Journal of the Korean Operations Research and Management Science Society (한국경영과학회지)

The Korean Operations Research and Management Science Society (한국경영과학회)
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Efficiency Analysis of Public Service Organizations Using Stochastic Frontier Analysis

확률변경분석을 이용한 공공서비스 조직의 효율성 분석

  • Received : 2014.11.05
  • Accepted : 2015.01.07
  • Published : 2015.02.28
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Abstract

An organization must restructure itself once it makes outsourcing decisions. Outsourcing is a strategy that a company adopts to direct internal efforts into strengthening its core business processes while contracting other companies for strategically less critical tasks thereby improving organizational production efficiency, and the strategy inevitably involves organizational restructuring. While public service organizations have increasingly embraced outsourcing as well, only a handful of studies analyze the change in efficiency from organizational restructuring. Therefore, this study uses Stochastic Frontier Analysis (SFA) to test whether efficiency improved in Korea Expressway Corporation's restructured branch offices. Korea Expressway Corporation evaluated and grouped its branches based on road extensions management, traffic volume, the number of snow days, road deterioration, and the number of junctions to differentially allocate its personnel and budget. The extent of efficiency improvement in each group was compared, and results show that inefficiency did not exist in any of the groups. The efficiency index among the three group categories was similar across the board; 9 offices in the A-group with its expanded personnel and budget had an efficiency index of 0.954, 12 offices in the B-group with unchanged personnel and budget conditions had an index of 0.950, and 12 offices in the C-group with reduced personnel and budget had an index of 0.937. SFA facilitates efficiency analyses because it does not require pre-restructuring data. This study is easy to apply in practice and empirically tests efficiency improvement in organizational restructuring based on data collected from all the branch offices in Korea Expressway Corporation.

Keywords

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