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The Practice of Management Science in R&D Project Management

Author

Listed:
  • Matthew J. Liberatore

    (Temple University)

  • George J. Titus

    (Temple University)

Abstract

The results of an empirical study on the current usage of quantitative techniques for R&D project management in "Fortune 500" industrial firms are presented. A nonrandom sample of 40 respondents from 29 firms were selected to represent a mix of industrial sectors and geographic regions. The information was obtained via personal interview of R&D budget heads and some high level staff. Extensive demographic data on the respondent and his company were collected and related to familiarity and usage of project management techniques. Data were also collected on the perceived impact of techniques on project decision making, and any recent/planned changes in the cadre of techniques. Heavy use and high perceived impact of financial methods for project selection, selective use of network models, some dissatisfaction over the methods available for project scheduling and control, and no usage of mathematical programming models for R&D resource allocation were key findings. As a result, R&D managers must have a thorough understanding of the capital budgeting techniques used by their organizations. Also, the initial training for R&D managers in project management should provide a broad-based introduction to the available methods and techniques, while emphasizing organizational "fit" considerations. Finally, it is suggested that R&D managers enlist the support of management scientists in the development of decision support systems for R&D project management, especially for multi-project planning and control.

Suggested Citation

  • Matthew J. Liberatore & George J. Titus, 1983. "The Practice of Management Science in R&D Project Management," Management Science, INFORMS, vol. 29(8), pages 962-974, August.
    • Handle: RePEc:inm:ormnsc:v:29:y:1983:i:8:p:962-974
    DOI: 10.1287/mnsc.29.8.962
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    Cited by:

    1. 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.
    2. Sachon, Marc & Paté-Cornell, Elisabeth, 2002. "Managing technology development for safety-critical systems," IESE Research Papers D/465, IESE Business School.
    3. Bubshait, K.A. & Selen, W.J., 1988. "Estimation of the relationship between project attributes and the implementation of engineering management tools," Other publications TiSEM e9acbbbc-af11-43c8-8632-3, Tilburg University, School of Economics and Management.
    4. 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.
    5. Bubshait, K.A. & Selen, W.J., 1988. "Estimation of the relationship between project attributes and the implementation of engineering management tools," Research Memorandum FEW 350, Tilburg University, School of Economics and Management.
    6. 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.
    7. Siddhartha Sampath & Esma S. Gel & John W. Fowler & Karl G. Kempf, 2015. "A Decision-Making Framework for Project Portfolio Planning at Intel Corporation," Interfaces, INFORMS, vol. 45(5), pages 391-408, October.
    8. Davies, Andrew & Manning, Stephan & Söderlund, Jonas, 2018. "When neighboring disciplines fail to learn from each other: The case of innovation and project management research," Research Policy, Elsevier, vol. 47(5), pages 965-979.
    9. Anıl Can & Gündüz Ulusoy, 2014. "Multi-project scheduling with two-stage decomposition," Annals of Operations Research, Springer, vol. 217(1), pages 95-116, June.
    10. Hajli, Nick & Sims, Julian & Zadeh, Arash H. & Richard, Marie-Odile, 2017. "A social commerce investigation of the role of trust in a social networking site on purchase intentions," Journal of Business Research, Elsevier, vol. 71(C), pages 133-141.
    11. Yu, Xinning & Lan, Yanfei & Zhao, Ruiqing, 2021. "Strategic green technology innovation in a two-stage alliance: Vertical collaboration or co-development?," Omega, Elsevier, vol. 98(C).
    12. Christoph H. Loch & Stylianos Kavadias, 2002. "Dynamic Portfolio Selection of NPD Programs Using Marginal Returns," Management Science, INFORMS, vol. 48(10), pages 1227-1241, October.
    13. A Morton & D Bird & A Jones & M White, 2011. "Decision conferencing for science prioritisation in the UK public sector: a dual case study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 50-59, January.

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