IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v41y2013i1p28-30.html
   My bibliography  Save this article

DEA, directional distance functions and positive, affine data transformation

Author

Listed:
  • Färe, Rolf
  • Grosskopf, Shawna

Abstract

In this paper we take up the problem of positive, affine data translation within a Data Envelopment Analysis (DEA) framework.

Suggested Citation

  • Färe, Rolf & Grosskopf, Shawna, 2013. "DEA, directional distance functions and positive, affine data transformation," Omega, Elsevier, vol. 41(1), pages 28-30.
  • Handle: RePEc:eee:jomega:v:41:y:2013:i:1:p:28-30
    DOI: 10.1016/j.omega.2011.07.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030504831200028X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.omega.2011.07.011?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    2. Wade D. Cook & Joe Zhu, 2007. "Data Irregularities And Structural Complexities In Dea," Springer Books, in: Joe Zhu & Wade D. Cook (ed.), Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, chapter 0, pages 1-11, Springer.
    3. Wade D. Cook & Joe Zhu, 2007. "Rank Order Data In Dea," Springer Books, in: Joe Zhu & Wade D. Cook (ed.), Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, chapter 0, pages 13-34, Springer.
    4. R. G. Chambers & Y. Chung & R. Färe, 1998. "Profit, Directional Distance Functions, and Nerlovian Efficiency," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 351-364, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali, 2015. "A new slacks-based measure of Malmquist–Luenberger index in the presence of undesirable outputs," Omega, Elsevier, vol. 51(C), pages 29-37.
    2. Mehdiloozad, Mahmood & Sahoo, Biresh K. & Roshdi, Israfil, 2014. "A generalized multiplicative directional distance function for efficiency measurement in DEA," European Journal of Operational Research, Elsevier, vol. 232(3), pages 679-688.
    3. Colesnic, Olga & Kounetas, Konstantinos & Michael, Polemis, 2020. "Estimating risk efficiency in Middle East banks before and after the crisis: A metafrontier framework," Global Finance Journal, Elsevier, vol. 46(C).
    4. Charles, Vincent & Färe, Rolf & Grosskopf, Shawna, 2016. "A translation invariant pure DEA model," European Journal of Operational Research, Elsevier, vol. 249(1), pages 390-392.
    5. Imre Dobos & Gyöngyi Vörösmarty, 2019. "Evaluating green suppliers: improving supplier performance with DEA in the presence of incomplete data," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(2), pages 483-495, June.
    6. Branda, Martin, 2015. "Diversification-consistent data envelopment analysis based on directional-distance measures," Omega, Elsevier, vol. 52(C), pages 65-76.
    7. Davutyan, Nurhan & Bilsel, Murat & Tarcan, Menderes, 2015. "Migration, Risk-Adjusted Mortality, Varieties of Congestion and Patient Satisfaction in Turkish Provincial General Hospitals," Data Envelopment Analysis Journal, now publishers, vol. 1(2), pages 135-169, July.
    8. Aparicio, Juan & Pastor, Jesus T. & Vidal, Fernando, 2016. "The directional distance function and the translation invariance property," Omega, Elsevier, vol. 58(C), pages 1-3.
    9. Taylan G. Topcu & Konstantinos Triantis, 2022. "An ex-ante DEA method for representing contextual uncertainties and stakeholder risk preferences," Annals of Operations Research, Springer, vol. 309(1), pages 395-423, February.
    10. Muralidharan Loganathan & M. H. Bala Subrahmanya, 2023. "Efficiency of Entrepreneurial Universities in India: A Data Envelopment Analysis," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(2), pages 1120-1144, June.
    11. Panayiotis Tzeremes, 2020. "Productivity, efficiency and firm’s market value: Microeconomic evidence from multinational corporations," Bulletin of Applied Economics, Risk Market Journals, vol. 7(1), pages 95-105.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kao, Chiang, 2020. "Measuring efficiency in a general production possibility set allowing for negative data," European Journal of Operational Research, Elsevier, vol. 282(3), pages 980-988.
    2. Barra, Cristian & Zotti, Roberto, 2014. "Handling negative data using Data Envelopment Analysis: a directional distance approach applied to higher education," MPRA Paper 55570, University Library of Munich, Germany.
