L
Liang Liang
Researcher at University of Science and Technology of China
Publications - 261
Citations - 10757
Liang Liang is an academic researcher from University of Science and Technology of China. The author has contributed to research in topics: Data envelopment analysis & Supply chain. The author has an hindex of 51, co-authored 224 publications receiving 8736 citations. Previous affiliations of Liang Liang include Harbin Institute of Technology & Hefei University of Technology.
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DEA models for non-homogeneous DMUs with different input configurations
TL;DR: The generation of outputs for a province is viewed as a set of processes created by the different configurations of natural resources available, and a DEA type of methodology is developed to evaluate these processes.
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Supply Chain Loss Averse Newsboy Model With Capital Constraint
TL;DR: It is shown that the retailer's loss aversion has a significant impact on the capital constraint problem, and it is interesting that bankruptcy protection encourages a cash-constrained retailer to adopt an aggressive ordering strategy.
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Using common weights and efficiency invariance principles for resource allocation and target setting
TL;DR: A new mechanism to simultaneously adopt the principles of common weights and efficiency invariance in allocating multiple resources and setting multiple targets among DMUs is proposed.
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A multiple criteria ranking method based on game cross-evaluation approach
Jie Wu,Liang Liang +1 more
TL;DR: An approach to evaluate and rank alternatives in MCDM via an extension of DEA method, namely DEA game cross-efficiency model in Liang, Wu, Cook and Zhu, in which each alternative is viewed as a player who seeks to maximize its own score (or desirability), under the condition that the cross-evaluation scores of each of other alternatives does not deteriorate.
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Augmenting Fixed Framework Agreements in Humanitarian Logistics with a Bonus Contract
TL;DR: In this article, the authors proposed using a bonus contract as a supplemental agreement to fixed framework agreements (FFAs) to incentivize suppliers to reduce delivery lead times and develop a performance measurement model using deprivation level functions (DLFs) to measure effectiveness, efficiency and cost effectiveness of an HL operation.