Digital neighborhood frameworks in community-centric urban infrastructure planning

The rise of the digital neighborhood paradigm presents complex challenges for urban planners and policymakersentering data-informed infrastructure ecosystems and deciding resource allocation priorities – a crucial topic in urbandevelopment research. This study investigates the structure and behavioral dynamics of digitally-mediated communitiesand aims to contribute to the literature on the “smart urbanization” problem. This paper addresses this knowledge gapwith empirical evidence on how community-centric digital frameworks are used for planning infrastructure investmentsby different types of municipal entities at different stages of neighborhood development, in medium-sized urban areas. Itexplains how digital engagement platforms and institutional structures, rules, decision-making protocols, and participatorymechanisms interconnect to influence infrastructure planning outcomes using the conceptual lens and method ofcorrelational urban analytics, the digital infrastructure mapping concept, and a regression-based diagnostic method. Ourfindings show that due to the particular governance dynamics of digitally-networked communities, local actors do notwelcome the uncertainties related to automated planning algorithms, and the benefit of predictive insights from digitalinfrastructure modeling is lower than the social cost of abandoning traditional consultative planning. They reveal thatthe “stability bias” (maintaining a familiar governance routine) plays a role in resistance to digital planning models anddelayed policy adaptation. In addition, it is believed that these behavioral tendencies may have long-term implications todata-driven decision-making adoption trajectories