Local Rules and Fitness Landscapes: A Catastrophe Model

  • Tim Haslett
  • Simon Moss
  • Charles Osborne
  • Paul Ramm


This paper examines the imposition of “local rules” in five mail delivery centres of Australia Post. Local rules are patterns of behaviour used by subunits of an organization to optimise their payoff. These local rules may ultimately benefit the total organization. Fitness landscapes are used to examine the emergence of local rules in this workplace. This research examined the relationship between the time taken to sort the mail and the volume of this mail. Work rates show a clear catastrophe shift; that is, work rates suddenly drop when the volume of mail exceeds a certain level, as Postal Delivery Officers apply local rules to maximise gains inherent in the pay structures. Such behaviour is close to that predicted by Kauffman (1995) in computer simulations of lattices and may be indicative of the application of local rules in organizations. The implications of the use of local rules are that behaviour in social systems may be dictated by systemic and emergent processes which are outside immediate management control. A further implication is that organizations may be structured to a significant extent by such local rules.

local rules fitness landscapes work effort catastrophe shift adaptive behaviour 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Akerlof, G. A. (1982). Labor contracts as partial gift exchange. Quarterly Journal of Economics, 97: 543-568.Google Scholar
  2. Albanese, R. & Van Fleet, D. D., (1985). Rational Behavior in Groups: The Free-Riding Tendency. Academy of Management Review, 10: 244-255.Google Scholar
  3. Alexander, R., Herbert, G., DeSchon, R., & Hanges, P. (1992). An examination of least squares regression modelling catastrophe theory. Psychological Bulletin, 111: 366-379.Google Scholar
  4. Alfano, G. & Marwell. G. (1980). Experiments on the provision of public goods by groups III: Nondivisibility and free riding in “real” groups. Social Psychology Quarterly, 43: 300-309.Google Scholar
  5. Barua, A., Lee, C-H. & Whinston, A. B. (1995). Incentives and computing systems for teambased organizations. Organization Science, 6: 487-504.Google Scholar
  6. Brickner, M. A., Harkins, S. G., & Ostrom, T. M. (1986). Effects of personal involvement: Thought-provoking implications for social loafing. Journal of Personality and Social Psychology, 51: 763-769.Google Scholar
  7. Brief, A. P., & Aldag, R. J. (1989). The economic functions of work. In G. R. Ferris and K. M. Rowland (Eds.), Research in personnel and human resources management: (pp. 1-23). Greenwich: JAI Press.Google Scholar
  8. Carneal, J. P. & Fuller, C. R. (1995) A biologically inspired controller. Journal of the Acoustical Society of America, 98: 386-96.Google Scholar
  9. Cooper, C. L., Dyck, B., & Frohlich, N. (1992). Improving the effectiveness of gainsharing: The role of fairness and participation. Administrative Science Quarterly, 37: 471-490.Google Scholar
  10. Cruz, J. M. & Chua, L. O. (1995). Application of cellular neural networks to model population dynamics. IEEE Transactions on Circuits & Systems. Part I, Fundamental Theory and Applications, 42: 715-20.Google Scholar
  11. Earley, P. C. (1989). Social loafing and collectivism: A comparison of the United States and the People' Republic of China. Administrative Science Quarterly, 34: 565-581.Google Scholar
  12. Epstein, J. M & Axtell, R. (1996). Growing artificial societies: Social science from the bottom up. Complex Adaptive Systems series. Cambridge and London: MIT Press.Google Scholar
  13. Feldman, B. & Nagel K. (1993). Lattice games with strategic takeover. In L. Nadel & D. Stein (Eds) 1992 Lectures in Complex Systems: SFI Studies in the Sciences of Complexity,. (pp. 603-614), Reading, MA: Addison-Wesley.Google Scholar
  14. Fehr, E., Kirchsteiger, G., & Riedl, A. (1996). Involuntary unemployment and non-compensating wage differentials in an experimental labour market. Economic Journal, 106: 106-121.Google Scholar
