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Beyond Gaussian averages: redirecting international business and management research toward extreme events and power laws

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Abstract

Practicing managers live in a world of ‘extremes’, but international business and management research is based on Gaussian statistics that rule out such extremes. On occasion, positive feedback processes among interactive data points cause extreme events characterized by power laws. They seem ubiquitous; we list 80 kinds of them – half each among natural and social phenomena. We use imposed tension and Per Bak's ‘self-organized criticality’ to argue that Pareto-based science and statistics (based on interdependence, positive feedback, scalability, (nearly) infinite variance, and emphasizing extremes) should parallel the traditional dominance of Gaussian statistics (based on independent data points, finite variance and emphasizing averages). We question quantitative journal publications depending on Gaussian statistics. The cost is inaccurate science and irrelevance to practitioners. In conclusion, no statistical findings should be accepted into business studies if they gain significance via some assumption device by which extreme events and (nearly) infinite variance are ignored. Accordingly, we suggest redirecting international business studies, and management research in general.

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Notes

  1. In order: Peters and Waterman (1982); Robison (1986); Tichy and Sherman (1994); Bredeson (1999); O'Reilly and Pfeffer (2000); Collins (2001); Fusaro and Miller (2002); Burgelman (2002); Horcajo (2005); Newhouse (2007).

  2. A fractal is ‘a rough or fragmented geometric shape that can be subdivided in parts, each of which is (at least approximately) a reduced copy of the whole’ (Mandelbrot and Hudson, 2004: 121). Similarity across scale is called ‘self-similarity’.

  3. Our discussion of the organizational and managerial implications of scale-free theory appears elsewhere because of obvious space limitations; see Andriani and McKelvey (2007).

  4. ‘Agent’ refers to semi-autonomous entities (i.e., ‘parts’ of systems), such as atoms, molecules, biomolecules, organelles, organs, organisms, species, processes, people, groups, firms, industries, etc.

  5. This is the most comprehensive list of power law phenomena across all sciences to date.

  6. While it appears so in the few words we show, word usage is not a function of word length overall.

  7. TWAs are relatively self-contained economic and social units, calculated by dividing a national territory into units that maximize internal home-to-work commuting and minimize inter-TWA commuting (ISTAT, 1997). TWAs represent an algorithmic way to define the micro-units of analysis of economic geography and economic sociology. In Italy TWAs are organized into a taxonomy (Sforzi, 1990; Cannari and Signorini, 2000) that divides the agglomerations into two groups: industrial-cluster-based (type D) and non-cluster-based (type A) agglomerations. The classification ranks industrial agglomerations according to the probability of including within their boundary an industrial cluster. The theoretical ground for this work is rooted in the Neo-Marshallian theory of industrial clusters (Storper, 1997). Type D: r=0.997, P<0.0001, slope β=−0.995. Type A: r=0.995, P<0.0001, slope β=−0.997.

  8. Actually, ‘we would fix, sell, or close’ (Tichy and Sherman, 1994: 108).

  9. Quoted in West and Deering (1995: 83).

  10. A classic form of this, known as the ‘Bose–Einstein condensate,’ explains the onset of superconductivity: at the tension limit – in this case because of extreme cold – particles shift from independence to interactivity, thereby allowing superconductivity. For more, see: [www document] http://en.wikipedia.org/wiki/Bose-Einstein_condensate (accessed 30 March 2007).

References

  • Abbott, A. (2001) Time Matters, University of Chicago Press: Chicago, IL.

    Google Scholar 

  • Abrams, D.M. and Strogatz, S.H. (2003) ‘Modelling the dynamics of language death’, Nature 424 (6951): 900.

    Article  Google Scholar 

  • Adamic, L.A. and Huberman, B.A. (2000) ‘The nature of markets in the World Wide Web’, Quarterly Journal of Electronic Commerce 1 (1): 5–12.

    Google Scholar 

  • Aiello, W., Chung, F. and Lu, L. (2000) ‘A random graph model for massive graphs’, Proceedings of the 32nd Annual ACM Symposium on Theory of Computing, ACM Press: Portland, OR, pp: 171–180.

    Google Scholar 

  • Albert, R., Jeong, H. and Barabási, A.-L. (1999) ‘Diameter of the World Wide Web’, Nature 401 (6749): 130–131.

    Article  Google Scholar 

  • Anderson, C. (2006) The Long Tail, Random House Business Books: London.

