IDEAS home Printed from https://ideas.repec.org/a/jas/jasssj/2014-49-5.html
   My bibliography  Save this article

Intervention Strategies and the Diffusion of Collective Behavior

Author

Listed:

Abstract

This paper examines the intervention strategies for the diffusion of collective behavior, such as promoting innovation adoption and repressing a strike. An intervention strategy refers to controlling the behaviors of a small number of individuals in terms of their social or personal attributes, including connectivity (i.e., the number of social ties one holds), motivation (i.e., an individual’s intrinsic cost–benefit judgment on behavior change), and sensitivity (i.e., the degree to which one follows others). Extensive agent-based simulations demonstrate that the optimal strategy fundamentally depends on the goal and time of intervention. Moreover, the nature of the social network (determined by homophily type and level) moderates the effectiveness of a strategy. These results have substantial implications for the design and evaluation of intervention programs.

Suggested Citation

  • Hai-hua Hu & Jun Lin & Wen-tian Cui, 2015. "Intervention Strategies and the Diffusion of Collective Behavior," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(3), pages 1-16.
    • Handle: RePEc:jas:jasssj:2014-49-5
    as

    Download full text from publisher

    File URL: https://www.jasss.org/18/3/16/16.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kent D. Miller & Frances Fabian & Shu‐Jou Lin, 2009. "Strategies for online communities," Strategic Management Journal, Wiley Blackwell, vol. 30(3), pages 305-322, March.
    2. Hazhir Rahmandad & John Sterman, 2008. "Heterogeneity and Network Structure in the Dynamics of Diffusion: Comparing Agent-Based and Differential Equation Models," Management Science, INFORMS, vol. 54(5), pages 998-1014, May.
    3. David A. Siegel, 2009. "Social Networks and Collective Action," American Journal of Political Science, John Wiley & Sons, vol. 53(1), pages 122-138, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hu, Hai-hua & Lin, Jun & Qian, Yanjun & Sun, Jian, 2018. "Strategies for new product diffusion: Whom and how to target?," Journal of Business Research, Elsevier, vol. 83(C), pages 111-119.
    2. Ahmadreza Asgharpourmasouleh & Atiye Sadeghi & Ali Yousofi, 2017. "A Grounded Agent-Based Model of Common Good Production in a Residential Complex: Applying Artificial Experiments," SAGE Open, , vol. 7(4), pages 21582440177, October.
    3. Wolfram Elsner, 2019. "Policy and state in complexity economics," Chapters, in: Nikolaos Karagiannis & John E. King (ed.), A Modern Guide to State Intervention, chapter 1, pages 13-48, Edward Elgar Publishing.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stam, Wouter, 2009. "When does community participation enhance the performance of open source software companies?," Research Policy, Elsevier, vol. 38(8), pages 1288-1299, October.
    2. Lewe, J.-H. & Hivin, L.F. & Mavris, D.N., 2014. "A multi-paradigm approach to system dynamics modeling of intercity transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 188-202.
    3. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    4. Ellinas, Christos & Allan, Neil & Johansson, Anders, 2016. "Project systemic risk: Application examples of a network model," International Journal of Production Economics, Elsevier, vol. 182(C), pages 50-62.
    5. Cowan, Kelly R. & Daim, Tugrul U., 2011. "Review of technology acquisition and adoption research in the energy sector," Technology in Society, Elsevier, vol. 33(3), pages 183-199.
    6. Lu, Xuefei & Borgonovo, Emanuele, 2023. "Global sensitivity analysis in epidemiological modeling," European Journal of Operational Research, Elsevier, vol. 304(1), pages 9-24.
    7. Rana Basu & Prabha Bhola, 2015. "Exploring Quality Management Practices and Its Pattern Analysis in Indian Service SMEs," Journal of Enterprising Culture (JEC), World Scientific Publishing Co. Pte. Ltd., vol. 23(02), pages 199-235, June.
    8. Ahmadreza Asgharpourmasouleh & Atiye Sadeghi & Ali Yousofi, 2017. "A Grounded Agent-Based Model of Common Good Production in a Residential Complex: Applying Artificial Experiments," SAGE Open, , vol. 7(4), pages 21582440177, October.
    9. Nguyen, Le Khanh Ngan & Howick, Susan & Megiddo, Itamar, 2024. "A framework for conceptualising hybrid system dynamics and agent-based simulation models," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1153-1166.
    10. repec:jtr:journl:v:6:y:2013:i:1:p:121-132 is not listed on IDEAS
    11. Naim Kapucu & Sean Beaudet, 2020. "Network Governance for Collective Action in Implementing United Nations Sustainable Development Goals," Administrative Sciences, MDPI, vol. 10(4), pages 1-21, December.
    12. Santos, Mário & Bastos, Rita & Cabral, João Alexandre, 2013. "Converting conventional ecological datasets in dynamic and dynamic spatially explicit simulations: Current advances and future applications of the Stochastic Dynamic Methodology (StDM)," Ecological Modelling, Elsevier, vol. 258(C), pages 91-100.
    13. Thomas Bossuroy, 2011. "Ethnic Solidarity and the Individual Determinants of Ethnic Identification," SALDRU Working Papers 69, Southern Africa Labour and Development Research Unit, University of Cape Town.
    14. Wouter Vermeer & Otto Koppius & Peter Vervest, 2018. "The Radiation-Transmission-Reception (RTR) model of propagation: Implications for the effectiveness of network interventions," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-21, December.
    15. Lei Xu & Ronggui Ding & Lei Wang, 2022. "How to facilitate knowledge diffusion in collaborative innovation projects by adjusting network density and project roles," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1353-1379, March.
    16. Jan Kwakkel & Willem Auping, 2021. "Reaction: A commentary on Lustick and Tetlock (2021)," Futures & Foresight Science, John Wiley & Sons, vol. 3(2), June.
    17. Tesfatsion, Leigh, 2017. "Modeling Economic Systems as Locally-Constructive Sequential Games," ISU General Staff Papers 201704300700001022, Iowa State University, Department of Economics.
    18. Abedi, Vahideh Sadat, 2019. "Compartmental diffusion modeling: Describing customer heterogeneity & communication network to support decisions for new product introductions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    19. Lixin Zhou & Jie Lin & Yanfeng Li & Zhenyu Zhang, 2020. "Innovation Diffusion of Mobile Applications in Social Networks: A Multi-Agent System," Sustainability, MDPI, vol. 12(7), pages 1-17, April.
    20. Amini, Mehdi & Wakolbinger, Tina & Racer, Michael & Nejad, Mohammad G., 2012. "Alternative supply chain production–sales policies for new product diffusion: An agent-based modeling and simulation approach," European Journal of Operational Research, Elsevier, vol. 216(2), pages 301-311.
    21. Teglio, Andrea, 2020. "On the typicality of the representative agent," MPRA Paper 105407, University Library of Munich, Germany.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jas:jasssj:2014-49-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Francesco Renzini (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.