IDEAS home Printed from https://ideas.repec.org/a/wly/mgtdec/v41y2020i3p461-472.html
   My bibliography  Save this article

A hybrid multi‐attribute decision‐making procedure for ranking project proposals: A historical data perspective

Author

Listed:
  • Amar Oukil
  • Srikrishna Madhumohan Govindaluri

Abstract

This paper develops a hybrid multiattribute decision‐making methodology for ranking project proposals (PPs) through a judicious usage of historical data of completed projects to determine attribute weights, enabling elimination of problems associated with projected data such as cost and schedule overruns of real‐world projects. The weights generated from data envelopment analysis are explicitly utilized for ranking PPs while allowing subjectivity to be ingeniously incorporated into the decision process. The new approach is implemented for ranking 25 PPs, and the rankings it yields are found indifferent to the decision maker's attitude, which ascertains the robustness of the ranking methodology.

Suggested Citation

  • Amar Oukil & Srikrishna Madhumohan Govindaluri, 2020. "A hybrid multi‐attribute decision‐making procedure for ranking project proposals: A historical data perspective," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(3), pages 461-472, April.
    • Handle: RePEc:wly:mgtdec:v:41:y:2020:i:3:p:461-472
    DOI: 10.1002/mde.3113
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/mde.3113
    Download Restriction: no
    File URL: https://libkey.io/10.1002/mde.3113?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
    ---><---

    References listed on IDEAS

    as
    1. Oral, Muhittin & Oukil, Amar & Malouin, Jean-Louis & Kettani, Ossama, 2014. "The appreciative democratic voice of DEA: A case of faculty academic performance evaluation," Socio-Economic Planning Sciences, Elsevier, vol. 48(1), pages 20-28.
    2. Oukil, Amar, 2020. "Exploiting value system multiplicity and preference voting for robust ranking," Omega, Elsevier, vol. 94(C).
    3. Cook, Wade D. & Ruiz, José L. & Sirvent, Inmaculada & Zhu, Joe, 2017. "Within-group common benchmarking using DEA," European Journal of Operational Research, Elsevier, vol. 256(3), pages 901-910.
    4. V. Srinivasan & Allan Shocker, 1973. "Estimating the weights for multiple attributes in a composite criterion using pairwise judgments," Psychometrika, Springer;The Psychometric Society, vol. 38(4), pages 473-493, December.
    5. Mohsen M.D. Hassan & Amar Oukil, 2021. "Design of efficient systems of commercial material handling equipment for supply chain and logistics facilities using DEA," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 39(2), pages 241-272.
    6. 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.
    7. Liu, John S. & Lu, Wen-Min, 2010. "DEA and ranking with the network-based approach: a case of R&D performance," Omega, Elsevier, vol. 38(6), pages 453-464, December.
    8. Cook, Wade D. & Green, Rodney H., 2000. "Project prioritization: a resource-constrained data envelopment analysis approach," Socio-Economic Planning Sciences, Elsevier, vol. 34(2), pages 85-99, June.
    9. Muhittin Oral & Ossama Kettani & Pascal Lang, 1991. "A Methodology for Collective Evaluation and Selection of Industrial R&D Projects," Management Science, INFORMS, vol. 37(7), pages 871-885, July.
    10. Eilat, Harel & Golany, Boaz & Shtub, Avraham, 2008. "R&D project evaluation: An integrated DEA and balanced scorecard approach," Omega, Elsevier, vol. 36(5), pages 895-912, October.
    11. Mehdi Toloo & Soroosh Nalchigar & Babak Sohrabi, 2018. "Selecting most efficient information system projects in presence of user subjective opinions: a DEA approach," 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(4), pages 1027-1051, December.
    12. Amar Oukil & Srikrishna Madhumohan Govindaluri, 2017. "A systematic approach for ranking football players within an integrated DEA‐OWA framework," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 38(8), pages 1125-1136, December.
    13. 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.
    14. Huang, Chi-Cheng & Chu, Pin-Yu & Chiang, Yu-Hsiu, 2008. "A fuzzy AHP application in government-sponsored R&D project selection," Omega, Elsevier, vol. 36(6), pages 1038-1052, December.
    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. 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. Yuzhong Lu & Zengrui Tian & Guillermo A. Buitrago, 2021. "Evaluation and selection of Chinese government venture capital investment projects: A research based on analytic hierarchy process and intuitionistic fuzzy set–technique for order of preference by sim," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(4), pages 821-835, June.

