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A Scoring Methodology for Assessing the Suitability of Management Science Models

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  • William E. Souder

    (Northwestern University)

Abstract

In this study, five major criteria (realism, flexibility, capability, ease of use, and cost) for evaluating the suitability of management science models for R&D project selection are established, through personal interviews with R&D administrators and management scientists. A suitability rating system, based on these criteria, is used by the author to rate twenty-six management science models for their suitability of use in R&D project selection decision making. Profitablility index and scoring types of models were found to have generally higher ease of use and lower cost performances than the other types. The linear and nonlinear models had generally higher flexibility, while the linear, nonlinear and zero-one models had generally higher realism than the other model types.

Suggested Citation

  • William E. Souder, 1972. "A Scoring Methodology for Assessing the Suitability of Management Science Models," Management Science, INFORMS, vol. 18(10), pages 526-543, June.
    • Handle: RePEc:inm:ormnsc:v:18:y:1972:i:10:p:b526-b543
    DOI: 10.1287/mnsc.18.10.B526
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    Cited by:

    1. Scobie, Grant M., 1984. "Investment in Agricultural Research: Some Economic Principles," Economics Working Papers 232447, CIMMYT: International Maize and Wheat Improvement Center.
    2. Parker, Barnett R., 1995. "Ensuring a responsive health care planning function in developing regions of the world," Evaluation and Program Planning, Elsevier, vol. 18(3), pages 281-293.
    3. Noh, Heeyong & Seo, Ju-Hwan & Sun Yoo, Hyoung & Lee, Sungjoo, 2018. "How to improve a technology evaluation model: A data-driven approach," Technovation, Elsevier, vol. 72, pages 1-12.
    4. Cho, Yonghee & Yoon, Seong-Pil & Kim, Karp-Soo, 2016. "An industrial technology roadmap for supporting public R&D planning," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 1-12.
    5. Greig, I.D., 1981. "Agricultural Research Management and the Ex Ante Evaluation of Research Proposals : A Review," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 49(02), pages 1-22, August.
    6. J. Guinea & E. Sela & A. J. Gómez-Núñez & T. Mangwende & A. Ambali & N. Ngum & H. Jaramillo & J. M. Gallego & A. Patiño & C. Latorre & S. Srivanichakorn & B. Thepthien, 2015. "Impact oriented monitoring: A new methodology for monitoring and evaluation of international public health research projects," Research Evaluation, Oxford University Press, vol. 24(2), pages 131-145.

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