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Transcription:

CIRJE-J-60 2001 8

A note on new product project selection model: Empirical analysis in chemical industry Kenichi KuwashimaUniversity of Tokyo Junichi TomitaUniversity of Tokyo August, 2001 Abstract By focusing its attention on one particular scoring method that is used to evaluate R&D projects, this paper seeks to specify empirically the factors that discriminate successful projects from failed projects in the Japanese chemical industry. Our statistical analysis revealed that when projects are evaluated in this industry, three factors, marketability, technology, and synergistic potential, tend to be valued by practitioners approximately in a 3:2:1 ratio. Although the project evaluations in this research were conducted ex-post, the findings suggest that the results may also be applicable in the project selection stage. Building on our findings, we propose a Continuous Improvement Scoring Method (CISM) that contains continuous improvement cycles and links ex-ante project selection with ex-post project evaluation. 2

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Continuous Improvement Scoring MethodCISM 5

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(1993)12, pp.17-21. (1997)New Score 9, pp.39-47. Asher, D. T. (1962) A linear programming model for the allocation of R and D efforts, IRE Transactions on Engineering Management, EM20(4), pp.114-120. Augood, Derek R. (1973) A review of R&D evaluation methods, IEEE Transactions on Engineering Management, 9(4), pp.154-157. Baker, Norman R. & William Pound (1964) R&D project selection: Where we stand, IEEE Transactions on Engineering Management, EM-11, December, pp.124-134. Baker, Norman. R., William. E. Souder, C. R. Shumway, Micheal P. Maher & Albert. H. Rubenstein (1976) A budget allocation model for large hierarchical R&D organization, Management Science, 23(1), pp.59-70. Clark, Kim B. & Takahiro Fujimoto (1991) Product Development Performance, Harvard Business School Press., 1993 Cooper, Robert G. (1981) An empirically derived new product project selection model, IEEE Transactions on Engineering Management, EM28(3), pp.54-61. Cooper, Robert G. (1985) Selecting Winning New Product Projects: Using the New Prod System, Journal of Product Innovation Management, 2, pp.34-44. Dean, Burton V. & Meir J. Nishry (1965) Scoring and profitability models for evaluating and selecting engineering projects, Operations Research, 13(4), pp.550-569. Disman, Solomon (1962) Selecting R&D projects for profit, Chemical Engineering, 24, December, pp.87-90. Eisenhardt, Kathleen M. & Behnam N. Tabrizi (1995) Accelerating adaptive processes: Product innovation in the global computer industry, Administrative Science Quarterly, 40, March, pp.84-110. (1986) 1(2), pp.152-157. 15

2000. (2000) Discussion Paper Series CIRJE-J-32,. (1998) R&D. Hess, Sidney W. (1962) A dynamic programming approach to R&D budgeting and project selection, IRE Transactions on Engineering Management, 9(4), pp.170-179. 198328(11), pp.4-8. 1993. (1999)33(2), pp.88-104. Mottley, C. M. & R. D. Newton (1959) The selection of projects for industrial research, Operations Research, 7, November-December, pp.740-741. (1992), 7(3), pp.210-223. (1986) 1(1), pp.35-42. POEM (1971). Presley, Adrien & Donald Liles2000R&D validation planning: A methodology to link technical validations to benefits measurement,r&d Management, 30(1), pp.55-65. Schmidt, Robert L. & James R. Freeland (1992) Recent progress in modeling R&D project-selection processes, IEEE Transactions on Engineering Management, 39(2), pp.189-201. Souder, William E. & Tomislav, Mandakovic (1986) R&D project-selection models, Research Management, 29(4), pp.36-42. Stahl, Michael J. & Adrian H. Harrel1983 Identifying operative goals by modeling project selection decisions in research and development, IEEE Transactions on Engineering Management, EM-30(4), pp.223-228. (1996) 4, pp.6-12. (1992), 7(3), pp.198-203. (1998), 13(2), pp.42-47. 16