دانلود رایگان مقاله راندمان اندازه گیری محصولات جانبی روابط والد فرزندان مدل dea

abstractIn the usual data envelopment analysis (DEA) setting, as pioneered by Charnes et al. (1978), it is assumed that a set of decision making units (DMUs) is to be evaluated in terms of their relative efficiencies in converting a bundle of inputs into a bundle of outputs. The usual assumption in DEA is that each output is impacted by each and every member of the input set. One particular area of recent research is that relating to partial input to output impacts where the main issue addressed is that in many settings not all inputs impact all outputs. In that situation the authors view the DMU as consisting of a set of mutually exclusive subunits, with each subunit having its own unique bundle of inputs and outputs. Examined as well in this area, is the presence of multiple processes for generating sets of outputs. Missing from that earlier work is consideration of the presence of outputs in the form of by-products, giving rise to a parent-offspring phenomenon. One of the modelling complications there is that the parent assumes two different roles; as an input affecting the offspring, while at the same time being the dominant output. This gives rise to a model that we refer to as conditional two-stage. Another complication is that in the presence of multiple processes, by-products often arise out of only a subset of those processes. In the current paper we develop a DEA-type of methodology to handle partial input to output impacts in the presence of by-products.

5. Conclusions and Further Research

In the original Data Envelopment Analysis (DEA) model that is used to measure the relative efficiencies of peer decision-making units (DMUs), it is assumed that in a multiple input, multiple output setting, all members of the input bundle affect the entire output bundle. There are many situations in real world, however, where this assumption does not hold, and where partial input to output interactions occur. Earlier work by Beasley (1995), Molinero (1996), Zu et al. (2013), Cook et al. (2013) and Imanirad et al. (2013) examined various aspects of the partial input/output problem, which was later extended in Li et al. (2015) to include multiple processes. The application used to develop the ideas in Cook et al. (2013) and Imanirad et al. (2013) involved measuring efficiencies of a set of steel fabrication plants.