D
Dan L. Shunk
Researcher at Arizona State University
Publications - 31
Citations - 1051
Dan L. Shunk is an academic researcher from Arizona State University. The author has contributed to research in topics: Supply chain & Supply chain management. The author has an hindex of 18, co-authored 31 publications receiving 999 citations.
Papers
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Value Chains Versus Supply Chains
TL;DR: In this paper, the authors discuss the need to relate the concepts of the value chain and the supply chain in a more comprehensive and integrative manner, and conclude with suggestions regarding the need for synchronizing value and supply chains to optimize business performance.
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AIDEA: a methodology for supplier evaluation and selection in a supplier-based manufacturing environment
TL;DR: A modified data envelopment analysis (DEA) method for supplier selection which can operate under conditions of imprecise information and elimination of the poor discriminatory power and inability of traditional DEA to rank the efficient suppliers is presented.
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Matching indirect procurement process with different B2B e-procurement systems
Joong-In Kim,Dan L. Shunk +1 more
TL;DR: The matching between indirect procurement process and different e-procurement systems, at both the high-level and low-level activities, is provided for identifying and articulating the areas where various e- procurement systems can be utilized in a hybrid and seamless manner.
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Understanding the effects of requirements volatility in software engineering by using analytical modeling and software process simulation
TL;DR: An executable system dynamics simulation model developed to help project managers comprehend the complex impacts related to requirements volatility on a software development project is introduced.
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A combined dispatching criteria approach to scheduling semiconductor manufacturing systems
TL;DR: In this paper, a modified dispatching approach that combines multiple dispatching criteria into a single rule with the objective of simultaneously optimizing multiple objectives is proposed for the scheduling problem of semiconductor manufacturing systems.