Social and Private Learning with Endogenous Decision Timing

Contributions to Economic Analysis, 2006

We consider a simple model in which a population of individuals with idiosyncratic willingnesses to pay must choose repeatedly either to buy or not a unit of a single homogeneous good at a given price. Utilities of buyers have positive externalities due to social interactions among customers. If the latter are strong enough, the system has multiple Nash equilibria, revealing coordination problems. We assume that individuals learn to make their decisions repeatedly. We study the performances along the learning path as well as at the customers' reached equilibria, for different learning schemes based on past earned and/or forgone payoffs. Results are presented as a function of the price, for weak and strong social interactions. Pure reinforcement learning is shown to hinder convergence to the Nash equilibrium, even when it is unique. For strong social interactions, coordination on the optimal equilibrium through learning is reached only with some of the learning schemes, under restrictive conditions. The issues of the learning rules are shown to depend crucially on the values of their parameters, and are sensitive to the agents' initial beliefs.

Technological Forecasting and Social Change, 2007

Diffusion models of technological innovations are often based on an epidemic structure which has a good fit to historical data but whose communication assumptions lack explanatory power. They assume a simplified decision process, uniform decision criteria across adopters categories, and a fully interconnected social structure. The objective of this paper is to show that the dynamics of social factors during technological substitutions have significant effects on substitution patterns. The success of a paradigmatic shift is not only a function of technological characteristics but also depends on change agents and many social dynamics. Such complexity requires analysis at several levels of granularity. We start with cognitive processes at the individual level using concepts from cognitive psychology and decision making under uncertainty and then move to interpersonal communications at the aggregate social level. We show that population heterogeneity generates different decision criteria and a social topology which greatly affect perceptions and the formation of expectations. The structure of interpersonal networks also explains how the relevance and credibility of information impact the critical mass dynamics of technology adoption. A more complete model accounting for social interactions provides a useful framework for understanding complex substitution patterns and reducing the risk of misreading the market.

The Journal of Economic …, 1998

2001

Abstract: We offer a model to explain why groups of people sometimes converge upon poor decisions and are prone to fads, even though they can discuss the outcomes of their choices. Models of informational herding or cascades have examined how rational individuals learn by observing predecessors' actions, and show that when individuals stop using their own private signals, improvements in decision quality cease.

We consider a population of agents that can choose between two risky technologies: an old one for which they know the expected outcome, and a new one for which they have only a prior. We confront different environments. In the benchmark case agents are isolated and can perform costly experiments to infer the quality of the new technology. In the other cases agents are settled in a network and can observe the outcomes of neighbors. We analyze long-run efficiency of the models. We observe that in expectations the quality of the new technology may be overestimated when there is a network spread of information. This is due to a herding behavior that is efficient only when the new technology is really better than the old one. We also observe that between different network structures there is not a clear dominance.

The European Physical Journal B, 2012

When the full stock of a new product is quickly sold in a few days or weeks, one has the impression that new technologies develop and conquer the market in a very easy way. This may be true for some new technologies, for example the cell phone, but not for others, like the blue-ray. Novelty, usefulness, advertising, price, and fashion are the driving forces behind the adoption of a new product. But, what are the key factors that lead to adopt a new technology? In this paper we propose and investigate a simple model for the adoption of an innovation which depends mainly on three elements: the appeal of the novelty, the inertia or resistance to adopt it, and the interaction with other agents. Social interactions are taken into account in two ways: by imitation and by differentiation, i.e., some agents will be inclined to adopt an innovation if many people do the same, but other will act in the opposite direction, trying to differentiate from the "herd". We determine the conditions for a successful implantation of the new technology, by considering the strength of advertising and the effect of social interactions. We find a balance between the advertising and the number of anti-herding agents that may block the adoption of a new product. We also compare the effect of social interactions, when agents take into account the behavior of the whole society or just a part of it. In a nutshell, the present model reproduces qualitatively the available data on adoption of innovation.

2017

Agents, embedded in a social network, first decide whether or not to adopt a new costly technology, and, then, choose their level of productivity effort. The latter choice is affected by the social norm of each individual so that she loses utility from failing to conform to the average effort of her peers (local-average model). Contrary to the local-aggregate model, we show that, in the second stage, if agents are ex ante identical but have different positions in the network, they all exert the same effort level, which corresponds to the first best. We also demonstrate that multiple equilibria may arise in the two-stage game. We show under which conditions symmetric and asymmetric subgame-perfect Nash equilibria emerge and why they are inefficient. Finally, we propose different subsidy policies that can restore the first-best solutions.

