Annals of Operations Research

, Volume 238, Issue 1–2, pp 475–496

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

  • Konstantinos Petridis
  • Alexander Chatzigeorgiou
  • Emmanouil Stiakakis
Article

DOI: 10.1007/s10479-015-2045-8

Cite this article as:
Petridis, K., Chatzigeorgiou, A. & Stiakakis, E. Ann Oper Res (2016) 238: 475. doi:10.1007/s10479-015-2045-8
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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 (S-T 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.

Keywords

Data Envelopment Analysis Efficiency OR in software Multiobjective programming Linear Programming 

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Aston Business SchoolAston UniversityBirminghamUK
  2. 2.Department of Applied InformaticsUniversity of MacedoniaThessalonikiGreece

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