شبکه های زنجیره تامین با ریسک های مالی و اعتبارات تجاری تحت عدم قطعیت اقتصادی

The focus of this paper is to provide an analytical framework which can be used to investigate how financial risks affect the values of interconnected supply chain firms from a network perspective, and how financial risks affect the supply chain firms' profitability as well as the cash and credit transactions. In particular, we develop a variational inequality equilibrium model in conjunction with capital asset pricing model (CAPM) and the net present value (NPV) to determine the optimal supply chain prices, profits, and implicit equity values of supply chain firms under financial risks and economic uncertainty. We illustrate the analytical framework with computational studies which yield interesting managerial implications to the following questions: (1) How do financial risks and economic uncertainty affect the values of interconnected supply chain firms from a network perspective? (2) How do financial risks and economic uncertainty affect the supply chain firms' profitability as well as the cash and credit transactions? (3) How does the effect of financial risks change under different competition scenarios?

Supply chains have become complex global networks where suppliers, manufacturers, distributors, and retailers are highly interconnected through material/product flows, information flows, and financial flows (Coyle et al., 2008). Such complex network systems are vulnerable to various risks, among which financial risk has become increasingly prominent and critical since the global financial and economic meltdown in 2007. For example, Circuit City, once the second largest U.S. electronics retailer, filed bankruptcy and liquidated all its retail stores in 2009 after its suppliers had been concerned about its financial situation and refused to extend trade credits (Church and Clothier, 2009). For another example, approximately 670,000 suppliers closed across China in 2009 due to insufficient demands, delayed payments, and tight credit markets (Fenton, 2009). A recent global survey conducted by McKinsey Quarterly reported that the financial volatility is among the top three risk factors that concern the supply chain managers (McKinsey & Company, 2008). It is now a business imperative for the managers to reconsider their strategies and reevaluate the values of their supply chain partners as well as their own businesses under financial and economic uncertainty. Note that the nature of the problem requires one to consider the financial risks of the highly interconnected supply chain firms from a network perspective. The main contribution of this paper is to use a novel approach that merges the theory in corporate finance and network equilibrium analysis to provide a modeling framework where inter-firm financial relationships are reflected in network connections. The model proposed in this paper allows one to investigate how financial risks affect the values of interconnected firms in supply chain networks, and how financial risks affect the supply chain firms' profitability as well as the cash and credit transactions. The interface between supply chain management and finance is an emerging research area that has drawn increasing attentions from researchers. Applequist et al. (2000) proposed a new method to evaluate the risk and uncertainty of chemical manufacturing supply chains where the authors utilized the capital asset pricing model (CAPM) to construct the benchmark risk premium for facility investment decisions. In our paper CAPM will also be used to construct the risk premiums for the cash flows from supply chain partners. We also use the net present value (NPV) method to estimate the value of the cash flows under risks. Net present value (NPV) is a standard method in corporation finance to compute the benefit of a project over time and under risk. The NPV method has been widely adopted in supply chain management to analyze various problems. For example, Sun and Queyranne (2002) developed a multiproduct, multistage production and inventory model where the net present value of the total cost was optimized. Yang et al. (2005) proposed a mixed inventory model with variable lead times based on the NPV method. For more applications of the NPV method in supply chain management, see Wee and Law (2001), Chung et al. (1998) and Moon and Yun (1993). A number of studies have focused on the utilization of trade credit in supply chains. Ho et al. (2008) presented an integrated supplier–buyer inventory model where they assumed that the market demand is sensitive to the retail price and the supplier uses a trade credit policy. The authors investigated the optimal pricing, shipment and inventory policy for the problem. Huang and Hsu (2008) investigated the retailer's inventory policy under two levels of trade credit. The authors allowed the retailer and the supplier to transact through either partial or full trade credit. For more studies regarding trade credit in supply chains, see Thangam and Uthayakumar (2010) and Jaber and Osman (2006). These papers primarily focused on the optimal trade credit policy of one or two supply chain firms. Our paper, on the other hand, investigates how cash and trade credit transactions in supply chain networks are influenced by financial risks and economic uncertainty. Cruz et al. (2006) focused on the risk management and financial engineering of integrated global supply chain networks and social networks. The authors modeled the dynamic co-evolution of the product transactions, the product prices, and the relationship levels on the supernetwork until an equilibrium pattern is achieved. Liu and Nagurney (2007) established supernetwork equivalence between transportation networks and financial networks under the mean-variance framework. Our research differs from the above mentioned studies in that we take an innovative approach which merges the theory in corporate finance into network equilibrium modeling to incorporate financial risks into business connections among firms in supply chain networks. To our knowledge, this is the first network model that analyzes the equilibrium among heterogeneous firms in supply chain networks with a focus on the financial values and risks of supply chain relationships under economic uncertainty. In particular, we utilize our model to investigate the following questions: 1. How do financial risks and economic uncertainty affect the values of interconnected supply chain firms from a network perspective? 2. How do financial risks and economic uncertainty affect the supply chain firms' profitability as well as the cash and credit transactions? 3. How does the effect of financial risks change under different competition scenarios? Our results show that in equilibrium, a supplier's marginal profit received from a manufacturer with lower sensitivity to economic uncertainty is lower than that from a manufacturer with higher sensitivity; and a supplier's marginal profit received from a manufacturer with higher growth potential is lower than that from a manufacturer with lower growth potential. Such results suggest that suppliers be willing to sacrifice some profits to gain more businesses from manufacturers with lower financial risks or with higher growth potential. We also find that firms with lower financial risk and lower sensitivity to economic uncertainty are more valuable from their suppliers' perspective since these firms are more likely to generate steady revenue streams for the suppliers during economic downturns. The firms with lower financial risks may get better discount in term of purchasing prices which will help them lower costs and gain higher demand in the competition. As a result, such firms may have higher profits than the firms with higher financial risks. In addition, as the economic uncertainty increases, the values of suppliers' implicit equity stakes in the buyer firms will decline. However, the gap between the values of firms with lower and higher financial risks will become wider which will make the firms with lower financial risks more competitive and more profitable. Moreover, our results show that as the economic growth or inflation rate increases, the values of suppliers' implicit equity stakes in the buyer firms will decline. The higher rate of growth or inflation will reduce the gap between the values of firms with different levels of financial risks, which will make the competitive advantage of the firms with lower financial risks become smaller. Finally, we find that competition will enlarge the gap between the manufacturers' implicit equity values perceived by the suppliers, which will further increase the profit of the manufacturer with lower financial risk, and will further decrease the profit of the manufacturer with higher financial risk. This paper is organized as follows: In Section 2, we develop the supply chain network model with corporate financial risks and trade credits. We model heterogenous decision-makers in supply chain networks, and construct the equilibrium conditions, along with the variational inequality formulation. We also provide some interesting analytical results. In Section 3, we provide the model's qualitative properties, and propose a computational procedure. In Section 4, we present a series of computational examples to study the impacts of financial risk and economic uncertainty on the values, profits, and decisions of supply chain firms from a network perspective. Section 5 highlights the managerial insights and concludes the paper.

