IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v88y2014icp91-97.html
   My bibliography  Save this article

Choosing effective dates from multiple optima in Technology Forecasting using Data Envelopment Analysis (TFDEA)

Author

Listed:
  • Lim, Dong-Joon
  • Anderson, Timothy R.
  • Inman, Oliver Lane

Abstract

Technology Forecasting using Data Envelopment Analysis (TFDEA) provides an effective means to forecast technological capability over time without the burden of fixed a priori weighting schemes. However, there are situations where result reproduction can be a challenge as first pointed out in a previous Technological Forecasting and Social Change article [11]. When using a commonly used extension of TFDEA, there are circumstances where multiple optimal solutions can complicate analysis. This paper addresses this issue through extending the TFDEA model in a manner consistent with common Data Envelopment Analysis (DEA) techniques. The extension is then demonstrated using datasets from previous publications on fighter jet and commercial airplane technology where the issue of multiple optima has been observed. The results indicate that traditional TFDEA may generate varying forecasts depending on the software used, which can be dealt with by introducing a secondary objective function. Therefore, researchers should explicitly state which secondary objective function they are using for the TFDEA applications.

Suggested Citation

  • Lim, Dong-Joon & Anderson, Timothy R. & Inman, Oliver Lane, 2014. "Choosing effective dates from multiple optima in Technology Forecasting using Data Envelopment Analysis (TFDEA)," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 91-97.
    • Handle: RePEc:eee:tefoso:v:88:y:2014:i:c:p:91-97
    DOI: 10.1016/j.techfore.2014.06.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162514001930
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2014.06.003?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. Cooper, William W. & Ruiz, Jose L. & Sirvent, Inmaculada, 2007. "Choosing weights from alternative optimal solutions of dual multiplier models in DEA," European Journal of Operational Research, Elsevier, vol. 180(1), pages 443-458, July.
    2. 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.
    3. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, November.
    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. Azarnoosh Kafi & Behrouz Daneshian & Mohsen Rostamy-Malkhalifeh, 2021. "Forecasting the confidence interval of efficiency in fuzzy DEA," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(1), pages 41-59.
    2. Azarnoosh Kafi & Behrouz Daneshian & Mohsen Rostamy-Malkhalifeh, 2021. "Forecasting the confidence interval of efficiency in fuzzy DEA," Operations Research and Decisions, Wroclaw University of Science Technology, Faculty of Management, vol. 31, pages 41-59.
    3. 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.
    4. 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.
    5. Harrison, Gillian & Thiel, Christian, 2017. "An exploratory policy analysis of electric vehicle sales competition and sensitivity to infrastructure in Europe," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 165-178.
    6. Lim, Dong-Joon, 2016. "Inverse DEA with frontier changes for new product target setting," European Journal of Operational Research, Elsevier, vol. 254(2), pages 510-516.
    7. Lu, Louis Y.Y. & Hsieh, Chih-Hung & Liu, John S., 2016. "Development trajectory and research themes of foresight," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 347-356.
    8. Zhang, Hao & Daim, Tugrul & Zhang, Yunqiu (Peggy), 2021. "Integrating patent analysis into technology roadmapping: A latent dirichlet allocation based technology assessment and roadmapping in the field of Blockchain," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    9. An, Qingxian & Tao, Xiangyang & Xiong, Beibei & Chen, Xiaohong, 2022. "Frontier-based incentive mechanisms for allocating common revenues or fixed costs," European Journal of Operational Research, Elsevier, vol. 302(1), pages 294-308.

