IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v208y2024ics0040162524004931.html
   My bibliography  Save this article

Exploring interventions for improving rural digital governance performance: A simulation study of the data-driven institutional pressure transmission mechanism

Author

Listed:
  • Liu, Yuan
  • Xi, Shu
  • Wei, June
  • Li, Xuan

Abstract

Considering the technological and institutional nature, along with the inherent complexity, of the rural digital governance context, a data-driven institutional pressure transmission (D-IPT) mechanism is developed in this study. This mechanism aims to facilitate effective regulation of villagers' behaviours, thereby improving rural digital governance performance. Firstly, we proposed a conceptual model based on complex adaptive systems theory and institutional theory to demonstrate how this mechanism can ensure an improvement of the emergent rural digital governance performance. Subsequently, we translated the conceptual model into a computational representation, thereby constructing a theory-informed simulation model. A behavioural dataset consists of 1,255,206 rural households from 119 villages over a span of 18 months was used to instantiate and validate the simulation model based on a specific scenario. Then, we designed five simulation experiments to investigate interventions aimed at harnessing the D-IPT mechanism more effectively to improve the rural digital governance performance. The results show that interventions targeting interaction efficiency, interaction frequency, and institutional environment configuration significantly affect the role of the D-IPT mechanism in enhancing rural governance performance. Finally, we discussed the theoretical and practical implications of the D-IPT mechanism.

Suggested Citation

  • Liu, Yuan & Xi, Shu & Wei, June & Li, Xuan, 2024. "Exploring interventions for improving rural digital governance performance: A simulation study of the data-driven institutional pressure transmission mechanism," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
    • Handle: RePEc:eee:tefoso:v:208:y:2024:i:c:s0040162524004931
    DOI: 10.1016/j.techfore.2024.123695
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162524004931
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2024.123695?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jannis Beese & M. Kazem Haki & Stephan Aier & Robert Winter, 2019. "Simulation-Based Research in Information Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(4), pages 503-521, August.
    2. Louisa Prause & Sarah Hackfort & Margit Lindgren, 2021. "Digitalization and the third food regime," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 38(3), pages 641-655, September.
    3. Christoph Zott, 2003. "Dynamic capabilities and the emergence of intraindustry differential firm performance: insights from a simulation study," Strategic Management Journal, Wiley Blackwell, vol. 24(2), pages 97-125, February.
    4. Shen, Zhiyang & Wang, Songkai & Boussemart, Jean-Philippe & Hao, Yu, 2022. "Digital transition and green growth in Chinese agriculture," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    5. Roland W. Scholz & Eric J. Bartelsman & Sarah Diefenbach & Lude Franke & Arnim Grunwald & Dirk Helbing & Richard Hill & Lorenz Hilty & Mattias Höjer & Stefan Klauser & Christian Montag & Peter Parycek, 2018. "Unintended Side Effects of the Digital Transition: European Scientists’ Messages from a Proposition-Based Expert Round Table," Sustainability, MDPI, vol. 10(6), pages 1-48, June.
    6. Nelson P. Repenning, 2002. "A Simulation-Based Approach to Understanding the Dynamics of Innovation Implementation," Organization Science, INFORMS, vol. 13(2), pages 109-127, April.
    7. Gabriela Viale Pereira & Maria Alexandra Cunha & Thomas J. Lampoltshammer & Peter Parycek & Maurício Gregianin Testa, 2017. "Increasing collaboration and participation in smart city governance: a cross-case analysis of smart city initiatives," Information Technology for Development, Taylor & Francis Journals, vol. 23(3), pages 526-553, July.
    8. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, December.
    9. Richard Vidgen & Xiaofeng Wang, 2009. "Coevolving Systems and the Organization of Agile Software Development," Information Systems Research, INFORMS, vol. 20(3), pages 355-376, September.
    10. J. Doyne Farmer & Duncan Foley, 2009. "The economy needs agent-based modelling," Nature, Nature, vol. 460(7256), pages 685-686, August.
    11. Robert Drazin & Lloyd Sandelands, 1992. "Autogenesis: A Perspective on the Process of Organizing," Organization Science, INFORMS, vol. 3(2), pages 230-249, May.
    12. Sariyer, Gorkem & Mangla, Sachin Kumar & Kazancoglu, Yigit & Jain, Vranda & Ataman, Mustafa Gokalp, 2023. "Data-driven decision making for modelling covid-19 and its implications: A cross-country study," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    13. Carter, William & Pezeshkan, Amir, 2023. "The complexity of entrepreneurial ecosystem evolution and new venture policy: The case of the U.S. commercial space ecosystem," Technological Forecasting and Social Change, Elsevier, vol. 192(C).
    14. Russell, Martha G. & Smorodinskaya, Nataliya V., 2018. "Leveraging complexity for ecosystemic innovation," Technological Forecasting and Social Change, Elsevier, vol. 136(C), pages 114-131.
    Full references (including those not matched with items on IDEAS)