  15. Flay, B. R. (1978). Catastrophe theory in social psychology: some applications to attitudes and social behavior. Behavioral Science, 23: 334-350.Google Scholar
  16. George, J. M. (1992). Extrinsic and intrinsic origins of perceived social loafing in organizations. Academy of Management Journal, 35: 191-202.Google Scholar
  17. Gresov, C., Haveman, H. A., and Oliva, T. A. 1993. Organizational design, inertia and the dynamics of competitive response. Organizational Science, 4: 181-207.Google Scholar
  18. Grover, W. D. (1997). Self-organizing broad-band transport networks. Proceedings of the IEEE, 85: 1582-611.Google Scholar
  19. Guastello, S. J. (1981). Catastrophe modelling of equity in organizations. Behavioral Science, 26: 63-74.Google Scholar
  20. Guastello, S. J. (1982). Moderator regression and the cusp catastrophe: Application of two-stage personnel selection, training, therapy and policy evaluation. Behavioral Science, 27, 259-272.Google Scholar
  21. Guastello, S. J. (1982). Color matching and shift work: An industrial application of the cuspdifference equation. Behavioral Science, 27: 131-139.Google Scholar
  22. Guastello S. J. (1985). Euler buckling in a wheelbarrow obstacle course: A catastrophe with complex lag. Behavioral Science, 30: 204-212.Google Scholar
  23. Guastello S. J. (1987). A butterfly catastrophe model of motivation in organizations: academic performance. Journal of Applied Psychology 72: 165-182.Google Scholar
  24. Guastello S. J. (1988). Catastrophe modelling of the accident process: Organizational subunit size. Psychological Bulletin 103: 246-255.Google Scholar
  25. Guastello S. J. (1991). Psychosocial variables related to transit accidents. Work and Stress 5: 17-28.Google Scholar
  26. Guastello S. J. (1992). Clash of paradigms: A critique of the examination of the polynomial regression technique for evaluating catastrophe theory hypotheses. Psychological Bulletin 111: 375-379.Google Scholar
  27. Guastello, S.J. (1995). Chaos, catastrophe and human affairs. Applications of nonlinear dynamics to work, organizations and social evolution. Mahwah, New Jersey: Erbaum.Google Scholar
  28. Guastello, S. J. (1998). Self organization in leadership emergence Nonlinear Dynamics, Psychology, and the Life Sciences 2: 303-316.Google Scholar
  29. Hanges, P. J., Braverman, E. P., and Rentsch, J. R. (1991). Changes in raters' perceptions of subordinates: a catastrophe model. Journal of Applied Psychology 76: 878-888.Google Scholar
  30. Harkins, S. G., Latane, B., & Williams, K. (1980). Social loafing: Allocating effort or taking it easy. Journal of Experimental Social Psychology 16: 457-465.Google Scholar
  31. Harkins, S. G. & Petty, R. E. (1982).The effects of task difficulty and task uniqueness on social loafing. Journal of Personality and Social Psychology 43:, 1214-1229.Google Scholar
  32. Harkins, S. G., & Szymanski, K. (1989). Social loafing and group evaluation. Journal of Personality and Social Psychology 56: 934-941.Google Scholar
  33. Haslett, T. R., Smyrnios, K. & Osborne, C. (1998). A cusp catastrophe analysis of anxiety levels in pre-university students. Journal of Psychology 132: 2-24.Google Scholar
  34. Hansen, D. G. (1997). Worker performance and group incentives: A case study Industrial & Labor Relations Review 51: 37-49.Google Scholar
  35. Herbig, P. A. (1991). A cusp catastrophe model of the adoption of an industrial innovation. Journal of Product Innovation Management, 8, 127-137Google Scholar
  36. Hobsbawm, E. J. (1964). Labouring men: Studies in the history of labour. London: Weidenfeld and Nicolson.Google Scholar
  37. Holland, J. (1989). Using classifier systems to study adaptive nonlinear networks. In D. Stein, (Ed.), Lectures in the Sciences of Complexity, (pp. 463-499), CA: Addison Wesley Longman.Google Scholar
  38. Holland, J (1995). Hidden Order. Reading, Massachusetts: Addison-Wesley.Google Scholar