    Google Scholar 

  • Anderson, N., Herriot, P. and Hodgkinson, G.P. (2001) ‘The practitioner–researcher divide in industrial work and organizational (IWO) psychology’, Journal of Occupational and Organizational Psychology 74 (4): 391–411.

    Article  Google Scholar 

  • Anderson, P.W. (1997) ‘Some Thoughts About Distribution in Economics’, in W.B. Arthur, S.N. Durlauf and D.A. Lane (eds.), The Economy as an Evolving Complex System II, Addison-Wesley: Reading, MA, pp: 565–567.

    Google Scholar 

  • Andriani, P. (2003a) ‘The emergence of self-organisation in social systems: the case of the geographic industrial clusters’, Unpublished PhD dissertation, Durham Business School, University of Durham, Durham, UK.

  • Andriani, P. (2003b) ‘Using Complexity Theory to Define Industrial Clusters’, in E. Mitleton-Kelly (ed.), Complex Systems and Evolutionary Perspectives of Organisations, Elsevier: Oxford, pp: 127–146.

    Google Scholar 

  • Andriani, P. and McKelvey, B. (2005) ‘Beyond Gaussian averages: redirecting management research toward extreme events and power laws’, Academy of Management Annual Conference, Honolulu, HA, http://www.dur.ac.uk/resources/dbs/faculty/working-papers/BeyondGaussianAverages19Jun06.pdf (accessed 27 September 2007).

  • Andriani, P. and McKelvey, B. (2007) ‘Extremes, power laws, and scale-free dynamics in organizations: theory and research implications’, Academy of Management Annual Conference, Philadelphia, PA, August.

  • Auerbach, F. (1913) ‘Das Gesetz der Bevolkerungskoncentration’, Petermanns Geographische Mitteilungen 59 (1): 74–76.

    Google Scholar 

  • Axtell, R.L. (2001) ‘Zipf distribution of US firm sizes’, Science 293 (5536): 1818–1820.

    Article  Google Scholar 

  • Bak, P. (1996) How Nature Works: The Science of Self-Organized Criticality, Copernicus: New York.

    Book  Google Scholar 

  • Bak, P. and Sneppen, K. (1993) ‘Punctuated equilibrium and criticality in a simple model of evolution’, Physical Review Letters 71 (24): 4083–4086.

    Article  Google Scholar 

  • Baldwin, C.Y. and Clark, K.B. (2000) Design Rules: The Power of Modularity, MIT Press: Cambridge, MA.

    Google Scholar 

  • Ball, P. (2004) Critical Mass: How One Thing Leads to Another, Farrar, Straus & Giroux: New York.

    Google Scholar 

  • Barabási, A.-L. (2002) Linked: The New Science of Networks, Perseus: Cambridge, MA.

    Google Scholar 

  • Barabási, A.-L. and Bonabeau, E. (2003) ‘Scale-free networks’, Scientific American 288 (May): 60–69.

    Article  Google Scholar 

  • Barabási, A.-L., Albert, L., Jeong, H. and Bianconi, G. (2000) ‘Response to: ‘Power-law distribution of the World-Wide Web’ (by L.A. Adamic and B.A. Huberman)’, Science 287 (5461): 2115a.

    Article  Google Scholar 

  • Baryshev, Y. and Teerikorpi, P. (2002) Discovery of Cosmic Fractals, World Scientific: River Edge, NJ.

    Book  Google Scholar 

  • Battiston, S. and Catanzaro, M. (2003) ‘Statistical properties of corporate board and director networks’, Working paper, Laboratoire de Physique Statistique ENS, Paris.

  • Baum, J.A.C. and Silverman, B.S. (2001) ‘Complexity, Attractors and Path Dependence and Creation in Technological Evolution’, in R. Garud and P. Karnoe (eds.), Path Dependence and Creation, Lawrence Erlbaum: Mahwah, NJ, pp: 169–209.

    Google Scholar 

  • Bennis, W.G. and O'Toole, J. (2005) ‘How business schools lost their way’, Harvard Business Review 83 (5): 96–104.

    Google Scholar 

  • Bettencourt, L.M.A., Lobo, J. and Strumsky, D. (2005) ‘Invention in the city: increasing returns to scale in metropolitan patenting’, Working paper, Harvard Business School, Boston, MA.

