-sale information disclosure practices.

Keywords: Online advance selling; information disclosure; blockchain; return services; pricing and inventory decisions (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0217595924400098

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