  39. Huberman, B. A. & Hogg, T. (1993). The emergence of computational ecologies In L Nadel & D. Stein (Eds.), 1992 Lectures in Complex Systems: SFI Studies in the Sciences of Complexity, Lect. Vol. V. (pp. 185-205), Reading, MA: Addison-Wesley.Google Scholar
  40. Huberman, B. A. & Hogg, T. (1993). Better than the best: the power of cooperation In L Nadel & D. Stein (Eds.), 1992 Lectures in Complex Systems: SFI Studies in the Sciences of Complexity, Lect. Vol. V. (pp. 163-184), Reading, MA: Addison-Wesley.Google Scholar
  41. Jackson, J. M., & Harkins, S. G. (1985). Equity in effort: An explanation of the social loafing effect. Journal of Personality and Social Psychology, 49, 1199-1206.Google Scholar
  42. Jahoda, M. (1981). Work, employment, and unemployment: Values, theories, and approaches in social research. American Psychologist, 36, 184-191.Google Scholar
  43. Jones, G.R. (1984). Task visibility, free riding, and shirking: Explaining the effect of structure and technology on employee behavior. Academy of Management Review, 9, 684-695.Google Scholar
  44. Judge, T. A. & Chandler, T. D. (1996). Individual-level determinants of employee shirking Relations Industrielles-Industrial Relations, 51, 468-487.Google Scholar
  45. Kandel, E. & Lazear, E. P. (1992). Peer Pressure and Partnerships. Journal of Political Economy, 100, 801-817.Google Scholar
  46. Karau, S. J. & Williams, K. D. (1993). Social loafing: A meta-analytic review and theoretical integration. Journal of Personality and Social Psychology, 65, 681-706.Google Scholar
  47. Karau, S. J. & Williams, K. D. (1995). Social loafing: Research findings, implications, and future directions. Current Directions in Psychological Science, 4, 134-140.Google Scholar
  48. Kauffman, S.A. (1989). Principles of adaptation in complex systems. In D. Stein, (Ed.), Lectures in the Sciences of Complexity SFI Studies in the Sciences of Complexity, (pp. 527-618), CA: Addison Wesley Longman.Google Scholar
  49. Kauffman, S.A. (1989). Adaptation on Rugged Fitness Landscapes. In D. Stein, (Ed.), Lectures in the Sciences of Complexity SFI Studies in the Sciences of Complexity, (pp. 619-712). CA: Addison Wesley Longman.Google Scholar
  50. Kaufman, R. G., & Oliva, T. A. (1994). Multivariate catastrophe model estimation: method and application. Academy of Management Journal, 47, 206-221.Google Scholar
  51. Kerr, N. L., & Bruun, S. E. (1983). Dispensability of member effort and group motivation losses: Free-rider effects. Journal of Personality and Social Psychology, 44, 78-94.Google Scholar
  52. Kidwell, R. E. Jr. & Bennett, N. (1993). Employee propensity to withhold effort: A conceptual model to intersect three avenues research. Academy of Management Review, 18, 429-456.Google Scholar
  53. Knoke, D. (1990). Organizing for collective action: The political economies of associations. New York: de Gruyter.Google Scholar
  54. Latane, B., Williams, K. D., & Harkins, S. (1979). Many hands make light the work: The causes and consequences of social loafing. Journal of Personality and Social Psychology, 37, 822-832.Google Scholar
  55. Lazear, E. (1986). Salaries and Piece Rates. Journal of Business, 59, 405-431.Google Scholar
  56. Marwell, G. & Ames, R. E. (1979). Experiments on the provision of public goods, I: Resources, interest, group size, and the free-rider problem. American Journal of Social Psychology, 84, 1335-1360.Google Scholar
  57. Marwell, G., & Ames, R. E. (1980). Experiments on the provision of public goods, II: Resources, interest, group size, and the free-rider problem. American Journal of Sociology, 85, 926-937.Google Scholar
  58. Marwell, G., & Ames, R. E. (1981). Economists free ride, does anyone else? Experiments on the provision of public goods. Journal of Public Economics, 15, 295-310.Google Scholar
  59. Nalbantian, H. R. & Schotter, A. (1997). Productivity under group incentives: An experimental study. American Economic Review, 87, 314-341.Google Scholar