    3. Cherchye, Laurens & De Rock, Bram & Walheer, Barnabé, 2016. "Multi-output profit efficiency and directional distance functions," Omega, Elsevier, vol. 61(C), pages 100-109.
    4. Zotti, Roberto & Barra, Cristian, 2014. "Human capital development, knowledge spillovers and local growth: Is there a quality effect of university efficiency?," MPRA Paper 60065, University Library of Munich, Germany.
    5. K Kerstens & I Van de Woestyne, 2011. "Negative data in DEA: a simple proportional distance function approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1413-1419, July.
    6. Podinovski, Victor V. & Bouzdine-Chameeva, Tatiana, 2019. "Cone extensions of polyhedral production technologies," European Journal of Operational Research, Elsevier, vol. 276(2), pages 736-743.
    7. Mehdiloo, Mahmood & Podinovski, Victor V., 2021. "Strong, weak and Farrell efficient frontiers of technologies satisfying different production assumptions," European Journal of Operational Research, Elsevier, vol. 294(1), pages 295-311.
    8. Jie Wu & Zhixiang Zhou, 2015. "A mixed-objective integer DEA model," Annals of Operations Research, Springer, vol. 228(1), pages 81-95, May.
    9. Beatriz García-Cornejo & José A. Pérez-Méndez & David Roibás & Alan Wall, 2020. "Efficiency and Sustainability in Farm Diversification Initiatives in Northern Spain," Sustainability, MDPI, vol. 12(10), pages 1-18, May.
    10. Kristiaan Kerstens & Ignace Van de Woestyne, 2018. "Enumeration algorithms for FDH directional distance functions under different returns to scale assumptions," Annals of Operations Research, Springer, vol. 271(2), pages 1067-1078, December.
    11. Ravelojaona, Paola, 2019. "On constant elasticity of substitution – Constant elasticity of transformation Directional Distance Functions," European Journal of Operational Research, Elsevier, vol. 272(2), pages 780-791.
    12. Idiano D’Adamo & Cinzia Daraio & Simone Di Leo & Léopold Simar, 2024. "A Flexible and Sustainable Analysis of Waste Efficiency at the European Level," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 25(4), pages 881-894, December.
    13. Margareta Gardijan & Zrinka Lukač, 2018. "Measuring the relative efficiency of the food and drink industry in the chosen EU countries using the data envelopment analysis with missing data," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(3), pages 695-713, September.
    14. Mehdiloozad, Mahmood & Zhu, Joe & Sahoo, Biresh K., 2018. "Identification of congestion in data envelopment analysis under the occurrence of multiple projections: A reliable method capable of dealing with negative data," European Journal of Operational Research, Elsevier, vol. 265(2), pages 644-654.
    15. Podinovski, V. V., 2005. "Selective convexity in DEA models," European Journal of Operational Research, Elsevier, vol. 161(2), pages 552-563, March.
    16. Caitlin O’Loughlin & Léopold Simar & Paul W. Wilson, 2023. "Methodologies for assessing government efficiency," Chapters, in: António Afonso & João Tovar Jalles & Ana Venâncio (ed.), Handbook on Public Sector Efficiency, chapter 4, pages 72-101, Edward Elgar Publishing.
    17. Long Qian & Yunjie Zhou & Ying Sun, 2023. "Regional Differences, Distribution Dynamics, and Convergence of the Green Total Factor Productivity of China’s Cities under the Dual Carbon Targets," Sustainability, MDPI, vol. 15(17), pages 1-26, August.
    18. Alessandra Cepparulo & Gilles Mourre, 2020. "How and How Much? The Growth-Friendliness of Public Spending through the Lens," European Economy - Discussion Papers 132, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    19. Barnabé Walheer, 2018. "Cost Malmquist productivity index: an output-specific approach for group comparison," Journal of Productivity Analysis, Springer, vol. 49(1), pages 79-94, February.
    20. Fusco, Elisa, 2023. "Potential improvements approach in composite indicators construction: The Multi-directional Benefit of the Doubt model," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jomega:v:41:y:2013:i:1:p:28-30. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/375/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.