Jose M. Cruz

This paper presents a decision model that captures supply-side disruption risks, social risks, and demand-side uncertainty within an integrated global supply chain and corporate social responsibility (CSR) modelling and analysis framework. The global supply chain decision-makers must decide on the level of investment in CSR activities and the choice of trading partners (manufacturer or retailer) given their CSR consciousness and perceived riskiness in order to maximise profit and minimise their overall risk. The model incorporates individual attitudes towards disruption risks among the manufacturers and the retailers, with the demands for the product associated with the retailers being random. The model allows one to investigate the effects of heterogeneous CSR activities in a global supply chain and to compute the resultant equilibrium pattern of product outputs, transactions, product prices, and levels of social responsibility activities. The results show that CSR activities can potentially be used to mitigate global supply chain risk.

We study the allocation of machines in a job shop environment to groups of jobs so as to obtain a collection of disjoint production lines minimising the overall cycle time. Jobs are often grouped according to similarities based on functionality or production process, but in some settings it makes more sense to group jobs according to batch size to exploit differences in setup and run times among technologies and machine types. We formulate a model to find an optimal group partition of jobs and an optimal assignment of machines to groups. We show that the problem is hard and formulate a heuristic based on genetic algorithms to find approximate solutions.

In this paper, we develop a framework that captures the effects of information management and risk-sharing contracts in supply chain networks. In particular, we analyse the impact of strategic information acquisition and sharing on supply chain disruption risks and costs and we evaluate the supply chain performance of risk-sharing contracts. Risk-sharing contracts specify who needs to incur the costs when supply chain disruptions occur. We develop a model that consists of three tiers of multi-criteria decision-makers, manufacturers, retailers, and demand markets. We describe the behaviour or each decision-maker, derive the finite-dimensional variational inequality formulation of the equilibrium conditions of the supply chain and present numerical examples. The numerical examples highlight that it is not a priori clear which participant in the supply chain network will benefit from increased information-sharing activities. Our models indicate that the beneficiary of reduced information-sharing costs is in some cases dependent on the negotiation power of participants and that it is also dependent on the type of risk-sharing contract used. Furthermore, the numerical examples show that, in some cases, information-sharing and risk-sharing contracts are complements while in other cases they are substitutes.

In this chapter, we analyze the effects of levels of social relationship on the global supply chain networks vulnerability. Relationship levels in our framework are assumed to influence transaction costs as well as risk for the decision-makers. We propose a network performance measure for the evaluation of the global supply chain networks efficiency and vulnerability. The measure captures risk, transaction cost, price, transaction flow, revenue, and demand information in the context of the decision-makers behavior the network. The network consists of manufacturers, retailers, and consumers. Manufacturers and retailers are multicriteria decisionmakers who decide about their production and transaction quantities as well as the level of social relationship they want to pursue in order to maximize net return and minimize risk. The model allows us to investigate the interplay of the heterogeneous decision-makers in the supply chain and to compute the resultant equilibrium pattern of product outputs, transactions, product prices, and levels of social relationship. The results show that high levels of relationship can lead to lower overall cost and therefore lower price and higher product transaction. Moreover, we use the performance measure to assess which nodes in the supply networks are themost vulnerable in the sense that their removal will impact the performance of the network in the most significant way.

In this paper we develop a framework for the modeling and analysis of supply chain networks with corporate social responsibility through integrated environmental decision-making. We consider the multicriteria decision-making behaviour of the various decision-makers (manufacturers, retailers, and consumers), which includes the maximization of net returns, the minimization of emissions (waste), and the minimization of risk. Increasing levels of social responsibility activities between decision-makers are assumed to reduce transaction costs, waste, as well as risk. We derive the optimality conditions, define the equilibrium state for the supply chain network, and derive the equivalent finite-dimensional variational inequality, the solution of which yields the equilibrium product flows transacted between the tiers of the supply chain network as well as the nodal prices. We then utilize the variational inequality formulation to provide qualitative properties of the equilibrium flow and price patterns and to propose a computational scheme, which is then applied to compute the solution to several numerical examples.