Integrating the Social Vulnerability of Host Communities and the Objective Functions of Associated Stakeholders during Disaster Recovery Processes Using Agent-Based Modeling

Agent-based modeling is being increasingly used to simulate socio-techno-ecosystems that involve social dynamics. Humans face constraints that they sometimes wish to challenge, and when they do so, they often trigger changes at the scale of the social group too. Including such adaptation dynamics explicitly in our models would allow simulation of the endogenous emergence of rule changes. This paper discusses such an approach in an institutional framework and develops a sequence that allows modeling of endogenous rule changes. Parts of this sequence are implemented in a NetLogo KISS model to provide some illustrative results.

Download Full-text

How the Spread of User-Generated Contents (UGC) Shapes International Tourism Distribution: Using Agent-Based Modeling to Inform Strategic UGC Marketing

Journal of Travel Research ◽

10.1177/0047287520951639 ◽

2020 ◽

pp. 004728752095163

Author(s):

Ye Zhang ◽

Jie Gao ◽

Shu Cole ◽

Peter Ricci

Keyword(s):

Social Networking ◽

Social Networking Sites ◽

Real Life ◽

Cost Effective ◽

Agent Based Modeling ◽

Research Approach ◽

Agent Based ◽

The Social ◽

Travel Decision ◽

Media Channels

While user-generated contents (UGC) are recognized as increasingly important to destination marketing, many DMOs are uncertain how to strategically manage them to their best advantage, largely due to their lack of understanding of mechanisms underlying the UGC effects. By integrating multiple theories of travel decision-making and UGC distribution, this study develops and validates an agent-based model to inform DMOs of potential causal mechanisms of how individual tourists’ UGC behavioral features shape international arrival distribution via the social media channels of review sites (RSs) and social networking sites (SNSs). Simulated experiments with the model decompose and assess the complex UGC behavioral effects, which further suggest context-based favorable UGC distribution statuses for DMOs’ strategic UGC marketing. The model developed following a rigid procedure offers a promising UGC research approach toward the combination of restrictive causal conceptualization and real-life replicability. It also provides an adaptive prototype for cost-effective UGC effect assessments by DMOs.

Download Full-text

Agent-based Modeling: The Right Mathematics for the Social Sciences?

The Elgar Companion to Recent Economic Methodology ◽

10.4337/9780857938077.00018 ◽

2013 ◽

Cited By ~ 17

Author(s):

Paul L. Borrill ◽

Leigh Tesfatsion

Keyword(s):

Social Sciences ◽

Agent Based Modeling ◽

Agent Based ◽

The Social ◽

The Right

Download Full-text

Identifying Influence Agents That Promote Physical Activity Through the Simulation of Social Network Interventions: Agent-Based Modeling Study (Preprint)

10.2196/preprints.12914 ◽

2018 ◽

Author(s):

Thabo J van Woudenberg ◽

Bojan Simoski ◽

Eric Fernandes de Mello Araújo ◽

Kirsten E Bevelander ◽

William J Burk ◽

...

Keyword(s):

