Livan, G;
(2019)
Don't follow the leader: how ranking performance reduces meritocracy.
Royal Society Open Science
, 6
(11)
, Article 191255. 10.1098/rsos.191255.
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Abstract
In the name of meritocracy, modern economies devote increasing amounts of resources to quantifying and ranking the performance of individuals and organizations. Rankings send out powerful signals, which lead to identifying the actions of top performers as the 'best practices' that others should also adopt. However, several studies have shown that the imitation of best practices often leads to a drop in performance. So, should those lagging behind in a ranking imitate top performers or should they instead pursue a strategy of their own? I tackle this question by numerically simulating a stylized model of a society whose agents seek to climb a ranking either by imitating the actions of top performers or by randomly trying out different actions, i.e. via serendipity. The model gives rise to a rich phenomenology, showing that the imitation of top performers increases welfare overall, but at the cost of higher inequality. Indeed, the imitation of top performers turns out to be a self-defeating strategy that consolidates the early advantage of a few lucky-and not necessarily talented-winners, leading to a very unequal, homogenized and effectively non-meritocratic society. Conversely, serendipity favours meritocratic outcomes and prevents rankings from freezing.
| Type: | Article |
|---|---|
| Title: | Don't follow the leader: how ranking performance reduces meritocracy |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1098/rsos.191255 |
| Publisher version: | https://doi.org/10.1098/rsos.191255 |
| Language: | English |
| Additional information: | © 2019 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
| Keywords: | agent-based modelling, meritocracy, performance measurement, serendipity |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10087277 |
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