This paper seeks to review current research on supply chain management (SCM) within the context of tourism. SCM in the manufacturing industry has attracted widespread research interests over the past two decades while SCM studies in the tourism industry are very limited. Stakeholders in the tourism industry interact with each other to resolve their divergent business objectives with different operating scopes. The potential benefit of considering not only individual enterprises but also the tourism value chain becomes evident.The paper examines the characteristics of tourism products, identifies and explores core issues and concepts in tourism supply chains (TSC) and tourism supply chain management (TSCM). While the literature on TSCM or its equivalents emerges recently, the progress is variable with most research being focused on distribution and marketing activities, without fully considering the whole range of different suppliers involved in the provision and consumption of tourism products. This paper provides a systematic review of current tourism studies from the TSCM perspective and develops a framework for TSCM research which should be of great value not only to those who wish to extend their research into this new and exciting area, but also to tourism and hospitality decision makers. The paper also identifies key research questions in TSCM worthy of future theoretical and empirical explorations.

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This paper seeks to address the challenge of designing effective supply chain systems that integrate platform product decisions, manufacturing process decisions, and supply sourcing decisions. Specifically, this paper considers the specific scenario of optimizing the configuration of the supply chain system given commonality among platform products. The paper uses and extends the concept of Generic Bills of Materials (GBOM) of a product family as a unified framework for qualitatively capturing and representing the structure of its supply chain. This qualitative model is then enhanced by a mathematical model developed to quantify the relationships among various design decisions. Endeavoring to solve the mathematical model more efficiently, we propose an effective heuristic method using Genetic Algorithm (GA). Although GA generally does not guarantee the optimal solution, the best heuristic solutions obtained in this study are consistent with the optimal solutions obtained using Dynamic Programming. The resulting mathematical model and solution algorithm are then used to investigate the mutual impact between the design decisions of platform products and of processes in the supply chain through sensitivity analyses. Several useful managerial insights are generated and discussed. #

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