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International audience; We propose a hybrid microsimulation and agent-based model of mobility integrating migration and residential mobility. We tested it on the evolution of the population of the Cantal, a French “département” with 150,000 inhabitants. We calibrated it using various data sources from 1990 to 2006, and tested its predictions on other data of the same period and on the period 2007-2012. The spatial heterogeneity of the evolution is well reproduced and the model makes surprisingly correct predictions despite numerous simplifying assumptions. From this calibration we learnt more about how to model residential mobility and migration considering an agent-based model approach.

Making a suitable career choice is a difficult task. Every year, many adolescents prematurely end their studies, commonly citing “having made the wrong choice” as the main reason. This is a problem, both for the adolescents making these choices, and for society, which bears at least part of the cost of higher education. A thorough understanding of how adolescents make these career choices is essential to identifying the factors responsible for why the wrong choices are often made. Identity development theory emphasizes the role of exploration in career choice, but neglects many of the micro-level processes likely to play an important role. Similarly, traditional decision theory often focuses on optimization of choice, thereby neglecting the cognitive mechanisms that may explain deviations from optimal choice. Here, we present a novel computational approach to modeling long-term decision making. We combine elements of the macro-level theory on identity development with a firm rooting in micro-level cognitive processes. Specifically, we model decision making as an iterative process in which individuals can explore new options or more deeply investigate options that are already under consideration. The output of our model allows us to analyze how the quality of decisions depends on various factors, such as aspiration levels, the tendency to explore new options, and the ability to judge the fit of an option with one’s interests and capabilities. We present some preliminary results that already show our approach can lead to surprising conclusions, encouraging further development of this model in the future.

Both classical social psychological theories and recent formal models of opinion differentiation and bi-polarization assign a prominent role to negative social influence. Negative influence is defined as shifts away from the opinion of others and hypothesized to be induced by discrepancy with or disliking of the source of influence. There is strong empirical support for the presence of positive social influence (a shift towards the opinion of others), but evidence that large opinion differences or disliking could trigger negative shifts is mixed. We examine positive and negative influence with controlled exposure to opinions of other individuals in one experiment and with opinion exchange in another study. Results confirm that similarities induce attraction, but results do not support that discrepancy or disliking entails negative influence. Instead, our findings suggest a robust positive linear relationship between opinion distance and opinion shifts.

Axelrod (1997) showed how local convergence in cultural influence can preserve cultural diversity. We argue that central implications of Axelrod's model may change profoundly, if his model is integrated with the assumption of social influence as assumed by an earlier generation of modelers. Axelrod and all follow up studies employed instead the assumption that influence is interpersonal (dyadic). We show how the combination of social influence with homophily allows solving two important problems. Our integration of social influence yields monoculture in small societies and diversity increasing in population size, consistently with empirical evidence but contrary to earlier models. The second problem was identified by Klemm et al.(2003a,b), an extremely narrow window of noise levels in which diversity with local convergence can be obtained at all. Our model with social influence generates stable diversity with local convergence across a much broader interval of noise levels than models based on interpersonal influence., 20 pages, 3 figures, Paper presented at American Sociological Association 103rd Annual Meeting, August 1-4, 2008, Boston, MA. Session on Mathematical Sociology

Why are people inclined to build friendships and maintain durable, non-reproductive relationships? Previous computational modeling work showed that it can be an efficient survival strategy to choose interaction partners based on relationship length, even if, as a consequence, individuals become unconditionally cooperative in long-term relationships (interpersonal commitment). Such committed individuals can outperform conditional cooperators who play in a fair, reciprocal manner (e.g. tit for tat). However, previous studies did not conduct a sufficiently strict test of the viability of commitment because they did not account for exploiters who specifically take advantage of the tolerance of commitment players. We allow for this by extending previous studies with the possibility of randomly mutating strategies under evolutionary pressures, and thus give a much larger coverage of an infinite strategy space. Our results point to the lack of stable strategies: we find that emerging populations alternate between temporarily stable states. We also show that the viability of strategies increases with increasing levels of interpersonal commitment, and that the effect of interpersonal commitment on viability is larger than the effect of fairness.

