Automating agent-based modeling: Data-driven generation and application of innovation diffusion models

Jensen, Thorben; Chappin, E.J.L.

doi:10.1016/j.envsoft.2017.02.018

Cited by 13 publications

(14 citation statements)

References 23 publications

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“…Statistical analysis of such empirical data provides a measure of the state of opinion that is close to the reality in society. However, Jensen and Chappin 15 analyzed observations of concurrent events and noted that reaching a mechanistic understanding of social phenomena is more difficult than employing a statistical inference approach 15 . Although there are currently many unrelated methodologies employed to understand the characteristics of social acceptance, no standard practices are emerging 16 – 18 .…”

Section: Introductionmentioning

confidence: 99%

Agent based simulation with data driven parameterization for evaluation of social acceptance of a geothermal development: a case study in Tsuchiyu, Fukushima, Japan

Masuda

Bahr

Tsuchiya

et al. 2022

Sci Rep

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Development of geothermal power plants and local geothermal energy initiatives have lagged due to the social problems such as conflicts with stakeholders such as Onsen (Hot Spa) owners, despite the abundant geothermal resources. Study area was Tsuchiyu Onsen in Fukushima prefecture, Tohoku (Northeast) District, Japan, where the Great East Japan Earthquake and Fukushima Nuclear Accident occurred in 2011, and the reconstruction and local initiatives of geothermal energy were still unclear. Agent-based modeling is an effective methodology for modeling and analysis of opinion formation. Parameter estimation method was proposed to extract appropriate parameters from various factors through a Bayesian Network. The characteristics of stakeholders and communities that affected opinion formation in the survey area were successfully extracted. Here we show the sufficient methodology to quantify the characteristics of each person using survey data, and to extract the parameters of the agent by data-driven inverse analysis. By using this methodology, we could reproduce opinion diversity, which is a property of opinion formation in real communities. This result suggests that the model replicates the actual formation of opinion in Tsuchiyu, where the economy was boosted by the construction of a binary cycle power plant.

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Section: Introductionmentioning

confidence: 99%

Agent based simulation with data driven parameterization for evaluation of social acceptance of a geothermal development: a case study in Tsuchiyu, Fukushima, Japan

Masuda

Bahr

Tsuchiya

et al. 2022

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Statistical analysis of such empirical data provides a measure of the state of opinion that is close to the reality in society. However, Jensen and Chappin (2017) analyzed observations of concurrent events and noted that reaching a mechanistic understanding of social phenomena is more difficult than employing a statistical inference approach 15 .…”

Section: Introductionmentioning

confidence: 99%

“…In particular, the value of bounded confidence is a primary influence on agents' behavior. Many other models employ a similar fundamental system of opinion formation; however, various kinds of agent parameters have been proposed to improve model performance 15,[19][20][21][22][23][24] . This modeling methodology is suitable for understanding the behavioral trends of opinion formation, and for evaluating policies for consensus-building by scenario simulation.…”

Section: Introductionmentioning

confidence: 99%

Agent-Based Simulation with Data-Driven Parameterization for Evaluation of Social Acceptance of a Geothermal Development

Tsuchiya

Masuda

Bahr

et al. 2021

Preprint

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Development of geothermal power plants and local geothermal energy initiatives have lagged due to the social problems such as conflicts with stakeholders such as Onsen (Hot Spa) owners, despite the abundant geothermal resources. Study area was Tsuchiyu Onsen in Fukushima prefecture, Tohoku (Northeast) District, Japan, where the Great East Japan Earthquake and Fukushima Nuclear Accident occurred in 2011, and the reconstruction and local initiatives of geothermal energy were still unclear. Agent-based modeling (ABM) is an effective methodology for modeling and analysis of opinion formation. Parameter estimation method was proposed to extract appropriate parameters from various factors through a Bayesian Network. The characteristics of stakeholders and communities that affected opinion formation in the survey area were successfully extracted. Here we show the sufficient methodology to quantify the characteristics of each person using survey data, and to extract the parameters of the agent by data-driven inverse analysis. By using this methodology, we could reproduce opinion diversity, which is a property of opinion formation in real communities. This result suggests that the model replicates the actual formation of opinion in Tsuchiyu, where the economy was boosted by the construction of a binary cycle power plant.

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“…formation of diffusion process [5]- [7], mining of driving or inhibiting factors [8], [9], and most recently the microscopic exploration of innovation adoption [10]- [12].…”

Section: Introductionmentioning

confidence: 99%

A Multiplex Network Perspective of Innovation Diffusion: An Information-Behavior Framework

2020

IEEE Access

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Information transmission of innovation and peer effect among firms have significant impacts on innovation adoption decisions of firms, but those effects usually depend on the different types of inter-firm networks. Therefore, the diffusion of innovation (DOI) can be regarded as a process occurring in complex systems composed of different types of interactions, which can be categorized into links belonging to different layers of multiplex networks. This study aims to shed light on the complexity of innovation diffusion from the perspective of an information-behavior framework based on multiplex networks. The process of technology innovation adoption is formulated into two stages including information perception and decision making, and a novel innovation diffusion model based on duplex inter-firm networks, in which one layer has influence on information transmission and the other carrys the peer effect, is further proposed in this study. The simulation experiments indicate that the random-scale-free duplex networks are favourable to the diffusion speed while scale-free-scale-free duplex networks are conducive to the diffusion range. Moreover, within the scale-free-scale-free duplex networks, the diffusion speed will increase with the increasing of the power law index in the information network and decrease with the increasing of the power law index of the behavior network. The study contributes to the literature by establishing duplex network model that distinguishes links between information and behavior networks, and offers insights concerning optimization of network configuration in the promotion of DOI. INDEX TERMS Multiplex networks, diffusion of innovation, information-behavior framework, agent-based modeling.

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Automating agent-based modeling: Data-driven generation and application of innovation diffusion models

Cited by 13 publications

References 23 publications

Agent based simulation with data driven parameterization for evaluation of social acceptance of a geothermal development: a case study in Tsuchiyu, Fukushima, Japan

Agent based simulation with data driven parameterization for evaluation of social acceptance of a geothermal development: a case study in Tsuchiyu, Fukushima, Japan

Agent-Based Simulation with Data-Driven Parameterization for Evaluation of Social Acceptance of a Geothermal Development

A Multiplex Network Perspective of Innovation Diffusion: An Information-Behavior Framework

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