Physical Activity ◽

Social Networks ◽

Social Network ◽

Selection Criteria ◽

Agent Based Modeling ◽

Agent Based ◽

Network Characteristics ◽

Social Network Intervention ◽

The Social ◽

Network Intervention

BACKGROUND Social network interventions targeted at children and adolescents can have a substantial effect on their health behaviors, including physical activity. However, designing successful social network interventions is a considerable research challenge. In this study, we rely on social network analysis and agent-based simulations to better understand and capitalize on the complex interplay of social networks and health behaviors. More specifically, we investigate criteria for selecting influence agents that can be expected to produce the most successful social network health interventions. OBJECTIVE The aim of this study was to test which selection criterion to determine influence agents in a social network intervention resulted in the biggest increase in physical activity in the social network. To test the differences among the selection criteria, a computational model was used to simulate different social network interventions and observe the intervention’s effect on the physical activity of primary and secondary school children within their school classes. As a next step, this study relied on the outcomes of the simulated interventions to investigate whether social network interventions are more effective in some classes than others based on network characteristics. METHODS We used a previously validated agent-based model to understand how physical activity spreads in social networks and who was influencing the spread of behavior. From the observed data of 460 participants collected in 26 school classes, we simulated multiple social network interventions with different selection criteria for the influence agents (ie, in-degree centrality, betweenness centrality, closeness centrality, and random influence agents) and a control condition (ie, no intervention). Subsequently, we investigated whether the detected variation of an intervention’s success within school classes could be explained by structural characteristics of the social networks (ie, network density and network centralization). RESULTS The 1-year simulations showed that social network interventions were more effective compared with the control condition (beta=.30; t100=3.23; P=.001). In addition, the social network interventions that used a measure of centrality to select influence agents outperformed the random influence agent intervention (beta=.46; t100=3.86; P<.001). Also, the closeness centrality condition outperformed the betweenness centrality condition (beta=.59; t100=2.02; P=.046). The anticipated interaction effects of the network characteristics were not observed. CONCLUSIONS Social network intervention can be considered as a viable and promising intervention method to promote physical activity. We demonstrated the usefulness of applying social network analysis and agent-based modeling as part of the social network interventions’ design process. We emphasize the importance of selecting the most successful influence agents and provide a better understanding of the role of network characteristics on the effectiveness of social network interventions.

Download Full-text

Dynamics in Human and Primate Societies

10.1093/oso/9780195131673.001.0001 ◽

2000 ◽

Cited By ~ 5

Keyword(s):

Social Sciences ◽

Computer Science ◽

Case Studies ◽

Social Problems ◽

Cultural Anthropology ◽

Agent Based Modeling ◽

Small Scale ◽

Agent Based ◽

Recent Advances ◽

The Social

As part of the SFI series, this book presents the most up-to-date research in the study of human and primate societies, presenting recent advances in software and algorithms for modeling societies. It also addresses case studies that have applied agent-based modeling approaches in archaeology, cultural anthropology, primatology, and sociology. Many things set this book apart from any other on modeling in the social sciences, including the emphasis on small-scale societies and the attempts to maximize realism in the modeling efforts applied to social problems and questions. It is an ideal book for professionals in archaeology or cultural anthropology as well as a valuable tool for those studying primatology or computer science.

Download Full-text

Understanding the Social Contagion Effect of Safety Violations within a Construction Crew: A Hybrid Approach Using System Dynamics and Agent-Based Modeling

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph15122696 ◽

2018 ◽

Vol 15 (12) ◽

pp. 2696 ◽

Cited By ~ 6

Author(s):

Huakang Liang ◽

Ken-Yu Lin ◽

Shoujian Zhang

Keyword(s):

System Dynamics ◽

Critical Role ◽

Management Strategies ◽

Hybrid Approach ◽

Agent Based Modeling ◽

Social Contagion ◽

Contagion Effect ◽

Prevention Measures ◽

Agent Based ◽

The Social

Previous research has recognized the importance of eliminating safety violations in the context of a social group. However, the social contagion effect of safety violations within a construction crew has not been sufficiently understood. To address this deficiency, this research aims to develop a hybrid simulation approach to look into the cognitive, social, and organizational aspects that can determine the social contagion effect of safety violations within a construction crew. The hybrid approach integrates System Dynamics (SD) and Agent-based Modeling (ABM) to better represent the real world. Our findings show that different interventions should be employed for different work environments. Specifically, social interactions play a critical role at the modest hazard levels because workers in this situation may encounter more ambiguity or uncertainty. Interventions related to decreasing the contagion probability and the safety–productivity tradeoff should be given priority. For the low hazard situation, highly intensive management strategies are required before the occurrence of injuries or accidents. In contrast, for the high hazard situation, highly intensive proactive safety strategies should be supplemented by other interventions (e.g., a high safety goal) to further control safety violations. Therefore, this research provides a practical framework to examine how specific accident prevention measures, which interact with workers or environmental characteristics (i.e., the hazard level), can influence the social contagion effect of safety violations.

