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AbstractThis article uses computer simulations as a means of assessing two different models for the competition between two languages from the interdisciplinary perspective of complex systems. These models allow for the analysis of the role of bilingual speakers and they consider two of the basic factors determining the use of each language: their relative prestige and the language loyalty of their speakers. Here we assess the effect of these parameters in different social networks, with the aim of contributing to the understanding of the role of bilingualism and social networks in processes of language contact. We first present a qualitative analysis based on a simulation tool that we have designed, in order to visualize the dynamics of the models. Secondly, we consider a qualitative analysis of the role of complex networks, identifying mechanisms for the rapid extinction of a language and for situations of language segregation. Finally, we present a quantitative analysis which shows, counter-intuitively, a transition from a final scenario of language maintenance to one of language shift as language loyalty increases. Other findings are: (i) that the scenario of language coexistence is reduced in the presence of bilingual agents; and (ii) that networks which allow for local effects reduce further the situations for which language maintenance is possible.

The diversity of views on causality and mechanisms -- ABM and the vertical view on mechanisms -- The diversity of ABMs -- ABMs and causal inference -- Causal Inference in experimental and observational methods -- Method diversity and causal inference.

We use an agent-based model to investigate the interdependent dynamics between individual agency and emergent socioeconomic structure, leading to institutional change in a generic way. Our model simulates the emergence and exit of institutional units, understood as generic governed social structures. We show how endogenized trust and exogenously given leader authority influences institutional change, i.e., diversity in institutional life-cycles. It turns out that these governed institutions (de)structure in cyclical patterns dependent on the overall evolution of trust in the artificial society, while at the same time, influencing this evolution by supporting social learning. Simulation results indicate three scenarios of institutional life-cycles. Institutions may, (1) build up very fast and freeze the artificial society in a stable but fearful pattern (ordered system); (2) exist only for a short time, leading to a very trusty society (highly fluctuating system); and (3) structure in cyclical patterns over time and support social learning due to cumulative causation of societal trust (complex system).

We use an agent-based model to investigate the interdependent dynamics between individual agency and emergent socioeconomic structure, leading to institutional change in a generic way. Our model simulates the emergence and exit of institutional units, understood as generic governed social structures. We show how endogenized trust and exogenously given leader authority influences institutional change, i.e., diversity in institutional life-cycles. It turns out that these governed institutions (de)structure in cyclical patterns dependent on the overall evolution of trust in the artificial society, while at the same time, influencing this evolution by supporting social learning. Simulation results indicate three scenarios of institutional life-cycles. Institutions may, (1) build up very fast and freeze the artificial society in a stable but fearful pattern (ordered system) ; (2) exist only for a short time, leading to a very trusty society (highly fluctuating system) ; and (3) structure in cyclical patterns over time and support social learning due to cumulative causation of societal trust (complex system).

2015 Spring. ; Includes illustrations (some color). ; Includes bibliographical references (pages 98-107). ; Public expectations for what constitute responsible practices of mining and other extractive companies have been evolving and becoming evermore complex. As focal organizations struggle to come to terms with increased expectation, tools must be developed to assess performance and, if possible, predict and forecast how their performance will be received by stakeholders in the future. The main purpose of this work is to provide a tool for assessing the current state and longevity of public perceptions of corporations who are already measuring their social performance. This tool should allow managers and other decision makers within a focal organization to plan for and manage social risk to their operations by giving them a sense of the potential social outcomes that a specific project may generate. In addition, it may provide insight to others interested in the social license of a given project, such as governments, NGO's, and individual stakeholders and stakeholder groups. The work provided herein is comprised of an agent-based model of fluctuations in social license to operate through the use of opinion diffusion and stakeholder network creation. Agent-based modeling is a bottom-up approach that explores complex macroscopic phenomena through the implementation of simple microscopic rules for the behavior of individual agents. This method allows researchers to explore and quantify potential outcomes. The model created for this work demonstrates the change in social license for a group of stakeholders with a specific distribution of influence and individual consensus levels. Furthermore, it successfully recreates network structures thought to be associated with different levels of durability of the social license granted by a stakeholder network. These network structures are analyzed for their stability and ability to self-propagate within the model.

Biogas production from manure has been proposed as a partial solution to energy and environmental concerns. However, manure markets face distortions caused by considerable unbalance between supply and demand and environmental regulations imposed for soil and water protection. Such market distortions influence the cooperation between animal farmers, biogas producers and arable land owners causing fluctuations in manure prices paid (or incurred) by animal farmers. This paper adopts an agent-based modeling approach to investigate the interactions between manure suppliers, i.e., animal farmers, and biogas producers in an industrial symbiosis case example consisting of 19 municipalities in the Overijssel region (eastern Netherlands). To find the manure price for successful cooperation schemes, we measure the impact of manure discharge cost, dimension and dispersion of animal farms, incentives provided by the government for bioenergy production, and the investment costs of biogas plants for different scales on the economic returns for both actor types and favorable market conditions. Findings show that manure exchange prices may vary between −3.33 €/t manure (i.e., animal farmer pays to biogas producer) and 7.03 €/t manure (i.e., biogas producer pays to animal farmer) and thanks to cooperation, actors can create a total economic value added between 3.73 €/t manure and 39.37 €/t manure. Hence, there are cases in which animal farmers can profitably be paid, but the presence of a supply surplus not met by demand provides an advantage to arable land owners and biogas producers in the price contracting phase in the current situation in the Netherlands.

We use an agent-based model to investigate the interdependent dynamics between individual agency and emergent socioeconomic structure, leading to institutional change in a generic way. Our model simulates the emergence and exit of institutional units, understood as generic governed social structures. We show how endogenized trust and exogenously given leader authority influences institutional change, i.e., diversity in institutional life-cycles. It turns out that these governed institutions (de)structure in cyclical patterns dependent on the overall evolution of trust in the artificial society, while at the same time, influencing this evolution by supporting social learning. Simulation results indicate three scenarios of institutional life-cycles. Institutions may, (1) build up very fast and freeze the artificial society in a stable but fearful pattern (ordered system); (2) exist only for a short time, leading to a very trusty society (highly fluctuating system); and (3) structure in cyclical patterns over time and support social learning due to cumulative causation of societal trust (complex system).