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Efficiency measurement in dynamic two-stage network structures with flexible intermediate materials

Kordrostami S., Seyedboveir S., Daneshian B., Amirteimoori A.

Operations Research and Decisions

2018

Vol. 28, No. 3

63--76

Data envelopment analysis (DEA) is a nonparametric method for evaluating the relative efficiency of decision making units (DMUs) described by multiple inputs and multiple outputs. Since DEA was introduced in the 1970s, it has been widely applied to measure the efficiency of a wide variety of production and operation systems, including two-stage production systems with a series or parallel structure. The outputs from the first stage to the next stage are called intermediate factors (or measures). In some real applications, an intermediate material or some part of it can become the final output or input to the second stage of production. Previously existing models cannot be employed directly to measure the efficiency of such systems. The authors introduce a dynamic DEA model that identifies the structure of flexible intermediate factors to maximise the measure of overall system efficiency.

Efficiency measurement using nonparametric production analysis in the presence of undesirable outputs : an application to power plants

Amirteimoori A., Kordrostami S., Fooladvand M.

Operations Research and Decisions

2017

Vol. 27, No. 3

5--20

In order to deal with undesirable products in models of performance analysis, we need to replace the assumption of free disposability by weak disposability and this assumption has been used to model undesirable products as outputs. The traditional axiom of weak disposability of Shephard (1970) is given in a multiplier form and, in this sense, the level of bad outputs is equal to zero if and only if the level of the desirable outputs is equal to zero. An alternative definition of the weak disposability of outputs in additive form has been proposed. An axiomatic foundation has been introduced to construct a new production technology space in the presence of undesirable outputs. The model is illustrated using real data from 92 coal fired power plants.