Integrating the theory of planned behavior in agent-based models: A systematic review of applications of pro-environmental behaviors.

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Title: Integrating the theory of planned behavior in agent-based models: A systematic review of applications of pro-environmental behaviors.
Authors: Taraghi, Mahdi1 (AUTHOR) mtaraghi@iu.edu, Yoder, Landon1 (AUTHOR)
Source: Ecological Modelling. Sep2025, Vol. 508, pN.PAG-N.PAG. 1p.
Subjects: Green behavior, Social scientists, Human behavior models, Planned behavior theory, Environmental protection
Abstract: • A systematic review of 36 studies operationalizing TPB in agent-based models for PEBs. • Highlights inconsistent TPB operationalization across modeling practices. • Replicability challenges persist, as only 19% shared both model documentation and code. • Calls for reusable TPB building blocks to enhance modeling standardization. • Interdisciplinary collaboration is key to behavioral model design. This paper systematically reviews how agent-based models apply the Theory of Planned Behavior (TPB) to simulate pro-environmental behaviors across diverse domains, including environmental conservation, water management, agriculture and energy. We reviewed 36 studies to examine how researchers operationalize TPB, incorporate empirical data, and follow best practices for transparency and replicability. Given the static and abstract nature of TPB, modelers have employed diverse mechanisms to operationalize it in agent-based models, using external and internal control variables as intermediary proxies alongside social network structures. Moreover, nearly half of the reviewed studies either incorporated an extended version of TPB in their models or integrated TPB with other behavioral models, showing its flexibility to be integrated with other behavioral models. While 47% of the case study-based research obtained TPB data from self-developed quantitative surveys to inform their agent-based models, only a small subset of these surveys adhered to the principle of compatibility—a key prerequisite for the predictive validity of the TPB. Also, despite growing efforts to promote transparency and replicability through practices such as employing the ODD protocol for model descriptions and sharing code, only 19% of studies shared both their protocol documentation and models, highlighting the need for further progress to fully achieve these objectives. To mitigate ambiguities and enhance consistency in translating TPB constructs into computational representations, we advocate for development of reusable building blocks as a way to establish community standards. Furthermore, stronger collaboration between modelers and social scientists is essential for designing theory-driven surveys that accurately inform agent behavior. [ABSTRACT FROM AUTHOR]
Copyright of Ecological Modelling is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
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  Data: Integrating the theory of planned behavior in agent-based models: A systematic review of applications of pro-environmental behaviors.
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  Data: <searchLink fieldCode="AR" term="%22Taraghi%2C+Mahdi%22">Taraghi, Mahdi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> mtaraghi@iu.edu</i><br /><searchLink fieldCode="AR" term="%22Yoder%2C+Landon%22">Yoder, Landon</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Ecological+Modelling%22">Ecological Modelling</searchLink>. Sep2025, Vol. 508, pN.PAG-N.PAG. 1p.
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  Data: <searchLink fieldCode="DE" term="%22Green+behavior%22">Green behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Social+scientists%22">Social scientists</searchLink><br /><searchLink fieldCode="DE" term="%22Human+behavior+models%22">Human behavior models</searchLink><br /><searchLink fieldCode="DE" term="%22Planned+behavior+theory%22">Planned behavior theory</searchLink><br /><searchLink fieldCode="DE" term="%22Environmental+protection%22">Environmental protection</searchLink>
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  Label: Abstract
  Group: Ab
  Data: • A systematic review of 36 studies operationalizing TPB in agent-based models for PEBs. • Highlights inconsistent TPB operationalization across modeling practices. • Replicability challenges persist, as only 19% shared both model documentation and code. • Calls for reusable TPB building blocks to enhance modeling standardization. • Interdisciplinary collaboration is key to behavioral model design. This paper systematically reviews how agent-based models apply the Theory of Planned Behavior (TPB) to simulate pro-environmental behaviors across diverse domains, including environmental conservation, water management, agriculture and energy. We reviewed 36 studies to examine how researchers operationalize TPB, incorporate empirical data, and follow best practices for transparency and replicability. Given the static and abstract nature of TPB, modelers have employed diverse mechanisms to operationalize it in agent-based models, using external and internal control variables as intermediary proxies alongside social network structures. Moreover, nearly half of the reviewed studies either incorporated an extended version of TPB in their models or integrated TPB with other behavioral models, showing its flexibility to be integrated with other behavioral models. While 47% of the case study-based research obtained TPB data from self-developed quantitative surveys to inform their agent-based models, only a small subset of these surveys adhered to the principle of compatibility—a key prerequisite for the predictive validity of the TPB. Also, despite growing efforts to promote transparency and replicability through practices such as employing the ODD protocol for model descriptions and sharing code, only 19% of studies shared both their protocol documentation and models, highlighting the need for further progress to fully achieve these objectives. To mitigate ambiguities and enhance consistency in translating TPB constructs into computational representations, we advocate for development of reusable building blocks as a way to establish community standards. Furthermore, stronger collaboration between modelers and social scientists is essential for designing theory-driven surveys that accurately inform agent behavior. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Ecological Modelling is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1016/j.ecolmodel.2025.111231
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      – Code: eng
        Text: English
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        StartPage: N.PAG
    Subjects:
      – SubjectFull: Green behavior
        Type: general
      – SubjectFull: Social scientists
        Type: general
      – SubjectFull: Human behavior models
        Type: general
      – SubjectFull: Planned behavior theory
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      – SubjectFull: Environmental protection
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      – TitleFull: Integrating the theory of planned behavior in agent-based models: A systematic review of applications of pro-environmental behaviors.
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            NameFull: Taraghi, Mahdi
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            NameFull: Yoder, Landon
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            – D: 01
              M: 09
              Text: Sep2025
              Type: published
              Y: 2025
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              Value: 508
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