Supply chain coordination by risk sharing contracts under random production yield and deterministic demand

From a large body of research studies we know that properly designed contracts can facilitate coordinated decision making of multiple actors in a supply chain (SC) so that efficiency losses for the SC as a whole can be avoided. In a newsvendor-type SC with stochastic demand it is well-known that due to the double marginalization effect a simple wholesale price contract will not achieve coordination. More complex contracts, however, do so, especially those which enable an appropriate sharing of risks between the SC actors. While the effectiveness of risk sharing contracts is well understood for SC situations with random demand and reliable supply, we do not know much about respective SC coordination problems if demand is deterministic, but supply is unreliable due to random production yield

Coordination of Decentralized Supply Chains: A Literature Review

Due to the fact that the double margin exists in the decentralized supply chain, many papers focus on the coordination of decentralized supply chain. In this paper, we classify these papers into three parts according to the structure of supply chain. The first kind of supply chain consists of one upstream supplier and one downstream retailer. The second one consists of multiple suppliers and a single retailer. The last one refers to the supply chain with multiple suppliers and a single retailer. This paper can enable readers to get the knowledge of existing research on supply chain coordination. We also give some interesting future research concerning this topic

Supply chain coordination by risk sharing contracts under random production yield and deterministic demand

From a large body of research studies we know that properly designed contracts can facilitate coordinated decision making of multiple actors in a supply chain (SC) so that efficiency losses for the SC as a whole can be avoided. In a newsvendor-type SC with stochastic demand it is well-known that due to the double marginalization effect a simple wholesale price contract will not achieve coordination. More complex contracts, however, do so, especially those which enable an appropriate sharing of risks between the SC actors. While the effectiveness of risk sharing contracts is well understood for SC situations with random demand and reliable supply, we do not know much about respective SC coordination problems if demand is deterministic, but supply is unreliable due to random production yield. For a buyer-supplier SC representing the latter SC setting, it is analyzed how the distribution of risks affects the coordination of buyer's ordering and supplier's production decision. In a basic random yield, deterministic demand setting both parties are exposed to risks of over-production or underdelivery, respectively, if a simple wholesale price contract is applied. The resulting risk distribution will always be such that SC coordination cannot be achieved. It can be shown, however, that two more sophisticated contract types with penalty and reward elements for the supplier can change the risk distribution in such a way that SC coordination is possible under random yield. Additionally, it is proved that also the wholesale price contract will guarantee SC coordination if the supplier has a second (emergency) procurement source at her disposal that is more costly, but reliable. Moreover, restricting oneself to wholesale price contracts it is shown that it can be beneficial to both parties to utilize this emergency source even if it is not profitable from a SC perspective.Supply chain coordination, contracts, random yield, risk sharing, emergency procurement

Supply Chain Contracting in the Presence of Supply Uncertainty and Store Brand Competition