The right-wing PVV and the left-wing SP are seen as populist parties who are fierce ideological adversaries in the Dutch political spectrum. We study the similarities and differences in municipal contexts that explain their electoral success. Results of the 2010 national elections at the municipality level are analyzed for nearly all (N=403) Dutch municipalities. Hypotheses are formulated based on integrated group threat theory and relative deprivation theory. Results indicate similarities but also clear differences in the contexts in which SP and PVV thrive. PVV is more successful in municipalities with more immigrants and a higher average perception of unsafety, SP thrives more under local socioeconomic deprivation.

Last decade, small group teaching has increasingly been implemented at universities, such as Learning Communities (LCs) at the Faculty of Behavioral and Social Sciences at the University of Groningen. LCs were compared to mentor groups, with the main difference that LCs are small groups who follow all courses together across the first semester, whereas mentor groups meet only once a week. A positive relationship was expected between social and academic interaction and respectively self-efficacy and early study success and that these relationships were stronger for LCs compared to mentor groups. The survey data came from 407 first-year social sciences' students. The multilevel analyses showed that contact hours, social and academic interaction were positively related to self-efficacy. Academic interaction and self-efficacy contributed each to early study success. For students in LCs the positive effect of academic integration on self-efficacy was stronger than for students in mentor groups.

Two theoretical approaches underlie this investigation of the determinants of early study success among first-year university students. Specifically, to extend Walberg’s educational productivity model, this study draws on the expectancy-value theory of achievement motivation in a contemporary university context. The survey data came from 407 first-year students, and the measure of early study success reflects the weighted grade point average at two moments during their first semester. A path model reveals that the proposed extended educational productivity framework explains early study success well. The operationalised educational productivity factors (age, prior achievement, psychosocial environment, programme satisfaction, study skills) and achievement motivation (expectancy) all relate to early study success, directly or indirectly through expectancy and self-study. The two theoretical approaches jointly provide a thorough understanding of early study success. These results have notable implications for tracking students and for further research.

In our Policy Forum, we argued for the development of a policy dashboard to manage complex financial-economic systems based on an interdisciplinary network analysis and behavioral modeling approach.The argument about fraud is not one against models or our complexity approach, and economic theory offers ways to investigate what fraud and breaching of trust would do to a system. For example, methods and insight from the theory of evolutionary biology and evolutionary game theory can be used to include agents that “cheat” the system by not following accepted sets of rules in their behavior.

Precise analysis of agent-based model (ABM) outputs can be a challenging and even onerous endeavor. Multiple runs or Monte Carlo sampling of one's model (for the purposes of calibration, sensitivity or parameter-outcome analysis) often yield a large set of trajectories or state transitions which may, under certain measurements, characterize the model's behavior. These temporal state transitions can be represented as a directed graph (or network) which is then amenable to network analytic and graph theoretic measurements. Building on strategies of aggregating model outputs from multiple runs into graphs, we devise a temporally-constrained graph aggregating state changes from runs and examine its properties in order to characterize the behavior of a land-use change ABM, the RHEA model. Features of these graphs are transformed into measures of complexity which in turn vary with different parameter or experimental conditions. This approach provides insights into the model behavior beyond traditional statistical analysis. We find that increasing the complexity in our experimental conditions can ironically decrease the complexity in the model behavior.

The 'mutual-investment' model argues that when employers invest more in the social exchange relationship between them and their employees, their employees will show more effort. In this paper we relate the 'mutual-investment' model to training and promotion (possibilities) and examine if these kinds of career-enhancing measures influence the willingness of employees within organizations to work overtime. To test this hypothesis, a vignette experiment was conducted in five organizations (N = 388; 1,531 vignettes). Multilevel analyses show that employees are more willing to work overtime when their employer has provided for training, when the employee recently was promoted, when the supervisor was supportive in the past and when co-workers approve of working overtime and behave similarly. But we did not find that future promotion chances affect willingness to work overtime.

We are grateful for the opportunity that Bendor, Diermeier, and Ting (hereafter BDT) have provided to address important questions about the empirical content of learning theoretic solutions to the collective action problem. They discuss two well-known classes of adaptive models— stochastic learning models like that of Bush and Mosteller (1955) that have been applied to collective action and social exchange (Macy 1990, 1991a, 1991b, 1993; Macy and Flache 2002; Flache and Macy 2002) and theories of satisficing in organizational behavior advanced by Simon (1955) and Cyert and March (1963). According to Popper (1974, p. 986), when ad hoc assumptions are introduced “to explain a particular difficulty” and these assumptions “cannot be tested independently,” the theory is immunized from refutation. A theory that can explain anything can explain nothing, hence it lacks empirical content. Popper pointed to Darwinism as an example of a theory that is “almost tautological” (Popper 1978). Consequentialist explanations— such as those based on rational choice, natural selection, or reinforcement learning—lack empirical content when any outcome can be explained by proposing some preference, fitness, or aspiration that cannot be tested independently of the outcomes they explain. [....]

