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TALENT VERSUS LUCK: THE ROLE OF RANDOMNESS IN SUCCESS AND FAILURE

ALESSANDRO PLUCHINO

Department of Physics and Astronomy, University of Catania, Via S.Sofia 64, Catania 95123, Italy

INFN-CT, Via S. Sofia 64, Catania 95123, Italy

E-mail Address: [email protected]

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ALESSIO EMANUELE BIONDO

Department of Economics and Business, University of Catania, Corso Italia 55, Catania 95129, Italy

E-mail Address: [email protected]

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, and

ANDREA RAPISARDA

http://orcid.org/0000-0001-8290-8183

Department of Physics and Astronomy, University of Catania, Via S.Sofia 64, Catania 95123, Italy

INFN-CT, Via S. Sofia 64, Catania 95123, Italy

Complexity Science Hub Vienna, Austria

E-mail Address: [email protected]

Corresponding author.

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https://doi.org/10.1142/S0219525918500145Cited by:70 (Source: Crossref)

This article is part of the issue:

Topical Issue — Quantifying Success; Guest Editors: Roberta Sinatra and Renaud Lambiotte

Abstract

The largely dominant meritocratic paradigm of highly competitive Western cultures is rooted on the belief that success is mainly due, if not exclusively, to personal qualities such as talent, intelligence, skills, smartness, efforts, willfulness, hard work or risk taking. Sometimes, we are willing to admit that a certain degree of luck could also play a role in achieving significant success. But, as a matter of fact, it is rather common to underestimate the importance of external forces in individual successful stories. It is very well known that intelligence (or, more in general, talent and personal qualities) exhibits a Gaussian distribution among the population, whereas the distribution of wealth — often considered as a proxy of success — follows typically a power law (Pareto law), with a large majority of poor people and a very small number of billionaires. Such a discrepancy between a Normal distribution of inputs, with a typical scale (the average talent or intelligence), and the scale-invariant distribution of outputs, suggests that some hidden ingredient is at work behind the scenes. In this paper, we suggest that such an ingredient is just randomness. In particular, our simple agent-based model shows that, if it is true that some degree of talent is necessary to be successful in life, almost never the most talented people reach the highest peaks of success, being overtaken by averagely talented but sensibly luckier individuals. As far as we know, this counterintuitive result — although implicitly suggested between the lines in a vast literature — is quantified here for the first time. It sheds new light on the effectiveness of assessing merit on the basis of the reached level of success and underlines the risks of distributing excessive honors or resources to people who, at the end of the day, could have been simply luckier than others. We also compare several policy hypotheses to show the most efficient strategies for public funding of research, aiming to improve meritocracy, diversity of ideas and innovation.

