The Bright Side of Price Volatility in Global Commodity Procurement

Author:

Xing Wei1ORCID,Liu Liming2ORCID,Zhang Fuqiang3ORCID,Zhao Qian4ORCID

Affiliation:

1. School of Economics and Management, China University of Petroleum (Huadong), Qingdao 266580, China;

2. School of Business, Southern University of Science and Technology, Shenzhen 518005, China;

3. Olin Business School, Washington University in St. Louis, St. Louis, Missouri 63130;

4. Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia, 42122 Reggio Emilia, Italy

Abstract

This paper studies two competing firms’ choices between the contingent-price contract (CPC) and fixed-price contract (FPC) in global commodity procurement. The FPC price is determined when signing the contract, whereas the CPC price is pegged to an underlying index and remains open until the delivery date. Under both contracts, each firm determines its order quantity based on the updated belief about the market demand. The unrealized CPC price correlates with the market demand, allowing a firm to update its belief about the CPC price using demand information, thereby generating a price-learning effect. We find that, contrary to conventional wisdom, a larger price volatility could benefit the firms, and, under differentiated contracts, a firm might benefit from the improvement of forecast accuracy at its rival. We further show that the price-learning effect plays a critical role in the firms’ contract choices. First, significant price volatility forces the firms to pursue the responsiveness of the CPC. Second, the firms may adopt differentiated contracts to enhance their responses to market changes and dampen competition, and a higher competition intensity more likely leads to contract differentiation. Third, the firms in a small market seek responsiveness and contract differentiation rather than cost efficiency. This study reveals the bright side of price volatility and takes a step toward understanding the effect of two-dimensional information updating. This paper was accepted by Jeannette Song, operations management. Funding: This work was supported in part by the National Natural Science Foundation of China [W. Xing was supported by Grant 72071210, L. Liu was supported by Grant 72371122, and F. Zhang was supported by Grants 71929201 and 72131004]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.00304 .

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

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