Improving Efficiency Assessment of Psychiatric Halfway Houses: A Context-Dependent Data Envelopment Analysis Approach

This study proposes the approach of context-dependent data envelopment analysis (DEA) to measure operating performance in halfway houses to enable suitable adjustments at the current economic scale. The proposed approach can be used to discriminate the performance of efficient halfway houses and provide more accurate DEA results related to the performance of all halfway houses in a region or a country. The relative attractiveness and progress were also evaluated, and individual halfway houses’ competitive advantage and potential competitors could be determined. A case study of 38 halfway houses in Taiwan was investigated by our proposed approach. Findings suggest that fifteen halfway houses belong to the medium level, which can be classified into a quadrant by examining both their attractiveness score and progress score. The results can be used to allocate community resources to improve the operational directions and develop incentives for halfway houses with attractive and progressive values, which can reduce the institutionalization and waste of medical resources caused by the long-term hospitalization of patients with mental illnesses. Our proposed approach can also provide references for operators and policy makers to improve the management, accreditation, and resource allocation of institutions.

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A slack-based measure of efficiency in context-dependent data envelopment analysis

Omega ◽

10.1016/j.omega.2004.06.001 ◽

2005 ◽

Vol 33 (4) ◽

pp. 357-362 ◽

Cited By ~ 68

Author(s):

H MORITA ◽

K HIROKAWA ◽

J ZHU

Keyword(s):

Data Envelopment Analysis ◽

Dependent Data ◽

Data Envelopment ◽

Context Dependent

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Evaluating the comparative efficiency of the postal services in OECD countries using context-dependent and measure-specific data envelopment analysis

Benchmarking An International Journal ◽

10.1108/bij-10-2013-0098 ◽

2015 ◽

Vol 22 (5) ◽

pp. 839-856 ◽

Cited By ~ 4

Author(s):

Süleyman Çakır ◽

Selçuk Perçin ◽

Hokey Min

Keyword(s):

Data Envelopment Analysis ◽

Oecd Countries ◽

Data Envelopment ◽

Postal Service ◽

Public Enterprises ◽

Policy Makers ◽

Content Type ◽

Comparative Efficiency ◽

Postal Services ◽

Context Dependent

Purpose – In an effort to help policy makers develop competitive postal service strategies, the purpose of this paper is to evaluate the comparative operating efficiencies of postal services across the Organization for Economic Cooperation and Development (OECD) nations and then identify room for service improvement. Design/methodology/approach – As a better alternative to the conventional data envelopment analysis (DEA) which requires the proportional improvements of inputs and outputs simultaneously, the authors propose the combined use of both context-dependent and measure-specific DEAs to measure the relative attractiveness and progress of the national postal operators of OECD countries. Findings – Defying the conventional notion that public enterprises operate less efficiently than private enterprises, the author discovered that some state-owned public enterprises such as postal service operators could still be efficient if managed properly. Even inefficient postal services operators could significantly improve their service performances, once they identified the root causes of their service failures. Through a series of model experiments and testing, the authors found that proposed context-dependent and measure-specific DEA models were more useful for finding such causes than the conventional DEA model. Practical implications – For public officials and policy makers, the proposed DEAs can pinpoint what it takes to become more efficient and what steps need to be taken to improve postal service operations gradually. Originality/value – This paper is the first to combine the context-dependent DEA with measure-specific DEA to evaluate the comparative efficiency (or progress) and inefficiency (or regress) of the national postal operators of 25 OECD countries.

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