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https://doi.org/10.21203/rs.3....
Article . 2023 . Peer-reviewed
License: CC BY
Data sources: Crossref
SSRN Electronic Journal
Article . 2022 . Peer-reviewed
Data sources: Crossref
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Pitfalls and Solutions in Inverse Models of Data Envelopment Analysis with Network Structures

Authors: Zohreh Moghaddas; Farhad Hosseinzadeh Lotfi; Morteza Yazdani;

Pitfalls and Solutions in Inverse Models of Data Envelopment Analysis with Network Structures

Abstract

AbstractToday, data envelopment analysis models with network structures are widely used to evaluate the performance of production systems and activities in various fields. the relationships between the internal stages of the network provides more information about the performance of each stage as well as their effects on the performance of the entire network to the managers and decision-makers. The inverse data envelopment analysis model is introduced to estimate useful information to system decision-makers, about analyzing the sensitivity of system inputs or outputs as long as the efficiency score is kept unchanged or improved according to the managers preferences. Managers can apply their important preferences and policies on resources, including input and output when analyzing production, resource allocation process, increasing resource efficiency, etc. on the system to use the results for future decisions. In this article, we will discuss the problems of infeasibility that can occur in theory and application for the inverse model of data envelopment analysis with network structure. After introducing these problems, an innovative idea is presented to prevent these shortcomings. Then, various problems are supposed, in terms of theory and applications, and are solved with case studies.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
hybrid
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