Nonparametric Production Technologies with Multiple Component Processes

• 成果类型: Article
• 署名作者: Podinovski, Victor V.; Olesen, Ole Bent; Sarrico, Claudia S.
• 署名单位: Loughborough University; University of Southern Denmark; Universidade de Lisboa
• 刊物名称: OPERATIONS RESEARCH
• ISSN/ISSBN: 0030-364X
• DOI: 10.1287/opre.2017.1667
• 发表日期: 2018
• 页码: 282-300
• 关键词: data envelopment analysis; multicomponent efficiency measurement; directional distance functions; dea models; Technical efficiency; scale elasticity; bank branches; performance; frontiers; returns

摘要

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.