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Environmental Impact Assessment of the Heterogeneity in Consumers’ Usage Behavior: An Agent‐Based Modeling Approach

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  • Ardeshir Raihanian Mashhadi
  • Sara Behdad

Abstract

The aim of this study is to develop a framework for understanding the heterogeneity and uncertainties present in the usage phase of the product life cycle through utilizing the capabilities of an agent‐based modeling (ABM) technique. An ABM framework is presented to model consumers’ daily product usage decisions and to assess the corresponding electricity consumption patterns. The theory of planned behavior (TPB), with the addition of the habit construct, is used to model agents’ decision‐making criteria. A case study is presented on the power management behavior of personal computer users and the possible benefits of using smart metering and feedback systems. The results of the simulation demonstrate that the utilization of smart metering and feedback systems can promote the energy conservation behaviors and reduce the total PC electricity consumption of households by 20%.

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  • Ardeshir Raihanian Mashhadi & Sara Behdad, 2018. "Environmental Impact Assessment of the Heterogeneity in Consumers’ Usage Behavior: An Agent‐Based Modeling Approach," Journal of Industrial Ecology, Yale University, vol. 22(4), pages 706-719, August.
    • Handle: RePEc:bla:inecol:v:22:y:2018:i:4:p:706-719
    DOI: 10.1111/jiec.12622
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    Cited by:

    1. Walzberg, Julien & Dandres, Thomas & Merveille, Nicolas & Cheriet, Mohamed & Samson, Réjean, 2019. "Assessing behavioural change with agent-based life cycle assessment: Application to smart homes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 365-376.
    2. Bourceret, Amélie & Amblard, Laurence & Mathias, Jean-Denis, 2022. "Adapting the governance of social–ecological systems to behavioural dynamics: An agent-based model for water quality management using the theory of planned behaviour," Ecological Economics, Elsevier, vol. 194(C).
    3. Junming Zhu, 2020. "Suggested use? On evidence‐based decision‐making in industrial ecology and beyond," Journal of Industrial Ecology, Yale University, vol. 24(5), pages 943-950, October.
    4. Bourceret, Amélie & Amblard, Laurence & Mathias, Jean-Denis, 2023. "How do farmers’ environmental preferences influence the efficiency of information instruments for water quality management? Evidence from a social-ecological agent-based model," Ecological Modelling, Elsevier, vol. 478(C).
    5. Piya Kerdlap & Aloisius Rabata Purnama & Jonathan Sze Choong Low & Daren Zong Loong Tan & Claire Y. Barlow & Seeram Ramakrishna, 2022. "Comparing the environmental performance of distributed versus centralized plastic recycling systems: Applying hybrid simulation modeling to life cycle assessment," Journal of Industrial Ecology, Yale University, vol. 26(1), pages 252-271, February.
    6. Hongyun Si & Jian-gang Shi & Daizhong Tang & Shiping Wen & Wei Miao & Kaifeng Duan, 2019. "Application of the Theory of Planned Behavior in Environmental Science: A Comprehensive Bibliometric Analysis," IJERPH, MDPI, vol. 16(15), pages 1-26, August.
    7. Walzberg, Julien & Dandres, Thomas & Merveille, Nicolas & Cheriet, Mohamed & Samson, Réjean, 2020. "Should we fear the rebound effect in smart homes?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 125(C).

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