TY - JOUR
T1 - Measuring Spatio-temporal Efficiency
T2 - An R Implementation for Time-Evolving Units
AU - Digkas, Georgios
AU - Petridis, Konstantinos
AU - Chatzigeorgiou, Alexander
AU - Stiakakis, Emmanouil
AU - Emrouznejad, Ali
PY - 2020/12
Y1 - 2020/12
N2 - Classical data envelopment analysis models have been applied to extract efficiency when time series data are used. However, these models do not always yield realistic results, especially when the purpose of the study is to identify the peers of the decision making unit (DMU) under investigation. This is due to the fact that apart from the spatial distance of DMUs, which is the basis on which efficiency is extracted, the distance in time between DMUs is also important in identifying the most suitable peer that could serve as a benchmark for the DMU under investigation. Based on these two dimensions, i.e. the spatial and the temporal, the concept of spatio-temporal efficiency is introduced and a mixed integer linear programming model is proposed to obtain its value. This model yields a unique past peer for benchmarking purposes based on both dimensions. The implementation has been performed in the R language, where the user can provide, through a graphical interface, the data (inputs and outputs for successive versions of a DMU) for which the spatio-temporal efficiency is measured. Applications to the real world and particularly from the discipline of software engineering are provided to show the applicability of the model to temporally arranged data. Profiling results of the code in the R language are also provided showing the effectiveness of the implementation.
AB - Classical data envelopment analysis models have been applied to extract efficiency when time series data are used. However, these models do not always yield realistic results, especially when the purpose of the study is to identify the peers of the decision making unit (DMU) under investigation. This is due to the fact that apart from the spatial distance of DMUs, which is the basis on which efficiency is extracted, the distance in time between DMUs is also important in identifying the most suitable peer that could serve as a benchmark for the DMU under investigation. Based on these two dimensions, i.e. the spatial and the temporal, the concept of spatio-temporal efficiency is introduced and a mixed integer linear programming model is proposed to obtain its value. This model yields a unique past peer for benchmarking purposes based on both dimensions. The implementation has been performed in the R language, where the user can provide, through a graphical interface, the data (inputs and outputs for successive versions of a DMU) for which the spatio-temporal efficiency is measured. Applications to the real world and particularly from the discipline of software engineering are provided to show the applicability of the model to temporally arranged data. Profiling results of the code in the R language are also provided showing the effectiveness of the implementation.
KW - Computational economics
KW - DEA
KW - LP
KW - MILP
KW - R platform
KW - Spatio-temporal efficiency
UR - http://www.scopus.com/inward/record.url?scp=85076841227&partnerID=8YFLogxK
UR - https://link.springer.com/article/10.1007%2Fs10614-019-09945-4
U2 - 10.1007/s10614-019-09945-4
DO - 10.1007/s10614-019-09945-4
M3 - Article
AN - SCOPUS:85076841227
SN - 0927-7099
VL - 56
SP - 843
EP - 864
JO - Computational Economics
JF - Computational Economics
ER -