By Qingyu Zhang

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In the next section, we provide the relevant literature review. We then outline the notation and basic assumptions of our model and develop a dynamic program with the aim of minimizing the total expected delivery cost. Next, we propose three heuristic decision rules, which we evaluate by numerical simulation. We wrap up the chapter with a summary of our main results and some ideas for future research. LiteRAtURe ReVieW Literature examining transshipment models can be classified by several major characteristics: emergency situations or non-emergency situations, one-period or multiple-period, two-location or multiple-location, periodic review system or continuous review system, and static demand or dynamic demand.

Supply Chain Management Review, 8(3), 56-63. A. (1992). Pooling in two-location inventory systems with non-negligible replenishment lead times. Management Science, 38(8), 1067-1083. J. (2003). An improved heuristic for deciding on emergency transshipments. European Journal of Operational Research, 148, 384-400. B. (1978). Determining reorder points when demand is lumpy. Management Science, 24(6), 623-632.   Chapter III E-Com Supply Chain and SMEs Ron Craig Wilfrid Laurier University, Canada ABStRAct This chapter considers the perspective of small and medium-sized enterprises (SMEs) in supply chains.

The electronic supply chain: Its impact on the current and future structure of strategic alliances, partnerships and logistics leadership. International Journal of Physical Distribution & Logistics Management, 32(8), 703-719.   Chapter II Dynamic Transshipment in the Digital Age Shilei Yang Washington State University, USA Bintong Chen Washington State University, USA Charles L. Munson Washington State University, USA ABStRAct In recent years, e-retailing has become the growth engine for the retailing industry.

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