Download Full-text

Agent-Based Modeling: Value Added to Social Work Research

Families in Society The Journal of Contemporary Social Services ◽

10.1177/1044389419842764 ◽

2019 ◽

Vol 100 (3) ◽

pp. 305-311

Author(s):

Emily S. Ihara ◽

JoAnn S. Lee

Keyword(s):

Social Work ◽

Research Methods ◽

Value Added ◽

Agent Based Modeling ◽

Computational Method ◽

Social Phenomena ◽

Agent Based ◽

Social Work Research ◽

Rigorous Research ◽

The Social

Social workers have taken large strides in adopting rigorous research methods, yet there have been computational advances that could enhance the social work knowledge base. This article introduces a computational method, agent-based modeling, which can facilitate theoretical and methodological innovations by strengthening the alignment of our research methods with common social work theories. We review three theories, identify how current methods do not allow for the full exploration of the social phenomena under investigation, and provide justification for using agent-based modeling.

Download Full-text

Creativity in a theory of entrepreneurship

Journal of Entrepreneurship and Public Policy ◽

10.1108/jepp-d-18-00084 ◽

2019 ◽

Vol 8 (4) ◽

pp. 442-469 ◽

Cited By ~ 3

Author(s):

James Lee Caton

Keyword(s):

Computational Simulation ◽

Building Blocks ◽

Agent Based Modeling ◽

Competitive System ◽

Policy Makers ◽

Content Type ◽

Agent Based ◽

The Social ◽

New Knowledge ◽

The Individual

Purpose The purpose of this paper is to integrate a detailed theory of perception and action with a theory of entrepreneurship. It considers how new knowledge is developed by entrepreneurs and how the level of creativity is regulated by a competitive system. It also shows how new knowledge may create value for the innovator as well as for other entrepreneurs in the system. Design/methodology/approach The theory builds on existing literature on creativity and entrepreneurship. It considers how transformation of mental technologies occurs at the individual and system levels, and how this transformation influences value creation. Findings Under a competitive system, the level of creativity is regulated by the need for new ways of doing things. Periods of crisis wherein old means of coordination begin to fail often precipitate an increase in creativity, whereas a lack of crisis often allows the system to settle to a stable equilibrium with lower levels of creativity. Research limitations/implications The combination of methodology and methods facilitates a description of discrete building blocks that guide perception and enable creativity. This framing enables consideration of how a changing set of knowledge interacts with a system of prices. Practical implications Policy makers must take care not to encumber markets with costs that unnecessarily constrain creativity, as experimentation makes the economic system robust to shocks. Social implications This work provides a framing of cognition that allows for a linking of agent understanding that permits explicit description of coordination between agents. It relates perception and ends of the individual to constraints enforced by the social system. Originality/value As far as the author is concerned, no other work ties together a robust framing of cognition with computational simulation of market processes. This research deepens understanding in multiple fields, most prominently for agent-based modeling and entrepreneurship.

Download Full-text

Kesuksesan Knowledge Transfer Di Laboratorium Perguruan Tinggi Melalui Pengelompokkan Rekan Kerja Menggunakan Agent-Based Modeling And Simulation

Jurnal Teknik Industri ◽

10.22219/jtiumm.vol19.no2.205-119 ◽

2018 ◽

Vol 19 (2) ◽

pp. 205

Author(s):

Fadillah Ramadhan ◽

Afrin Fauzya Rizana ◽

Rispianda Rispianda ◽

Yoanita Yuniati

Keyword(s):

Knowledge Transfer ◽

Modeling And Simulation ◽

Agent Based Modeling ◽

Simulation Approach ◽

Agent Based ◽

Social Agent ◽

Adaptive Process ◽

The Social ◽

The University ◽

University Laboratory

One of aspect that contributes to improving organizations performance is knowledge transfer effectiveness. On the other hand, knowledge transfer is a dynamic interaction between people, process, and environment so that activity related to knowledge transfer categorized as a complex and adaptive process. The use of agent-based modeling and simulation approach is very appropriate in modeling knowledge transfer due to its ability to deal with the dynamic, complex, and adaptive process. Moreover, the agent-based approach has the ability in describing the interaction between the social agent that possess particular behavior. The purposes of this study are to identify the factors that influence the success of knowledge transfer in the university laboratory. In addition, the results show that agent-based modeling and simulation approach can determine the best scenario that can increase the success of knowledge transfer based on grouping of colleagues.

Download Full-text