  • Bigger Jr, J.T., Steinman, R.C., Rolnitzky, L.M., Fleiss, J.L., Albrecht, P. and Cohen, R.J. (1996) ‘Power law behavior of RR-interval variability in healthy middle-aged persons, patients with recent acute myocardial infarction, and patients with heart transplants’, Circulation 93 (12): 2142–2151.

    Article  Google Scholar 

  • Braybrooke, D. and Lindblom, C.E. (1963) A Strategy of Decision, Free Press: New York.

    Google Scholar 

  • Bredeson, C. (1999) The Challenger Disaster, Enslow: Berkeley Heights, NJ.

    Google Scholar 

  • Brief, A.P. and Dukerich, M. (1991) ‘Theory in Organizational Behavior: Can it be Useful?’, in B.M. Staw (ed.) Research in Organizational Behavior, Vol. 13, JAI Press, Inc.: Greenwich, CT, pp: 327–352.

    Google Scholar 

  • Brock, W.A. (2000) ‘Some Santa Fe scenery’, in D. Colander (ed.) The Complexity Vision and the Teaching of Economics, Edward Elgar: Cheltenham, pp: 29–49.

    Google Scholar 

  • Brú, A., Albertos, S., Luis Subiza, J., García-Asenjo, J.L. and Brú, I. (2003) ‘The universal dynamics of tumor growth’, Biophysical Journal 85 (5): 2948–2961.

    Article  Google Scholar 

  • Buchanan, M. (2000) Ubiquity: The Science of History … or Why the World Is Simpler Than We Think, Weidenfeld & Nicolson: London.

    Google Scholar 

  • Buchanan, M. (2004) ‘Power laws and the new science of complexity management’, Strategy+Business 34 (Spring): 70–79.

    Google Scholar 

  • Buckley, P.J. and Carter, M.J. (2004) ‘A formal analysis of knowledge combination in multinational enterprises’, Journal of International Business Studies 35 (5): 371–384.

    Article  Google Scholar 

  • Buckley, P.J. and Ghauri, P.N. (2004) ‘Globalisation, economic geography and the strategy of multinational enterprises’, Journal of International Business Studies 35 (2): 81–98.

    Article  Google Scholar 

  • Buckley, P.J. and Lessard, D.R. (2005) ‘Regaining the edge for international business research’, Journal of International Business Studies 36 (6): 595–599.

    Article  Google Scholar 

  • Burgelman, R.A. (2002) Strategy is Destiny, Free Press: New York.

    Google Scholar 

  • Camacho, J. and Solé, R.V. (1999) ‘Scaling and Zipf's Law in ecological size spectra’, Working paper, Santa Fe Institute: Santa Fe, NM.

  • Cannari, L. and Signorini, L.F. (2000) ‘Nuovi Strumenti per la Classificazione dei Sistemi Locali’, in L.F. Signorini (ed.), Modelli di Sviluppo Locale, Meridiana: Roma, pp: 123–151.

    Google Scholar 

  • Carneiro, R.L. (1987) ‘The evolution of complexity in human societies and its mathematical expression’, International Journal of Comparative Sociology 28 (2–3): 111–128.

    Google Scholar 

  • Carreras, B.A., Newman, D.E., Dobson, I. and Poole, A.B. (2004) ‘Evidence for self-organized criticality in a time series of electric power system blackouts’, IEEE Transactions on Circuits and Systems I 51 (9): 1733–1740.

    Article  Google Scholar 

  • Casti, J.L. (1994) Complexification, Abacus: London.

    Google Scholar 

  • Cederman, L.E. (2003) ‘Modeling the size of wars: from billiard balls to sandpiles’, American Political Science Review 97 (1): 135–150.

    Article  Google Scholar 

  • Cilliers, P. (1998) Complexity and Postmodernism, Routledge: London.

    Google Scholar 

  • Clementi, F. and Gallegati, M. (2005) ‘Pareto's Law of Income Distribution: Evidence for Germany, the United Kingdom, and the United States’, in A. Chatterjee, S. Yarlagadda and B.K. Chakrabarti (eds.) Econophysics of Wealth Distributions, Springer: Milan, Italy, pp: 3–14.

    Chapter  Google Scholar 

  • Cohen, M.D., March, J.G. and Olsen, J.P. (1972) ‘A garbage can model of organizational choice’, Administrative Science Quarterly 17 (1): 1–25.

    Article  Google Scholar 

  • Collins, J. (2001) Good to Great, HarperBusiness: New York.

