A spatiotemporal Data Envelopment Analysis (S-T DEA) approach: the need to assess evolving units

Konstantinos Petridis*, Alexander Chatzigeorgiou, Emmanouil Stiakakis

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

One of the major challenges in measuring efficiency in terms of resources and outcomes is the assessment of the evolution of units over time. Although Data Envelopment Analysis (DEA) has been applied for time series datasets, DEA models, by construction, form the reference set for inefficient units (lambda values) based on their distance from the efficient frontier, that is, in a spatial manner. However, when dealing with temporal datasets, the proximity in time between units should also be taken into account, since it reflects the structural resemblance among time periods of a unit that evolves. In this paper, we propose a two-stage spatiotemporal DEA approach, which captures both the spatial and temporal dimension through a multi-objective programming model. In the first stage, DEA is solved iteratively extracting for each unit only previous DMUs as peers in its reference set. In the second stage, the lambda values derived from the first stage are fed to a Multiobjective Mixed Integer Linear Programming model, which filters peers in the reference set based on weights assigned to the spatial and temporal dimension. The approach is demonstrated on a real-world example drawn from software development.
Original languageEnglish
Pages (from-to)475-496
Number of pages22
JournalAnnals of Operations Research
Volume238
Issue number1-2
Early online date30 Oct 2015
DOIs
Publication statusPublished - 1 Mar 2016

Bibliographical note

The final publication is available at Springer via http://dx.doi.org/10.1007/s10479-015-2045-8

Keywords

  • Data Envelopment Analysis
  • efficiency
  • OR in software
  • multiobjective programming
  • linear programming

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