Previous research has pointed to the potential of counter-punishment opportunities to undermine the positive effects of ‘altruistic punishment’ on cooperation in collective good games. These studies may have excluded important aspects of punishment in real life settings, notably the ambiguity whether punishment is a retaliation for previous punishment or a sanction imposed for free-riding. To derive expectations, we draw on an earlier social exchange model of the ambiguity of positive sanctions as a means of social control in a repeated collective action game. We argue that counter-punishment may become considerably less attractive for free riders who experienced a sanction, when the possibility to retaliate is embedded in a longer term ongoing exchange relationship. In such a setting, counterpunishment may evoke in turn retaliation or fail to prevent future sanctions from norm enforcers. To test our expectations, we extend the collective good experiments of Fehr and Gächter (2000) with a counter-punishment condition, to assess the extent to which counter-punishment opportunities impair the effectiveness of punishment as a solution to the cooperation problem in collective good games. We compared a treatment in which counter-punishment was not possible to a treatment in which it was, keeping all other conditions equal. Results showed that there was both free-riding and costly punishment in the treatment without counter-punishment. When counter-punishment was added, we found that the opportunity to counter-punish did not lead to significant levels of actual counter-punishment in the first place, although there was still free-riding and costly punishment of free-riders. This supports the view of punishment as an effective enforcement instrument of cooperation in a collective-good situation, even when counter-punishment is possible. This has led us to devise a follow-up study in which we test possible explanations for the absence of counter-punishment. Data for this follow-up are currently being collected.

Contemporary theories of rational behavior in human society augment the orthodox model of rationality both by adding various forms of bounded rationality and relaxing the assumptions of self-interest and materialistic preferences. This entry discusses how these extensions of the theory of rational behavior are increasingly applied to explain rational behavior in society. First, the baseline model of rational behavior and its extensions are discussed, with particular emphasis on heuristics, learning theory and theories of social preferences. Subsequently, applications to rational behavior in societal realms are addressed. Three areas of application are discussed in particular, production of collective goods, social networks and rationality in organizations

Research on the influence of the number of ethnic minority group classmates on majority group students' interethnic attitudes produced conflicting results. With data from 728 early adolescents, we found that the effect of the ethnic class composition depends on two opposing student-level mechanisms. First, majority group students who liked a larger number of minority group classmates developed more positive attitudes toward minority groups. Second, students who disliked a larger number of outgroup classmates developed more negative outgroup attitudes. In our sample, these two effects neutralized each other because the sample consisted of about the same number of students that liked most of their outgroup classmates and students that disliked most outgroup classmates. Results were consistent in cross-sectional and longitudinal analyses. These results support a new interpretation of the mixed findings in past research, suggesting that past studies may have differed in the number of students who liked and disliked outgroup classmates.

This paper addresses theoretically the question how virtual communication may affect cooperation in work teams. The degree of team virtualization, i.e. the extent to which interaction between team members occurs online, is related to parameters of the exchange. First, it is assumed that in online interaction task uncertainties are higher than in face-to-face contacts. Second, the gratifying value of peer rewards is assumed to be lower in online contacts. Thirdly, it is assumed that teams are different in the extent to which members depend on their peers for positive affections, operationalized by the extent to which team members are interested in social relationships for their own sake, independently from their work interactions. Simulation results suggest both positive and negative effects of team virtualization on work-cooperation.

Multi-Agenten-Modellierung ist eine Form der Computermodellierung die darauf abzielt zu erklären, wie soziale Phänomene aus dem komplexen Zusammenspiel interdependenter Individuen entstehen. Der vorliegende Beitrag gibt eine kurze Einführung in die Grundlagen sozialwissenschaftlicher Multi-Agenten-Modellierung. Wir besprechen dabei wichtige Modellierungsentscheidungen und Modellierungsalternativen. Am Anwendungsbeispiel der Erklärung von Meinungsdiversität wird illustriert, wie Simulationsexperimente mit einem Multi-Agenten-Modell und inhaltliche sozialwissenschaftliche Theoriebildung aufeinander bezogen werden können. Auf Basis der Programmiersprache NetLogo legen die Autoren das Modell als einfaches Beispielprogramm vor. Abschließend werden methodologische Prinzipien und Probleme der Multi-Agenten-Modellierung besprochen und Hinweise auf weiterführende Literatur gegeben.

