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.
Papers
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An AIC-based approach to identify the most influential variables in eco-efficiency evaluation
TL;DR: The most influential undesirable output in determining provincial industrial systems' eco-efficiency of China is Sulphur dioxide emission and the proposed Akaike information criteria (AIC) rule is robust under different eco- efficiency measurements.
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Achieving enhanced mechanical, pseudoelastic and elastocaloric properties in Ni-Mn-Ga alloys via Dy micro-alloying and isothermal mechanical cyclic training
TL;DR: In this paper, the combination of Dy micro-alloying and isothermal mechanical cyclic training (IMCT) was utilized to enhance the mechanical, pseudoelastic and elastocaloric properties of Ni-Mn-Ga shape memory alloys.
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Renewable WO3/Bi2O3 heterojunction for Photoelectrochemical and Visual Dual-mode Detection of Hydrogen Sulfide
TL;DR: In this paper , a renewable tungsten trioxide/bismuth oxide (WO3/Bi2O3) heterojunction for dual-mode photoelectrochemical (PEC) and visual determination of pernicious H2S was presented.
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Radial and non-radial DEA models undesirable outputs: an application to OECD countries
Gongbing Bi,Liang Liang,Jie Wu +2 more
TL;DR: In this article, two proposed DEA models are applied to evaluate the performance of 26 countries within OECD, in which two inputs (population and total energy consumption), two desirable outputs (GDP and total power generation) and one undesirable output (2 CO emission) are considered, and some managerial implications are evaluated.
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A New Business Mode for FTs Chain in an E-Commerce Environment
TL;DR: The study shows that, in most cases, the mix mode improves overall profit of FTs chain and considers the seasonality and the short life cycle of fashion items in analyzing the relationship between the e-retailer's optimal inventory level and demand distribution parameters.