The dynamics of closeness and betweenness

Although both betweenness and closeness centrality are claimed to be important for the effectiveness of someones network position, it has not been explicitly studied which networks emerge if actors follow incentives for these two positional advantages. We propose such a model and observe that network dynamics differ considerably in a scenario with either betweenness or closeness incentives compared to a scenario in which closeness and betweenness incentives are combined. Considering social consequences, we find low clustering when actors strive for either type of centrality. Surprisingly, actors striving for closeness are likely to reach networks with relatively low closeness and high betweenness, while this is the other way round for actors striving for betweenness. This shows that in both situations the network formation process implies a social dilemma in which the social optimum is not reached by individual optimizing.networks, closeness centrality, betweenness centrality, actor utility, network dynamics, social dilemma

Heterogeneity and Increasing Returns May Drive Socio-Economic Transitions

There are clear benefits associated with a particular consumer choice for many current markets. For example, as we consider here, some products might carry environmental or `green' benefits. Some consumers might value these benefits while others do not. However, as evidenced by myriad failed attempts of environmental products to maintain even a niche market, such benefits do not necessarily outweigh the extra purchasing cost. The question we pose is, how can such an initially economically-disadvantaged green product evolve to hold the greater share of the market? We present a simple mathematical model for the dynamics of product competition in a heterogeneous consumer population. Our model preassigns a hierarchy to the products, which designates the consumer choice when prices are comparable, while prices are dynamically rescaled to reflect increasing returns to scale. Our approach allows us to model many scenarios of technology substitution and provides a method for generalizing market forces. With this model, we begin to forecast irreversible trends associated with consumer dynamics as well as policies that could be made to influence transition

Social motives in network formation: an experiment

Literature on network formation typically assumes that people create and remove relations as to maximize their outcome in the network. It is mostly neglected that people might also care about the outcomes of others when creating and removing links. In the current paper, we develop an experiment to investigate whether people show preferences that involve the outcomes of others during network formation. We find varying evidence for effects of social motives in the settings we compare in the experiment. In the final part of the paper, we discuss some explanations for these findings

Third-Party Effects

Most theories about effects of social embeddedness on trust define mechanisms that assume someone’s decision to trust is based on the reputation of the person to be trusted or on other available information. However, there is little empirical evidence about how subjects use the information that is available to them. In this chapter, we derive hypotheses about the effects of reputation and other information on trust from a range of theories and we devise an experiment that allows for testing these hypotheses simultaneously. We focus on the following mechanisms: learning, imitation, social comparison, and control. The results show that actors learn particularly from their own past experiences. Considering third-party information, imitation seems to be especially important

Signals of belonging: emergence of signalling norms as facilitators of trust and parochial cooperation

Mechanisms of social control reinforce norms that appear harmful or wasteful, such as mutilation practices or extensive body tattoos. We suggest such norms arise to serve as signals that distinguish between ingroup “friends” and outgroup “foes”, facilitating parochial cooperation. Combining insights from research on signalling and parochial cooperation, we incorporate a trust game with signalling in an agent-based model to study the dynamics of signalling norm emergence in groups with conflicting interests. Our results show that costly signalling norms emerge from random acts of signalling in minority groups that benefit most from parochial cooperation. Majority groups are less likely to develop costly signalling norms. Yet, norms that prescribe sending costless group identity signals can easily emerge in groups of all sizes – albeit, at times, at the expense of minority group members. Further, the dynamics of signalling norm emergence differ across signal costs, relative group sizes, and levels of ingroup assortment. Our findings provide theoretical insights into norm evolution in contexts where groups develop identity markers in response to environmental challenges that put their interests at odds with the interests of other groups. Such contexts arise in zones of ethnic conflict or during contestations of existing power relations

An experimental study of network effects on coordination in asymmetric games

Network structure has often proven to be important in understanding the decision behavior of individuals or agents in different interdependent situations. Computational studies predict that network structure has a crucial influence on behavior in iterated 2 by 2 asymmetric ‘battle of the sexes’ games. We test such behavioral predictions in an experiment with 240 human subjects. We found that as expected the less ‘random’ the network structure, the better the experimental results are predictable by the computational models. In particular, there is an effect of network clustering on the heterogeneity of convergence behavior in the network. We also found that degree centrality and having an even degree are important predictors of the decision behavior of the subjects in the experiment. We thus find empirical validation of predictions made by computational models in a computerized experiment with human subjects

Implementing punishment and reward in the public goods game: the effect of individual and collective decision rules

Punishments and rewards are effective means for establishing cooperation in social dilemmas. We compare a setting where actors individually decide whom to sanction with a setting where sanctions are only implemented when actors collectively agree that a certain actor should be sanctioned. Collective sanctioning decisions are problematic due to the difficulty of reaching consensus. However, when a decision is made collectively, perverse sanctioning (e.g. punishing high contributors) by individual actors is ruled out. Therefore, collective sanctioning decisions are likely to be in the interest of the whole group. We employ a laboratory experiment where subjects play Public Goods Games with opportunities for punishment or reward that is implemented either by an individual, a majority, or unanimously. For both punishment and reward, contribution levels are higher in the individual than the majority condition, and higher under majority than unanimity. Often, majority agreement or unanimity was not reached on punishments or rewards