  60. Oliva T. A., Desarbo, W.S., Day, D.L. & Jedidi, K. (1987). GEMCAT; A general multivariate methodology for estimating catastrophe models. Behavioral Science, 32, 121-137.Google Scholar
  61. Oliva, T. A., Oliver, R. L. & MacMillan, I. C. (1992) A catastrophe model for developing service satisfaction strategies. Journal of Marketing, 56, 83-95.Google Scholar
  62. Olson, M. (1965) The logic of collective action: Public goods and the theory of groups. Cambridge, MA: Harvard University Press.Google Scholar
  63. Orbell, J., & Dawes, R. (1981). Social dilemmas. In G. M. Stephenson and M. Davis (Eds.), Progress in applied social psychology, vol. 1 (pp. 37-63). Wiley: New York.Google Scholar
  64. Osterman, P. (1994). Supervision, discretion, and work organization American Economic Review, 84, 380-384.Google Scholar
  65. Rapoport, A. (1987). Research paradigms and expected utility models for the provision of step-level public goods. Psychological Review, 94, 74-83.Google Scholar
  66. Roethlisberger, F. J., & Dickson, W. J. (1939). Management and the worker. Cambridge, MA: Harvard University Press.Google Scholar
  67. Rice, R. W., Phillips, S. M., & McFarlin, D. B. (1990). Multiple discrepancies and pay satisfaction. Journal of Applied Psychology, 75, 386-393.Google Scholar
  68. Rushton, J. P., & Sonentino, R. M. (Eds.), (1981). Alruism and helping behavior: Social personality and developmental perspectives. Hillsdale, NJ: Erlbaum.Google Scholar
  69. Shepperd, J. A. (1993). Productivity loss in performance groups:Amotivation analysis. Psychological Bulletin, 113, 67-81.Google Scholar
  70. Sheridan, J. E. (1985). The catastrophe model of employee withdrawal leading to low job performance, high absenteeism, and job turnover during the first year of employment. Academy of Management Journal, 28, 88-109.Google Scholar
  71. Spicer, M. W. (1985). A public choice approach to motivating people in bureaucratic organizations. Academy of Management Review, 10, 518-526.Google Scholar
  72. Taylor, F. W. (1911). The principles of scientific management. New York, Harper.Google Scholar
  73. Thornton, B. S. & Hung, W. T. (1996). Catastrophe theory implications for rightsizing when planning interim solutions for progressing from a partial mainframe to client-server distributed databases: 3D previewing of possible problems. SIAM Review, 38, 487-95.Google Scholar
  74. Vroom, V. (1964). Work and motivation. New York: Wiley.Google Scholar
  75. Wagner, J. A. (1995). Studies of individualism-collectivism: Effects on cooperation in groups. Special Issue: Intra-and Interorganizational Cooperation. Academy of Management Journal, 38, 152-172.Google Scholar
  76. Williams, K., Harkins, S., & Latane, B. (1981). Identifiability as a deterrent to social loafing: Two cheering experiments. Journal of Personality and Social Psychology, 40, 303-311.Google Scholar
  77. Williams, K. D., Karau, S. J. & Bourgeois, M. J. (1993). Working on collective tasks: Social loafing and social compensation. In M. A. Hogg & D. Abrams, (Eds.), Group motivation: Social psychological perspectives (pp. 130-148). London: Harvester Wheatsheaf.Google Scholar
  78. Yellen, J. (1984). Efficiency wage models of unemployment. American Economic Review Proceedings. 74, 200-205.Google Scholar
  79. Zeeman, E. C., Hall, C. S., Harrison P. J., Marriage, G. H., & Shapland P. H. (1976). A model for institutional disturbances. British Journal of Mathematical and Statistical Psychology, 29, 66-80.Google Scholar

Copyright information

© Human Sciences Press, Inc. 2000

Authors and Affiliations

  • Tim Haslett
    • 1
  • Simon Moss
    • 2
  • Charles Osborne
    • 3
  • Paul Ramm
    • 4
  1. 1.Department of ManagementMonash University, Caulfield EastAustralia
  2. 2.Department of PsychologyMonash UniversityAustralia
  3. 3.Physics DepartmentMonash UniversityVictoriaAustralia
  4. 4.Victoria/Tasmania Retail BrnachAustralia PostAustralia

Personalised recommendations