IDEAS home Printed from https://ideas.repec.org/a/kap/iaecre/v9y2003i3p175-18810.1007-bf02295441.html
   My bibliography  Save this article

Variable selection for dynamic measures of efficiency in the computer industry

Author

Listed:
  • Phillip Fanchon

Abstract

Data Envelopment Analysis (DEA) measures of efficiency are very sensitive to the choice of variables for two reasons: the number of efficient firms is directly related to the number (n) of variables and the selection of the n variables greatly affects the measure of efficiency. A methodology is proposed which identifies the optimal number of variables, and which identifies the contribution of each variable to the measure of efficiency. The computer industry is used as an example to illustrate the method. Copyright International Atlantic Economic Society 2003

Suggested Citation

  • Phillip Fanchon, 2003. "Variable selection for dynamic measures of efficiency in the computer industry," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 9(3), pages 175-188, August.
    • Handle: RePEc:kap:iaecre:v:9:y:2003:i:3:p:175-188:10.1007/bf02295441
    DOI: 10.1007/BF02295441
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF02295441
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/BF02295441?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. Timothy F. Bresnahan & Shane Greenstein, 1999. "Technological Competition and the Structure of the Computer Industry," Journal of Industrial Economics, Wiley Blackwell, vol. 47(1), pages 1-40, March.
    2. Finn Førsund & Nikias Sarafoglou, 2002. "On the Origins of Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 23-40, January.
    3. Forbes, C.S. & King, M.L. & Morgan, A., 1995. "A Small Sample Variable Selection Procedure," Monash Econometrics and Business Statistics Working Papers 15/95, Monash University, Department of Econometrics and Business Statistics.
    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. Matthew F. Mitchell, 2000. "The scale of production in technological revolutions," Staff Report 269, Federal Reserve Bank of Minneapolis.
    6. Jati K. Sengupta, 2000. "Stochastic Efficiency Analysis," World Scientific Book Chapters, in: Dynamic And Stochastic Efficiency Analysis Economics of Data Envelopment Analysis, chapter 4, pages 97-128, World Scientific Publishing Co. Pte. Ltd..
    7. Golan, Amos, 2001. "A simultaneous estimation and variable selection rule," Journal of Econometrics, Elsevier, vol. 101(1), pages 165-193, 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.
    9. Indranil Bardhan & William Cooper & Subal Kumbhakar, 1998. "A Simulation Study of Joint Uses of Data Envelopment Analysis and Statistical Regressions for Production Function Estimation and Efficiency Evaluation," Journal of Productivity Analysis, Springer, vol. 9(3), pages 249-278, March.
    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. Solórzano-Taborga, Pablo & Alonso-Conde, Ana Belén & Rojo-Suárez, Javier, 2018. "Efficiency and Persistence of Spanish Absolute Return Funds || Eficiencia y persistencia de los fondos de retorno absolutos españoles," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 25(1), pages 186-214, Junio.
    2. Efendic Velid & Hadziahmetovic Nejra, 2017. "The social and financial efficiency of microfinance institutions: the case of Bosnia and Herzegovina," South East European Journal of Economics and Business, Sciendo, vol. 12(2), pages 85-101, December.
    3. Nataraja, Niranjan R. & Johnson, Andrew L., 2011. "Guidelines for using variable selection techniques in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 215(3), pages 662-669, December.
    4. Jamal Ouenniche & Skarleth Carrales, 2018. "Assessing efficiency profiles of UK commercial banks: a DEA analysis with regression-based feedback," Annals of Operations Research, Springer, vol. 266(1), pages 551-587, July.
    5. Villanueva-Cantillo, Jeyms & Munoz-Marquez, Manuel, 2021. "Methodology for calculating critical values of relevance measures in variable selection methods in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 290(2), pages 657-670.
    6. Karagiannis, Roxani & Karagiannis, Giannis, 2023. "Nonparametric estimates of price efficiency for the Greek infant milk market: Curing the curse of dimensionality with shannon entropy," Economic Modelling, Elsevier, vol. 121(C).
    7. Raul Moragues & Juan Aparicio & Miriam Esteve, 2023. "Ranking the Importance of Variables in a Nonparametric Frontier Analysis Using Unsupervised Machine Learning Techniques," Mathematics, MDPI, vol. 11(11), pages 1-24, June.
    8. Apostolos G. Christopoulos & Ioannis G. Dokas & Sofia Katsimardou & Konstantinos Vlachogiannatos, 2016. "Investigation of the relative efficiency for the Greek listed firms of the construction sector based on two DEA approaches for the period 2006–2012," Operational Research, Springer, vol. 16(3), pages 423-444, October.
    9. Toloo, Mehdi & Tone, Kaoru & Izadikhah, Mohammad, 2023. "Selecting slacks-based data envelopment analysis models," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1302-1318.
    10. Eskelinen, Juha, 2017. "Comparison of variable selection techniques for data envelopment analysis in a retail bank," European Journal of Operational Research, Elsevier, vol. 259(2), pages 778-788.

