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Effectiveness of Organizational Responses to Technological Change in the Production Process

Author

Listed:
  • Marcie J. Tyre

    (Massachusetts Institute of Technology, Sloan School of Management, E52-564, Cambridge, Massachusetts 02139)

  • Oscar Hauptman

    (Harvard Business School, Harvard University, Boston, Massachusetts 02163)

Abstract

This paper examines the effectiveness of organizational problem solving in response to technological change in the production process. First, the paper measures the degree of uncertainty associated with a given technological change by examining (1) the novelty of specific new features and functions, and (2) the required departure from established operating assumptions and organizational relationships. Second, the paper identifies three modes of problem solving that organizations use in dealing with technological change: modification prior to implementation (preparatory search), joint work with external technical experts during production start-up (joint search), and integration of engineering and manufacturing functions engaged in start-up (functional overlap). The effectiveness of these approaches is then tested on a sample of 48 new process introductions undertaken in eight plants by a leading global producer of precision metal components. Results indicate that the measured characteristics of technological change are significant predictors of the difficulties encountered in introducing new process technology. Findings also suggest that intensive problem solving efforts can significantly improve change outcomes, both shortening the period of disruption experienced and increasing the operating gains achieved. In addition, there was some evidence that the three organizational problem solving activities discussed here are not equally effective for responding to all types of process change. Specifically, the higher the level of technical novelty involved, the less useful was overlap between engineering and manufacturing functions. This challenges the general prescription that cross-functional team involvement in major technical projects always should be maximized, regardless of the nature of the change involved.

Suggested Citation

  • Marcie J. Tyre & Oscar Hauptman, 1992. "Effectiveness of Organizational Responses to Technological Change in the Production Process," Organization Science, INFORMS, vol. 3(3), pages 301-320, August.
    • Handle: RePEc:inm:ororsc:v:3:y:1992:i:3:p:301-320
    DOI: 10.1287/orsc.3.3.301
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    Citations

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    Cited by:

    1. Vits, Jeroen & Gelders, Ludo & Pintelon, Liliane, 2006. "Production process changes: A dynamic programming approach to manage effective capacity and experience," International Journal of Production Economics, Elsevier, vol. 104(2), pages 473-481, December.
    2. Cheryl Gaimon & Gülru F. Özkan & Karen Napoleon, 2011. "Dynamic Resource Capabilities: Managing Workforce Knowledge with a Technology Upgrade," Organization Science, INFORMS, vol. 22(6), pages 1560-1578, December.
    3. von Hippel, Eric & Tyre, Marcie J., 1995. "How learning by doing is done: problem identification in novel process equipment," Research Policy, Elsevier, vol. 24(1), pages 1-12, January.
    4. Heine, Michelle Lane & Grover, Varun & Malhotra, Manoj K., 2003. "The relationship between technology and performance: a meta-analysis of technology models," Omega, Elsevier, vol. 31(3), pages 189-204, June.
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    7. Lucio Cassia & Tommaso Minola & Stefano Paleari, 2011. "Entrepreneurship, technology and change: a review and proposal for an interpretative framework," Working Papers 1103, Department of Management, Information and Production Engineering, University of Bergamo.
    8. Caron H. St John & Richard W. Pouder & Alan R. Cannon, 2003. "Environmental Uncertainty and Product–Process Life Cycles: A Multi‐level Interpretation of Change Over Time," Journal of Management Studies, Wiley Blackwell, vol. 40(2), pages 513-541, March.
    9. Cesaroni, Fabrizio & Duque, Lola C., 2010. "Marketing for technologies: S-D Logic and the Open Innovation paradigm," DEE - Working Papers. Business Economics. WB wb100702, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    10. Pérez, Carlos J. & Ponce, Carlos J., 2015. "Disruption costs, learning by doing, and technology adoption," International Journal of Industrial Organization, Elsevier, vol. 41(C), pages 64-75.
    11. Tyre, Marcie J. (Marcie Jadine) & Eppinger, Steven D. & Csizinszky, Eva M. H. & Leaders for Manufacturing Program., 1993. "Systematic versus intuitive problem solving on the shop floor : does it matter?," Working papers 3716-93., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    12. Leone, Maria Isabella & Messeni Petruzzelli, Antonio & Natalicchio, Angelo, 2022. "Boundary spanning through external technology acquisition: The moderating role of star scientists and upstream alliances," Technovation, Elsevier, vol. 116(C).
    13. Kelley, Maryellen R. & Arora, Ashish, 1996. "The role of institution-building in US industrial modernization programs," Research Policy, Elsevier, vol. 25(2), pages 265-279, March.
    14. Jordan Vazquez & Cécile Godé & Jean-Fabrice Lebraty, 2019. "Environnement big data et prise de décision intuitive : le cas de la Police Nationale des Bouches du Rhône," Post-Print halshs-02188451, HAL.
    15. Janice E. Carrillo & Cheryl Gaimon, 2004. "Managing Knowledge-Based Resource Capabilities Under Uncertainty," Management Science, INFORMS, vol. 50(11), pages 1504-1518, November.
    16. Dvir, D. & Lipovetsky, S. & Shenhar, A. & Tishler, A., 1998. "In search of project classification: a non-universal approach to project success factors," Research Policy, Elsevier, vol. 27(9), pages 915-935, December.
    17. Bayona, Cristina & Garcia-Marco, Teresa & Huerta, Emilio, 2001. "Firms' motivations for cooperative R&D: an empirical analysis of Spanish firms," Research Policy, Elsevier, vol. 30(8), pages 1289-1307, October.
    18. GuiDeng Say & Gurneeta Vasudeva, 2020. "Learning from Digital Failures? The Effectiveness of Firms’ Divestiture and Management Turnover Responses to Data Breaches," Strategy Science, INFORMS, vol. 5(2), pages 117-142, June.
    19. Anita L. Tucker & Ingrid M. Nembhard & Amy C. Edmondson, 2007. "Implementing New Practices: An Empirical Study of Organizational Learning in Hospital Intensive Care Units," Management Science, INFORMS, vol. 53(6), pages 894-907, June.
    20. Afuah, Allan Nembo. & Utterback, James M., 1941-, 1995. "Dynamic competitive strategies : a technological evolution perspective," Working papers #137-95. Working paper (S, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    21. Virpi Turkulainen & Morgan L. Swink, 2017. "Supply Chain Personnel as Knowledge Resources for Innovation—A Contingency View," Journal of Supply Chain Management, Institute for Supply Management, vol. 53(3), pages 41-59, July.
    22. Bourke, Jane & Roper, Stephen, 2016. "AMT adoption and innovation: An investigation of dynamic and complementary effects," Technovation, Elsevier, vol. 55, pages 42-55.

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