    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. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2017. "Validation of Agent-Based Models in Economics and Finance," LEM Papers Series 2017/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    2. John Qi Dong, 2021. "Technological choices under uncertainty: Does organizational aspiration matter?," Strategic Management Journal, Wiley Blackwell, vol. 42(5), pages 898-916, May.
    3. Jason M. Barr, 2019. "Domenico Delli Gatti, Giorgio Fagiolo, Mauro Gallegati, Matteo Richiardi and Alberto Russo (eds): Agent-Based Models in Economics: A Toolkit," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 45(3), pages 477-480, June.
    4. Bill McKelvey & Benyamin B. Lichtenstein & Pierpaolo Andriani, 2012. "When organisations and ecosystems interact: toward a law of requisite fractality in firms," International Journal of Complexity in Leadership and Management, Inderscience Enterprises Ltd, vol. 2(1/2), pages 104-136.
    5. Sudharshan, Devanathan & Furrer, Olivier & Arakoni, Ramesh A., 2013. "Robust Imitation Strategies," FSES Working Papers 446, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    6. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
    7. Delli Gatti,Domenico & Fagiolo,Giorgio & Gallegati,Mauro & Richiardi,Matteo & Russo,Alberto (ed.), 2018. "Agent-Based Models in Economics," Cambridge Books, Cambridge University Press, number 9781108400046, January.
    8. Tian, Qing & Holland, John H. & Brown, Daniel G., 2016. "Social and economic impacts of subsidy policies on rural development in the Poyang Lake Region, China: Insights from an agent-based model," Agricultural Systems, Elsevier, vol. 148(C), pages 12-27.
    9. Santiago J. Gangotena, 2017. "Dynamic coordinating non-equilibrium," The Review of Austrian Economics, Springer;Society for the Development of Austrian Economics, vol. 30(1), pages 51-82, March.
    10. Midha, Joshua, 2024. "Assessing Emerging Markets through Transactional Dynamics: A New Multi-Dimensional Valuation Framework," SocArXiv d8jkt, Center for Open Science.
    11. Auke Hoekstra & Maarten Steinbuch & Geert Verbong, 2017. "Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation," Complexity, Hindawi, vol. 2017, pages 1-23, December.
    12. Leonardo Augusto Amaral Terra & João Luiz Passador, 2018. "Strategies for the Study of Complex Socio-Economic Systems: an Approach Using Agent-Based Simulation," Systemic Practice and Action Research, Springer, vol. 31(3), pages 311-325, June.
    13. Florian Chávez-Juárez, 2017. "On the Role of Agent-based Modeling in the Theory of Development Economics," Review of Development Economics, Wiley Blackwell, vol. 21(3), pages 713-730, August.
    14. Fadiran, Gideon & Fadiran, David & Ibn-Mohammed, Taofeeq, 2017. "Macroeconomic Policy effects on development transition – Views from Agent based model," MPRA Paper 103197, University Library of Munich, Germany, revised Dec 2018.
    15. Midha, Joshua, 2024. "Assessing Emerging Markets through Transactional Dynamics: A New Multi-Dimensional Valuation Framework," SocArXiv d8jkt_v1, Center for Open Science.
    16. Georg Holtz & Christian Schnülle & Malcolm Yadack & Jonas Friege & Thorben Jensen & Pablo Thier & Peter Viebahn & Émile J. L. Chappin, 2020. "Using Agent-Based Models to Generate Transformation Knowledge for the German Energiewende—Potentials and Challenges Derived from Four Case Studies," Energies, MDPI, vol. 13(22), pages 1-26, November.
    17. Justin Tan & Hongjuan Zhang & Liang Wang, 2015. "Network Closure or Structural Hole? The Conditioning Effects of Network–Level Social Capital on Innovation Performance," Entrepreneurship Theory and Practice, , vol. 39(5), pages 1189-1212, September.
    18. Kenneth Hemmerechts & Nohemi Jocabeth Echeverria Vicente & Dimokritos Kavadias, 2017. "The Order of Human Interdependencies: Simulating Elias’ One-level Multi-person Models," Sociological Research Online, , vol. 22(4), pages 105-131, December.
    19. F. LeRon Shults & Wesley J. Wildman, 2020. "Human Simulation and Sustainability: Ontological, Epistemological, and Ethical Reflections," Sustainability, MDPI, vol. 12(23), pages 1-16, December.
    20. Bill Gibson, 2012. "Trade, Employment and the Informal Sector: An Agent-based Analysis," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 6(2), pages 277-310, May.

    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:eee:tefoso:v:208:y:2024:i:c:s0040162524004931. 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: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    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.