Abstract
PurposeThe purpose of this paper is to conduct a large-sample empirical investigation of how relational capital impacts bullwhip at the supplier.Design/methodology/approachThe study uses mandatory disclosures in regulatory filings of US firms to identify a supplier’s major customers and constructs empirical proxies of supply chain relational capital, i.e., length of the relationship between suppliers and customers and partner interdependence. Multivariate regression analyses are performed to examine the effects of relational capital on bullwhip at the supplier.FindingsThe findings show that bullwhip at the supplier is greater when customers are more dependent on their suppliers, but is reduced when suppliers share longer relationships with their customers. The results also provide additional insights on several firm characteristics that impact supplier bullwhip, including shocks in order backlog, selling intensity and variations in profit margins. Furthermore, the authors document that the effect of supply chain relationships on bullwhip tends to vary across industries and over time.Originality/valueThe study employs a novel data set that is constructed using firms’ financial disclosures. This large panel data set consisting of 13,993 observations over 36 years enables thorough and robust analyses to characterize supply chain relationships and gain a deeper understanding of their impact on bullwhip.
Highlights
The bullwhip effect (BWE) is considered to be a key phenomenon in supply chain management
The above contrasting views present an interesting empirical question about the net effect of relational capital on BWE that we investigate in this study
Consistent with hypothesis H2, we present our set of two-sided hypotheses as follows: Hypothesis (H3a): The dependence of a supplier on its customers has a negative impact on supplier bullwhip
Summary
The bullwhip effect (BWE) is considered to be a key phenomenon in supply chain management. The principal notion of BWE is that demand variability increases as one moves upstream in a supply chain This can cause several inefficiencies for the upstream supplier including poor forecasting, stockouts, high inventory, lower service levels, capacity planning issues, higher costs, and increased supply chain risk (Metters, 1997; Billington, 2010). The importance of this problem has prompted extensive research since the early works of Simon (1952) and Forrester (1958) using theoretical frameworks as well as experimental settings (Kahn, 1987; Sterman, 1989; Metters, 1997; Lee et al, 1997a, 1997b; and more recently Cao et al, 2017, to name a few).. The costs and inefficiencies linked to BWE underscore the importance of understanding influential factors that might help mitigate the BWE, an effect that previous studies have shown to exist globally
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