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The Effect of Task Uncertainty and Decentralization on Project Team Performance

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Abstract

This paper investigates relationships among task uncertainty, level of centralization, and project team performance. Team performance is measured in three dimensions: cost, time, and quality. Adopting an information processing view and contingency theory, the authors discuss tradeoffs among the three performance dimensions of a project team. Results from the simulation study indicate that, under high task uncertainty, a decentralized team performs better in terms of cost and time, but a centralized team performs better in terms of quality. Under low task uncertainty, there is no performance difference between a centralized team and a decentralized team in terms of cost and time, but a centralized team performs better in terms of quality. The paper suggests that researchers pay attention to the relative impact of centralization and decentralization on different dimensions of organizational performance, and managers adopt an organizational structure that performs better in a performance dimension that counts more to enhance overall performance.

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References

  • Bourgeois, L.J. III (1985), “Strategic Goals, Perceived Uncertainty, and Economic Performance in Volatile Environments,” Academy of Management Journal, 28(3), 548–573.

    Google Scholar 

  • Burton, R.M. and B. Obel (1998), Strategic Organizational Diagnosis and Design: Developing Theory for Application. Kluwer Academic Publishers, Boston, MA.

    Google Scholar 

  • Burton, R.M. and B. Obel (1995), “The Validity of Computational Models in Organization Science: From Model Realism to Purpose of the Model,” Computational and Mathematical Organization Theory, 1(1), 57–71.

    Google Scholar 

  • Campion, M.A., G.J. Medsker and A.C. Higgs (1993), “Relations Between Work Group Characteristics and Effectiveness: Implications for Designing Effective Work Groups,” Personnel Psychology, 46(4), 823–850.

    Google Scholar 

  • Carley, K.M. (1995), “Computational and Mathematical Organization Theory: Perspective and Directions,” Computational and Mathematical Organization Theory, 1(1), 39–65.

    Google Scholar 

  • Carley, K.M. and Z. Lin (1997), “A Theoretical Study of Organizational Performance under Information Distortion,” Management Science, 43(7), 976–997.

    Google Scholar 

  • Carley, K.M. and D.M. Svoboda (1997), “Modeling Organizational Adaptation as a Simulated Annealing Process,” Sociological Methods and Research, 25(1), 138–168.

    Google Scholar 

  • Chang, M. and J.H. Harrington, Jr. (1998), “Organizational Structure and Firm Innovation in a Retail Chain,” Computational & Mathematical Organization Theory, 3(4), 267–288.

    Google Scholar 

  • Daft, R.L. and N.B. Macintosh (1981), “A Tentative Exploration into the Amount and Equivocality of Information Processing in Organizational Work Units,” Administrative Science Quarterly, 26, 207–224.

    Google Scholar 

  • D'Aveni, R.A. (1994), Hypercompetition: Managing the Dynamics of Strategic Maneuvering. Free Press, New York.

    Google Scholar 

  • Donaldson, L. (1996), “Normal Science of Structural Contingency Theory,” in S.R. Clegg, C. Hardy and W.R. Nord (Eds.) Handbook of Organizational Studies. London: Sage.

    Google Scholar 

  • Eisenhardt, K.M. (1989), “Making Fast Strategic Decisions in High-Velocity Environments,” Academy of Management Journal, 32(3), 543–575.

    Google Scholar 

  • Eisenhardt, K.M. (1993), “High Reliability Organizations Meet High Velocity Environments: Common Dilemmas in Nuclear Power Plants, Aircraft Carriers, and Microcomputer Firms,” in K.H. Roberts (Ed.) New Challenges to Understanding Organizations. New York: Macmillan Publishing Company.

    Google Scholar 

  • Galbraith, J. (1973), Designing Complex Organizations. Addison-Wesley Publishing Co., Reading, MA.

    Google Scholar 

  • Gigone, D. and R. Hastie (1993), “The Common Knowledge Effect: Information Sharing and Group Judgment,” Journal of Personality and Social Psychology, 65, 959–974.

    Google Scholar 

  • Gittell, J.H. (2000), “Paradox of Coordination and Control,” California Management Review, 42(3), 101–117.

    Google Scholar 

  • Guzzo, R.A. and M.W. Dickson (1996), “Teams in Organizations: Recent Research on Performance and Effectiveness,” Annual Review of Psychology, 47, 304–338.

    Google Scholar 

  • Hackman, J.R. (1987), “The Design of Work Teams,” in J. Lorsch (Ed.) Handbook of Organizational Behavior. Englewood Cliffs, NJ: Prentice-Hall.

    Google Scholar 

  • Jayaram, J., C. Droge and S.K. Vickery (1999), “The Impact of Human Resource Management Practices on Manufacturing Performance,” Journal of Operations Management, 18, 1–20.

    Google Scholar 

  • Jin, Y. and R.E. Levitt (1996), “The Virtual Team Design: A Computational Model of Project Organizations,” Computational and Mathematical Organization Theory, 2(3), 171–195.

    Google Scholar 

  • Keats, B.W. and M.A. Hitt (1988), “A Causal Model of Linkages Among Environmental Dimensions, Macro Organizational Characteristics, and Performance,” Academy of Management Journal, 31(3), 570–598.

    Google Scholar 

  • Kumar, A., P.S. Ow and M.J. Prietula (1993), “Organizational Simulation and Information Systems Design,” Management Science, 39(2), 218–240.

    Google Scholar 

  • Lawrence, P.R. and J.W. Lorsch (1967), Organization and Environment: Managing Differentiation and Integration. Harvard Business School Press, Boston, MA.

