Cultivation of Impact Networks via Trusted Governance and Distributed Leadership

Abstract: Background: Complex and chaotic problems that characterize today’s biggest challenges require collaboration across different stakeholders. One collaborative structure is so called impact networks. In these networks, tasks are coordinated among different actors without central control. As there are typically no official leaders, a culture of trust is crucial. Impact networks could be empowered by the combination of distributed leadership and automated and trusted governance, e.g., via a decentralized autonomous organization (DAO). In fact, trust and distributed leadership have been identified as elements that unlock other key enablers for successful impact networks, such as collective intelligence and resource mobilization. Objective: The purpose of this thesis is to investigate whether an automated and trusted governance mechanism together with distributed leadership improve a network’s collective intelligence and capacity of mobilization to increase its social, environmental , and economic impact. Methodology: The study follows a quantitative approach fÅNor data collection and data analysis. Structural Equation Modeling (SEM) has been selected as the main tool for the study. Based on an extensive literature review, five latent variables were identified and hypotheses were formulated to study the relationship between the variables. Data was gathered via a questionnaire that 161 people answered. The sample consisted mainly of professionals within the engineering sector with different backgrounds and positions, the majority with several years of experience. The gathered data was processed using Python and according to the SEM methodology to confirm the hypotheses. Results: The results of the study suggest that distributed leadership has a positive effect on a network’s collective intelligence and mobilization. Trusted, transparent and automated governance also exhibit a positive effect on collective intelligence, but the relationship with mobilization is insignificant. Finally, the results imply that both collective intelligence and mobilization have a positive effect on a network’s social, environmental, and economic impact. Conclusions: The results in this thesis identifies distributed leadership as the single most important variables out of the five as it unlocks the potential of collective intelligence to ultimately have an impact environmentally, socially, and/or economically. Recommendation for future research: Future studies may dive deeper into the study of trust and governance, since the model in this thesis partly contradicts the underlying theory. The questionnaire can possibly be improved with newly formulated items and be targeted to a specific group of professionals within the field. It could also be interesting to perform an exploratory factor analysis to assess if the indicators accurately measure the latent constructs. Keywords: Trusted governance, automated governance, distributed leadership, collective intelligence, mobilization, impact network.