Trade Credit and Customer Portfolio Approach to Managing Cash Flow Variability

Nikolay Osadchiy (), William Schmidt () and Jing Wu ()
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Nikolay Osadchiy: Goizueta Business School, Emory University, Atlanta, Georgia 30322
William Schmidt: Goizueta Business School, Emory University, Atlanta, Georgia 30322
Jing Wu: CUHK Business School, The Chinese University of Hong Kong, Hong Kong

Manufacturing & Service Operations Management, 2025, vol. 27, issue 3, 935-954

Abstract: Problem definition : Cash flow variability is driven by operational decisions and influences operating performance and valuation. Despite this and the early role that operations management scholarship had on cash flow management theory, the prevailing approaches for managing cash flow variability focus on financial remedies. Our research extends this set of remedies by proposing customer portfolio management and selective trade credit as operational hedges for reducing cash flow variability. Methodology/results : We empirically validate our proposal by studying a causal relationship between new customer acquisitions and cash-flow variability using a large database of customer-supplier relationships that we join with quarterly financial reports. We strengthen the inferences from this analysis by assembling random samples of customers for each firm in our study and show that the firms’ actual customer portfolios yield lower cash variability compared with the counterfactual sets of randomly sampled customers. Using aggregate and link-level trade credit data, we show that trade credit harmonization is associated with reduced cash flow variability. Managerial implications : Our analysis shows that firms can reduce their cash variability by (i) pursuing customers with desirable order patterns that offset the cash flow variability from serving legacy customers and (ii) selectively offering customers trade credit that harmonizes payment terms in the customer portfolio.

Keywords: cash flow variability; supply networks; customer portfolio; trade credit; large language model (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormsom:v:27:y:2025:i:3:p:935-954

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