Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-18T14:02:15.745Z Has data issue: false hasContentIssue false

Chaos in Human Behavior: The Case of Work Motivation

Published online by Cambridge University Press:  10 January 2013

José Navarro*
Affiliation:
Universidad de Barcelona (Spain)
Carlos Arrieta
Affiliation:
Universidad de Costa Rica (Costa Rica)
*
Correspondence concerning this article should be addressed to José Navarro. Facultad de Psicología. Departamento de Psicología Social. Paseo Valle de Hebrón, 171. 08820 Barcelona. (Spain). E-mail: [email protected]

Abstract

This study considers the complex dynamics of work motivation. Forty-eight employees completed a work-motivation diary several times per day over a period of four weeks. The obtained time series were analysed using different methodologies derived from chaos theory (i.e. recurrence plots, Lyapunov exponents, correlation dimension and surrogate data). Results showed chaotic dynamics in 75% of cases. The findings confirm the universality of chaotic behavior within human behavior, challenge some of the underlying assumptions on which work motivation theories are based, and suggest that chaos theory may offer useful and relevant information on how this process is managed within organizations.

Se realizó un estudio con el objetivo de explorar la posible dinámica caótica de la motivación en el trabajo. Cuarenta y ocho trabajadores contestaron un diario sobre su motivación en el trabajo varias veces al día durante cuatro semanas. Las series obtenidas fueron sometidas a diferentes técnicas de análisis no lineal derivadas de la teoría del caos (gráficos de recurrencia, exponentes de Lyapunov, dimensión de correlación y surrogate data). Los resultados mostraron dinámicas caóticas en un 75% de los casos. Ello confirma la universalidad del comportamiento caótico también dentro del comportamiento humano. Tales resultados cuestionan algunos de los supuestos fundamentales en los que se basan las teorías más establecidas y sugieren que la teoría del caos puede ofrecer información útil y relevante acerca de cómo gestionar la motivación en contextos laborales.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abraham, F. D.& Gilgen, A. R. (Eds.). (1995). Chaos theory in psychology. Westport, CT: Prager Publishers.Google Scholar
Ancona, D. G., Goodman, P.& Tushman, M. (2001). Time: a new research lens. Academy of Management Review, 26(4), 645663.Google Scholar
Ancona, D. G., Okhuysen, G.& Perlow, L. (2001). Taking time to integrate temporal research. Academy of Management Review, 26(4), 512529.Google Scholar
Arthur, W. B. (1999). Complexity and the Economy. Science, 284, 107109.Google Scholar
Bahrami, B., Seyedsadjadi, R., Babadi, B.& Noroozian, M. (2005). Brain complexity increases in mania. Neuroreport: For Rapid Communication of Neuroscience Research, 16(2), 187191.Google Scholar
Bandura, A. (1997). Self-efficacy: the exercise of control. New York: Freeman.Google Scholar
Belaire-Franch, J.& Contreras, D. (2002). Recurrence plots in nonlinear time series analysis: free software. Journal of Statistical Software, 7(9), 118.CrossRefGoogle Scholar
Bolger, N., Davis, A.& Rafaeli, E. (2003). Diary methods: Capturing life as it is lived. Annual Review of Psychology, 54, 579616.Google Scholar
Cheng, Y. T.& Van de Ven, A. H. (1996). Learning the innovation journey: Order out chaos? Organization Science, 7(6), 593614.Google Scholar
Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. NY: Harper and Row Publishers.Google Scholar
Cvitanovic, P. (1989). Universality in chaos (2nd ed.). Bristol: Adam Hilger.Google Scholar
Dalal, R. S.& Hulin, C. L. (2008). Motivation for what? A multivariante dynamic perspective of the criterion. In Kanfer, R., Chen, G. & Pritchard, R. (Eds.), Work motivation. Past, present and future (pp. 63100). New York: Routledge.Google Scholar