    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. Juan Aparicio & Magdalena Kapelko & Juan F. Monge, 2020. "A Well-Defined Composite Indicator: An Application to Corporate Social Responsibility," Journal of Optimization Theory and Applications, Springer, vol. 186(1), pages 299-323, July.
    2. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, February.
    3. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    4. Peter Fernandes Wanke & Rebecca de Mattos, 2014. "Capacity Issues and Efficiency Drivers in Brazilian Bulk Terminals," Brazilian Business Review, Fucape Business School, vol. 11(5), pages 72-98, October.
    5. Matthias Klumpp & Dominic Loske, 2021. "Sustainability and Resilience Revisited: Impact of Information Technology Disruptions on Empirical Retail Logistics Efficiency," Sustainability, MDPI, vol. 13(10), pages 1-20, May.
    6. George Halkos & Roman Matousek & Nickolaos Tzeremes, 2016. "Pre-evaluating technical efficiency gains from possible mergers and acquisitions: evidence from Japanese regional banks," Review of Quantitative Finance and Accounting, Springer, vol. 46(1), pages 47-77, January.
    7. Duk Hee Lee & Il Won Seo & Ho Chull Choe & Hee Dae Kim, 2012. "Collaboration network patterns and research performance: the case of Korean public research institutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(3), pages 925-942, June.
    8. A. M. Aldanondo & V. L. Casasnovas, 2015. "Input aggregation bias in technical efficiency with multiple criteria analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 22(6), pages 430-435, April.
    9. 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.
    10. Subhash C. Ray & Lei Chen, 2015. "Data Envelopment Analysis for Performance Evaluation: A Child’s Guide," Springer Books, in: Subhash C. Ray & Subal C. Kumbhakar & Pami Dua (ed.), Benchmarking for Performance Evaluation, edition 127, chapter 0, pages 75-116, Springer.
    11. Fukuyama, Hirofumi & Sekitani, Kazuyuki, 2012. "Decomposing the efficient frontier of the DEA production possibility set into a smallest number of convex polyhedrons by mixed integer programming," European Journal of Operational Research, Elsevier, vol. 221(1), pages 165-174.
    12. Mohsen Afsharian & Anna Kryvko & Peter Reichling, 2011. "Efficiency and Its Impact on the Performance of European Commercial Banks," FEMM Working Papers 110018, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    13. Miningou, Élisé Wendlassida & Vierstraete, Valérie, 2013. "Households' living situation and the efficient provision of primary education in Burkina Faso," Economic Modelling, Elsevier, vol. 35(C), pages 910-917.
    14. Tao Ding & Ya Chen & Huaqing Wu & Yuqi Wei, 2018. "Centralized fixed cost and resource allocation considering technology heterogeneity: a DEA approach," Annals of Operations Research, Springer, vol. 268(1), pages 497-511, September.
    15. Branda, Martin, 2013. "Diversification-consistent data envelopment analysis with general deviation measures," European Journal of Operational Research, Elsevier, vol. 226(3), pages 626-635.
    16. Korhonen, Pekka J. & Dehnokhalaji, Akram & Nasrabadi, Nasim, 2018. "A lexicographic radial projection onto the efficient frontier in Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 265(3), pages 1005-1012.
    17. Rize Jing & Tingting Xu & Xiaozhen Lai & Elham Mahmoudi & Hai Fang, 2019. "Technical Efficiency of Public and Private Hospitals in Beijing, China: A Comparative Study," IJERPH, MDPI, vol. 17(1), pages 1-18, December.
    18. Chin‐wei Huang & Hsiao‐Yin Chen, 2023. "Using nonradial metafrontier data envelopment analysis to evaluate the metatechnology and metafactor ratios for the Taiwanese hotel industry," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(4), pages 1904-1919, June.
    19. W. Cooper & C. Lovell, 2011. "History lessons," Journal of Productivity Analysis, Springer, vol. 36(2), pages 193-200, October.
    20. Trinks, Arjan & Mulder, Machiel & Scholtens, Bert, 2020. "An Efficiency Perspective on Carbon Emissions and Financial Performance," Ecological Economics, Elsevier, vol. 175(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:tefoso:v:88:y:2014:i:c:p:91-97. 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.sciencedirect.com/science/journal/00401625 .

    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.