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In Schelling’s “checkerboard” model of segregation, individuals’ moderately held preferences about the proportion of their neighbors who are similar versus dissimilar to them can, through an automatic and mathematical process, yield dramatic population-level segregative behaviors. The notion of such an automatic segregative process would seem to have implications for spatial dynamics when a group home for persons with disabilities is introduced into a community. This study sought to examine those implications alongside data in the research literature regarding community acceptance of group homes.

Using an agent-based modeling approach, computer simulations were constructed to apply Schelling’s model, as well as an alternative model, to community reaction to the introduction of group homes for persons with disabilities. Simulation conditions were set to roughly correspond to the proportion of group homes or other congregate living situations, as well as vacant dwellings, in a typical community in the United States.

The simulations predict that group homes will, to varying degrees, become spatially isolated within their communities. These predictions conflict with previous research findings that suggest minimal relocation of neighbors and rapid adjustment of communities to the presence of group homes.

Simulations of an automatic segregative process might offer a baseline or a “null hypothesis” of sorts, allowing us to more fully understand the extent of the social and socioeconomic forces that serve to moderate or override such an automatic process, allowing communities to adjust to group homes’ presence.

Does the classical liberal emphasis on freedom of association provide an intellectual cover for bigotry? We formulate this question in economic terms using James Buchanan’s economic approach to ethics, according to which moral values can be understood as preferences about other people’s behaviors. We discuss two possible market failures associated with freedom of association: inter-group externalities and Schelling-type emergent segregation. We show that the classical liberal position about freedom of association, as elaborated in Buchanan and Tullock’s Calculus of Consent, is fully equipped to deal with the first one, but not with the second. The progressive view that some preferences are so offensive that they should be dismissed rather than engaged or negotiated with can be reframed as an attempt to solve the emergent segregation problem, but it is vulnerable to political economy problems of its own, in particular to an inherent tendency to over-expand the meaning of “bigotry.”

The purpose of this article is to provide an overview of agent-based modeling as an alternative method for public administration research. It is focused on encouraging public administration scholars to come to better understanding of the method.

This article performed a comprehensive review of methodological issues relative to agent-based modeling.

After reviewing the current research themes in public administration and the methodological nature of agent-based modeling, we found that agent-based modeling can help researchers to advance theories by means of sophisticated thought experiment which is not possible by formal modeling and verbal reasoning. We also pointed out that agent-based modeling does not substitute empirical research, but can add much value through being part of a mixed-method and multidisciplinary research.

We suggested that interested researchers may need to take a strategic approach in developing and describing a pertinent model and reporting its results.

Agent-based modeling has rarely been used in public administration research. The article provides an introductory overview for researchers not familiar with ABM and suggests to the academic community future venues that would unfold from agent-based modeling.

The purpose of this paper is to explain the emergence of non‐cooperative behaviour after the economic transition in Estonia.

The paper uses a combined research design, in that evolutionary game theory and network segregation models are enriched with semi‐structured interviews. Simulations are used to deal with analytical complexity; in this case a prisoners' dilemma situation is used and randomness is created through the exogenous shock of opening the network to “aliens”.

Consequently, it is found that individuals in large and small communities differ in their behavioural strategies: in an open community, players are more self‐interested and reciprocate only benevolent behaviour; in a regular community, people rely on cooperative social norms. Case specific information leads to the suggestion that in open networks people behave cooperatively only in teams of up to four members. Increasing the random connections in a network makes people use group segregation – that is, they behave cooperatively in regular connections and in a self‐regarding manner towards others.

The method brings certain limitations to the implications of the results – simulations are sensitive to the initial conditions set up using qualitative data.

In managerial areas the results can provide at least two insights. First, it is obvious that only small teams (with personal connections) can be fully cooperative. In this case, the ideal number of co‐operators is four. In larger teams, individuals find it more profitable to segregate an inner circle and others. Second, if players are interpreted as firms, then competition between firms will prevail even in small communities (where new players can penetrate the market) and thus any cartel or other cooperative action will fail.

The main value of the research is twofold: it allows to introduce the combined research methodology and explain the mental change after transition in the 1990s. The first enables to reduce the methodological impediments researchers find in the qualitative‐quantitative dichotomy. The second explains the emergence of, and changes to, the behavioural or moral codes as a result of rational social learning.

The pattern of racial segregation in U.S. elementary and secondary schools has changed significantly over the last 25 years. This chapter examines the relationship between the racial composition of schools and the choices white parents make concerning the schools their children attend. Restricted access files at the Bureau of the Census allow us to identify each household's Census block of residence and, in turn, suburban public school districts and urban public school attendance areas. We find that the racial composition of schools and neighborhoods are very important in the school and location decisions of white families.

