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A data envelopment analysis game theory approach for constructing composite indicator: An application to find out development degree of cities in West Azarbaijan province of Iran

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  • Omrani, Hashem
  • Fahimi, Pegah
  • Mahmoodi, Abdollah

Abstract

Data envelopment analysis (DEA) model has been widely applied for constructing composite indicator and finding development degree of areas. With the increasing number of indicators, the distinguish power of DEA model is decreased. In this paper, in order to increase distinguish power in DEA model and find out the fair weights in cross-efficiency DEA context, the game theory approach is applied. The DEA-Game theory approach is used to rank cities in West Azarbaijan province of Iran. First, 68 suitable indicators are determined and then, the indicators are classified in 10 sectors. Finally, the actual data for year 2013 is gathered and DEA-Game theory model is applied. To verify and validate the DEA-Game theory approach, simple additive weighting (SAW) and TOPSIS methods are used and the results are compared. The Spearman correlation between DEA-Game, SAW and TOPSIS models shows that the DEA-Game theory model is suitable for constructing the composite indicators.

Suggested Citation

  • Omrani, Hashem & Fahimi, Pegah & Mahmoodi, Abdollah, 2020. "A data envelopment analysis game theory approach for constructing composite indicator: An application to find out development degree of cities in West Azarbaijan province of Iran," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    • Handle: RePEc:eee:soceps:v:69:y:2020:i:c:s003801211730109x
    DOI: 10.1016/j.seps.2018.12.002
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