    Google Scholar 

  • Cook, W., Ormerod, P. and Cooper, E. (2004) ‘Scaling behaviour in the number of criminal acts committed by individuals’, Journal of Statistical Mechanics: Theory and Experiment [www document] http://www.iop.org/EJ/article/1742-5468/2004/07/P07003/jstat4_07_p07003.html (accessed 31 March 2007).

  • Delli Gatti, D., Di Guilmi, C., Gaffeo, E. and Gallegati, M. (2004) ‘Bankruptcy as an exit mechanism for systems with a variable number of components’, Physica A 334 (1–3): 8–13.

    Article  Google Scholar 

  • De Vany, A. (2004) Hollywood Economics, Routledge: New York.

    Google Scholar 

  • de Solla Price, D.J. (1965) ‘Networks of scientific papers’, Science 149 (3683): 510–515.

    Article  Google Scholar 

  • Dezsö, Z., Almaas, E., Lukács, A., Rácz, B., Szakadát, I. and Barabási, A.-L. (2006) ‘The dynamics of information access on the Web’, Physical Review E 73 (6): 066132 (6 pages).

    Article  Google Scholar 

  • Diatlov, V. (2005) ‘Information technology in practice of organising’, Unpublished PhD dissertation, School of Management, University of Southampton, Southampton, UK.

  • Dumé, B. (2005) ‘Global terrorism follows a power law’, Physicsweb (February): 1–2, [www document] http://physicsweb.org/articles/news/9/2/6/1. (accessed 31 March 2007).

  • Ebel, H., Mielsch, L.-I. and Bornholdt, S. (2002) ‘Scale-free topology of e-mail networks’, Physical Review E 66 (3): 035103 (4 pages).

    Article  Google Scholar 

  • Estoup, J.B. (1916) Gammes Stenographiques, Institut Stenographique de France: Paris.

    Google Scholar 

  • Faloutsos, M., Faloutsos, P. and Faloutsos, C. (1999) ‘On power-law relationships of the Internet topology’, ACM SIGCOMM Computer Communication Review 29 (4): 251–262.

    Article  Google Scholar 

  • Fusaro, P.C. and Ross, M.M. (2002) What Went Wrong at Enron, Wiley: New York.

    Google Scholar 

  • Gardner, M. (1978) ‘White and brown music, fractal curves and 1/f fluctuations’, Scientific American 238 (4): 16–32.

    Article  Google Scholar 

  • Gell-Mann, M. (2002) ‘What is Complexity?’, in A.Q. Curzio and M. Fortis (eds.), Complexity and Industrial Clusters, Physica-Verlag: Heidelberg, pp: 13–24.

    Chapter  Google Scholar 

  • Ghoshal, S. (2005) ‘Bad management theories are destroying good management practices’, Academy of Management Learning and Education 4 (1): 75–91.

    Article  Google Scholar 

  • Goldberger, A.L., Rigney, D.R. and West, B.J. (1990) ‘Chaos and fractals in human physiology’, Scientific American 262 (2): 42–49.

    Article  Google Scholar 

  • Greene, W.H. (2002) Econometric Analysis, 5th edn, Prentice-Hall: Englewood Cliffs, NJ.

    Google Scholar 

  • Gunz, H., Lichtenstein, B.B. and Long, R. (2001) ‘Self-organization in career systems: a view from complexity science’, Management 5 (1): 63–88.

    Google Scholar 

  • Gutenberg, B. and Richter, R.F. (1944) ‘Frequency of earthquakes in California’, Bulletin of the Seismological Society of America 34 (4): 185–188.

    Google Scholar 

  • Hackett, A.P. (1967) 70 Years of Best Sellers, 1895–1965, Bowker: New York.

    Google Scholar 

  • Haire, M. (1959) ‘Biological Models and Empirical Histories of the Growth of Organizations’, in M. Haire (ed.), Modern Organization Theory, Wiley: New York, pp: 272–306.

    Google Scholar 

  • Harzing, A.W. (2002) ‘Acquisitions vs greenfield investments: international strategy and management of entry modes’, Strategic Management Journal 23 (3): 211–227.

    Article  Google Scholar 

  • Haskell, J.P., Ritchie, M.E. and Olff, H. (2002) ‘Fractal geometry predicts varying body size scaling relationships for mammal and bird home ranges’, Nature 418 (6897): 527–530.

