Inputs zur gesellschaftlichen Entscheidungsfindung

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.

Calls for supporting sustainability through more and better research rest on an incomplete understanding of scientific evidence use. We argue that a variety of barriers to a transformative impact of evidence arises from diverse actor motivations within different stages of evidence use. We abductively specify this variety in policy and practice arenas for three actor motivations (truth-seeking, sense-making, and utility-maximizing) and five stages (evidence production, uptake, influence on decisions, effects on sustainability outcomes, and feedback from outcome evaluations). Our interdisciplinary synthesis focuses on the sustainability challenge of reducing environmental and human health risks of agricultural pesticides. It identifies barriers resulting from (1) truth-seekers’ desire to reduce uncertainty that is complicated by evidence gaps, (2) sense-makers’ evidence needs that differ from the type of evidence available, and (3) utility-maximizers’ interests that guide strategic evidence use. We outline context-specific research–policy–practice measures to increase evidence use for sustainable transformation in pesticides and beyond.

Pre-adoption phases of innovation are understudied in the innovation literature. This article addresses pre-adoption phases of innovation by running a prospective analysis. We assess the readiness of municipalities for the adoption of a digital tool that brings about process innovation concerning stakeholder management. Through an online survey, we elicit the public managers’ attitudes and their adoption expectation towards the tool. By drawing on insights from Diffusion of Innovation Theory and Theory of Planned Behaviour, we investigate which attributes of innovation along with managerial, organisational and environmental factors, contribute to a favourable attitude and an increased likelihood of innovation adoption. Our analysis reveals that while the perceived attributes of innovation such as its relative advantage and compatibility are major determinants of attitude formation and adoption expectation, pro-digitalisation beliefs, innovation-oriented organisational culture and environmental context factors such as high population and rates of new residential growth are critical in translation of positive attitudes to increased likelihood of adoption. Hence, in addition to perceived attributes of innovation and managerial characteristics, our findings also highlight the importance of organisational and environmental factors to the adoption expectation, and thus provide a more nuanced understanding of pre-adoption phases of innovation.