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References

1. Bak, P., Tang, C. and Wiesenfeld, K. , Self-organized criticality, Phys. Rev. A 38 (1988) 364–374. Web of Science, Google Scholar
2. Barabási, A.-L. and Albert, R. , Emergence of scaling in random networks, Science 286 (5439) (1999) 509–512. Web of Science, Google Scholar
3. Newman, M. E. J. , Power laws, Pareto distributions and Zipf’s law, Contemp. Phys. 46 (5) (2005) 323–351. Web of Science, Google Scholar
4. Tsallis, C. , Introduction to Nonextensive Statistical Mechanics: Approaching a Complex World (Springer, 2009). Google Scholar
5. Pareto, V. , Cours d’Economique Politique, Vol. 2 (Lausanne, F. Rouge Editeur, 1896). Google Scholar
6. Steindl, J. , Random Processes and the Growth of Firms — A Study of the Pareto Law, Charles Griffin and Company (London, 1965). Google Scholar
7. Atkinson, A. B. and Harrison, A. J. , Distribution of Total Wealth in Britain (Cambridge University Press, 1978). Google Scholar
8. Persky, J. , Retrospectives: Pareto’s law, J. Econ. Perspect. 6 (1992) 181–192. Web of Science, Google Scholar
9. Klass, O. S., Biham, O., Levy, M., Malcai, O. and Solomon, S. , The Forbes 400 and the Pareto wealth distribution, Econ. Lett. 90 (2006) 290–295. Web of Science, Google Scholar
10. Hardoon, D., An economy for the 99%, Oxfam GB, Oxfam House, John Smith Drive, Cowley, Oxford, OX4 2JY, UK (2017). Google Scholar
11. Bouchaud, J.-P. and Mézard, M. , Wealth condensation in a simple model of economy, Physica A 282 (2000) 536–554. Web of Science, Google Scholar
12. Dragulescu, A. and Yakovenko, V. M. , Statistical mechanics of money, Eur. Phys. J. B 17 (2000) 723–729. Web of Science, Google Scholar
13. Chakraborti, A. and Chakrabarti, B. K. , Statistical mechanics of money: How saving propensity affects its distribution, Eur. Phys. J. B 17 (2000) 167–170. Web of Science, Google Scholar
14. Patriarca, M., Chakraborti, A. and Germano, G. , Influence of saving propensity on the power law tail of wealth distribution, Physica A 369 (2) (2006) 723–736. Web of Science, Google Scholar
15. Scalas, E. , Random exchange models and the distribution of wealth, Eur. Phys. J. 225 (2016) 3293–3298. Google Scholar
16. During, B., Georgiou, N. and Scalas, E. , A stylised model for wealth distribution, in Economic Foundations of Social Complexity Science, Akura, Yuji and Kirman, Alan (eds.) (Springer, 2017), pp. 95–117. Google Scholar
17. Sinatra, R., Wang, D., Deville, P., Song, C. and Barabási, A.-L. , Quantifying the evolution of individual scientific impact, Science 354 (2016) 6312. Web of Science, Google Scholar
18. Einav, L. and Yariv, L. , What’s in a surname? The effects of surname initials on academic success, J. Econ. Perspect. 20 (1) (2006) 175–188. Web of Science, Google Scholar
19. Ruocco, G., Daraio, C., Folli, V. and Leonetti, M. , Bibliometric indicators: The origin of their log-normal distribution and why they are not a reliable proxy for an individual scholar’s talent, Palgrave Commun. 3 (2017) 17064, https://doi.org/10.1057/palcomms.2017.64. Web of Science, Google Scholar
20. Jurajda, S. and Munich, D. , Admission to selective schools, alphabetically, Econ. Educ. Rev. 29 (6) (2010) 1100–1109. Web of Science, Google Scholar
21. Van Tilburg, W. A. P. and Igou, E. R. , The impact of middle names: Middle name initials enhance evaluations of intellectual performance, Eur. J. Soc. Psychol. 44 (4) (2014) 400–411. Web of Science, Google Scholar
22. Laham, S. M., Koval, P. and Alter, A. L. , The name-pronunciation effect: Why people like Mr. Smith more than Mr. Colquhoun, J. Exp. Soc. Psychol. 48 (2012) 752–756. Web of Science, Google Scholar
23. Silberzahn, R. and Uhlmann, E. L. , It pays to be Herr Kaiser: Germans with noble-sounding last names more often work as managers, Psychol. Sci. 24 (12) (2013) 2437–2444. Web of Science, Google Scholar
24. Coffey, B. and McLaughlin, P. , From lawyer to judge: Advancement, sex, and name-calling, SSRN Electron. J. (2009) https://doi.org/10.2139/ssrn.1348280, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1348280. Google Scholar
25. Milanovic, B. , Global inequality of opportunity: How much of our income is determined by where we live? Rev. Econ. Stat. 97 (2) (2015) 452–460. Web of Science, Google Scholar
