Daniel Seifert
Supply chain management is widely accepted as a means for companies to gain competitive advantage. While product and information flows have been widely covered in the literature, relatively little attention has been paid to the management of a supply chain's finances. The objective of this dissertation, therefore, is to add to the emerging literature on financial flows. One inroad to researching financial flows in supply chains is to build on finance theory. Research in finance has analyzed financial flows from a credit point of view. Although researchers have identified more than ten motives for why firms offer and demand trade credit, a comprehensive review of this literature is missing. Following an introduction in Chapter 1, we therefore review this literature in Chapter 2 of this dissertation. We find that two explanations for the existence of trade credit receive broad support. Suppliers offer trade credit to increase product sales. Buyers demand trade credit to circumvent credit rationing. Following the review, we develop a detailed agenda for future research. We find that the relevant operations management literature builds only on a fraction of the insights from the finance literature and propose in-depth studies of capital access, transaction pooling, and control protection as promising areas for future research. Another way to researching financial flows in the context of supply chains is to leverage the methodological richness of the finance domain. In Chapter 3, we therefore investigate optimal financial flows by analyzing secondary data through multivariate regression. To test our hypotheses, we compile panel data on 3,383 groups of public United States firms from three databases. One of these databases is Revere Relationships, a relatively novel database on commercial relations. We find that our data are consistent with the causal relations and theoretical predictions of the operations management literature. Firm profitability is positively associated with payment delay. Payment delay, in turn, is positively associated with the capital cost difference between buyer and supplier and negatively associated with the price elasticity of demand and the deterioration rate of inventory. However, we do not observe any significant interactions between these factors, which raises a number of questions for future research. Another well established methodology in the finance domain is the analysis of stock market reactions to corporate events. Supply chain researchers have used this methodology to analyze the effect of corporate events such as product introduction delays, total quality management implementations, and supply chain disruptions. However, despite the fact that supply chain management is concerned with connected entities, these studies have mainly focused on single firms. In Chapter 4, we therefore study the shareholder value loss associated with disruption announcements across suppliers, customers, and rivals. Our event study finds that suppliers experience -1.24%, customers -0.07%, and rivals -0.19% abnormal stock market returns over a two-day period when firms announce supply chain disruptions. We also implement cross-sectional regression to test several hypotheses. For suppliers, dependence on the disruption announcing firm aggravates the effect. The substitutability of the disruption announcing firm, however, seems to be irrelevant in both the suppliers' and the customers' case. To facilitate the adoption of our results by practicing managers, we consolidate the previously generated insights and propose three trade credit strategies ("win-win", "follow", and "squeeze") and a decision tree in Chapter 5. Furthermore, we highlight an innovative example of a win-win strategy (reverse factoring) and examine it through a survey of 213 finance and operations managers. On average, we find that companies that use reverse factoring benefit from a reduction in working capital of 13%. The same managers report that suppliers benefit, too, by reducing working capital by 14%. However, we find that three factors distinguish successful from less successful implementations – choosing the right banking partner, ensuring CEO sponsorship, and involving at least 60% of the supply base. We complete the dissertation with a conclusion in Chapter 6.
EPFL2010
