Allocating the Subsidy Among Urban Public Transport Enterprises for Good Performance and Low Carbon Transportation: An Application of DEA

Qianzhi Dai (), Yongjun Li (), Qiwei Xie () and Liang Liang ()
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Qianzhi Dai: School of Management University of Science and Technology of China
Yongjun Li: School of Management University of Science and Technology of China
Qiwei Xie: Institute of Automation Chinese Academy of Sciences
Liang Liang: School of Management University of Science and Technology of China

Chapter Chapter 15 in LTLGB 2012, 2013, pp 59-65 from Springer

Abstract: Abstract This paper proposes a stimulating mechanism for allocating subsidies to urban public transport enterprises. The allocation method is based on data envelopment analysis and the satisfaction degrees of urban public transport enterprises. It first finds the set of subsidy allocation that can keep the Pareto efficient for both the whole urban public transit industry and each urban public transport enterprise to reflect the efficiency principle, and then yields a unique subsidy allocation scheme from the set of subsidy allocations with considering the equity of satisfaction degrees. The allocation mechanism can reflect the market competition regulation on some level and benefit to achieve the goal of Green Transport in urban public transit industry. An example of allocating the subsidy among urban public transport enterprises is illustrated.

Keywords: Data envelopment analysis (DEA); Subsidy allocation; Efficiency; Satisfaction degree; Equity; Low carbon transportation (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/978-3-642-34651-4_15

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