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Recent Advances in R&D Benefit Measurement and Project Selection Methods

Author

Listed:
  • Norman Baker

    (Department of Quantitative Analysis, College of Business Administration, University of Cincinnati, Cincinnati, Ohio 45221)

  • James Freeland

    (Graduate School of Business, Stanford University, Stanford, California, 94305)

Abstract

The purpose of this paper is to provide a current assessment of the literature addressed to quantitative models of the R and D project selection and resource allocation decision. In order to facilitate the critique and assessment the literature is somewhat arbitrarily divided into benefit measurement and resource allocation methods. The strengths and limitations of existing knowledge are identified with an emphasis on empirical investigations. Several research areas are identified and briefly described.

Suggested Citation

  • Norman Baker & James Freeland, 1975. "Recent Advances in R&D Benefit Measurement and Project Selection Methods," Management Science, INFORMS, vol. 21(10), pages 1164-1175, June.
    • Handle: RePEc:inm:ormnsc:v:21:y:1975:i:10:p:1164-1175
    DOI: 10.1287/mnsc.21.10.1164
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    Cited by:

    1. Strauss, John, 1981. "Social Objective Functions in Agricultural Research," Evaluation of Agricultural Research, Proceedings of a Workshop, Minneapolis, MN, May 12-13, 1980, Miscellaneous Publication 8 49060, University of Minnesota, Agricultural Experiment Station.
    2. Scobie, Grant M., 1984. "Investment in Agricultural Research: Some Economic Principles," Economics Working Papers 232447, CIMMYT: International Maize and Wheat Improvement Center.
    3. Kengpol, Athakorn & O'Brien, Christopher, 2001. "The development of a decision support tool for the selection of advanced technology to achieve rapid product development," International Journal of Production Economics, Elsevier, vol. 69(2), pages 177-191, January.
    4. Scott A. Shane & Karl T. Ulrich, 2004. "50th Anniversary Article: Technological Innovation, Product Development, and Entrepreneurship in Management Science," Management Science, INFORMS, vol. 50(2), pages 133-144, February.
    5. Glickman, Theodore S., 2008. "Program portfolio selection for reducing prioritized security risks," European Journal of Operational Research, Elsevier, vol. 190(1), pages 268-276, October.
    6. Santhanam, Radhika & Kyparisis, George J., 1996. "A decision model for interdependent information system project selection," European Journal of Operational Research, Elsevier, vol. 89(2), pages 380-399, March.
    7. Wang, Jue & Xu, Wei & Ma, Jian & Wang, Shouyang, 2013. "A vague set based decision support approach for evaluating research funding programs," European Journal of Operational Research, Elsevier, vol. 230(3), pages 656-665.
    8. Kun Chen & Xian-tong Ren & Guo-liang Yang & Hai-bo Qin, 2022. "The other side of the coin: The declining of Chinese social science," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 127-143, January.
    9. Oral, Muhittin & Kettani, Ossama & Cinar, Unver, 2001. "Project evaluation and selection in a network of collaboration: A consensual disaggregation multi-criterion approach," European Journal of Operational Research, Elsevier, vol. 130(2), pages 332-346, April.
    10. Wang, Juite & Hwang, W.-L., 2007. "A fuzzy set approach for R&D portfolio selection using a real options valuation model," Omega, Elsevier, vol. 35(3), pages 247-257, June.
    11. Fernández Carazo, Ana & Gómez Núñez, Trinidad & Guerrero Casas, Flor M. & Caballero Fernández, Rafael, 2008. "Evaluación y clasificación de las técnicas utilizadas por las organizaciones, en las últimas décadas, para seleccionar proyectos = Evaluation and classification of the techniques used by organizations," 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. 5(1), pages 67-115, June.
    12. 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.
    13. 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.
    14. Jade Herbots & Willy Herroelen & Roel Leus, 2007. "Dynamic order acceptance and capacity planning on a single bottleneck resource," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(8), pages 874-889, December.
    15. Eilat, Harel & Golany, Boaz & Shtub, Avraham, 2006. "Constructing and evaluating balanced portfolios of R&D projects with interactions: A DEA based methodology," European Journal of Operational Research, Elsevier, vol. 172(3), pages 1018-1039, August.
    16. Kim, Suwon & Nam, Chan-gi & Lee, Sangwoo & Kim, Seongcheol, 2017. "A public R&D resource allocation model for 5G mobile industry in Korea," 28th European Regional ITS Conference, Passau 2017 169472, International Telecommunications Society (ITS).
    17. Nicholas G. Hall & Daniel Zhuoyu Long & Jin Qi & Melvyn Sim, 2015. "Managing Underperformance Risk in Project Portfolio Selection," Operations Research, INFORMS, vol. 63(3), pages 660-675, June.
    18. Kengpol, Athakorn & Tuominen, Markku, 2006. "A framework for group decision support systems: An application in the evaluation of information technology for logistics firms," International Journal of Production Economics, Elsevier, vol. 101(1), pages 159-171, May.
    19. Wu, Yunna & Xu, Chuanbo & Ke, Yiming & Li, Xinying & Li, Lingwenying, 2019. "Portfolio selection of distributed energy generation projects considering uncertainty and project interaction under different enterprise strategic scenarios," Applied Energy, Elsevier, vol. 236(C), pages 444-464.
    20. Fang Liu & Wei-dong Zhu & Yu-wang Chen & Dong-ling Xu & Jian-bo Yang, 2017. "Evaluation, ranking and selection of R&D projects by multiple experts: an evidential reasoning rule based approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1501-1519, June.
    21. Liu, Duan & Zhou, Qianzhen & Chen, Shiqi & Wan, Hong & He, Hongbo, 2021. "Capital market access and innovation efficiency: A natural experiment from China’s pilot VAT reform in 2012," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 549-566.
    22. Yu, Gun Jea & Hong, KiHoon, 2016. "Patents and R&D expenditure in explaining stock price movements," Finance Research Letters, Elsevier, vol. 19(C), pages 197-203.

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