two-stage production systems under variable returns to scale technology: a dea approach

Authors

roza azizi

reza kazemi matin

abstract

data envelopment analysis (dea) is a non-parametric approach for performance analysis of decision making units (dmus) which uses a set of inputs to produce a set of outputs without the need to consider internal operations of each unit. in recent years, there have been various studies dealt with two-stage production systems, i.e. systems which consume some inputs in their first stage to produce some intermediate outputs which are used as the inputs of the second stage in producing final outputs. one of these researches done by kao and hwang (2008) gives a decomposition of system efficiency score based on the efficiency of its sub-processes in the case of constant returns to scale (crs) technology. this paper presents an extension of this approach for the technologies with variable returns to scale (vrs) and explains the results.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

Two-stage Production Systems under Variable Returns to Scale Technology: A DEA Approach

Data envelopment analysis (DEA) is a non-parametric approach for performance analysis of decision making units (DMUs) which uses a set of inputs to produce a set of outputs without the need to consider internal operations of each unit. In recent years, there have been various studies dealt with two-stage production systems, i.e. systems which consume some inputs in their first stage to produce ...

full text

Characterization of efficient points of the production possibility set under variable returns to scale in DEA

  We suggest a method for finding the non-dominated points of the production possibility set (PPS) with variable returns to scale (VRS) technology in data envelopment analysis (DEA). We present a multiobjective linear programming (MOLP) problem whose feasible region is the same as the PPS under variable returns to scale for generating non-dominated points. We demonstrate that Pareto solutions o...

full text

DEA cross-efficiency evaluation under variable returns to scale

Cross-efficiency evaluation in data envelopment analysis (DEA) has been developed under the assumption of constant returns to scale (CRS), and no valid attempts have been made to apply the cross-efficiency concept to the variable returns to scale (VRS) condition. This is due to the fact that negative VRS cross-efficiency arises for some decision-making units (DMUs). Since there exist many insta...

full text

A Modification of Relational Two-Stage DEA with Variable Returns to Scale

Traditional studies in two-stage data envelopment analysis (DEA) assumed that the outputs of the first stage completely input into the second stage. But we think that assumption is not realistic becauses of efficiency loss. This paper modifies the traditional relational two-stage DEA with Variable Returns to Scale (VRS) by abandon this assumption. By introduction of efficiency loss to measure t...

full text

Scale Efficient Targets in Production Systems With Two-stage Structure Under Imprecise Data Assumption

Traditional data envelopment analysis (DEA) models evaluate two-stage decision making unit (DMU) as a black box and neglect the connectivity may exist among the stages. This paper looks inside the system by considering the intermediate activities between the stages where the first stage uses inputs to produce outputs which are the inputs to the second stage along with its own inputs. Additional...

full text

Creating Full Envelopment in Data Envelopment Analysis with Variable Returns to Scale Technology

In this paper, weak defining hyperplanes and the anchor points in DEA, as an important subset of the set of extreme efficient points of the Production Possibility Set (PPS), are used to construct unobserved DMUs and in the long run to improve the envelopment of all observed DMUs. There has been a surge of articles on improving envelopment in recent years. What has been done first is in Constant...

full text

My Resources

Save resource for easier access later


Journal title:
journal of optimization in industrial engineering

Publisher: qiau

ISSN 2251-9904

volume Volume 3

issue Issue 5 2010

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023