Nonparametric Production Technologies with Multiple Component Processes

Victor V. Podinovski (), Ole Bent Olesen () and Cláudia S. Sarrico ()
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Victor V. Podinovski: School of Business and Economics, Loughborough University, Loughborough LE11 3TU, United Kingdom
Ole Bent Olesen: Department of Business and Economics, The University of Southern Denmark, DK-5230 Odense M, Denmark
Cláudia S. Sarrico: ISEG Lisbon School of Economics and Management, Universidade de Lisboa, 1200-781 Lisboa, Portugal; and CIPES Centre for Research in Higher Education Policies, 4450-137 Matosinhos, Portugal

Operations Research, 2018, vol. 66, issue 1, 282-300

Abstract: We develop a nonparametric methodology for assessing the efficiency of decision-making units operating in a production technology with several component processes. The latter is modeled by the new multiple hybrid returns-to-scale (MHRS) technology, formally derived from an explicitly stated set of production axioms. In contrast with the existing models of data envelopment analysis (DEA), the MHRS technology allows the incorporation of component-specific and shared inputs and outputs that represent several proportional (scalable) component production processes as well as nonproportional inputs and outputs. Our approach does not require information about the allocation of shared inputs and outputs to component processes or any assumptions about this allocation. We demonstrate the usefulness of the suggested approach in an application in the context of secondary education and also in a Monte Carlo study based on a simulated data generating process.

Keywords: data envelopment analysis; efficiency; multiple-component technology • secondary education (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (16)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:66:y:2018:i:1:p:282-300

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