 Duality and profit efficiency for the hyperbolic measure modelMargaréta Halická and Maria Trnovska European Journal of Operational Research, 2019, vol. 278, issue 2, 410-421 Abstract: The hyperbolic measure (HM) model is a radial, non-oriented model that is often used in Data Envelopment Analysis (DEA). It is formulated as a non-linear programming problem and hence the conventional linear programming methods, customarily used in DEA, cannot be applied to it in general. In this paper, we reformulate the hyperbolic measure model in a semidefinite programming framework which opens the way to solving the HM model by reliable and efficient interior point algorithms and allows us to benefit from simple primal-dual correspondence in semidefinite programming. We derive the dual of the HM model and so, for the first time, establish its multiplier form. We also offer an economic interpretation of the dual HM model via a comparison with the multiplier form of the directional distance model and relate the HM score to the so-called Nerlovian profit efficiency. Keywords: Data envelopment analysis; Semidefinite programming; Hyperbolic distance function; Return to dollar; Profit efficiency (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:278:y:2019:i:2:p:410-421 DOI: 10.1016/j.ejor.2018.12.001 Access Statistics for this article European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati More articles in European Journal of Operational Research from Elsevier |
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