26. Du, Q., Gao, H. and Levi, M. D. , The relative-age effect and career success: Evidence from corporate CEOs, Econ. Lett. 117 (3) (2012) 660–662. Web of Science, Google Scholar
27. Deaner, R. O., Lowen, A. and Cobley, S. , Born at the wrong time: Selection bias in the NHL draft, PLoS One 8 (2) (2013) e57753. Web of Science, Google Scholar
28. Brooks, D. , The Social Animal: The Hidden Sources of Love, Character, and Achievement (Random House, 2011), p. 424. Google Scholar
29. Iacopini, I., Milojevic, S. and Latora, V. , Network dynamics of innovation processes, Phys. Rev. Lett. 120 (2018) 048301. Web of Science, Google Scholar
30. Tomasetti, C., Li, L. and Vogelstein, B. , Stem cell divisions, somatic mutations, cancer etiology, and cancer prevention, Science 355 (2017) 1330–1334. Web of Science, Google Scholar
31. Newgreen, D. F. et al., Differential clonal expansion in an invading cell population: Clonal advantage or dumb luck? Cells Tissues Organs 203 (2017) 105–113. Web of Science, Google Scholar
32. Snyder, R. E. and Ellner, S. P. , We happy few: Using structured population models to identify the decisive events in the lives of exceptional individuals, Am. Nat. 188 (2) (2016) E28–E45. Web of Science, Google Scholar
33. Snyder, R. E. and Ellner, S. P. , Pluck or luck: Does trait variation or chance drive variation in lifetime reproductive success? Am. Nat. 191 (4) (2018) E90–E107. Web of Science, Google Scholar
34. Taleb, N. N. , Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets (Random House, 2001). Google Scholar
35. Taleb, N. N. , The Black Swan: The Impact of the Highly Improbable (Random House, 2007). Google Scholar
36. Mauboussin, M. J. , The Success Equation: Untangling Skill and Luck in Business, Sports, and Investing (Harvard Business Review Press, 2012). Google Scholar
37. Frank, R. H. , Success and Luck: Good Fortune and the Myth of Meritocracy (Princeton University Press, 2016). Google Scholar
38. Watts, D. J. , Everything Is Obvious: Once You Know the Answer (Crown Business, 2011). Google Scholar
39. Salganik, M. J., Dodds, P. S. and Watts, D. J. , Experimental study of inequality and unpredictability in an artificial cultural market, Science 311 (2006) 854–856. Web of Science, Google Scholar
40. Travis, M., Hofman, J. M., Sharma, A., Anderson, A. and Watts, D. J. , Exploring limits to prediction in complex social systems, in Proc. 25th ACM Int. World Wide Web Conf. (2016), pp. 683–694. arXiv:1602.01013 [cs.SI], https://dl.acm.org/citation.cfm?doid=2872427.2883001. Google Scholar
41. Stewart, J., The distribution of talent, Marilyn Zurmuehlin Working Papers in Art Education, Vol. 2 (1983), pp. 21–22. Google Scholar
42. Sinha, S. and Pan, R. K. , How a “Hit” is born: The emergence of popularity from the dynamics of collective choice, in Econophysics and Sociophysics: Trends and Perspectives, Chakrabarti, B. K., Chakraborti, A. and Chatterjee, A. (Wiley-VCH Verlag GmbH & Co. KGaA, 2006), https://doi.org/10.1002/9783527610006.ch15. Google Scholar
43. Fortin, J.-M. and Curr, D. J. , Big science vs. little science: How scientific impact scales with funding, PLoS One 8 (6) (2013) e65263. Web of Science, Google Scholar
44. Jacob, B. A. and Lefgren, L. , The impact of research grant funding on scientific productivity, J. Public Econ. 95 (2011) 1168–1177. Web of Science, Google Scholar
45. O’Boyle, J. E. and Aguinis, H. , The best and the rest: Revisiting the norm of normality of individual performance, Pers. Psychol. 65 (2012) 79–119. https://doi.org/10.1111/j.1744-6570. 2011.01239.x. Web of Science, Google Scholar
46. Denrell, J. and Liu, C. , Top performers are not the most impressive when extreme performance indicates unreliability, Proc. Nat. Acad. Sci. 109 (24) (2012) 9331–9336. Web of Science, Google Scholar
47. Pluchino, A., Rapisarda, A. and Garofalo, C. , The Peter principle revisited: A computational study, Physica A 389 (3) (2010) 467–472. Web of Science, Google Scholar
48. Pluchino, A., Garofalo, C., Rapisarda, A., Spagano, S. and Caserta, M. , Accidental politicians: How randomly selected legislators can improve parliament efficiency, Physica A 390 (21) (2011) 3944–3954. Web of Science, Google Scholar
49. Pluchino, A., Rapisarda, A. and Garofalo, C. , Efficient promotion strategies in hierarchical organizations, Physica A 390 (20) (2011) 3496–3511. Web of Science, Google Scholar