    Article  Google Scholar 

  • Haunschild, P.R. and Sullivan, B.N. (2002) ‘Learning from complexity: effects of prior accidents and incidents on airlines’ learning’, Administrative Science Quarterly 47 (4): 609–643.

    Article  Google Scholar 

  • Hegyi, G., Néda, Z. and Santos, M.A. (2007) ‘Wealth distribution and Pareto's law in the Hungarian medieval society’, [www document] http://arxiv.org/abs/physics/0509045 (accessed 27 September 2007).

  • Holland, J.H. (1988) ‘The Global Economy as an Adaptive System’, in P.W. Anderson, K.J. Arrow and D. Pines (eds.), The Economy as an Evolving Complex System, Addison-Wesley: Reading, MA, pp: 117–124.

    Google Scholar 

  • Holton, G. (1993) Science and Anti-Science, Harvard University Press: Cambridge, MA.

    Google Scholar 

  • Horcajo, X. (2005) ‘Tangento’ en Parmalat? La Investigación del caso Parmalat, HTML document available from Amazon.com.

  • Hughes, D., Paczuski, M., Dendy, R.O., Helander, P. and McClements, K.G. (2003) ‘Solar flares as cascades of reconnecting magnetic loops’, Physical Review Letters 90 (13): 131101.

    Article  Google Scholar 

  • Hughes, D.W. and Nathan, H.W. (1994) ‘The distribution of asteroid sizes and its significance’, Planetary and Space Science 42 (4): 291–295.

    Article  Google Scholar 

  • ISTAT INdS (1997) I Sistemi Locali del Lavoro, Vol. 10, Argomenti, ISTAT: Roma.

  • Jenkinson, I.R. (2004) ‘Book review of Handbook of Scaling Methods in Aquatic Ecology (L. Seuront and P.G. Strutton, eds.)’, Journal of Plankton Research 26 (5): 585–587.

    Article  Google Scholar 

  • Kauffman, S.A. (1995) At Home in the Universe, Oxford University Press: Oxford, UK.

    Google Scholar 

  • Kaye, B. (1993) Chaos and Complexity, VCH: New York.

    Google Scholar 

  • Kirchgaessner, S. and Kelleher, E. (2005) ‘UK bombs drive insurance debate’, Financial Times Europe Monday, July 11, p: 5.

  • Koertge, N. (1998) A House Built on Sand: Exposing Postmodernist Myths about Science, Oxford University Press: New York.

    Book  Google Scholar 

  • Krugman, P. (1996) The Self-Organizing Economy, Blackwell: Malden, MA.

    Google Scholar 

  • Lawler, E.E., Mohrman Jr, A.M., Mohrman, S.A., Ledford Jr, G.E. and Cummings, T.G. (1985) Doing Research that is Useful for Theory and Practice, Lexington Books: New York.

    Google Scholar 

  • Lee, Y., Amaral, L.A.N., Canning, D., Meyer, M. and Stanley, H.E. (1998) ‘Universal features in the growth dynamics of complex organizations’, Physical Review Letters 81 (15): 3275–3278.

    Article  Google Scholar 

  • Levy, S. and Donhowe, G. (1962) ‘Exploration of a biological model of industrial organization’, Journal of Business 35 (4): 335–342.

    Article  Google Scholar 

  • Levy, M. and Solomon, S. (1997) ‘New evidence for the power-law distribution of wealth’, Physica A 242 (1–2): 90–94.

    Article  Google Scholar 

  • Liljeros, F., Edling, C.R., Amaral, L.A.N., Stanley, H.E. and Aberg, Y. (2001) ‘The web of human sexual contacts’, Nature 411 (6840): 907–908.

    Article  Google Scholar 

  • Lindblom, C.E. (1959) ‘The science of ‘muddling through’’, Public Administration Review 19 (2): 79–88.

    Article  Google Scholar 

  • Lotka, A.J. (1926) ‘The frequency distribution of scientific productivity’, Journal of the Washington Academy of Sciences 16 (12): 317–323.

    Google Scholar 

  • Luscombe, N.M., Qian, J., Zhang, Z., Johnson, T. and Gerstein, M. (2002) ‘The dominance of the population by a selected few: power-law behaviour applies to a wide variety of genomic properties’, Genome Biology 3 (8): research004.1–research004.7.

    Article  Google Scholar 

  • Mandelbrot, B.B. (1983) The Fractal Geometry of Nature, Freeman: New York.

