Reliable container supply chain under disruption.

In this study, we develop a reliable formulation based on a container network flow problem, along with the full implementation of an empty container management strategy in the context of an integer linear programming model. The proposed approach can play a key role in coping with disruption in the network and can offer a proactive measure for effective disruption management to maintain a stable level of reliability in supply capability. To formulate a reliable container network problem, we design the pattern of disruption, a rare and irregular uncertainty, based on binomial coefficients in the objective function. In this way, flow interruption due to disruption can be expressed in node- and arc-failures and can be properly managed. Furthermore, we provide a non-disruptive model based on a deterministic formulation derived from a bast-case scenario. Through numerical illustrations and sensitivity analyses, we conduct in-depth analyses on the impact of disruption in the container supply chain, and a benchmark model based on a bast-case scenario is used to determine disruption costs, for comparative study. In particular, the numerical experiments show that if both maritime and hinterland disruptions are not managed in advance, disruption costs derived from a benchmark model result in a significant surge according to increasing potential disruption risk. Throughout computational experiments, we also found that maritime disruption is more destructive to container supply capability than hinterland disruption is. In particular, critical findings show that when a certain level of threshold is violated, the proposed strategies are completely interrupted in a container supply chain. Therefore, proactive measures to keep up a reliability of container supply in a high-risk region are highly recommended for management side.

A mechanism design approach to a buyer's optimal auditing policy to induce responsible sourcing in a supply chain.

Responsible sourcing refers to the compliance of suppliers with environmental and social standards. In today's supply chains, buyers and external stakeholders use auditing mechanisms to induce responsible sourcing. For the first time, this paper investigates the effect of a buyer's audits on the tactical decisions of supply chains. We address a repeated game with one buyer and one critical supplier. At the strategic stage, the buyer chooses the optimal auditing efforts to induce responsible sourcing. At the tactical stages, the buyer and supplier compete with each other for their profit margins, while the buyer also determines the quantity of production. Moreover, the supplier chooses between responsible and irresponsible production. Two auditing mechanisms are defined for the buyer: strong incentive compatibility (SIC) and weak incentive compatibility (WIC). The effectiveness and backfiring conditions for these auditing mechanisms are identified. The former denotes that the mechanism can induce responsible sourcing, while the latter denotes the conflict between supply chain transparency and responsible sourcing. The results show that the supplier requires an efficiency wage for compliance with responsible sourcing standards. We find that auditing mechanisms in supply chains face an unintended consequence. Higher auditing efforts by the buyer reduce the supplier's wholesale price. This reduction may offset the greater potential for discovery obtained by higher auditing efforts. We also show that the effect of consumer awareness on responsible sourcing is not straightforward and depends strongly on the buyer's auditing mechanism. If the buyer chooses the SIC (WIC) auditing mechanism, consumer awareness always favors (threatens) responsible sourcing. Finally, this research suggests that coordination between buyers and external stakeholders contributes greatly to responsible sourcing.

Warehouse capacity sharing via transshipment for an integrated two-echelon supply chain.

Warehouse capacity constraint has been one obstacle to achieving the channel-wide optimal decision in inventory management. We studied an integrated inventory model consisting of a single vendor and multiple buyers with warehouse capacity sharing via transshipment. We proposed an optimal transshipment policy by developing nonlinear programming models and genetic algorithms as well as obtaining Karush-Kuhn-Tucker points. This inventory policy can significantly reduce the channel-wide cost and the performance is influenced by the consideration of fixed transshipment costs. Sensitivity analyses show that parameters have different impacts on the channel-wide cost and the performances of the algorithms.