Essec Business School

Not many ideas end up having a real, disruptive impact on the academic community. But, every once in a while, a scientific discovery will come along and really shake things up.

Indeed, many researchers have shown that fundamental research follows a bumpy trajectory in time. While there are major innovations which provoke structural breaks in science, they tend to be followed by long periods where researchers focus on exploiting their results and don’t seize new ideas.

The trouble is, major innovations are few and far between: even science’s “best ideas” can take years to be implemented or recognized as breakthroughs. For example, even in the “small world of economics”, those discoveries that are today seen as the corner stones of modern economics, often faced early rejection and unbelievable publication delays.[i]  On the other hand, scientific “fads” have sometimes driven scholars down fruitless research paths.

Researchers Radu Vranceanu (ESSEC and THEMA) and Damien Besancenot (University of Paris 13 and CEPN) offer another reason as to why breakthroughs are so few and far between. They explore this idea in their paper Fear of Novelty: A Model of Scientific Discovery with Strategic Uncertainty (Economic Inquiry, 2015).

“We wanted to provide an explanation for these ‘bumpy’ output trajectories in fundamental research by accounting for the coordination risk perceived by researchers considering whether to pursue or adopt a new idea,” explains Radu Vranceanu. “Obviously, when looking to publish research, scholars expose their findings to a large community of peers, and take the challenge of being judged and criticized by them. Just like anyone, researchers fear this kind of criticism and peer rejection. This explains why they light hedge their bets by following the heard, so to speak. As Keynes put it, ‘worldly wisdom teaches that it is better for reputation to fail conventionally than to succeed unconventionally.’”[ii]

“Researchers in sociology, for example, have shown that the success of an idea will depend on the degree of consensus it can generate.[iii] Taking this logic one step further, we argue that a new idea will reach the ‘science status’ only if a critical mass of researchers adopt it, test, and develop applications for it,” he continues. “In other words, a researcher will only decide to develop a new idea if he or she believes that a sufficient number of researchers are following the same research strategy. Knowledge of the belief formation mechanism is thus fundamental to gaining a deeper understanding of the idea adoption mechanism.”

In this context, professors Besancenot and Vranceanu choose to analyze the researcher's problem as a typical coordination game with strategic complementarities. A good illustration is the two-player Stag Hunt game. If they coordinate their actions, tow hunters can get for sure a big stag.  Each hunter, individually, can get for sure a measly hare. Obviously, they would be better-off with the stag, but without a coordination device, the rich outcome cannot be taken for granted, as each hunter, doubting about the intention of the other, could be tempted to choose the measly but sage to get  hare.

As Professor Vranceanu recall, with complete information and identical players, such games present what we call “multiple equilibria”. In the nineties, E. Carlson and H. Van Damme and, later on,  S. Morris and H. Shinn have shown that this indeterminacy can be removed if players receive only a biased signal of their variable defining the “state of the economy”: Since neither individual would know what the others’ beliefs about this key variable, there is a “threshold” state of the economy above which all players take the high-risk high-yield strategy and below which they would adopt the opposite low-reward but safe wait-and-see strategy.

In Besancenot and Vranceanu’s analysis of how paradigms emerge, they argue that new ideas have their own scientific value based on its perceived benefits to society and assume that researchers observe only a biased signal of the true scientific potential of any new idea. Given this individual-specific signal, researchers must choose between continuing their work in the existing paradigm and obtaining safe but modest payoffs or taking risks with the aim of developing a new idea. The new idea will create a successful field of research only if a critical mass of researchers simultaneously decide to adopt the idea. If this critical mass is reached, then the rewards of adopting the new idea depend on its scientific value; conversely, if critical mass is not reached, then the scholar who has spent time developing the new idea will not recover his investment.  

“We show that there is an ‘equilibrium cutoff scientific value’ above which a new strand of research is created and below which the new strand fails to emerge,” explains Professor Vranceanu. “If uncertainty is not very large, there are situations where the critical threshold is above the scientific value of the old ideas. Then, since some ‘good ideas’ might not be implemented: researcher behave as if they fear novelty. Actually, they fear that not enough researchers will decide to work in the same field.” In the opposite direction, in times of major scientific uncertainty, the critical threshold is below the value of the old ides; this would also explain why sometimes researches decide to follow “bad” ideas, or the emergence of fads in science.

As an upshot, coordination of efforts and investments is a critical requirement for the success of any research program or mission. Ideas developed by Besancenot and Vranceanu suggest that the standard methodology of Global Games might provide a suitable tool to analyze a broader range of problems in the economics of science.

Further Reading:

Abrahamson, E., 2009. Necessary conditions for the study of fads and fashions in science, Scandinavian Journal of Management, 25 (2), pp. 235-239.

Besancenot, D. and Vranceanu, R. (2015), FEAR OF NOVELTY: A MODEL OF SCIENTIFIC DISCOVERY WITH STRATEGIC UNCERTAINTY. Economic Inquiry. doi: 10.1111/ecin.12200

Bramoullé, Y., and Saint-Paul, G., 2010. Research cycles, Journal of Economic Theory, 145 (5), pp. 1890-1920.

Brock, W. A., and Durlauf, S. N., 1999. A formal model of theory choice in science, Economic Theory, 14 (1), pp. 113-130.

Carlsson, H. and Van Damme, E., 1993. Global games and equilibrium selection, Econometrica, 61 (5), pp. 989-1018.

Diamond, A. M., 1996, The Economics of Science, Knowledge and Policy, 9 (2-3), pp. 6-49.

Gardner, M., 1957, Fads and Fallacies in the Name of Science. Courier Dover Publications.

Kuhn, T.S., 1962. The Structure of Scientific Revolutions, University of Chicago Press, Chicago.

Merton, R K., 1957. Priorities in scientific discovery: a chapter in the sociology of science, American Sociological Review, 22 (6), pp. 635-659.

Morris, S., and Shin, H. S., 1998. Unique equilibrium in a model of self-fulfilling currency attacks, American Economic Review, 88 (3), pp. 587-597.

Stephan, P.E., 1996. The economics of science, Journal of Economic Literature, 34, pp. 1199-1235.