This book deals with decision making in environments of significant data un certainty, with particular emphasis on operations and production management applications. For such environments, we suggest the use of the robustness ap proach to decision making, which assumes inadequate knowledge of the decision maker about the random state of nature and develops a decision that hedges against the worst contingency that may arise. The main motivating factors for a decision maker to use the robustness approach are: * It does not ignore uncertainty and takes a proactive step in response to the fact that forecasted values of uncertain parameters will not occur in most environments; * It applies to decisions of unique, non-repetitive nature, which are common in many fast and dynamically changing environments; * It accounts for the risk averse nature of decision makers; and * It recognizes that even though decision environments are fraught with data uncertainties, decisions are evaluated ex post with the realized data. For all of the above reasons, robust decisions are dear to the heart of opera tional decision makers. This book takes a giant first step in presenting decision support tools and solution methods for generating robust decisions in a variety of interesting application environments. Robust Discrete Optimization is a comprehensive mathematical programming framework for robust decision making.

This book deals with decision making in environments of significant data un certainty, with particular emphasis on operations and production management applications. For such environments, we suggest the use of the robustness ap proach to decision making, which assumes inadequate knowledge of the decision maker about the random state of nature and develops a decision that hedges against the worst contingency that may arise. The main motivating factors for a decision maker to use the robustness approach are: * It does not ignore uncertainty and takes a proactive step in response to the fact that forecasted values of uncertain parameters will not occur in most environments; * It applies to decisions of unique, non-repetitive nature, which are common in many fast and dynamically changing environments; * It accounts for the risk averse nature of decision makers; and * It recognizes that even though decision environments are fraught with data uncertainties, decisions are evaluated ex post with the realized data. For all of the above reasons, robust decisions are dear to the heart of opera tional decision makers. This book takes a giant first step in presenting decision support tools and solution methods for generating robust decisions in a variety of interesting application environments. Robust Discrete Optimization is a comprehensive mathematical programming framework for robust decision making.

This monograph contains six thought-leading contributions on various topics related to supply chain finance and risk management. The issue culminated out of a recent (May 14-16, 2021) mini-conference on "Supply Chain Finance & Risk Management" organized by The Boeing Center for Supply Chain Innovation (BCSCI), Olin Business School, Washington University in St. Louis. In "Quadratic Hedging and Optimization of Option Exercise Policies", Nicola Secomandi explores a model for optimizing option exercise policies under any given equivalent martingale measure and anchoring quadratic hedging to the resulting value of the policy. In "Operations Revenue Insurance", Paolo Guiotto, Andrea Roncoroni and Romeo Tedongap propose a new framework for the optimal design of a financial instrument to hedge nonclaimable risk embedded by business and operating revenues. In "Crowdfunding Adoption in the Presence of Word-of-Mouth Communication", Fasheng Xu, Xiaomeng Guo, Guang Xiao and Fuqiang Zhang investigate a firm's optimal funding choice when launching a product in the market with word-of-mouth communication. In "Data Sharing in Innovations", Zhi Chen and Jussi Keppo discuss how the success of data-driven products depends on a firm's access to big data and the challenges of data collection and sharing in innovations using the autonomous vehicle industry as an example. In "Coordination Problems in Platform Markets Under Uncertainty", Hamed Ghoddusi presents a dynamic coordination problem under uncertainty that is common in platform markets and provides novel insights on this problem between two sides of a platform under uncertainty. In "Value Games", Matthew J. Sobel shows that insights and algorithms based on sequential games with a profit criterion and negligible bankruptcy risk can be adapted to maximize value.