    Google Scholar 

  • Mandelbrot, B.B. and Hudson, R.L. (2004) The (Mis)Behavior of Markets, Profile: London.

    Google Scholar 

  • Mantegna, R.N. and Stanley, H.E. (2000) An Introduction to Econophysics, Cambridge University Press: Cambridge, UK.

    Google Scholar 

  • Marcus, A.A. and Nichols, M.L. (1999) ‘On the edge: heeding the warnings of unusual events’, Organization Science 10 (4): 482–499.

    Article  Google Scholar 

  • Marsili, M. and Zhang, Y.-C. (1996) ‘Probabilistic fragmentation and effective power law’, Physical Review Letters 77 (17): 3577–3580.

    Article  Google Scholar 

  • McKelvey, B. (2003a) ‘From Fields to Science’, in R. Westwood and S. Clegg (eds.), Debating Organization, Blackwell: Oxford, UK, pp: 47–73.

    Google Scholar 

  • McKelvey, B. (2003b) ‘Postmodernism vs Truth in Management Theory’, in E. Locke (ed.) Research in the Sociology of Organizations, Vol. 21 Elsevier Science: Amsterdam, NL, pp: 113–168.

    Google Scholar 

  • McKelvey, B. (2006) ‘Comment on Van De Ven and Johnson's “Engaged scholarship”: Nice try, but…’, Academy of Management Review 31 (4): 822–829.

    Article  Google Scholar 

  • Meyer, A.D., Gaba, V. and Colwell, K.A. (2005) ‘Organizing far from equilibrium: non-linear change in organizational fields’, Organization Science 16 (5): 456–473.

    Article  Google Scholar 

  • Mintzberg, H. and McHugh, A. (1985) ‘Strategy formation in an adhocracy’, Administrative Science Quarterly 30 (2): 160–197.

    Article  Google Scholar 

  • Mintzberg, H., Ahlstrand, B. and Lampel, J. (1998) Strategy Safari, Pearson Education: London.

    Google Scholar 

  • Mirowski, P. (1989) More Heat Than Light, Cambridge University Press: Cambridge, UK.

    Book  Google Scholar 

  • Moss, S. (2002) ‘Policy analysis from first principles’, Proceedings of the National Academy of Sciences 99 (Suppl. 3): 7267–7274.

    Article  Google Scholar 

  • Nagel, K. and Paczuski, M. (1995) ‘Emergent traffic jams’, Physical Review E 51 (4): 2909–2918.

    Article  Google Scholar 

  • Nahshoni, E., Adler, E., Laniado, S. and Keren, G. (1998) ‘Fractal organization of the pointwise correlation dimension of the heart rate’, Med Hypotheses 51 (5): 367–376.

    Article  Google Scholar 

  • Nekola, J.C. and Brown, J.H. (2007) ‘The wealth of species: ecological communities, complex systems and the legacy of Frank Preston’, Ecology Letters 10 (3): 188–196.

    Article  Google Scholar 

  • Newhouse, J. (2007) Boeing vs Airbus, Knofp: New York.

    Google Scholar 

  • Newman, M.E.J. (2001) ‘The structure of scientific collaboration networks’, Proceedings of the National Academy of Sciences 98 (2): 404–409.

    Article  Google Scholar 

  • Newman, M.E.J. (2005) ‘Power laws, Pareto distributions and Zipf's law’, Contemporary Physics 46 (5): 323–351.

    Article  Google Scholar 

  • Newman, M., Barabási, A.-L. and Watts, D.J. (eds.) (2006) The Structure and Dynamics of Networks, Princeton University Press: Princeton, NJ.

    Google Scholar 

  • Nicolis, G. and Prigogine, I. (1989) Exploring Complexity, Freeman: New York.

    Google Scholar 

  • O’Reilly, C.A. and Pfeffer, J. (2000) Hidden Value, Harvard Business School Press: Boston, MA.

    Google Scholar 

  • Ormerod, P. (1994) The Death of Economics, Wiley: New York.

    Google Scholar 

  • Pareto, V. (1897) Cours d’Economie Politique, Rouge: Paris.

    Google Scholar 

  • Perrow, C. (1984) Normal Accidents, Basic Books: New York.

    Google Scholar 

  • Peters, T.J. and Waterman, R.H. (1982) In Search of Excellence, Harper & Row: New York.