The purpose of this paper is to provide an analysis and an optimization model of the spatial impact for the externalities derived from urban regeneration and rehabilitation of degraded and segregated historic heritage areas.

From the amount invested and state intervention locations, an impact index is put forward. The spatial distribution of these impact indexes in the interventions' area of influence will be the basis for the analysis. Hence, by setting some specific objectives of the decision agent about this distribution homogeneity, and with the aim of avoiding inner segregation and to facilitate the sustainable urban development and cohesion of the neighborhood as a whole, a model which will allow the allocation of the budget available among the different locations fixed a priori is proposed.

It is found that by comparing the spatial distributions of impact indexes obtained in both situations, a measure of the urban regeneration and rehabilitation process and its impact can be obtained.

In order to favour the neighborhoods' internal cohesion and to avoid inner segregation, the model enables one to better address priority areas of intervention inside a historic heritage urban area and to better achieve sustainable urbanization by providing a more equitable and efficient managing of resources.

Agent-based modelling and simulation (ABMS) has seen wide-spread success through its applications in the sciences and social sciences over the last 15 years. As ABMS is used to model more and more complex systems, there is going to be an increase in the number of input variables used within the simulation. Any uncertainty associated with these input variables can be investigated using sensitivity analysis, but when there is uncertainty surrounding several of these input variables, a single parameter sensitivity analysis is not adequate. Latin hypercube sampling (LHS) offers a way to sample variations in multiple parameters without having to consider all of the possible permutations. This paper introduces the application of LHS to ABMS via a case study that investigates the mortgage foreclosure contagion effect. This paper aims to discuss these issues.

Traditionally, uncertainty surrounding a single input variable is investigated using sensitivity analysis. That is, the variable is allowed to change to determine the impact of this variation on the simulation's output. When there is uncertainty about multiple input variables, then the number of simulation runs required to undertake this investigation greatly increases due to the permutations that need to be considered. LHS, which was first derived by McKay et al., offers a proven mechanism to reduce the number of simulation runs needed to complete a sensitivity analysis. This paper describes the LHS technique and its applications to an agent-based simulation (ABS) for investigating the foreclosure contagion effect.

The results from the foreclosure ABS runs have been characterized as “good”, “bad” or “ugly”, corresponding to whether or not a property market crash has occurred. As the only thing that can induce a property market crash within our model is the spread of foreclosing properties, these results indicate that the foreclosure contagion effect is dependent on how much impact a foreclosed property has on the price of the surrounding properties.

This paper describes the application of LHS to an agent-based foreclosure simulation. The foreclosure model and its results have been described in Gangel et al. Given a certain output “boundary” found within these results, it was highly appropriate to conduct an extensive sensitivity analysis on the simulation's input variables. The outcome of the LHS sensitivity analysis has given further insight into the foreclosure contagion effect thus demonstrating it was a beneficial exercise.

The purpose of this paper is to argue that in cross-cultural and strategic management, we must pay attention to the processes creating and maintaining culture. How can everyday interactions give rise to national, “deep” cultures, recognizable across centuries, or organizational cultures, recognizable across decades?

This is a conceptual paper using the evidence provided by research about cultural patterns, and using sociological status-power theory to explain the causation of these patterns. Emergence, also called self-organization, is introduced as mechanism connecting individual-level causation with resulting system-level patterns. Cases are used to illustrate points.

Simulation gaming and computational social simulation are introduced. These methods allow “growing” a system, thus allowing to experiment with potential interventions and their unanticipated effects.

This essay could have major implications for research, adding new methods to survey-based and case-based studies, and achieving a new synthesis. Strategic management today almost invariably involves cross-cultural elements. As a result, cross-cultural understanding is now strategically important.

The suggestions in this essay could lead to new collaborations in the study of culture and organizational processes. Examples include team formation, negotiation, mergers and acquisitions, trans-national collaboration, incentive systems and job interviews.

The suggestions in this essay could contribute to our ability of proactively steering processes in organizations. In particular, they can provide a check to the notion that a control measure necessarily results in its intended effect.

The synthesis of biological, sociological and cross-cultural psychological viewpoints with design-oriented method, using games or social simulations as research instruments, is original in the field.

The authors discuss the microfoundations of institutional theory, specifically as microfoundations are manifested in this volume of Research in the Sociology of Organizations. The authors argue that the main interest seems to be in better understanding macrofoundations: top-down forces from institutions to actors. Furthermore, throughout the volume institutions themselves are definitionally layered – in problematic ways – with a large array of other macroconstructs, including fields, logics, practices, habitus, situations, routines, and so forth. The authors argue that there is an opportunity to more carefully delineate microfoundations for institutional theory, by focusing on lower-level heterogeneity, agency, as well as the aggregate and emergent social processes that animate microfoundational explanation.