Supply Chain Finance focuses is on creating liquidity in the supply chain through various Buyer or Seller-led solutions with or without a facilitating technology. The role of supply chain finance (SCF) is to optimize both the availability and cost of capital within a given buyer-supplier supply chain. To add further value, information on the physical flow of goods can be monitored. The coupling of information enables lenders to mitigate financial risk within the supply chain. The mitigation of risk allows more capital to be raised, capital to be accessed sooner, or capital to be raised at lower rates. Supply chain participants reside in diverse economic environments, are of different sizes, face a variety of uncertainties, have different bargaining powers over its trading partners, and have different accessibilities to capital markets. Many forms of financing arrangements between buyers and suppliers have emerged intending to overcome challenges in their specific economic and business environments. Part 1 examines Supplier Financing. The three papers included in this section discuss supplier based financing issues including: motivation and rationale for supplier based financing, the optimal mix of bank financing and supplier financing, and empirical study of the impact of trade credit on firm performance. Part 2 focuses on Buyer Financing including three papers included that discuss buyer based financing issues in supply chains including the rationales of different types of buyer based financing arrangements and their impacts on supply chain performance. Part 3 reviews Inventory Models and Financing Consideration and the two papers in this part of the book explore how to coordinate the management of the cash flow and inventory flow within an organization and the relationship between a firm's inventory policy and its cost of capital. Part 4 examines Operational Investments and Financing Issues and includes four papers that address operational investments with explicit financing considerations.

Integrated Risk Management in Supply Chains examines supply chain risk management. The increased interest in the topic is due to a number of factors including the increased volatility of commodity prices and exchange rates, recent natural disasters, and the increased importance of multinational corporations. The motivation for risk management comes from a variety of sources: financial distress costs, managerial incentives, and other important reasons discussed in the remainder of this book. Understanding the motives is important because they provide insights into which risks should be managed and how a firm's risk management operations should be organized. The first part examines Buffering Supply Chain Risk with Operational Flexibility and deals with uncertainty in the form of routine variability, which includes fluctuations in demand. Part 2 reviews Supply Disruption. Both the preponderance of natural disasters and huge economic swings can cause extreme challenges across the supply chains. Although these types of risks are rare, they are highly consequential and buffering is insufficient to mitigate them. Instead, firms facing these risks must engage in contingency planning and must maintain redundancies in the system. This is why contingency planning is on the interface of operations and finance. Part 3 looks at Commodity Price Risks, which includes five papers on managing price risks - the first three papers are fundamental in that they ask when and how firms should manage price risks with hedging and how hedging affects operating policy and the remaining two papers examine the best practices in specific industries.

Emerging Technology & Advances in Supply Chain Finance & Risk Management reflects the state-of-the-art in research thought leadership in supply chain finance and risk management, and it contains great expository pieces on how advanced technologies are shaping supply chains and risk management within them. You will also find ideas on how supply chain finance and risk management can be best taught in our classrooms. The volume is divided into three parts, each part reflecting a major active research area of the field including: Part 1: Supply Chain Finance; Part 2: Financial Hedging and Commodity Risks; Part 3: Operational Strategies and Risk Management. Part 1 deals with the broad area of supply chain finance and programs that will better allow for working capital management within supply chains. Part 2 introduces concepts of hedging financial and operational risks due to uncertain commodity Prices, fluctuating exchange rates, and volatile interest rates. Emphasis is placed on understanding how financial hedges can be used for hedging relevant supply chain risks in a way that reflects modern view of financial risk management. Part 3 examines topics and solution approaches reflecting the more traditional treatments in the contemporary literature of operational and supply chain risks. This volume provides rich implications for future research directions in efforts to master the new complexities and uncertainties of the global business environment and better understand the impact of advanced technologies in global supply chains.

Advances in Supply Chain Finance and FinTech Innovations examines three themes: Financing Issues in Supply Chains look into popular working capital management financing practices: trade credits and guarantor practices including advanced trade credit practices in supply chains, guarantor financing practices for capital constrained retailers, and innovative practices of joint financing of capital constrained firms by a bank. FinTech Innovations for Supply Chains examines business model innovations for supply chain financing supported through new platform technologies (such as blockchain), and simple financial technologies effectively implemented for high impact in supply chain risk management. Advances in Risk Management of Operational Systems provide state-of-the art thinking on many risk issues in supply chain operations including disruption strategies over the product life cycle, the production planning complexities for a capital constrained manufacturer that uses Inventory Based Financing (IBF) scheme to fund its working capital needs, capacity procurement decision, capacity planning in the presence of demand and price uncertainty, and valuing complex real options in dynamic operational settings.