Journal
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
Volume 61, Issue -, Pages 204-216Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trd.2016.09.002
Keywords
Data envelopment analysis; Resource reallocation; Target setting; Environmental efficiency; Regional highway transportation system
Funding
- National Natural Science Funds of China [71222106, 71110107024, 71171001, 71471001, 71501139]
- Research Fund for the Doctoral Program of Higher Education of China [20133402110028]
- Foundation for the Author of National Excellent Doctoral Dissertation of P.R. China [201279]
- Fundamental Research Funds for the Central Universities [WK2040160008]
- Top-Notch Young Talents Program of China
- Internet of Things Industry Development Research Base Biding Project, Nanjing University of Posts and Telecommunications [JDS215005]
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In managerial decisions, situations frequently occur when the decision makers need to allocate/reallocate limited resources among a group of decision making units (DMUs) to improve the efficiencies of the DMUs and make better utilization of the limited resources. In this paper, we propose a resource reallocation and target setting approach for improving the environmental performance of the DMUs based on data envelopment analysis (DEA). Firstly, a model is given to identify the best revenue for each DMU in the resource reallocation and target setting process, and the concept of satisfaction degree of a DMU toward a resource allocation and target setting result is introduced. Then, under a DEA common weight evaluation framework, a centralized resource allocation and target setting model is proposed for reallocating the DMUs' discretionary inputs and setting output targets for the DMUs. Our approach can obtain for the DMUs a resource reallocation and target setting result which can not only guarantee that all the adjusted DMUs will be environment efficient in the new production period but also maximizes the minimum satisfaction degree among all the DMUs. Finally, the proposed approach is used for an empirical study of resource allocation and target setting for 30 regional highway transportation systems in China. (C) 2016 Elsevier Ltd. All rights reserved.
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