50. Biondo, A. E., Pluchino, A., Rapisarda, A. and Helbing, D. , Reducing financial avalanches by random investments, Phys. Rev. E 88 (6) (2013) 062814. Web of Science, Google Scholar
51. Biondo, A. E., Pluchino, A., Rapisarda, A. and Helbing, D. , Are random trading strategies more successful than technical ones, PLoS One 8 (7) (2013) e68344. Web of Science, Google Scholar
52. Biondo, A. E., Pluchino, A. and Rapisarda, A. , The beneficial role of random strategies in social and financial systems, J. Stat. Phys. 151 (3–4) (2013) 607–622. Web of Science, Google Scholar
53. Biondo, A. E., Pluchino, A. and Rapisarda, A. , Micro and macro benefits of random investments in financial markets, Contemp. Phys. 55 (4) (2014) 318–334. Web of Science, Google Scholar
54. Biondo, A. E., Pluchino, A. and Rapisarda, A. , Modeling financial markets by self-organized criticality, Phys. Rev. E 92 (4) (2015) 042814. Web of Science, Google Scholar
55. Wilensky, U., NetLogo. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL (1999), http://ccl.northwestern.edu/netlogo/. Google Scholar
56. Merton, R. K. , The Matthew effect in science, Science 159 (1968) 56–63. Web of Science, Google Scholar
57. Merton, R. K. , The Matthew effect in science, II: Cumulative advantage and the symbolism of intellectual property, Isis 79 (1988) 606–623. Web of Science, Google Scholar
58. Bol, T., de Vaan, M. and van de Rijt, A. , The Matthew effect in science funding, Proc. Natl. Acad. Sci. 115 (19) (2018) 4887–4890, https://doi.org/10.1073/pnas.1719557115. Web of Science, Google Scholar
59. Mongeon, P., et al., Concentration of research funding leads to decreasing marginal returns, Res. Eval. 25 (2016) 396–404. Web of Science, Google Scholar
60. Merton, R. K. and Barber, E. , The Travels and Adventures of Serendipity (Princeton University Press, 2004). Google Scholar
61. Murayama, K. et al., Management of science, serendipity, and research performance, Res. Policy 44 (4) (2015) 862–873. Web of Science, Google Scholar
62. Benias, P. C. et al., Structure and distribution of an unrecognized interstitium in human tissues, Sci. Rep. 8 (2018) 4947. Web of Science, Google Scholar
63. Flexner, A. , The Usefulness of Useless Knowledge (Princeton University Press, 2017). Google Scholar
64. Lucky science. Scientists often herald the role of serendipity in research. A project in Britain aims to test the popular idea with evidence, Nature Editorial, Vol. 554 (2018), https://www.nature.com/magazine-assets/d41586-018-01405-7/d41586-018-01405-7.pdf. Google Scholar
65. Yaqub, O. , Serendipity: Towards a taxonomy and a theory, Res. Policy 47 (2018) 169–179. Web of Science, Google Scholar
66. Page, S. E. , The Diversity Bonus: How Great Teams Pay Off in the Knowledge Economy (Princeton University Press, 2017). Google Scholar
67. Cimini, G., Gabrielli, A. and Sylos Labini, F. , The scientific competitiveness of nations, PLoS One 9 (12) (2014) e113470. https://doi.org/10.1371/journal.pone.0113470. Web of Science, Google Scholar
68. Curry, S. , Let’s move beyond the rhetoric: It’s time to change how we judge research, Nature 554 (2018) 147. Web of Science, Google Scholar
69. Nicholson, J. M. and Ioannidis, J. P. A. , Research grants: Conform and be funded, Nature 492 (2012) 34–36. Web of Science, Google Scholar
70. Bollen, J., et al., An efficient system to fund science: From proposal review to peer-to-peer distributions, Scientometrics 110 (2017) 521–528. Web of Science, Google Scholar
71. Garner, H. R., McIver, L. J. and Waitzkin, M. B. , Research funding: Same work, twice the money? Nature 493 (2013) 599–601. Web of Science, Google Scholar

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History

Received 28 May 2018

Revised 9 July 2018

Accepted 10 July 2018

Published: 27 July 2018

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This is an Open Access article published by World Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution 4.0 (CC-BY) License. Further distribution of this work is permitted, provided the original work is properly cited.

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TALENT VERSUS LUCK: THE ROLE OF RANDOMNESS IN SUCCESS AND FAILURE

Abstract

References

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