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Pengzhen Yin

Researcher at University of Science and Technology of China

Publications -  12
Citations -  460

Pengzhen Yin is an academic researcher from University of Science and Technology of China. The author has contributed to research in topics: Data envelopment analysis & Computer science. The author has an hindex of 7, co-authored 7 publications receiving 335 citations. Previous affiliations of Pengzhen Yin include Hefei University of Technology.

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DEA cross-efficiency evaluation considering undesirable output and ranking priority: a case study of eco-efficiency analysis of coal-fired power plants

TL;DR: Wang et al. as mentioned in this paper presented an equitable model for efficiency evaluation of decision-making units with undesirable outputs and introduced a technique for cross-efficiency evaluation considering undesirable outputs, and a ranking priority model was proposed considering the decision making units' intentions of pursuing the best ranking positions.
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Evaluating the environmental efficiency of a two-stage system with undesired outputs by a DEA approach: An interest preference perspective

TL;DR: A new DEA model is proposed to evaluate the environmental efficiency of a two-stage system with undesired outputs and three theorems are established to show the relationships between the interest preference parameter and the change of efficiency scores.
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A DEA-based two-stage network approach for hotel performance analysis: An internal cooperation perspective

TL;DR: A DEA-based bi-objective model is put forward to evaluate the hotel performance from the perspective that the two internal stages cooperate with each other, and offers a comprehensive benchmarking tool to improve hotel decision-making.
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DEA cross-efficiency evaluation based on satisfaction degree: an application to technology selection

TL;DR: In this paper, a new DEA cross-efficiency evaluation approach, which contains a maxmin model and two algorithms, is proposed based on the satisfaction degrees of the decision-making units (DMUs).
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Measuring energy and environmental performance for regions in China by using DEA-based Malmquist indices

TL;DR: Improved data envelopment analysis (DEA) models are utilized to evaluate the regional total-factor energy and environmental efficiency of China during the 11th 5-year plan period (2006–2010), showing that most of mainland China’s provincial-level regions have low energy andEnvironmental efficiency.