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Comparative advantage and disadvantage in DEA

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  • Agha Iqbal Ali
  • Catherine Lerme

Abstract

In this paper, we define comparative advantage and disadvantage within the framework of Data Envelopment Analysis (DEA). We develop models that address the measurement of comparative advantage and disadvantage entirely in terms of proportional changes in levels of output and input activities. The models allow inclusion of explicit limits on admissible tradeoffs across both types of activities. The assessment of comparative advantage and disadvantage establishes a framework for competitor analysis and the feasibility and desirability of strategic alliances. Copyright Kluwer Academic Publishers 1997

Suggested Citation

  • Agha Iqbal Ali & Catherine Lerme, 1997. "Comparative advantage and disadvantage in DEA," Annals of Operations Research, Springer, vol. 73(0), pages 215-232, October.
    • Handle: RePEc:spr:annopr:v:73:y:1997:i:0:p:215-232:10.1023/a:1018929228294
    DOI: 10.1023/A:1018929228294
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    Citations

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    Cited by:

    1. Wen-Min Lu & Qian Long Kweh & Chung-Wei Wang, 2021. "Integration and application of rough sets and data envelopment analysis for assessments of the investment trusts industry," Annals of Operations Research, Springer, vol. 296(1), pages 163-194, January.
    2. Timothy M. Devinney & David F. Midgley & Sunil Venaik, 2000. "The Optimal Performance of the Global Firm: Formalizing and Extending the Integration- Responsiveness Framework," Organization Science, INFORMS, vol. 11(6), pages 674-695, December.
    3. Cândida Ferreira, 2024. "The impact of bank market competition and stability on bank total factor productivity changes: evidence from a panel of European Union banks," Working Papers REM 2024/0315, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    4. Shengrui Zhang & Lei Chi & Tongyan Zhang & Yingjie Wang, 2023. "Optimization of Tourism Management Based on Regional Tourism Competitiveness Evaluation: Evidence from Ningxia Hui Autonomous Region, China," Sustainability, MDPI, vol. 15(12), pages 1-22, June.
    5. Cândida Ferreira, 2020. "Evaluating European Bank Efficiency Using Data Envelopment Analysis: Evidence in the Aftermath of the Recent Financial Crisis," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 26(4), pages 391-405, November.
    6. Li, Ye & Chen, Yiyan, 2021. "Development of an SBM-ML model for the measurement of green total factor productivity: The case of pearl river delta urban agglomeration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    7. Yu-Chen Lin & Hsihui Chang & Jengfang Chen & Guan-Syun Wu, 2014. "Accounting disclosure quality, capital market intensity and national productivity," Annals of Operations Research, Springer, vol. 221(1), pages 239-254, October.
    8. Md. Nazmul Huda Naim & Mohammed Sarfaraz Gani Adnan & Ashraf Dewan & Khatun E. Zannat, 2022. "Assessing the performance of public transport services in a developing country: A case study using data envelopment analysis," Growth and Change, Wiley Blackwell, vol. 53(1), pages 377-409, March.
    9. Asmild, Mette & Paradi, Joseph C. & Reese, David N. & Tam, Fai, 2007. "Measuring overall efficiency and effectiveness using DEA," European Journal of Operational Research, Elsevier, vol. 178(1), pages 305-321, April.
    10. Colamartino, Chiara & Dipierro, Anna Rita & Toma, Pierluigi & Frittelli, Massimo, 2023. "What lies behind the success of Italian GIs products? Questioning tradition in consortia via aggregated conditional efficiency," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).

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