Dechert, W. D. (Ed.). (1996). Chaos theory in economics. Methods, models and evidence. Cheltenham, UK: Edward Elgar Publishing.Google Scholar
Eidukaitis, A., Varoneckas, G.& Zemaityte, D. (2004). Applications of chaos theory in analyzing the cardiac rhythm in healthy subjects at different sleep. Human Physiology, 30(5), 551555.Google Scholar
Fried, Y., & Slowik, L.H. (2004). Enriching goal-setting theory with time: an integrated approach. Academy of Management Review, 29(3), 494–422.Google Scholar
George, J. M.& Jones, G. R. (2000). The role of time in theory and theory building. Journal of Management, 26(4), 657684.Google Scholar
Grassberger, P.& Procaccia, I. (1983). Characterization of strange attractors. Physical Review Letters, 50, 346349.Google Scholar
Guastello, S. J. (1998). Creative problem solving groups at the edge of chaos. Journal of Creative Behavior, 32(1), 3857.Google Scholar
Guastello, S. J. (2002). Managing emergent phenomena: Nonlinear dynamics in work organizations. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Guastello, S. J., Hyde, T.& Odak, M. (1998). Symbolic dynamic patterns of verbal exchange in a creative problem solving group. Nonlinear Dynamics, Psychology, and Life Sciences, 2(1), 3558.Google Scholar
Guastello, S. J., Johnson, E. A.& Rieke, M. L. (1999). Nonlinear dynamics of motivational flow. Nonlinear Dynamics, Psychology, and Life Sciences, 3(3), 259273.Google Scholar
Guastello, S. J., Koopmans, M.& Pincus, D. (Eds.) (2009). Chaos and complexity in psychology: Theory of nonlinear dynamical systems. New York: Cambridge University Press.Google Scholar
Heath, R. A. (2000). Nonlinear dynamics. Techniques and applications in Psychology. Mahwah, NJ: Lawrence Erlbaum Ass.Google Scholar
Hegger, R., Kantz, H.& Schreiber, T. (1999). Practical implementation of nonlinear time series methods: The TISEAN package. Chaos, 9(2), 413435.Google Scholar
Kanfer, R. (1990). Motivational theory and indutrial and organizational psychology. In Dunnette, M. & Hughs, L. M. (Eds.), Handbook of Industrial and Organizational Psychology (pp. 75170). Palo Alto, CA: Consulting Psychologist Press.Google Scholar
Kaplan, D.& Glass, L. (1995). Understanding nonlinear dynamics. New York: Oxford University Press.Google Scholar
Katzell, R. A. (1994). Contemporany meta-trends in industrial and organizational psychology. In Triandis, H. C., Dunnette, M. & Hughs, L. M. (Eds.), Handbook of Industrial and Organizational Psychology (pp. 189). Palo Alto, CA: Consulting Psychologist Press.Google Scholar
Locke, E. A.& Latham, G. P. (2004). What should we do about motivation theory? Six recommendations for the twenty-first century. Academy of Management Review, 29(3), 388403.Google Scholar
Lorenz, E. N. (1995). La esencia del caos [The esence of chaos]. Madrid: Debate. (Original work published 1993).Google Scholar
Masterpasqua, F.& Perna, P. A. (Eds.). (1997). The psychological meaning of chaos. Washington: APA.Google Scholar
Mathews, K. M., White, M. C.& Long, R. G. (1999). Why study the complexity in the social sciences? Human Relations, 52(4), 439462.Google Scholar
McGrath, J. E.& Kelly, J. R. (1986). Time and Human Interaction. New York: Guilford Press.Google Scholar
McGrath, J. E.& Tschan, F. (2004). Temporal matters in social psychology. Examining the role of time in the lives of groups and individuals. Washington, DC. APA.Google Scholar
Mitchell, T.& James, L. (2001). Building better theory: Time and the specification of when things happen. Academy of Management Review, 26(4), 530547.Google Scholar
Mosakowski, E.& Earley, P.C. (2000). A selective review of time assumptions in strategy research. Academy of Management Review, 25(4), 796812.Google Scholar
Munné, F. (2004). El retorno de la complejidad y la nueva imagen del ser humano: Hacia una psicología compleja [The return of complexity and the new image of human being: towards a complex psychology]. Revista Interamericana de Psicología, 38(1), 2129.Google Scholar
