Cooperation and Contagion in Web-Based, Networked Public Goods Experiments

A longstanding idea in the literature on human cooperation is that cooperation should be reinforced when conditional cooperators are more likely to interact. In the context of social networks, this idea implies that cooperation should fare better in highly clustered networks such as cliques than in networks with low clustering such as random networks. To test this hypothesis, we conducted a series of web-based experiments, in which 24 individuals played a local public goods game arranged on one of five network topologies that varied between disconnected cliques and a random regular graph. In contrast with previous theoretical work, we found that network topology had no significant effect on average contributions. This result implies either that individuals are not conditional cooperators, or else that cooperation does not benefit from positive reinforcement between connected neighbors. We then tested both of these possibilities in two subsequent series of experiments in which artificial seed players were introduced, making either full or zero contributions. First, we found that although players did generally behave like conditional cooperators, they were as likely to decrease their contributions in response to low contributing neighbors as they were to increase their contributions in response to high contributing neighbors. Second, we found that positive effects of cooperation were contagious only to direct neighbors in the network. In total we report on 113 human subjects experiments, highlighting the speed, flexibility, and cost-effectiveness of web-based experiments over those conducted in physical labs

Emergence of social networks via direct and indirect reciprocity

Many models of social network formation implicitly assume that network properties are static in steady-state. In contrast, actual social networks are highly dynamic: allegiances and collaborations expire and may or may not be renewed at a later date. Moreover, empirical studies show that human social networks are dynamic at the individual level but static at the global level: individuals' degree rankings change considerably over time, whereas network-level metrics such as network diameter and clustering coefficient are relatively stable. There have been some attempts to explain these properties of empirical social networks using agent-based models in which agents play social dilemma games with their immediate neighbours, but can also manipulate their network connections to strategic advantage. However, such models cannot straightforwardly account for reciprocal behaviour based on reputation scores ("indirect reciprocity"), which is known to play an important role in many economic interactions. In order to account for indirect reciprocity, we model the network in a bottom-up fashion: the network emerges from the low-level interactions between agents. By so doing we are able to simultaneously account for the effect of both direct reciprocity (e.g. "tit-for-tat") as well as indirect reciprocity (helping strangers in order to increase one's reputation). This leads to a strategic equilibrium in the frequencies with which strategies are adopted in the population as a whole, but intermittent cycling over different strategies at the level of individual agents, which in turn gives rise to social networks which are dynamic at the individual level but stable at the network level

Three is a crowd in iterated prisoner's dilemmas: experimental evidence on reciprocal behavior

Reciprocity or conditional cooperation is one of the most prominent mechanisms proposed to explain the emergence of cooperation in social dilemmas. Recent experimental findings on networked games suggest that conditional cooperation may also depend on the previous action of the player. We here report on experiments on iterated, multi-player Prisoner's dilemma, on groups of 2 to 5 people. We confirm the dependence on the previous step and that memory effects for earlier periods are not significant. We show that the behavior of subjects in pairwise dilemmas is qualitatively different from the cases with more players; After an initial decay, cooperation increases significantly reaching values above 80%. The strategy of the players is rather universal as far as their willingness to reciprocate cooperation is concerned, whereas there is much diversity in their initial propensity to cooperate. Our results indicate that, for cooperation to emerge and thrive, three is a crowd.This work has been supported in part by Ministerio de Ciencia e Innovación (Spain) through grants MOSAICO, RESINEE, PRODIEVO and ECO2009-10531, and by Comunidad de Madrid (Spain) through grants MODELICO-CM and EXCELECON