In today\u27s complex business environment, manufacturers are striving to maintain a competitive advantage over their supply chain partners. Manufacturers\u27 profitability is tightly linked to their strategic interactions with other entities in the supply chain. While numerous studies have been conducted to investigate such interactions in supply chains, certain issues remain unresolved. We apply a game-theoretic framework to analyze two distinct supply chain structures in the presence of supply uncertainty and store brand competition in two essays, respectively. In the first chapter, we study a decentralized assembly supply chain under supply uncertainty. In a decentralized assembly supply chain, one assembler assembles a set of $n$ components, each produced by a different supplier, into a final product to meet an uncertain market demand. Each supplier faces an uncertain production capacity such that only the lesser of the planned production quantity and the realized capacity can be delivered to the assembler. We assume that the suppliers\u27 random capacities and the random demand can follow an arbitrary continuous multivariate distribution. We formulate the problem as a two-stage Stackelberg game. The assembler and the suppliers adopt a so-called Vendor-Managed-Consigned-Inventory (VMCI) contract. We analytically characterize the equilibrium of this game, based on which we obtain several managerial insights. Surprisingly, we show that when a supplier\u27s production cost increases or when his component salvage value decreases, it hurts all other members and the entire supply chain, but it might sometimes benefit this particular supplier. Similarly, when the suppliers do not have supply uncertainty, it benefits the assembler but it does not necessarily benefit the suppliers. Furthermore, we demonstrate that when the suppliers\u27 capacities become more positively correlated, the assembler is always better off, but the suppliers might be better or worse off. Later in the chapter, we also solve the game under the conventional wholesale-price contract. We find that the assembler always prefers the VMCI contract, and the suppliers always prefer the wholesale price contract. In addition, we illustrate that the VMCI contract is more efficient than the wholesale price contract for this decentralized assembly supply chain. In the second chapter, we consider a two-tier decentralized supply chain with a national brand supplier and a retailer. The national brand supplier (she) distributes her products to consumers through the retailer. Meanwhile, the retailer (he) intends to develop and produce his own store brand through a manufacturing source that is different from the national brand supplier. The retailer holds the store brand production unit cost as private information, for which the national brand supplier only has a subjective assessment. Given a supply contract offered by the national brand supplier, the retailer simultaneously decides whether to accept the contract and whether to produce the store brand. The national brand supplier aims to design an optimal menu of contracts to maximize her expected profit as well as extract the retailer\u27s private cost information. We formulate the problem as a two-stage screening game to analyze the strategic interaction between the two players. Despite the inherent computational complexity, we are able to derive the optimal menu of contracts for the national brand supplier, of which the format depends on the national brand supplier\u27s unit production cost. Furthermore, we investigate how the model parameters affect the value of information for each member in the supply chain. We show that the retailer\u27s private cost information becomes less valuable to both the national brand supplier and the retailer when the national brand unit production cost increases. We also illustrate that when the gap between the two possible cost values increases, the private cost information becomes more valuable to the national brand supplier, however the value of information to the retailer himself can either increase or decrease. Finally, we demonstrate that when the perceived quality of the national brand increases, the value of information to the retailer first decreases then increases, but the impact on the value of information to the national brand supplier can be either positive or negative

Safety Stocks in Centralized and Decentralized Supply Chains under Different Types of Random Yields

Safety stock planning with focus on risk protection to cope with demand uncertainties is a very well researched topic in the field of supply chain management, in central as well as in local decision making systems. In contrast, there is only few knowledge about safety stock management in situations where supply risks have to be covered that are caused by uncertainties with respect to production yields. In this study, a two-stage manufacturer-retailer supply chain is considered in a single-period context that allows for an analytical study of the impact of yield randomness on safety stock determination. In order to concentrate the analysis on the effects of yield uncertainty demand will be assumed to be deterministic. We consider three basic types of yield randomness which represent different reasons for yield losses in production processes each, namely the stochastically proportional, binomial, and interrupted geometric yield type. It will be shown that these different yield risk specifications can bring about completely different properties with regard to the way safety stocks depend on various input parameters in supply chain planning. This holds especially for the impact of the demand size and for the influence of the level of product profitability in a supply chain. In an analytical model-based investigation it is demonstrated that these safety stock properties not only differ between the respective yield types, but also between systems of central and decentralized supply chain decision making. Thus, this study presents general insights into the importance of a correct yield type specification for an effective safety stock management and explains necessary differences in the stock distribution across supply chain stages in both centralized and decentralized settings

Enabling flexibility through strategic management of complex engineering systems

”Flexibility is a highly desired attribute of many systems operating in changing or uncertain conditions. It is a common theme in complex systems to identify where flexibility is generated within a system and how to model the processes needed to maintain and sustain flexibility. The key research question that is addressed is: how do we create a new definition of workforce flexibility within a human-technology-artificial intelligence environment? Workforce flexibility is the management of organizational labor capacities and capabilities in operational environments using a broad and diffuse set of tools and approaches to mitigate system imbalances caused by uncertainties or changes. We establish a baseline reference for managers to use in choosing flexibility methods for specific applications and we determine the scope and effectiveness of these traditional flexibility methods. The unique contributions of this research are: a) a new definition of workforce flexibility for a human-technology work environment versus traditional definitions; b) using a system of systems (SoS) approach to create and sustain that flexibility; and c) applying a coordinating strategy for optimal workforce flexibility within the human- technology framework. This dissertation research fills the gap of how we can model flexibility using SoS engineering to show where flexibility emerges and what strategies a manager can use to manage flexibility within this technology construct”--Abstract, page iii