    Google Scholar 

  • Levine, J.M. and R.L. Moreland (1998), “Small Groups,” in D.T. Gilbert, S.T. Fiske and G. Lindzey (Eds.) The Handbook of Social Psychology. Boston: McGraw-Hill.

    Google Scholar 

  • Levitt, R.E., G.P. Cohen, J.C. Kunz, C.I. Nass, T. Christiansen and Y. Jin (1994), “The 'Virtual Design Team': Simulating How Organization Structure and Information Processing Tools Affect Team Performance,” in K.M. Carley and M.J. Prietula (Eds.) Computational Organization Theory. Lawrence Earlbaum Associates.

  • Lin, Z. and K.M. Carley (1997), “Organizational Response: The Cost PerformanceTradeoff,”Management Science, 43(2), 217–234.

    Google Scholar 

  • Lin, Z. and K.M. Carley (2003), Designing Stress Resistant Organizations: Computational Theorizing and Crisis Applications. Boston, MA: Kluwer Academic Publishers.

    Google Scholar 

  • March, J.G. and H.A. Simon (1958), Organizations. Wiley, New York.

    Google Scholar 

  • McGrath, J.E. (1984), Groups: Interaction and Performance. Prentice-Hall, Englewood Cliffs, NJ.

    Google Scholar 

  • Mohr, L.B. (1971), “Organizational Technology and Organizational Structure,” Administrative Science Quarterly, 16(4), 444–459.

    Google Scholar 

  • Murray, A.I. (1989), “Top Management Group Heterogeneity and Firm Performance,” Strategic Management Journal, 10, 125–141.

    Google Scholar 

  • Nadler, D. and M. Tuhman (1988), Strategic Organization Design: Concepts, Tools, & Processes. Scott, Foresman and Company, Glenview, IL.

    Google Scholar 

  • O'Leary-Kelly, A.M., J.J. Martocchio and D.D. Frink (1994), “A Review of the Influence of Group Goals on Group Performance,” Academy of Management Journal, 37, 1285–1301.

    Google Scholar 

  • Pennings, J.M. (1975), “The Relevance of the Structural-Contingency Model for Organizational Effectiveness,” Administrative Science Quarterly, 20(3), 393–410.

    Google Scholar 

  • Perrow, C. (1967), “A Framework for the Comparative Analysis of Organizations,” American Sociological Review, 32, 194–208.

    Google Scholar 

  • Phelan, S.E. and Z. Lin (2001), “Promotion Systems and Organizational Performance: A Contingency Model,” Computational Mathematical Organization Theory, 7, 207–232.

    Google Scholar 

  • Pfeffer, J. (1978), Organizational Design. Harlan Davidson, Inc., Arlington Heights, IL.

    Google Scholar 

  • Pfeffer, J. (1997), New Directions for Organization Theory. Oxford University Press, New York.

    Google Scholar 

  • Roberts, K.H. (1990a), “Some Characteristics of One Type of High Reliability Organization,” Organization Science, 1(2), 160–176.

    Google Scholar 

  • Safizadeh, M.H. (1991), “The Case ofWorkgroups in Manufacturing Operations,” California Management Review, 33(4), 61–82.

    Google Scholar 

  • Schoonhoven, C. (1981), “Problems with Contingency Theory: Testing Assumptions HiddenWithin the Language of Contingency 'Theory,'” Administrative Science Quarterly, 26(3), 349–377.

    Google Scholar 

  • Shrivastava, P. and I.I. Mitroff (1987), “Strategic Management of Corporate Crisis,” Columbia Journal of World Business, 22(1), 5–11.

    Google Scholar 

  • Stasser, G. and D. Stewart (1992), “Discovery of Hidden Profiles by Decision-Making Groups: Solving a Problem Versus Making a Judgment,” Journal of Personality and Social Psychology, 63, 426–434.

    Google Scholar 

  • Stasser, G., D. Stewart and G.M. Wittenbaum (1995), “Expert Roles and Information Exchange During Discussion: The Importance of Knowing Who Knows What,” Journal of Experimental Social Psychology, 31, 244–265.

    Google Scholar 

  • Steiner, I.D. (1972), Group Process and Group Productivity. Academic Press, New York.

    Google Scholar 

  • Thompson, J.D. (1967), Organizations in Action. McGraw-Hill, New York.

    Google Scholar 

  • Victor, B. and R.S. Blackburn (1987), “Determinants and Consequences of Task Uncertainty: A Laboratory and Field Investigation,” Journal of Management Studies, 24(4), 387–404.

    Google Scholar 

  • Vité Inc. (2002), SimVision Version 3.8. Mountain View, CA.

  • Ward, P.T., J.K. McCreery, L.P. Ritzman and D. Sharma (1998), “Competitive Priorities in Operations Management,” Decision Sciences, 29(4), 1035–1046.

    Google Scholar 

  • Weick, K.E. and K.H. Roberts (1993), “Collective Mind in Organizations: Heedful Interrelating on Flight Decks,” Administrative Science Quarterly, 38(3), 357–381.

    Google Scholar 

  • Wong, S.S. and R.M. Burton (2001), “Virtual Teams: What are Their Characteristics, and Impact on Team Performance?” Computational and Mathematical Organization Theory, 6, 339–360.

    Google Scholar 

Download references

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Authors and Affiliations

  1. Fuqua School of Business, Duke University, 2138 Campus Drive, Durham, NC, 27708-6245, USA

    Jisung Kim & Richard M. Burton

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  1. Jisung Kim
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  2. Richard M. Burton
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Kim, J., Burton, R.M. The Effect of Task Uncertainty and Decentralization on Project Team Performance. Computational & Mathematical Organization Theory 8, 365–384 (2002). https://doi.org/10.1023/A:1025472702927

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