Name
Abstract | ||
|---|---|---|
AbstractWe 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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1287/opre.2017.1667 | Periodicals |
Keywords | Field | DocType |
data envelopment analysis,efficiency,multiple-component technology,secondary education | Monte Carlo method,Mathematical optimization,Secondary education,Axiom,Computer science,Nonparametric statistics,Data envelopment analysis,Operations management,Scalability | Journal |
Volume | Issue | ISSN |
66 | 1 | 0030-364X |
Citations | PageRank | References |
3 | 0.39 | 16 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Victor V. Podinovski | 1 | 182 | 19.92 |
| ole bent olesen | 2 | 35 | 4.21 |
| Cláudia S. Sarrico | 3 | 128 | 13.99 |