Agent-based Modeling in Digital Governance Research: A Review and Future Research Directions

Digital governanceDigital governance involves the application of information and communication technology (ICT) for achieving efficiency and effectiveness in government functions for all stakeholders. In addition to the expenditure on ICT, government bodies face key challenges arising from complexity in digital governance due to uncertainty, nonlinearity, and heterogeneity in processes and stakeholders, which need to be further understood and resolved. To that end, agent-based modelingAgent based modeling (ABM) (ABM) offers a powerful technique to represent and research complexities, uncertainties, nonlinearity, and heterogeneity in a digital governance ecosystem. In this chapter, we provide a systematic review of the literature over the last two decades, which has applied ABM for analyzing digital governance phenomena. Based on the review, with 78 relevant studies, we contribute by summarizing the current state of research in this area, identifying the literature gaps, and outlining directions for future researchFuture research. Specifically, our study highlights issues related to ABM design, implementation, validation, and adoption that remain unexplored. Salient future research directions include theory development with greater involvement of stakeholders, empirical frameworks’ development for ABM implementation with focus on scalability, interlinking of ABMAgent based modeling (ABM) with existing government knowledge bases, and applying ABM to less studied domains of digital governanceDigital governance.