Status beliefs link social distinctions, such as gender and race, to assumptions about competence and social worth. Recent modeling work in status construction theory suggests that interactions in small, task focused groups can lead to the spontaneous emergence and diffusion of such beliefs in larger populations. This earlier work has focused on dyads as the smallest possible groups in which status beliefs might emerge from face-to-face interaction. In today's societies, however, many task focused interactions take place in groups larger than dyads. In this article, we therefore develop an agent-based computational model that enables us to study the emergence of status beliefs in groups larger than dyads. With this model, we address questions such as: Do basic principles of task focused interaction systematically favor the emergence of status beliefs in groups larger than dyads? Does the time-frame over which small groups interact affect the likelihood with which status beliefs emerge? How does group size affect the emergence of status beliefs? Computational experimentation with the new model suggests that behavioral principles known to spontaneously create hierarchical differentiation between individual group members also tend to align these hierarchies with categorical differences and thereby facilitate the emergence of status beliefs. This tendency is stronger in smaller groups, and in groups that interact either for a very short or very long time. ispartof: Journal of Artificial Societies and Social Simulation vol:18 issue:2 status: published

a b s t r a c t This study investigates among ethnic minority adolescents how friendships with ethnic minority and majority group peers are related to their attitudes towards the majority outgroup. Friendships with majority group peers are proposed to be indirectly related to outgroup attitudes through host society identification. Friendships with ethnic ingroup peers are pro- posed to be indirectly related to outgroup attitudes through ethnic ingroup identification. Hypotheses were tested longitudinally among ethnic minority adolescents (n = 244) who recently entered middle schools in the Netherlands. Lagged structural equation models showed that friendships with majority group peers were related to stronger identification with the host society which was in turn related to improved attitudes toward the majority outgroup. Ingroup friendships and ingroup identification was not related to outgroup atti- tudes. Additional analyses indicated that the relation between host society identification and majority group friendships was bidirectional.

Concerns about models of cultural adaptation as analogs of genetic selection have led cognitive game theorists to explore learning-theoretic specifications. Two prominent examples, the Bush-Mosteller stochastic learning model and the Roth-Erev payoff-matching model, are aligned and integrated as special cases of a general reinforcement learning model. Both models predict stochastic collusion as a backward-looking solution to the problem of cooperation in social dilemmas based on a random walk into a self-reinforcing cooperative equilibrium. The integration uncovers hidden assumptions that constrain the generality of the theoretical derivations. Specifically, Roth and Erev assume a “power law of learning”—the curious but plausible tendency for learning to diminish with success and intensify with failure. Computer simulation is used to explore the effects on stochastic collusion in three social dilemma games. The analysis shows how the integration of alternative models can uncover underlying principles and lead to a more general theory.

Recent research argues that individual risk aversion favors cooperation in social dilemmas. The argument focuses on conditional cooperation in repeated interaction. The more risk averse actors are, the less they are inclined to put at risk ongoing cooperative relationships by attempts at unilateral exploitation. I argue that this reasoning may not suffice to capture risk effects in exchange networks, where actors face both decisions about cooperation and decisions about selection of new partners. I present a model that combines both decisions. Consistent with previous analyses, the model predicts that individual risk aversion favors rational cooperation in ongoing dyadic exchanges. However, simulations also reveal that risk aversion may negatively affect cooperation through reduced mobility in partner search. If actors consider partner change as risky, then risk-averse actors may stick to sub-optimal relationships, even if better alternatives are available that allow for higher levels of cooperative exchanges. Further simulations show nonlinear effects of individual risk preferences on the density and efficiency of exchange networks.

In this paper we compare two micro foundations for modelling human behaviour and decision making. We focus on perfect strategic rationality on the one hand and a simple reinforcement mechanism on the other hand. Iterated prisoner’s dilemmas serve as the play ground for the comparison. The main lesson of our analysis is that in the space of all possible 2 × 2 PDs different micro foundations do matter. This suggests that researchers can not safely rely on the assumption that implementing simple models of decision making will yield the same results that may be obtained when more sophisticated decision rules are built into the agents.