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Research, Development, and Engineering Metrics


  • John R. Hauser

    (Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142)


We seek to understand how the use of Research, Development, and Engineering (R,D&E) metrics can lead to more effective management of R,D&E. This paper combines qualitative and quantitative research to understand and improve the use of R,D&E metrics. Our research begins with interviews of 43 representative Chief Technical Officers, Chief Executive Offices, and researchers at 10 research-intensive international organizations. These interviews, and an extensive review of the literature, provide qualitative insights. Formal mathematical models attempt to explore these qualitative insights based on more general principles. Our research suggests that metrics-based evaluation and management vary according to the characteristics of the R,D&E activity. For applied projects, we find that project selection can be based on market-outcome metrics when firms use central subsidies to account for short-termism, risk aversion, and scope. With an efficient form of subsidies known as "tin-cupping," the business units have the incentives to choose the projects that are in the firm's best long-term interests. For core-technological development, longer time delays and more risky programs imply that popular R,D&E effectiveness metrics lead researchers to select programs that are not in the firm's long-term interest. Our analyses suggest that firms moderate such market-outcome metrics by placing a larger weight on metrics that attempt to measure research effort more directly. These metrics include standard measures such as publications, citations, patents, citations to patents, and peer review. For basic research, the issues shift to getting the right people and encouraging a breadth of ideas. Unfortunately, metrics that identify the "best people" based on research success lead directly to "not-invented-here" behaviors. Such behaviors result in research empires that are larger than necessary, but lead to fewer ideas. We suggest that firms use "research tourism" metrics, which encourage researchers to take advantage of research spillovers from universities, other industries, and, even, competitors.

Suggested Citation

  • John R. Hauser, 1998. "Research, Development, and Engineering Metrics," Management Science, INFORMS, vol. 44(12-Part-1), pages 1670-1689, December.
  • Handle: RePEc:inm:ormnsc:v:44:y:1998:i:12-part-1:p:1670-1689

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    References listed on IDEAS

    1. Rebecca Henderson & Iain Cockburn, 1996. "Scale, Scope, and Spillovers: The Determinants of Research Productivity in Drug Discovery," RAND Journal of Economics, The RAND Corporation, vol. 27(1), pages 32-59, Spring.
    2. Holmstrom, Bengt, 1989. "Agency costs and innovation," Journal of Economic Behavior & Organization, Elsevier, vol. 12(3), pages 305-327, December.
    3. Jeffrey I. Bernstein & M. Ishaq Nadiri, 1989. "Research and Development and Intra-industry Spillovers: An Empirical Application of Dynamic Duality," Review of Economic Studies, Oxford University Press, vol. 56(2), pages 249-267.
    4. Mansfield, Edwin, 1980. "Basic Research and Productivity Increase in Manufacturing," American Economic Review, American Economic Association, vol. 70(5), pages 863-873, December.
    5. repec:fth:harver:1473 is not listed on IDEAS
    6. Zvi Griliches, 1998. "Patent Statistics as Economic Indicators: A Survey," NBER Chapters,in: R&D and Productivity: The Econometric Evidence, pages 287-343 National Bureau of Economic Research, Inc.
    7. Julio J. Rotemberg & Garth Saloner, 1995. "Overt Interfunctional Conflict (and its Reduction Through Business Strategy)," RAND Journal of Economics, The RAND Corporation, vol. 26(4), pages 630-653, Winter.
    8. Jaffe, Adam B, 1989. "Real Effects of Academic Research," American Economic Review, American Economic Association, vol. 79(5), pages 957-970, December.
    9. Block, Zenas & Ornati, Oscar A., 1987. "Compensating corporate venture managers," Journal of Business Venturing, Elsevier, vol. 2(1), pages 41-51.
    10. Holmström, Bengt, 1989. "Agency Costs and Innovation," Working Paper Series 214, Research Institute of Industrial Economics.
    11. Taylor, Curtis R, 1995. "Digging for Golden Carrots: An Analysis of Research Tournaments," American Economic Review, American Economic Association, vol. 85(4), pages 872-890, September.
    12. Acs, Zoltan J & Audretsch, David B & Feldman, Maryann P, 1992. "Real Effects of Academic Research: Comment," American Economic Review, American Economic Association, vol. 82(1), pages 363-367, March.
    13. Richard R. Nelson, 1959. "The Simple Economics of Basic Scientific Research," Journal of Political Economy, University of Chicago Press, vol. 67, pages 297-297.
    14. Henry Grabowski & John Vernon, 1990. "A New Look at the Returns and Risks to Pharmaceutical R&D," Management Science, INFORMS, vol. 36(7), pages 804-821, July.
    15. Cohen, Wesley M & Levinthal, Daniel A, 1989. "Innovation and Learning: The Two Faces of R&D," Economic Journal, Royal Economic Society, vol. 99(397), pages 569-596, September.
    16. Gary Erickson & Robert Jacobson, 1992. "Gaining Comparative Advantage Through Discretionary Expenditures: The Returns to R&D and Advertising," Management Science, INFORMS, vol. 38(9), pages 1264-1279, September.
    17. George J. Stigler, 1961. "The Economics of Information," Journal of Political Economy, University of Chicago Press, vol. 69, pages 213-213.
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    Cited by:

    1. Nathalie Lazaric & Alain Raybaut, 2014. "Do incentive systems spur work motivation of inventors in high tech firms? A group-based perspective," Journal of Evolutionary Economics, Springer, vol. 24(1), pages 135-157, January.
    2. Elie Ofek & Miklos Sarvary, 2003. "R&D, Marketing, and the Success of Next-Generation Products," Marketing Science, INFORMS, vol. 22(3), pages 355-370, July.
    3. Kim, Bowon & Oh, Heungshik, 2002. "An effective R&D performance measurement system: survey of Korean R&D researchers," Omega, Elsevier, vol. 30(1), pages 19-31, February.
    4. Audia, Pino G. & Brion, Sebastien, 2007. "Reluctant to change: Self-enhancing responses to diverging performance measures," Organizational Behavior and Human Decision Processes, Elsevier, vol. 102(2), pages 255-269, March.
    5. Cassiman, Bruno & Di Guardo, Maria Chiara & Valentini, Giovanni, 2010. "Organizing links with science: Cooperate or contract?: A project-level analysis," Research Policy, Elsevier, vol. 39(7), pages 882-892, September.
    6. Nathalie Lazaric & Alain Raybaut, 2014. "Do incentive systems spur work motivations of inventors in high-tech firms," Post-Print halshs-00930186, HAL.
    7. Davila, Antonio, 2003. "Short-term economic incentives in new product development," Research Policy, Elsevier, vol. 32(8), pages 1397-1420, September.
    8. Lazzarotti, Valentina & Manzini, Raffaella & Mari, Luca, 2011. "A model for R&D performance measurement," International Journal of Production Economics, Elsevier, vol. 134(1), pages 212-223, November.
    9. Cherchye, L. & Abeele, P. Vanden, 2005. "On research efficiency: A micro-analysis of Dutch university research in Economics and Business Management," Research Policy, Elsevier, vol. 34(4), pages 495-516, May.
    10. Subramaniam Ananthram & Cecil Pearson & Samir Chatterjee, 2010. "Do organisational reform measures impact on global mindset intensity of managers?: Empirical evidence from Indian and Chinese service industry managers," Journal of Chinese Economic and Foreign Trade Studies, Emerald Group Publishing, vol. 3(2), pages 146-168, June.
    11. Cassiman, Bruno & Guardo, Chiara di & Valentini, Giovanni, 2005. "Organizing for innovation: R&D projects, activities and partners," IESE Research Papers D/597, IESE Business School.
    12. Davila, Tony, 2000. "Performance and the Design of Economic Incentives in New Product Development," Research Papers 1647, Stanford University, Graduate School of Business.
    13. Hauser, John R. & Katz, Gerald M. & International Center for Research on the Management of Technology., 1998. "Metrics : you are what you measure!," Working papers 172-98, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    14. Berg, Pekka & Leinonen, Mikko & Leivo, Virpi & Pihlajamaa, Jussi, 2002. "Assessment of quality and maturity level of R&D," International Journal of Production Economics, Elsevier, vol. 78(1), pages 29-35, July.


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