    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. Amar Oukil & Slim Zekri, 2021. "Investigating farming efficiency through a two stage analytical approach: Application to the agricultural sector in Northern Oman," Papers 2104.10943, arXiv.org.
    2. Finn Førsund, 2013. "Weight restrictions in DEA: misplaced emphasis?," Journal of Productivity Analysis, Springer, vol. 40(3), pages 271-283, December.
    3. W. Cooper & C. Lovell, 2011. "History lessons," Journal of Productivity Analysis, Springer, vol. 36(2), pages 193-200, October.
    4. 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.
    5. Glover, Fred & Sueyoshi, Toshiyuki, 2009. "Contributions of Professor William W. Cooper in Operations Research and Management Science," European Journal of Operational Research, Elsevier, vol. 197(1), pages 1-16, August.
    6. Shih, Jhih-Shyang & Harrington, Winston & Pizer, William A. & Gillingham, Kenneth, 2004. "Economies of Scale and Technical Efficiency in Community Water Systems," Discussion Papers 10788, Resources for the Future.
    7. Groot, Tom & Garcia-Valderrama, Teresa, 2006. "Research quality and efficiency: An analysis of assessments and management issues in Dutch economics and business research programs," Research Policy, Elsevier, vol. 35(9), pages 1362-1376, November.
    8. Petridis, Konstantinos & Malesios, Chrisovalantis & Arabatzis, Garyfallos & Thanassoulis, Emmanuel, 2013. "Efficiency analysis of forestry journals: Suggestions for improving journals’ quality," Journal of Informetrics, Elsevier, vol. 7(2), pages 505-521.
    9. Fiordelisi, Franco & Molyneux, Phil, 2010. "Total factor productivity and shareholder returns in banking," Omega, Elsevier, vol. 38(5), pages 241-253, October.
    10. Paradi, Joseph C. & Rouatt, Stephen & Zhu, Haiyan, 2011. "Two-stage evaluation of bank branch efficiency using data envelopment analysis," Omega, Elsevier, vol. 39(1), pages 99-109, January.
    11. Gattoufi, Said & Oral, Muhittin & Kumar, Ashok & Reisman, Arnold, 2004. "Epistemology of data envelopment analysis and comparison with other fields of OR/MS for relevance to applications," Socio-Economic Planning Sciences, Elsevier, vol. 38(2-3), pages 123-140.
    12. Halkos, George & Tzeremes, Nickolaos, 2012. "Evaluating professional tennis players’ career performance: A Data Envelopment Analysis approach," MPRA Paper 41516, University Library of Munich, Germany.
    13. Shafer, Scott M. & Byrd, Terry A., 2000. "A framework for measuring the efficiency of organizational investments in information technology using data envelopment analysis," Omega, Elsevier, vol. 28(2), pages 125-141, April.
    14. Halkos, George & Tzeremes, Nickolaos, 2011. "A conditional full frontier modelling for analyzing environmental efficiency and economic growth," MPRA Paper 32839, University Library of Munich, Germany.
    15. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    16. Mónika-Anetta Alt, 2012. "Measuring Romanian do-it-yourself retail chain’s efficiency during the economic crisis," Tržište/Market, Faculty of Economics and Business, University of Zagreb, vol. 24(1), pages 85-102.
    17. Krüger, Jens J., 2012. "A Monte Carlo study of old and new frontier methods for efficiency measurement," European Journal of Operational Research, Elsevier, vol. 222(1), pages 137-148.
    18. Maria Francesca Cracolici & Peter Nijkamp & Piet Rietveld, 2008. "Assessment of Tourism Competitiveness by Analysing Destination Efficiency," Tourism Economics, , vol. 14(2), pages 325-342, June.
    19. Halkos, George & Tzeremes, Nickolaos, 2011. "A non-parametric analysis of the efficiency of the top European football clubs," MPRA Paper 31173, University Library of Munich, Germany.
    20. Adler, Nicole & Raveh, Adi, 2008. "Presenting DEA graphically," Omega, Elsevier, vol. 36(5), pages 715-729, October.

    More about this item

    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:iaecre:v:9:y:2003:i:3:p:175-188:10.1007/bf02295441. 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.