When greediness and self-confidence meet in a social dilemma

A greedy personality is usually accompanied by arrogance and confidence. This work investigates the cooperation success condition in the context of biased payoff allocation and self-confidence. The first component allows the organizer in a spatial public goods game to receive a different proportion of goods than other participants. The second aspect influences the micro-level dynamics of strategy updates, wherein players can maintain their strategy with a certain weight. Analytical results are obtained on square lattices under the weak selection limit. If the organizer attempts to monopolize the public goods, cooperation becomes more attainable. If the confidence increases, cooperation is inhibited. Consequently, these elements have conflicting effects on cooperation, and their simultaneous presence can result in a heterogeneous change of the critical synergy factor. Our theoretical findings underscore the subtle implications of a mutual trait that may manifest as greediness or self-confidence under different circumstances, which are validated through Monte Carlo simulations.Comment: 15 pages, 7 figures, accepted for publication in Physica

Connected innovation: an international comparative study that identifies mixed modes of innovation

This paper offers a new angle on innovation modalities by adopting a recently emerging approach towards identifying innovation typologies via exploratory data analysis techniques with the aim to tease out some underlying latent variables that represent coherent innovation strategies for groups of firms. Mixed modes of innovation include aspects of both user and open innovation, and are employed to inform on such concepts. The modes of innovation are developed by exploring micro-level innovation survey data across 18 countries. The contributions of the paper lie in (a) the identification of five core innovation modes that are found in almost all countries; and (b) examining – via regression analysis – the role of different modes in firm performance

Group size effects and critical mass in public goods games

Understanding whether the size of the interacting group has an effect on cooperative behavior has been a major topic of debate since the seminal works on cooperation in the 1960s. Half a century later, scholars have yet to reach a consensus, with some arguing that cooperation is harder in larger groups, while others that cooperation is easier in larger groups, and yet others that cooperation attains its maximum in intermediate size groups. Here we add to this field of work by reporting a two-treatment empirical study where subjects play a Public Goods Game with a Critical Mass, such that the return for full cooperation increases linearly for early contributions and then stabilizes after a critical mass is reached (the two treatments differ only on the critical mass). We choose this game for two reasons: it has been argued that it approximates real-life social dilemmas; previous work suggests that, in this case, group size might have an inverted-U effect on cooperation, where the pick of cooperation is reached around the critical mass. Our main innovation with respect to previous experiments is that we implement a within-subject design, such that the same subject plays in groups of different size (from 5 to 40 subjects). Groups are formed at random at every round and there is no feedback. This allows us to explore if and how subjects change their choice as a function of the size of the group. We report three main results, which partially contrast what has been suggested by previous work: in our setting (i) the critical mass has no effect on cooperation; (ii) group size has a positive effect on cooperation; (iii) the most chosen option (played by about 50% of the subjects) is All Defection, followed by All Cooperation (about 10% of the subjects), whereas the rest have a slight trend to switch preferentially from defection to cooperation as the group size increases

Evolution of cooperation in multilayer networks

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementIndividuals take part in multiple layers of networks of interactions simultaneously. These interdependent networks account for the different sort of social ties individuals maintain per layer. In each layer individuals participate in N-Player Public Goods Games where benefits collected increase with amounts invested. It is, however, tempting to be a free-rider, i.e., to take advantage of the common pool without contributing to it, a situation from which a social dilemma results. This thesis offers new insights on how cooperation dynamics is shaped by multiple layers of social interactions and diversity of contributions invested per game. To this end, we resort to Evolutionary Game Theory and Network Science to provide a convenient framework to address the most important prototypical social conflicts and/or dilemmas in large networked populations. In particular, we propose a novel mean-field approach capable of tracking the self-organization of Cooperators when co-evolving with Defectors in a multilayer environment. We show that the emerging collective dynamics, which depends (i) on the underlying layer networks of interactions and (ii) on the criteria to share a finite investment across all games, often does not bear any resemblance with the local processes supporting them. Our findings suggest that, whenever individual investments are distributed among games or layers, resilience of cooperation against free-riders increases with the number of layers, and that cooperation emerges from a non-trivial organization of cooperation across the layers. In opposition, under constant, non-distributed investments, the level of cooperation shows little sensibility to variations in the number of layers. These findings put in evidence the importance of asymmetric contributions across games and social contexts in the emergence of human cooperation