This paper studied the impact of corporate financial risk and economic uncertainty on the values, profits, and decisions of supply chains from a network perspective. In particular, we developed a variational inequality model that considers heterogenous supply chain firms' decision-making and solves the equilibrium of the supply chain network. We also proved interesting analytical results, provided important qualitative properties for the model, and presented an algorithm that was guaranteed to converge. We then utilized a series of computational examples to answer three interesting questions regarding supply chain firms' value, profitability and decision-making under economic risk. In particular we proved that in equilibrium, suppliers' marginal profits received from manufacturers with lower sensitivity to economic uncertainty are lower than those from manufacturers with higher sensitivity; and suppliers' marginal profits received from manufacturers with higher growth potential are lower than those from manufacturers with lower growth potential. Such results indicate that suppliers are willing to sacrifice some profit margins to gain more businesses from manufacturers with lower financial risk or with higher growth potential. We also find that firms with lower sensitivity to economic uncertainty are more valuable to the suppliers since these firms are more likely to generate steady revenue streams for the suppliers during economic downturns. Hence, the suppliers may offer the firms with lower financial risks better discounts in term of purchasing prices which will help these firms reduce their costs and gain higher market shares in the competition. As a result, firms with lower financial risks and lower sensitivities to the economy may have higher profits than the firms with higher financial risks. In addition, as the economic uncertainty increases, suppliers' implicit equity stakes in the buyer firms will decline. However, the difference between the values of firms with different levels of financial risks will become larger which will make the firms with lower financial risks more competitive and more profitable. Moreover, our results show that as the economic growth or inflation rate rises, suppliers' implicit equity stakes in the buyer firms will decline. A higher rate of growth or inflation will reduce the gap between the values of firms with lower and higher financial risks. Finally, we find that competition will enlarge the gap between the manufacturers' implicit equity values perceived by the suppliers, which will further increase the profit of the manufacturer with lower financial risk, and will further decrease the profit of the manufacturer with higher financial risk. Our results reveal important managerial insights for supply chain decision-makers under economic uncertainty. First, the suppliers should understand that the manufacturers who are less sensitive to the economic uncertainty or have greater growth potential are more valuable. Thus, the suppliers should offer deeper discounts or better trade credit terms to try to build up relationships and gain more businesses with these manufacturers. In addition, the suppliers should know that greater economic uncertainty will make such manufacturers relatively more valuable than the other manufacturers while higher inflation or economic growth rate may reduce the values of these firms. The manufacturers, in turn, should optimize their business strategies to lower their sensitivities to the economic uncertainty which will increase their values perceived by their upstream suppliers' and may help them get better prices. Moreover, the manufacturers with higher sensitivity to economic uncertainty should try to differentiate their products and reduce the competition. This research can be extended in several directions. First, the model can further incorporate exchange rate risk and supply disruption risk to study how these risks affect the decision-makers considered in this paper. Additionally, we can investigate how supply chain decisions influence corporate financial risks from a network perspective.