    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. Oukil, Amar, 2020. "Exploiting value system multiplicity and preference voting for robust ranking," Omega, Elsevier, vol. 94(C).
    2. You, Yan Q. & Jie, Tao, 2016. "A study of the operation efficiency and cost performance indices of power-supply companies in China based on a dynamic network slacks-based measure model," Omega, Elsevier, vol. 60(C), pages 85-97.
    3. Youchao Tan & Yang Zhang & Roohollah Khodaverdi, 2017. "Service performance evaluation using data envelopment analysis and balance scorecard approach: an application to automotive industry," Annals of Operations Research, Springer, vol. 248(1), pages 449-470, January.
    4. Amado, Carla A.F. & Santos, Sérgio P. & Marques, Pedro M., 2012. "Integrating the Data Envelopment Analysis and the Balanced Scorecard approaches for enhanced performance assessment," Omega, Elsevier, vol. 40(3), pages 390-403.
    5. Davtalab-Olyaie, Mostafa & Asgharian, Masoud, 2021. "On Pareto-optimality in the cross-efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 288(1), pages 247-257.
    6. Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
    7. Petr Fiala, 2018. "Project portfolio designing using data envelopment analysis and De Novo optimisation," 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(4), pages 847-859, December.
    8. Partovi, Fariborz Y., 2011. "Corporate philanthropic selection using data envelopment analysis," Omega, Elsevier, vol. 39(5), pages 522-527, October.
    9. Wade Cook & Rodney Green, 2003. "Selecting Sites for New Facilities Using Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 19(1), pages 77-91, January.
    10. Chun, Dongphil & Hong, Sungjun & Chung, Yanghon & Woo, Chungwon & Seo, Hangyeol, 2016. "Influencing factors on hydrogen energy R&D projects: An ex-post performance evaluation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1252-1258.
    11. Zervopoulos, Panagiotis D. & Brisimi, Theodora S. & Emrouznejad, Ali & Cheng, Gang, 2016. "Performance measurement with multiple interrelated variables and threshold target levels: Evidence from retail firms in the US," European Journal of Operational Research, Elsevier, vol. 250(1), pages 262-272.
    12. Eilat, Harel & Golany, Boaz & Shtub, Avraham, 2008. "R&D project evaluation: An integrated DEA and balanced scorecard approach," Omega, Elsevier, vol. 36(5), pages 895-912, October.
    13. Qingyou Yan & Jie Tao, 2014. "Biomass Power Generation Industry Efficiency Evaluation in China," Sustainability, MDPI, vol. 6(12), pages 1-16, December.
    14. Chien-Ming Chen & Joe Zhu, 2011. "Efficient Resource Allocation via Efficiency Bootstraps: An Application to R&D Project Budgeting," Operations Research, INFORMS, vol. 59(3), pages 729-741, June.
    15. Gobbo, Simone Cristina de Oliveira & Mariano, Enzo Barberio & Gobbo Jr., José Alcides, 2021. "Combining social network and data envelopment analysis: A proposal for a Selection Employment Contracts Effectiveness index in healthcare network applications," Omega, Elsevier, vol. 103(C).
    16. Ghazi, Amineh & Hosseinzadeh Lotfi, Farhad, 2019. "Assessment and budget allocation of Iranian natural gas distribution company- A CSW DEA based model," Socio-Economic Planning Sciences, Elsevier, vol. 66(C), pages 112-118.
    17. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    18. Viera Roháčová, 2015. "A DEA based approach for optimization of urban public transport system," 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. 23(1), pages 215-233, March.
    19. Sahoo, Biresh & Singh, Ramadhar & Mishra, Bineet & Sankaran, Krithiga, 2015. "Research Productivity in Management Schools of India: A Directional Benefit-of-Doubt Model Analysis," MPRA Paper 67046, University Library of Munich, Germany.
    20. Oral, Muhittin, 2010. "E-DEA: Enhanced data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 207(2), pages 916-926, December.

    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:wly:mgtdec:v:41:y:2020:i:3:p:461-472. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www3.interscience.wiley.com/cgi-bin/jhome/7976 .

    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.