    Google Scholar 

  • Podobnik, B., Fu, D., Jagric, T., Grosse, I. and Stanley, H.E. (2006) ‘Fractionally integrated process for transition economics’, Physica A 362 (2): 465–470.

    Article  Google Scholar 

  • Poincaré, H. (1913) The Foundations of Science, Science Press: New York.

    Google Scholar 

  • Poole, M.S., Van de Ven, A.H., Dooley, K. and Holmes, M.E. (2000) Organizational Change and Innovation Processes, Oxford University Press: New York.

    Google Scholar 

  • Powell, M.S., White, D.R., Koput, K.W. and Owen-Smith, J. (2005) ‘Network dynamics and field evolution’, American Journal of Sociology 110 (4): 1132–1205.

    Article  Google Scholar 

  • Roberts, F.S. (1979) Measurement Theory, Encyclopedia of Math, Vol. 7, Addison-Wesley: Reading, MA.

    Google Scholar 

  • Robison, R. (1986) Indonesia: The Rise of Capital, Allan & Unwin: Sydney, Australia.

    Google Scholar 

  • Rynes, S.L., Bartunek, J.M. and Daft, R.L. (2001) ‘Across the great divide: knowledge creation and transfer between practitioners and academics’, Academy of Management Journal 44 (2): 340–355.

    Article  Google Scholar 

  • Scheinkman, J. and Woodford, M. (1994) ‘Self-organized criticality and economic fluctuations’, American Economic Review 84 (2): 417–421.

    Google Scholar 

  • Schumpeter, J. (1942) Capitalism, Socialism, and Democracy, New York: Harper & Row.

    Google Scholar 

  • Selvam, A.M. (2002) ‘Quantum like chaos in the frequency distributions of the bases A, C, G, T, in Drosophila DNA’, Apeiron 9 (4): 103–148.

    Google Scholar 

  • Sforzi, F. (1990) ‘The Quantitative Importance of Marshallian Industrial Districts in the Italian Economy’, in F. Pyke, G. Becattini and W. Sengenberger (eds.), Industrial Districts and Inter-Firm Co-Operation in Italy, International Institute for Labour Studies: Geneva, Switzerland, pp: 75–107.

    Google Scholar 

  • Shaver, J.M. (1998) ‘Accounting for endogeneity when assessing strategy performance: does entry mode choice affect FDI survival?’ Management Science 44 (4): 571–585.

    Article  Google Scholar 

  • Shin, C.W. and Kim, S. (2004) ‘Self-organized criticality and scale-free properties in emergent functional neural networks’, [www document] http://arxiv.org/abs/cond-mat/0408700v2. (accessed 31 March 2007).

  • Simon, H. (1955) ‘On a class of skewed distribution functions’, Biometrika 42 (3/4): 425–440.

    Article  Google Scholar 

  • Simon, H. (1962) ‘The architecture of complexity’, Proceedings of the American Philosophical Society 106 (6): 467–482.

    Google Scholar 

  • Song, C., Havlin, S. and Makse, H.A. (2005) ‘Self-similarity of complex networks’, Nature 433 (7024): 392–395.

    Article  Google Scholar 

  • Sornette, D. (2002) ‘Predictability of catastrophic events: material rupture, earthquakes, turbulence, financial crashes, and human birth’, Proceedings of the National Academy of Sciences 99 (Suppl. 1): 2522–2529.

    Article  Google Scholar 

  • Sornette, D. (2003) Why Stock Markets Crash, Princeton University Press: Princeton, NJ.

    Google Scholar 

  • Stanley, M.H.R., Amaral, L.A.N., Buldyrev, S.V., Havlin, S., Leschhorn, H., Maass, P., Salinger, M.A. and Stanley, H.E. (1996) ‘Scaling behavior in the growth of companies’, Nature 379 (6568): 804–806.

    Article  Google Scholar 

  • Starbuck, W.H. (2007) ‘Learning from Extreme Cases’, http://pages.stern.nyu.edu/~wstarbuc/extreweb/Extreweb_files/v3_document.htm (accessed 27 September 2007).

  • Stassinopoulos, D. and Bak, P. (1995) ‘Democratic reinforcement: a principle for brain function’, Physical Review E 51 (5): 5033–5039.

    Article  Google Scholar 

  • Stephan, G.E. (1983) ‘A research note on deriving the square-cube law of formal organizations from the theory of time-minimization’, Social Forces 61 (3): 847–854.

    Article  Google Scholar 

  • Storper, M. (1997) The Regional World, Guildford Press: New York.

