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Research, Development, and Engineering Metrics

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  • John R. Hauser

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

Abstract

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
    DOI: 10.1287/mnsc.44.12.1670
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    2. 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.
    3. Rosanna Spano & Fabrizia Sarto & Adele Caldarelli & Riccardo Vigano, 2016. "Innovation & Performance Measurement: An Adapted Balanced Scorecard," International Journal of Business and Management, Canadian Center of Science and Education, vol. 11(6), pages 194-194, May.
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    5. Chen, Chung-Chiang, 2010. "A performance evaluation of MSW management practice in Taiwan," Resources, Conservation & Recycling, Elsevier, vol. 54(12), pages 1353-1361.
    6. 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.
    7. Boehlje, Michael & Broring, Stefanie & Roucan-Kane, Maud, 2009. "Innovation In The Food Agricultural Industries: Acomplex Adaptive System," Working papers 56389, Purdue University, Department of Agricultural Economics.
    8. Duncan Simester & Juanjuan Zhang, 2010. "Why Are Bad Products So Hard to Kill?," Management Science, INFORMS, vol. 56(7), pages 1161-1179, July.
    9. Alexander Tkotz & Jan Christoph Munck & Andreas Erich Wald, 2018. "Innovation Management Control: Bibliometric Analysis Of Its Emergence And Evolution As A Research Field," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 22(03), pages 1-34, April.
    10. Juanjuan Zhang, 2016. "Deadlines in Product Development," Management Science, INFORMS, vol. 62(11), pages 3310-3326, November.
    11. 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.
    12. 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.
    13. Nathalie Lazaric & Alain Raybaut, 2014. "Do incentive systems spur work motivations of inventors in high-tech firms," Post-Print halshs-00930186, HAL.
    14. Damien Joseph & Soon Ang & Sandra A. Slaughter, 2015. "Turnover or Turnaway? Competing Risks Analysis of Male and Female IT Professionals’ Job Mobility and Relative Pay Gap," Information Systems Research, INFORMS, vol. 26(1), pages 145-164, March.
    15. Davila, Antonio, 2003. "Short-term economic incentives in new product development," Research Policy, Elsevier, vol. 32(8), pages 1397-1420, September.
    16. 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.
    17. 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.
    18. 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.
    19. Sema Nur Altug & Oya Ekici, 2022. "The Effects of Cooperation Between Internal and External stakeholders in R&D Projects on Perceived Success," Istanbul Management Journal, Istanbul University Business School, vol. 0(92), pages 83-115, June.
    20. Janet Bercovitz & Sandy D. Jap & Jack A. Nickerson, 2006. "The Antecedents and Performance Implications of Cooperative Exchange Norms," Organization Science, INFORMS, vol. 17(6), pages 724-740, December.
    21. Davila, Tony, 2000. "Performance and the Design of Economic Incentives in New Product Development," Research Papers 1647, Stanford University, Graduate School of Business.
    22. 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.
    23. 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.
    24. Robert Shishko & Donald H. Ebbeler & George Fox, 2004. "NASA technology assessment using real options valuation," Systems Engineering, John Wiley & Sons, vol. 7(1), pages 1-13.

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