The Blockchain Newsvendor: Value of Freshness Transparency and Smart Contracts

Motivated by blockchain applications in the fresh produce industry, we consider a newsvendor problem in which a retailer faces stochastic and freshness-dependent consumer demand. The retailer can adopt blockchain technology to have more transparent information on the freshness of supply. We quantify the value of blockchain-enabled freshness transparency by deriving closed-form expressions for the retailer’s expected profit growth and food waste reduction brought by blockchain adoption. Using publicly available data, we provide a numerical example illustrating that for Walmart’s strawberry business in the United States (which is about only 4% of Walmart’s fresh produce sales), blockchain can increase annual profit by [Formula: see text] million while eliminating 23 million pounds of food waste annually through operational improvements. Despite this substantial value for the retailer, blockchain adoption can decrease the expected profit of the retailer’s supplier. We design a family of threshold-type smart contracts contingent on a blockchain-based freshness consensus and examine when such contracts offer a win-win proposition to the retailer and the supplier. Moreover, when the retailer offers freshness-based price discounts, we find that less fresh supply leads to less food waste. In contrast, when the supplier adjusts the wholesale price based on freshness, less fresh supply causes more food waste. We also generalize our findings to the cases of (i) dual sourcing, (ii) noisy measurements in the Internet of Things sensors feeding data into blockchain, and (iii) the retailer’s culling processes. This paper was accepted by David Simchi-Levi, operations management. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.02949 .

• 저널Management Science · 71(8) · 6666–6682
• 토픽Blockchain Technology Applications and Security · Information Systems
• DOI10.1287/mnsc.2021.02949
• 저자N. Bora Keskin, Chenghuai Li, Jing‐Sheng Song