    Google Scholar 

  • Szeto, H.H., Cheng, P.Y., Decena, J.A., Cheng, Y.I., Wu, D.-L. and Dwyer, G. (1992) ‘Fractal properties in fetal breathing dynamics’, American Journal of Physiology – Regulatory Integrative Comparative Physiology 263 (1): R141–R147.

    Google Scholar 

  • Tichy, N.M. and Sherman, S. (1994) Control Your Destiny or Someone Else Will, HarperCollins: New York.

    Google Scholar 

  • Van de Ven, A.H. and Johnson, P.E. (2006) ‘Knowledge for theory and practice’, Academy of Management. Review 31 (4): 802–821.

    Article  Google Scholar 

  • Warren, K., Craciun, G. and Anderson-Butcher, D. (2005) ‘Everybody else is: networks, power laws and peer contagion in the aggressive recess behavior of elementary school boys’, Nonlinear Dynamics, Psychology, and Life Sciences 9 (2): 155–173.

    Google Scholar 

  • Watts, D.J. (2003) Six Degrees: The Science of a Connected Age, Norton: New York.

    Google Scholar 

  • Watts, D.J. and Strogatz, S.H. (1998) ‘Collective dynamics of “small-world” networks’, Nature 393 (6684): 440–442.

    Article  Google Scholar 

  • Wax, A., Yang, C., Backman, V., Badizadegan, K., Boone, C.W., Dasari, R.R. and Feld, M.S. (2002) ‘Cellular organization and substructure measured using angle-resolved low-coherence interferometry’, Biophysical Journal 82 (4): 2256–2264.

    Article  Google Scholar 

  • Weinberg, R.F. and Podladchikov, Y. (1994) ‘Diapiric ascent of magmas through power law crust and mantle’, Journal of Geophysical Research 99 (B5): 9543–9560.

    Article  Google Scholar 

  • West, B.J. (2006) Where Medicine Went Wrong, World Scientific: Singapore.

    Book  Google Scholar 

  • West, B.J. and Deering, B. (1995) The Lure of Modern Science: Fractal Thinking, World Scientific: Singapore.

    Book  Google Scholar 

  • West, G.B., Brown, J.H. and Enquist, B.J. (1997) ‘A general model for the origin of allometric scaling laws in biology’, Science 276 (4): 122–126.

    Article  Google Scholar 

  • West, B.J., Bologna, M. and Grigolini, P. (2003) Physics of Fractal Operators, Springer: Berlin.

    Book  Google Scholar 

  • Willis, J.C. (1922) Age and Area: A Study in Geographical Distribution and Origin of Species, Cambridge University Press: Cambridge, UK.

    Book  Google Scholar 

  • Willis, J.C. and Yule, G.U. (1922) ‘Some statistics of evolution and geographical distribution in plants and animals, and their significance’, Nature 109: 177–179.

    Article  Google Scholar 

  • Wuchty, S. and Almaas, E. (2005) ‘Peeling the yeast protein network’, Proteomics 5 (2): 444–449.

    Article  Google Scholar 

  • Zanette, D.H. and Manrubia, S.C. (2001) ‘Vertical transmission of culture and the distribution of family names’, Physica A 295 (1–2): 1–8.

    Article  Google Scholar 

  • Zipf, G.K. (1949) Human Behavior and the Principle of Least Effort, Hafner: New York.

    Google Scholar 

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Acknowledgements

We wish to thank two JIBS reviewers, Arie Y. Lewin for his encouragement and guidance and many other colleagues for their encouragement, comments, and advice on this project. Needless to say, errors remaining are ours.

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Authors and Affiliations

  1. Durham Business School, Durham, UK

    Pierpaolo Andriani

  2. The UCLA Anderson School of Management, Los Angeles, CA, USA

    Bill McKelvey

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  1. Pierpaolo Andriani
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  2. Bill McKelvey
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Correspondence to Bill McKelvey.

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Accepted by Arie Y Lewin, Editor-in-Chief, 2 August 2007. This paper has been with the authors for two revisions.

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Andriani, P., McKelvey, B. Beyond Gaussian averages: redirecting international business and management research toward extreme events and power laws. J Int Bus Stud 38, 1212–1230 (2007). https://doi.org/10.1057/palgrave.jibs.8400324

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  • DOI: https://doi.org/10.1057/palgrave.jibs.8400324

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