OPERATIONS, TECHNOLOGY, AND INFORMATION MANAGEMENT


Optimal Cash Management


with Payables Finance Operations Research, 72, 5, September-October 2024 LINK TO PAPER LINK TO LI CHEN VIDEO


LI CHEN


EMERSON PROFESSOR OF MANUFACTURING MANAGEMENT


Samuel Curtis Johnson Graduate School of Management


Cornell SC Johnson College of Business Cornell University


Co-authors • Li Chen


Emerson Professor of Manufacturing Management, Samuel Curtis


Johnson Graduate School of Management, Cornell SC Johnson College of Business, Cornell University


• Xiaoyue Yan, Lindquist College of Business, University of Oregon • Xiaobo Ding, Matrix Analytics Corporation, New York


Summary Te recent adoption of technology has the potential to make payables finance


more efficient and secure. Payables finance, also known as reverse factoring or supply chain finance, is a form of trade finance arrangement that provides a supplier with the option to receive a buyer’s payables early while allowing the buyer to extend its payment due date. A recent McKinsey report projected a broader adoption of payables finance in industry, with an estimated $2 trillion in readily financeable payables in supply chains. For example, Dow Chemical Company has recently claimed its use of payables finance for the first time on March 31, 2023, with confirmed outstanding obligations of $290 million.


In this paper, the authors study the supplier’s optimal cash policy under such a “frictionless” payables finance arrangement by extending the classic cash flow management literature in four fronts. Tey conclude that the optimal cash policy possesses the “non-borrow-up-to” and “non-invest-down-to” features that differ from the classic policy known in the literature. Further, they quanti- fy the value of payables finance to the supplier and determine the equilibrium payment term extension for the buyer. Value to the supplier is generated by the cash liquidity enabled by payables finance to hedge against cash flow uncer- tainty. To tackle the computational challenge of the problem, the authors de- rive easy-to-compute heuristic policies and system bounds with near-optimal performance, and they apply their model to data sets obtained from a major U.S. chemical company.


CONTENTS TO MAIN


| RESEARCH WITH IMPACT: CORNELL SC JOHNSON COLLEGE OF BUSINESS • 2024 EDITION


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