IDEAS home Printed from https://ideas.repec.org/a/kap/jproda/v32y2009i1p21-26.html
   My bibliography  Save this article

Production technologies based on combined proportionality assumptions

Author

Listed:
  • Victor Podinovski

Abstract

No abstract is available for this item.

Suggested Citation

  • Victor Podinovski, 2009. "Production technologies based on combined proportionality assumptions," Journal of Productivity Analysis, Springer, vol. 32(1), pages 21-26, August.
  • Handle: RePEc:kap:jproda:v:32:y:2009:i:1:p:21-26
    DOI: 10.1007/s11123-008-0113-7
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11123-008-0113-7
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11123-008-0113-7?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. Kerstens, Kristiaan & Vanden Eeckaut, Philippe, 1999. "Estimating returns to scale using non-parametric deterministic technologies: A new method based on goodness-of-fit," European Journal of Operational Research, Elsevier, vol. 113(1), pages 206-214, February.
    2. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
    3. Fare, Rolf & Grosskopf, Shawna & Lovell, C A Knox, 1983. " The Structure of Technical Efficiency," Scandinavian Journal of Economics, Wiley Blackwell, vol. 85(2), pages 181-190.
    4. 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.
    5. Cinzia Daraio & Léopold Simar, 2007. "Conditional nonparametric frontier models for convex and nonconvex technologies: a unifying approach," Journal of Productivity Analysis, Springer, vol. 28(1), pages 13-32, October.
    6. Simar, Leopold & Wilson, Paul W., 2002. "Non-parametric tests of returns to scale," European Journal of Operational Research, Elsevier, vol. 139(1), pages 115-132, May.
    7. V V Podinovski, 2004. "Bridging the gap between the constant and variable returns-to-scale models: selective proportionality in data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(3), pages 265-276, March.
    8. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    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. Zohreh Moghaddas & Alireza Amirteimoori & Reza Kazemi Matin, 2022. "Selective proportionality and integer-valued data in DEA: an application to performance evaluation of high schools," Operational Research, Springer, vol. 22(4), pages 3435-3459, September.
    2. Victor V. Podinovski & Wan Rohaida Wan Husain, 2017. "The hybrid returns-to-scale model and its extension by production trade-offs: an application to the efficiency assessment of public universities in Malaysia," Annals of Operations Research, Springer, vol. 250(1), pages 65-84, March.
    3. Podinovski, Victor V., 2017. "Returns to scale in convex production technologies," European Journal of Operational Research, Elsevier, vol. 258(3), pages 970-982.
    4. Barnabé Walheer, 2019. "Disaggregation for efficiency analysis," Journal of Productivity Analysis, Springer, vol. 51(2), pages 137-151, June.
    5. Victor V. Podinovski & Robert G. Chambers & Kazim Baris Atici & Iryna D. Deineko, 2016. "Marginal Values and Returns to Scale for Nonparametric Production Frontiers," Operations Research, INFORMS, vol. 64(1), pages 236-250, February.
    6. Podinovski, Victor V. & Ismail, Ihsan & Bouzdine-Chameeva, Tatiana & Zhang, Wenjuan, 2014. "Combining the assumptions of variable and constant returns to scale in the efficiency evaluation of secondary schools," European Journal of Operational Research, Elsevier, vol. 239(2), pages 504-513.
    7. 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.
    8. Seda Busra Sarac & Kazim Baris Atici & Aydin Ulucan, 2022. "Elasticity measurement on multiple levels of DEA frontiers: an application to agriculture," Journal of Productivity Analysis, Springer, vol. 57(3), pages 313-324, June.
    9. Barnabé Walheer, 2020. "Output, input, and undesirable output interconnections in data envelopment analysis: convexity and returns-to-scale," Annals of Operations Research, Springer, vol. 284(1), pages 447-467, January.

