Socio-technical challenges towards data-driven and integrated urban water management: A socio-technical network approach

Data-driven and integrated urban water management have been proposed to reduce surface water pollution in light of climate change and urbanization impacts. Besides technological innovation, data-driven and integrated management require information exchange among many actors, e.g., operators, engineers, or authorities. With the aim of achieving a more profound understanding of socio-technical infrastructures, such as urban water systems, I draw on the approach of socio-technical networks to study actors and infrastructure elements as well as multiple relations in-between. In this article, I investigate whether underlying socio-technical dependencies influence social interactions such as information exchange. More specifically related to data-driven and integrated management, I analyze potential challenges, such as organizational fragmentation, data access, and diverging perceptions. Based on empirical data from three case studies in Switzerland, I provide inferential results obtained from fitting exponential random graph models. Findings showed that actors' relatedness to infrastructure elements affects their information exchange. Among the cases, the presence of the three challenges varied and is potentially contingent upon system size, organizational form, or progress in terms of data-driven and integrated management. Thus, incorporating a socio-technical perspective on social actors and infrastructure elements could help to improve policy design and implementation aiming to achieve more sustainable cities.

Automated summary

Data-driven and integrated management is proposed to reduce surface water pollution, which requires information exchange and technological innovation. By studying socio-technical networks, this article investigates the influence of socio-technical dependencies on information exchange. Analyzing empirical data from three Swiss case studies, potential challenges such as organizational fragmentation, data access, and diverging perceptions are identified, and the findings show that actors' relatedness to infrastructure elements affects their information exchange.