Industrial and Corporate Change, 1996

Advances in stochastic system analysis have opened the way to a reconsideration of the processes through which behaviors spread in a population of individuals or organizations. One peculiar phenomenon affecting diffusion is information contagion (Arthur and Lane 1994). When agents have to choose on the basis of other people's experience, rather than relying on their own direct observations, information externalities arise that drive towards the emergence of the arbitrary, stable dominance of one product over the competing one. We reproduced in controlled laboratory conditions the process of information contagion. The experiments show that when agents can only resort to the observation of other people's experience in choosing between competing alternatives, the choice process generates some peculiar features: -information contagion among subjects generates self-reinforcing dynamics, amplifying initial asymmetries of products' market shares; -this in turn produces path-dependent trajectories, highly dependent on early events in the choice sequence; -arbitrary asymmetric market shares tend to be stable in the long run, exhibiting lock-in phenomena; -agents choice criteria are heterogenous, giving rise to a mix of positive and negative feedback in the choice process, with the mix and the timing of such criteria affecting the final outcome.

2018

The literature on network effects has a longstanding controversy regarding the possibility that markets may lock into an inferior technology. This controversy was triggered by Arthur’s (1989) model of positive feedback (success begets more success) in markets with competition between incompatible technologies. Critics point to the lack of compelling evidence for such lock-in. This confusion, in part, stems from a hidden assumption in the Arthur model influence of adopters never decays. We shed new light on this confusion by examining the implications of influence that decays over time. In the absence of influence decay, there is a good possibility that a market will lock-in to an inferior technology, as shown by prior work. However, when the influence of earlier adopters decays over time, the possibility of lock-in to an inferior technology is substantially attenuated. Despite the existence of positive feedback, this decay triggers a protracted period of technology competition, whic...

We report on an experiment that uses revealed preference to distinguish between rational social learning and behavioral bias. Subjects must choose between receiving a private signal or observing the past guesses of other subjects before guessing the state of the world. The design varies the persistence of the state across time. This changes whether choosing social or private information is optimal. We can therefore separate subjects who choose optimally from both those who excessively use social information ("herd animals") and those with excessive use of private information ("lone wolves"). While aggregate behavior appears unbiased, this is because the numbers of lone wolves and herd animals are approximately equal.

Review of Industrial Organization, 2003

The benefits accruing to a purchaser of a product due to the existing base of consumers of the same or compatible products are known as network externalities. This paper studies Katz and Shapiro’s (1986) model of network externalities in an experimental setting. Two sellers choose prices for competing technologies sold to two groups of four buyers purchasing sequentially in two stages. The results are qualitatively consistent with Katz and Shapiro’s equilibrium predictions. In certain sessions over three-quarters of first stage buyers purchase the more expensive technology anticipating that later arriving buyers will also buy this technology. In periods where a strong network has been established for a technology in the first stage, over 80 percent of second stage buyers buy that technology, even though in most cases it is priced higher. The data, however, differ from the point predictions of the model.

Journal of Marketing, 2014

Many firms capitalize on their customers’ social networks to improve the success rate of their new products. In this article, the authors analyze the dynamic effects of social influence and direct marketing on the adoption of a new high-technology product. Social influence is likely to play a role because the decision to adopt a high-involvement product requires extensive information gathering from various sources. The authors use call detail records to construct ego networks for a large sample of customers of a Dutch mobile telecommunications operator. Using a fractional polynomial hazard approach to model adoption timing and multiple social influence variables, they provide a fine-grained analysis of social influence. They show that the effect of social influence from cumulative adoptions in a customer's network decreases from the product introduction onward, whereas the influence of recent adoptions remains constant. The effect of direct marketing is also positive and decreas...

Journal of Public Economics, 1993

This paper considers the welfare implications of adoption of a new technology when this technology is characterized by costs of adaptation and some 'localized learning' effects. A twoperiod model is developed to represent the 'adoption game' between firms in a duopolistic framework. Optimal social 'patterns' of adoption are compared with private patterns emerging as equilibria of the game. It is shown that differences between the two patterns are due first to the shape of the demand function of the product sold on the duopolistic market, and secondly to strategic interaction effects between the adopting lirms. 'As Quirmbach (1986) showed, asymmetric patterns are a consequence of decreasing benefits, but this decrease results from strategic interactions since identical firms can only be distinguished with this respect [Reinganum (1981a)l.

American Journal of Sociology, 2005

We propose an individual-based model of innovation diffusion and explore its main dynamical properties. The model shares with the classical threshold models a distinction between a social (cultural) influence and a more personal assessment of the innovation, both playing a role in the decision of adoption. It includes several other features: information propagation, uncertainty, social influence depending on the uncertainty and interest states modifying the attitude toward the information. We show that the dynamics of adoption of the model can be understood as the combination of a social value evolution, and an information propagation which depends on the social value. The main result of the model exploration is that innovations which are in contradiction with the social values have less chances to propagate, even if they are very valuable for the personal pleasure or comfort, than innovations which are highly valuable culturally even if they have negative consequences on the individual comfort or pleasure. Moreover, the model also exhibits strong dynamical effects, in which the social value of the innovation changes radically under the influence of a minority of extremists.

JITE, 2002

We are grateful to Meg Meyer for very helpful conversations on the topic of this paper. Bru acknowledges the support of DGICYT project PB98-1402 and Vives of PB98-0696.