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Comparing products using data envelopment analysis

Author

Listed:
  • Doyle, JR
  • Green, RH

Abstract

Using an application of linear programming known as Data Envelopment Analysis (DEA), a method is described to compare products which vary in excellence along a number of dimensions, and for each of which there might be a number of associated "costs". The method is illustrated by comparing published benchmarks of 37 computer printers. Potential uses of a DEA analysis of products might be: to assist corporate buyers who may need to reconcile a diversity of present and future uses in one standardised purchase; in competitor analysis; in determining unexplored market niches; and as a normative model of product excellence against which product purchasing behaviour could be compared.

Suggested Citation

  • Doyle, JR & Green, RH, 1991. "Comparing products using data envelopment analysis," Omega, Elsevier, vol. 19(6), pages 631-638.
  • Handle: RePEc:eee:jomega:v:19:y:1991:i:6:p:631-638
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    Citations

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    Cited by:

    1. Mika Kortelainen & Timo Kuosmanen, 2007. "Eco-efficiency analysis of consumer durables using absolute shadow prices," Journal of Productivity Analysis, Springer, vol. 28(1), pages 57-69, October.
    2. Srinivas K. Reddy & Antonie Stam & Per J. Agrell, 2015. "Brand Equity, Efficiency and Valuation of Professional Sports Franchises: The Case of Major League Baseball," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 5(1), pages 63-89, January.
    3. Angel S. Fernandez-Castro & Peter C. Smith, 2002. "Lancaster's characteristics approach revisited: product selection using non-parametric methods," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 23(2), pages 83-91.
    4. Partovi, Fariborz Y., 2011. "Corporate philanthropic selection using data envelopment analysis," Omega, Elsevier, vol. 39(5), pages 522-527, October.
    5. Muhammet Enis Bulak & Murat Kucukvar, 2022. "How ecoefficient is European food consumption? A frontier‐based multiregional input–output analysis," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(5), pages 817-832, October.
    6. Lim, Dong-Joon & Anderson, Timothy R. & Shott, Tom, 2015. "Technological forecasting of supercomputer development: The March to Exascale computing," Omega, Elsevier, vol. 51(C), pages 128-135.
    7. Ruben Chumpitaz & Kristiaan Kerstens & Nicholas Paparoidamis & Matthias Staat, 2010. "Hedonic price function estimation in economics and marketing: revisiting Lancaster’s issue of “noncombinable” goods," Annals of Operations Research, Springer, vol. 173(1), pages 145-161, January.
    8. Matthias Staat & Maik Hammerschmidt, 2004. "A Super Efficiency Model for Product Evaluation," Microeconomics 0402011, University Library of Munich, Germany.
    9. Patrick McMullen & Gregory Frazier, 1999. "Using Simulation and Data Envelopment Analysis to Compare Assembly Line Balancing Solutions," Journal of Productivity Analysis, Springer, vol. 11(2), pages 149-168, April.
    10. Choi, Hyundo & Oh, Inha, 2010. "Analysis of product efficiency of hybrid vehicles and promotion policies," Energy Policy, Elsevier, vol. 38(5), pages 2262-2271, May.
    11. Kottas, Angelos T. & Bozoudis, Michail N. & Madas, Michael A., 2020. "Turbofan aero-engine efficiency evaluation: An integrated approach using VSBM two-stage network DEA," Omega, Elsevier, vol. 92(C).
    12. Seiford, Lawrence M. & Zhu, Joe, 2003. "Context-dependent data envelopment analysis--Measuring attractiveness and progress," Omega, Elsevier, vol. 31(5), pages 397-408, October.
    13. Mohammad Izadikhah & Reza Farzipoor Saen & Kourosh Ahmadi, 2017. "How to Assess Sustainability of Suppliers in the Presence of Dual-Role Factor and Volume Discounts? A Data Envelopment Analysis Approach," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(03), pages 1-25, June.
    14. Gary Ferrier & Julie Trivitt, 2013. "Incorporating quality into the measurement of hospital efficiency: a double DEA approach," Journal of Productivity Analysis, Springer, vol. 40(3), pages 337-355, December.
    15. H. H. Bauer & M. Staat & M. Hammerschmidt, 2003. "Value Based Benchmarking and Market Partitioning," Microeconomics 0309004, University Library of Munich, Germany.
    16. Ester Gutiérrez & Sebastián Lozano, 2020. "Benchmarking Formula One auto racing circuits: a two stage DEA approach," Operational Research, Springer, vol. 20(4), pages 2059-2083, December.
    17. González, Eduardo & Cárcaba, Ana & Ventura, Juan, 2015. "How car dealers adjust prices to reach the product efficiency frontier in the Spanish automobile market," Omega, Elsevier, vol. 51(C), pages 38-48.
    18. Samoilenko, Sergey & Osei-Bryson, Kweku-Muata, 2010. "Determining sources of relative inefficiency in heterogeneous samples: Methodology using Cluster Analysis, DEA and Neural Networks," European Journal of Operational Research, Elsevier, vol. 206(2), pages 479-487, October.

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