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Managing Knowledge-Based Resource Capabilities Under Uncertainty

Author

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  • Janice E. Carrillo

    () (Warrington College of Business, University of Florida, Gainesville, Florida 32611-7169)

  • Cheryl Gaimon

    () (DuPree College of Management, Georgia Institute of Technology, Atlanta, Georgia 30332-0520)

Abstract

A firm's ability to manage its knowledge-based resource capabilities has become increasingly important as a result of performance threats triggered by technology change and intense competition. At the manufacturing plant level, we focus on three repositories of knowledge that drive performance. First, the physical production or information systems represent knowledge embedded in the plant's technical systems. Second, the plant's workforce has knowledge, including diverse scientific information and skills, to effectively operate the technical systems. Third, the firm's managerial systems embody knowledge in the form of goals, reward systems, and control and coordination systems. Taken together, we consider the technical systems, workforce knowledge, and the managerial systems as the plant's knowledge-based resource capability. Two normative models are introduced offering insight on how plant performance is impacted by investments in workforce knowledge (training) or the technical systems (process change). The models explicitly recognize that the outcome of investments in knowledge-based change is uncertain due to factors including technical problems, worker resistance, and limited financial resources. Also, we recognize that workforce knowledge may be deployed to mitigate the outcome uncertainty encountered with process change. Investments in knowledge-based change cannot be fully understood in isolation of the managerial systems. In one model, the plant manager is motivated by an incentive system that rewards the realization of a threshold goal, whereas in the other model the incentive system emphasizes the realization of meeting a particular target goal. We also investigate the impact of the manager's view of uncertainty (her willingness to absorb risk), which is influenced by the managerial systems. Results show that different characterizations of the managerial systems have a profound effect on managerial behavior and plant-level performance.

Suggested Citation

  • Janice E. Carrillo & Cheryl Gaimon, 2004. "Managing Knowledge-Based Resource Capabilities Under Uncertainty," Management Science, INFORMS, vol. 50(11), pages 1504-1518, November.
  • Handle: RePEc:inm:ormnsc:v:50:y:2004:i:11:p:1504-1518
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    File URL: http://dx.doi.org/10.1287/mnsc.1040.0234
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    References listed on IDEAS

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    1. Janice E. Carrillo & Cheryl Gaimon, 2000. "Improving Manufacturing Performance Through Process Change and Knowledge Creation," Management Science, INFORMS, vol. 46(2), pages 265-288, February.
    2. James R. Dorroh & Thomas R. Gulledge & Norman K. Womer, 1994. "Investment in Knowledge: A Generalization of Learning By Experience," Management Science, INFORMS, vol. 40(8), pages 947-958, August.
    3. Charles H. Fine, 1986. "Quality Improvement and Learning in Productive Systems," Management Science, INFORMS, vol. 32(10), pages 1301-1315, October.
    4. Gulledge, Thomas Jr. & Khoshnevis, Behrokh, 1987. "Production rate, learning, and program costs: Survey and bibliography," Engineering Costs and Production Economics, Elsevier, vol. 11(4), pages 223-236, April.
    5. Nile W. Hatch & David C. Mowery, 1998. "Process Innovation and Learning by Doing in Semiconductor Manufacturing," Management Science, INFORMS, vol. 44(11-Part-1), pages 1461-1477, November.
    6. Robert D. Dewar & Jane E. Dutton, 1986. "The Adoption of Radical and Incremental Innovations: An Empirical Analysis," Management Science, INFORMS, vol. 32(11), pages 1422-1433, November.
    7. Pisano, Gary P., 1996. "Learning-before-doing in the development of new process technology," Research Policy, Elsevier, vol. 25(7), pages 1097-1119, October.
    8. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    9. Michael A. Lapré & Amit Shankar Mukherjee & Luk N. Van Wassenhove, 2000. "Behind the Learning Curve: Linking Learning Activities to Waste Reduction," Management Science, INFORMS, vol. 46(5), pages 597-611, May.
    10. Paul S. Adler & Kim B. Clark, 1991. "Behind the Learning Curve: A Sketch of the Learning Process," Management Science, INFORMS, vol. 37(3), pages 267-281, March.
    11. Fariborz Damanpour, 1996. "Organizational Complexity and Innovation: Developing and Testing Multiple Contingency Models," Management Science, INFORMS, vol. 42(5), pages 693-716, May.
    12. Charles H. Fine & Robert M. Freund, 1990. "Optimal Investment in Product-Flexible Manufacturing Capacity," Management Science, INFORMS, vol. 36(4), pages 449-466, April.
    13. George Li & S. Rajagopalan, 1998. "Process Improvement, Quality, and Learning Effects," Management Science, INFORMS, vol. 44(11-Part-1), pages 1517-1532, November.
    14. Amit Shankar Mukherjee & Michael A. Lapré & Luk N. Van Wassenhove, 1998. "Knowledge Driven Quality Improvement," Management Science, INFORMS, vol. 44(11-Part-2), pages 35-49, November.
    15. Terwiesch, Christian & E. Bohn, Roger, 2001. "Learning and process improvement during production ramp-up," International Journal of Production Economics, Elsevier, vol. 70(1), pages 1-19, March.
    16. Anne M. Spence & Evan L. Porteus, 1987. "Setup Reduction and Increased Effective Capacity," Management Science, INFORMS, vol. 33(10), pages 1291-1301, October.
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    Citations

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    Cited by:

    1. Vörös, József, 2013. "Multi-period models for analyzing the dynamics of process improvement activities," European Journal of Operational Research, Elsevier, vol. 230(3), pages 615-623.
    2. Cai, Shaohan & Yang, Zhilin, 2014. "On the relationship between business environment and competitive priorities: The role of performance frontiers," International Journal of Production Economics, Elsevier, vol. 151(C), pages 131-145.
    3. Yimin Wang & Wendell Gilland & Brian Tomlin, 2010. "Mitigating Supply Risk: Dual Sourcing or Process Improvement?," Manufacturing & Service Operations Management, INFORMS, vol. 12(3), pages 489-510, September.
    4. Martin-Tapia, Inmaculada & Aragon-Correa, Juan Alberto & Senise-Barrio, Maria Eugenia, 2008. "Being green and export intensity of SMEs: The moderating influence of perceived uncertainty," Ecological Economics, Elsevier, vol. 68(1-2), pages 56-67, December.
    5. Lai, Yung-Lung & Hsu, Maw-Shin & Lin, Feng-Jyh & Chen, Yi-Min & Lin, Yi-Hsin, 2014. "The effects of industry cluster knowledge management on innovation performance," Journal of Business Research, Elsevier, vol. 67(5), pages 734-739.
    6. Izlem Gozukara & Osman Yildirim, 2016. "Exploring the link between Distributive Justice and Innovative Behavior: Organizational Learning Capacity as a Mediator," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 6(2), pages 61-75, April.
    7. Larry J. Menor & M. Murat Kristal & Eve D. Rosenzweig, 2007. "Examining the Influence of Operational Intellectual Capital on Capabilities and Performance," Manufacturing & Service Operations Management, INFORMS, vol. 9(4), pages 559-578, May.
    8. White, Sheneeta W. & Badinelli, Ralph D., 2012. "A model for efficiency-based resource integration in services," European Journal of Operational Research, Elsevier, vol. 217(2), pages 439-447.

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