Munné, F. (2005). ¿Qué es la complejidad? [What's complexity?]. Encuentros de Psicología Social, 3(2), 617.Google Scholar
Navarro, J., Arrieta, C.& Ballén, C. (2007). An approach to the study of dynamics of work motivation using the diary method. Nonlinear Dynamics, Psychology, and Life Sciences, 11(4), 473498.Google Scholar
Pentland, W. E., Harvey, A. S., Lawton, M. P.& McColl, M. A. (1999). Time use research in social sciences. New York: Plenum Press.Google Scholar
Pincus, D. (2001). A framework and methodology for the study of nonlinear, self-organizing family dynamics. Nonlinear Dynamics, Psychology, and Life Sciences, 5(2), 139173.Google Scholar
Richards, D. (1990). Is strategic decision making chaotic? Behavioral Science, 35, 219232.Google Scholar
Robertson, G. P.& Combs, A. (Eds.). (1995). Chaos theory in psychology and the life sciences. Mahwah, NJ: Lawrence Erlbaum Ass.Google Scholar
Roe, R.A. (2005a). No more variables, please. Giving time a place in work and organizational psychology. In Sinangil, H. Kepir, Avallone, F. y Caetano, A. (Eds.). Convivence in Organizations and Society (pp. 1120). Milano: Guerini.Google Scholar
Roe, R.A. (2005b). Studying time in organizational behavior (on line). Maastricht Research School of Economics of Technology and Organization. Research Memoranda, number 048. (Retrieved March 21, 2009). Available in: http://edocs.ub.unimaas.nl/loader/file.asp?id=1120.Google Scholar
Rosenstein, M. T., Collins, J. J.& De Luca, C. J. (1993). A practical method for calculating largest Lyapunov exponents from small data sets. Physica, 65(D), 117134.Google Scholar
Russo, P. V.& Mandell, A. J. (1983). Metrics from nonlinear dynamics adapted for characterizing the behavior of nonequilibrium enzymatic rate functions. Anals of Biochemistry, 139, 9199.Google Scholar
Scollon, C., Diener, E., Oishi, S.& Biswas-Diener, R. (2005). An experience sampling and cross-cultural investigation of the relation between pleasant and unpleasant affect. Cognition and Emotion, 19(1), 2752.Google Scholar
Schreiber, T.& Schmitz, A. (2000). Surrogate time series. Physica D, 142(3–4), 346382.Google Scholar
Stajkovic, A.& Luthans, F. (1998). Self-efficacy and work-related task performance: A meta-analysis. Psychological Bulletin, 124(2), 240261.Google Scholar
Stam, C. J. (2005). Nonlinear dynamical analysis of EEG and MEG: Review of an emerging field. Clinical Neurophysiology, 116(10), 22662301.Google Scholar
Steers, R. M., Mowday, R. T.& Shapiro, D.L. (2004). The future of work motivation theory. Academy of Management Review, 29(3), 379387.Google Scholar
Tsonis, A. R. (1992). Chaos. From theory to applications. New York: Plenum Press.Google Scholar
Vallacher, R. R.& Nowak, A. (Eds.). (1994). Dynamical systems in social psychology. San Diego. CA: Academic Press.Google Scholar
Vroom, V. H. (1964). Work and motivation. New York: Wiley.Google Scholar
Weber, B.A.& Beverly, R. (2000). Data collection using handheld computers. Nursing Research, 49(3), 173175.Google Scholar
Williams, K. J., Donovan, J. J.& Dodge, T. L. (2000). Self-regulation of performance: Goal establishment and goal revision processes in athletes. Human Performance, 13, 159180.Google Scholar
Wolf, A., Swinney, H. L.& Vastano, J. A. (1985). Determining Lyapunov exponents from a time series. Physica, 16D, 285317.Google Scholar
Woyshville, M.. J., Lackamp, J. M., Eisegart, J. A.& Gilliland, J. A. M. (1999). On the meaning and measurement of affective instability. Clues from chaos theory. Biological Psychiatry, 45(3), 261299.Google Scholar
Yeragani, V. K., Rao, K. A., Smitha, M. R., Pohl, R. B., Balon, R.& Srinivasan, K. (2002). Diminished chaos of heart rate time series in patients with major depression. Biological Psychiatry, 51(9), 733744.Google Scholar