IDEAS home Printed from https://ideas.repec.org/p/mit/sloanp/2622.html
   My bibliography  Save this paper

The role of mathematical models in the study of product development

Author

Listed:
  • Hauser, John R.

Abstract

Cover title. Prepared for the 1996 Paul D. Converse Award Symposium, May 6-8, 1996 at the University of Illinois. "April 1996."

Suggested Citation

  • Hauser, John R., 1996. "The role of mathematical models in the study of product development," Working papers #148-96. Working paper (S, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    • Handle: RePEc:mit:sloanp:2622
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/1721.1/2622
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. Jaffe, Adam B, 1986. "Technological Opportunity and Spillovers of R&D: Evidence from Firms' Patents, Profits, and Market Value," American Economic Review, American Economic Association, vol. 76(5), pages 984-1001, December.
    3. Patrick Barwise, 1995. "Good Empirical Generalizations," Marketing Science, INFORMS, vol. 14(3_supplem), pages 29-35.
    4. Abel P. Jeuland & Steven M. Shugan, 1983. "Managing Channel Profits," Marketing Science, INFORMS, vol. 2(3), pages 239-272.
    5. Bernard Pras & Gilles Laurent & Gary L. Lilien, 1994. "Research Traditions in Marketing," Post-Print halshs-00150675, HAL.
    6. Hauser, John R. & Zettelmeyer, Florian., 1996. "Evaluating and managing the tiers of R&D," Working papers #145-96. Working paper (S, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    7. Michael Spence, 1973. "Job Market Signaling," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 87(3), pages 355-374.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. de Rassenfosse, Gaétan, 2013. "Do firms face a trade-off between the quantity and the quality of their inventions?," Research Policy, Elsevier, vol. 42(5), pages 1072-1079.
    2. Matthias Firgo & Peter Mayerhofer, 2015. "Wissens-Spillovers und regionale Entwicklung - welche strukturpolitische Ausrichtung optimiert des Wachstum?," Working Paper Reihe der AK Wien - Materialien zu Wirtschaft und Gesellschaft 144, Kammer für Arbeiter und Angestellte für Wien, Abteilung Wirtschaftswissenschaft und Statistik.
    3. Stefano Brusoni & Paola Criscuolo & Aldo Geuna, 2005. "The knowledge bases of the world's largest pharmaceutical groups: what do patent citations to non-patent literature reveal?," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 14(5), pages 395-415.
    4. Figueroa, Nicolás & Serrano, Carlos J., 2019. "Patent trading flows of small and large firms," Research Policy, Elsevier, vol. 48(7), pages 1601-1616.
    5. Bart Leten & Rene Belderbos & Bart Van Looy, 2016. "Entry and Technological Performance in New Technology Domains: Technological Opportunities, Technology Competition and Technological Relatedness," Journal of Management Studies, Wiley Blackwell, vol. 53(8), pages 1257-1291, December.
    6. Nesta, Lionel, 2008. "Knowledge and productivity in the world's largest manufacturing corporations," Journal of Economic Behavior & Organization, Elsevier, vol. 67(3-4), pages 886-902, September.
    7. Anindya Ghosh & Thomas Klueter, 2022. "The Role of Frictions due to Top Management in Alliance Termination Decisions: Insights from Established Bio‐Pharmaceutical Firms," Journal of Management Studies, Wiley Blackwell, vol. 59(5), pages 1315-1353, July.
    8. Oh, Jong-Min, 2017. "Absorptive capacity, technology spillovers, and the cross-section of stock returns," Journal of Banking & Finance, Elsevier, vol. 85(C), pages 146-164.
    9. Choi, Mincheol & Lee, Chang-Yang, 2021. "Technological diversification and R&D productivity: The moderating effects of knowledge spillovers and core-technology competence," Technovation, Elsevier, vol. 104(C).
    10. Dibiaggio, Ludovic & Nasiriyar, Maryam & Nesta, Lionel, 2014. "Substitutability and complementarity of technological knowledge and the inventive performance of semiconductor companies," Research Policy, Elsevier, vol. 43(9), pages 1582-1593.
    11. Turanay Caner & Susan K. Cohen & Frits Pil, 2017. "Firm heterogeneity in complex problem solving: A knowledge-based look at invention," Strategic Management Journal, Wiley Blackwell, vol. 38(9), pages 1791-1811, September.
    12. Matthias Firgo & Peter Mayerhofer, 2015. "Wissensintensive Unternehmensdienste, Wissens-Spillovers und regionales Wachstum. Teilprojekt 1: Wissens-Spillovers und regionale Entwicklung – Welche strukturpolitische Ausrichtung optimiert das Wach," WIFO Studies, WIFO, number 58342, April.
    13. Chen, Sheng-Syan & Chen, Yan-Shing & Liang, Woan-lih & Wang, Yanzhi, 2020. "Public R&D spending and cross-sectional stock returns," Research Policy, Elsevier, vol. 49(1).
    14. Elisabeth Bublitz, 2018. "Matching skills of individuals and firms along the career path," Oxford Economic Papers, Oxford University Press, vol. 70(2), pages 509-537.
    15. Michael J. Orlando, 2000. "On the importance of geographic and technological proximity for R&D spillovers : an empirical investigation," Research Working Paper RWP 00-02, Federal Reserve Bank of Kansas City.
    16. Jason Li-Ying & Yuandi Wang & Lutao Ning, 2016. "How do dynamic capabilities transform external technologies into firms’ renewed technological resources? – A mediation model," Asia Pacific Journal of Management, Springer, vol. 33(4), pages 1009-1036, December.
    17. Wang, Yanzhi, 2023. "Trade secrets laws and technology spillovers," Research Policy, Elsevier, vol. 52(7).
    18. Li, Zhengyu, 2016. "Essays on knowledge sourcing and technological capability : A knowledge structure perspective," Other publications TiSEM b8ff31fc-c57b-4bc3-b5a4-0, Tilburg University, School of Economics and Management.
    19. Michael J. Orlando, 2002. "Measuring R & D spillovers : on the importance of geographic and technological proximity," Research Working Paper RWP 02-06, Federal Reserve Bank of Kansas City.
    20. Shixiang Wang & Minyuan Zhao, 2018. "A tale of two distances: a study of technological distance, geographic distance and multilocation firms," Journal of Economic Geography, Oxford University Press, vol. 18(5), pages 1091-1120.

    More about this item

    Keywords

    HD28 .M414 no.3901-96;

    JEL classification:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mit:sloanp:2622. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: None (email available below). General contact details of provider: https://edirc.repec.org/data/ssmitus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.