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

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  • 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
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