    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. Michael Zschille, 2014. "Nonparametric measures of returns to scale: an application to German water supply," Empirical Economics, Springer, vol. 47(3), pages 1029-1053, November.
    2. Halkos, George & Tzeremes, Nickolaos, 2008. "Measuring regional public health provision," MPRA Paper 23762, University Library of Munich, Germany.
    3. Walter Briec & Kristiaan Kerstens, 2006. "Input, output and graph technical efficiency measures on non-convex FDH models with various scaling laws: An integrated approach based upon implicit enumeration algorithms," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 14(1), pages 135-166, June.
    4. Walter Briec & Kristiaan Kerstens & Philippe Venden Eeckaut, 2004. "Non-convex Technologies and Cost Functions: Definitions, Duality and Nonparametric Tests of Convexity," Journal of Economics, Springer, vol. 81(2), pages 155-192, February.
    5. Halkos, George & Tzeremes, Nickolaos, 2009. "Exploring the effect of countries’ economic prosperity on their biodiversity performance," MPRA Paper 32102, University Library of Munich, Germany.
    6. Podinovski, Victor V., 2017. "Returns to scale in convex production technologies," European Journal of Operational Research, Elsevier, vol. 258(3), pages 970-982.
    7. Bampatsou, Christina & Halkos, George, 2018. "Dynamics of productivity taking into consideration the impact of energy consumption and environmental degradation," Energy Policy, Elsevier, vol. 120(C), pages 276-283.
    8. Halkos, George & Tzeremes, Nickolaos, 2011. "A conditional full frontier approach for investigating the Averch-Johnson effect," MPRA Paper 35491, University Library of Munich, Germany.
    9. 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.
    10. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "Data envelopment analysis 1978–2010: A citation-based literature survey," Omega, Elsevier, vol. 41(1), pages 3-15.
    11. Podinovski, V. V., 2005. "Selective convexity in DEA models," European Journal of Operational Research, Elsevier, vol. 161(2), pages 552-563, March.
    12. Mehdiloo, Mahmood & Podinovski, Victor V., 2019. "Selective strong and weak disposability in efficiency analysis," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1154-1169.
    13. Pham, Manh D. & Zelenyuk, Valentin, 2019. "Weak disposability in nonparametric production analysis: A new taxonomy of reference technology sets," European Journal of Operational Research, Elsevier, vol. 274(1), pages 186-198.
    14. Cesaroni, Giovanni & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2017. "Global and local scale characteristics in convex and nonconvex nonparametric technologies: A first empirical exploration," European Journal of Operational Research, Elsevier, vol. 259(2), pages 576-586.
    15. Michael Zschille & Matthias Walter, 2012. "The performance of German water utilities: a (semi)-parametric analysis," Applied Economics, Taylor & Francis Journals, vol. 44(29), pages 3749-3764, October.
    16. Ljubica Nedelkoska, 2010. "Occupations at risk: The task content and job stability," Jena Economics Research Papers 2010-024, Friedrich-Schiller-University Jena.
    17. Léopold Simar & Paul W. Wilson, 2015. "Statistical Approaches for Non-parametric Frontier Models: A Guided Tour," International Statistical Review, International Statistical Institute, vol. 83(1), pages 77-110, April.
    18. Stéphane Blancard & Jean-Philippe Boussemart & Kristiaan Kerstens, 2003. "L'influence des contraintes de financement de court terme sur le profit des exploitations agricoles. Une approche non paramétrique," Economie & Prévision, La Documentation Française, vol. 159(3), pages 71-81.
    19. Halkos, George & Tzeremes, Nickolaos, 2012. "Evaluating professional tennis players’ career performance: A Data Envelopment Analysis approach," MPRA Paper 41516, University Library of Munich, Germany.
    20. Titl, Vitezslav & De Witte, Kristof, 2022. "How politics influence public good provision," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).

    More about this item

    Keywords

    Efficiency; Data envelopment analysis; Selective proportionality; Hybrid returns to scale; Scale efficiency; C61; C67;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models

    Statistics

    Access and download statistics

    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:kap:jproda:v:32:y:2009:i:1:p:21-26. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.