Supply chain cash-flow bullwhip effect: An analytical model for working capital variance propagation

Abstract

This research article probes the cash-flow bullwhip effect (CFB), a phenomenon precipitating an increase in the fluctuations of working capital within supply chains. A novel analytical model is proposed to delve into the CFB within a multi-echelon, serial supply chain, taking factors into account, such as demand autocorrelation, procurement lead time, and payment lead times. Our study implies that extended procurement lead times contribute to a heightened CFB, and a substantial discrepancy between a firm’s payment lead time and that of its customers results in a more pronounced CFB. Importantly, adopting shorter payment lead times for customers and extending them for suppliers can inflate the cash-flow bullwhip for all three constituent entities: the echelon, its customers, and suppliers. Our quantitative analysis reveals that strategies, such as payment batching and divulging end-customer demand information can mitigate the cash-flow bullwhip by as much as 49.5 and 53.7%, respectively. Empirical inspection of the CFB experienced by a sample of 786 companies from 2010 to 2019 demonstrates that ∼65% of these companies intensify their working capital variance. This underscores the need for cautious management of working capital variance and the adoption of suitable inventory and payment strategies to forestall financial turmoil within the supply chain.

Acknowledgments

We thank the anonymous reviewers for their valuable comments and suggestions, which helped to improve the quality of this manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Chintan Patil

Dr. Chintan Patil holds a dual-title Ph.D. in Industrial Engineering and Operations Research from The Pennsylvania State University, awarded in 2022. His doctoral research centered on investigating cash-flow bullwhip effects within supply chains. Currently, he serves as an Operations Research Scientist at Coupa Software’s Artificial Intelligence–Center of Excellence. In this capacity, he applies his expertise to contribute to developing innovative solutions in fraud detection.

Vittaldas V. Prabhu

Dr. Vittaldas V. Prabhu is Professor & Charles and Enid Schneider Faculty Chair in Service Enterprise Engineering in the Marcus Department of Industrial and Manufacturing Engineering at Penn State University. He works in the area of distributed control systems with a focus on manufacturing and service systems. He teaches courses in controls, manufacturing, retailing, and service systems. He got his Ph.D. in mechanical engineering from the University of Wisconsin-Madison.