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COOPER-framework: A Unified Standard Process for Non-parametric Projects

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  • Emrouznejad, A.
  • De Witte, K.

Abstract

Practitioners assess performance of entities in increasingly large and complicated datasets. If non-parametric models, such as Data Envelopment Analysis, were ever considered as simple push-button technologies, this is impossible when many variables are available or when data have to be compiled from several sources. This paper introduces by the ‘COOPER-framework’ a comprehensive model for carrying out non-parametric projects. The framework consists of six interrelated phases: Concepts and objectives, On structuring data, Operational models, Performance comparison model, Evaluation, and Result and deployment. Each of the phases describes some necessary steps a researcher should examine for a well defined and repeatable analysis. The COOPER-framework provides for the novice analyst guidance, structure and advice for a sound non-parametric analysis. The more experienced analyst benefits from a check list such that important issues are not forgotten. In addition, by the use of a standardized framework non-parametric assessments will be more reliable, more repeatable, more manageable, faster and less costly.

Suggested Citation

  • Emrouznejad, A. & De Witte, K., 2010. "COOPER-framework: A Unified Standard Process for Non-parametric Projects," Working Papers 18, Top Institute for Evidence Based Education Research.
    • Handle: RePEc:tir:wpaper:18
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    1. Ray,Subhash C., 2012. "Data Envelopment Analysis," Cambridge Books, Cambridge University Press, number 9781107405264.
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    Cited by:

    1. Sebastian Kohl & Jan Schoenfelder & Andreas Fügener & Jens O. Brunner, 2019. "The use of Data Envelopment Analysis (DEA) in healthcare with a focus on hospitals," Health Care Management Science, Springer, vol. 22(2), pages 245-286, June.
    2. Ali Emrouznejad, 2014. "Advances in data envelopment analysis," Annals of Operations Research, Springer, vol. 214(1), pages 1-4, March.
    3. Hatami-Marbini, Adel & Emrouznejad, Ali & Tavana, Madjid, 2011. "A taxonomy and review of the fuzzy data envelopment analysis literature: Two decades in the making," European Journal of Operational Research, Elsevier, vol. 214(3), pages 457-472, November.
    4. Ghasemi, M.-R. & Ignatius, Joshua & Emrouznejad, Ali, 2014. "A bi-objective weighted model for improving the discrimination power in MCDEA," European Journal of Operational Research, Elsevier, vol. 233(3), pages 640-650.
    5. Asatryan, Zareh & De Witte, Kristof, 2015. "Direct democracy and local government efficiency," European Journal of Political Economy, Elsevier, vol. 39(C), pages 58-66.
    6. Majid Baghery & Samuel Yousefi & Mustafa Jahangoshai Rezaee, 2018. "Risk measurement and prioritization of auto parts manufacturing processes based on process failure analysis, interval data envelopment analysis and grey relational analysis," Journal of Intelligent Manufacturing, Springer, vol. 29(8), pages 1803-1825, December.
    7. Victoria Wojcik & Harald Dyckhoff & Marcel Clermont, 2019. "Is data envelopment analysis a suitable tool for performance measurement and benchmarking in non-production contexts?," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 559-595, December.
    8. Jahangoshai Rezaee, Mustafa & Moini, Alireza & Makui, Ahmad, 2012. "Operational and non-operational performance evaluation of thermal power plants in Iran: A game theory approach," Energy, Elsevier, vol. 38(1), pages 96-103.
    9. Mahmoudi, Reza & Shetab-Boushehri, Seyyed-Nader & Hejazi, Seyed Reza & Emrouznejad, Ali & Rajabi, Parisa, 2019. "A hybrid egalitarian bargaining game-DEA and sustainable network design approach for evaluating, selecting and scheduling urban road construction projects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 130(C), pages 161-183.
    10. Emrouznejad, Ali & Rostami-Tabar, Bahman & Petridis, Konstantinos, 2016. "A novel ranking procedure for forecasting approaches using Data Envelopment Analysis," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 235-243.
    11. Youchao Tan & Udaya Shetty & Ali Diabat & T. Pakkala, 2015. "Aggregate directional distance formulation of DEA with integer variables," Annals of Operations Research, Springer, vol. 235(1), pages 741-756, December.
    12. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali & Toloo, Mehdi & Ghazizadeh, Mohammad Sadegh, 2016. "Eco-efficiency considering the issue of heterogeneity among power plants," Energy, Elsevier, vol. 111(C), pages 722-735.
    13. M. Khodabakhshi & K. Aryavash, 2014. "The fair allocation of common fixed cost or revenue using DEA concept," Annals of Operations Research, Springer, vol. 214(1), pages 187-194, March.

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