Purpose: All firms' business models are based on their interdependencies with other parties in their ecosystems. The Internet of Things (IoT) is beginning to fundamentally disrupt the agri-food industry, forcing the ecosystem to change. When an ecosystem is transforming, the interdependencies among its actors can create friction. Technology providers and core actors should consider these interdependencies as they update their strategies for value creation and capture. The purpose of the present research is to consider what it might take for agri-food firms to capitalize on these interdependencies by moving from traditional business models to business models based on collaboration and open innovation.Design/methodology/approach: The present paper draws on data from four online focus groups that we created to discuss how to co-create the business models agri-food firms need in a constantly changing environment. The paper presents an application of phenomenon-driven research (PDR), an engaged methodology. The study method enables novel pathways to develop and implement innovative solutions. This study draws on the interaction of theory and practice and involves multiple stakeholders with varying roles in the agri-food ecosystem.Findings: The authors found that any open innovation setup in agri-food needs to constantly reconfigure itself to balance the needs of farmers and the needs of the market. This interplay can only support the IoT-enabled ecosystem if continuous interaction and negotiation occur among various stakeholders of the food system. When the farmers' needs and the market's needs are aligned, the space for developing a collaborative and open business model is prepared.Originality/value: The insights gained from this study inspire action and commitment to common goals when developing collaboration-based business models (CBMs). The paper offers insights for players in the agri-food industry who are considering CBMs in the course of digital transformation.

Scientific knowledge dissemination is necessary to collaboratively develop solutions to today’s challenges among scientific, public, and commercial actors. Building on this, recent concepts (e.g., Third Mission) discuss the role and value of different dissemination mechanisms for increasing societal impact. However, the value individual scientists receive in exchange for disseminating knowledge differs across these mechanisms, which, consequently, affects their selection. So far, value capture mechanisms have mainly been described as appropriating monetary rewards in exchange for scientists’ knowledge (e.g., patenting). However, most knowledge dissemination activities in science do not directly result in capturing monetary value (e.g., social engagement). By taking a value capture perspective, this article conceptualizes and explores how individual scientists capture value from disseminating their knowledge. Results from our qualitative study indicate that scientists’ value capture consists of a measureable objective part (e.g., career promotion) and a still unconsidered subjective part (e.g., social recognition), which is perceived as valuable due to scientists’ needs. By advancing our understanding of value capture in science, scientists’ selection of dissemination mechanisms can be incentivized to increase both the value captured by themselves and society. Hence, policy makers and university managers can contribute to overcoming institutional and ecosystem barriers and foster scientists’ engagement with society.

This paper focuses on how companies deploy structural properties of adaptive capacity (multiplexity, redundancy and loose coupling) to cope with the phenomenon of internal challenges of Open Innovation (OI) implementation, i.e. organisational and cultural changes. We developed a single case study, which offered significant findings. First, the multiplexity of relationships in OI settings helps to face the challenges of organisational and cultural changes by triggering trust formation and interaction. Second, redundancy has twofold elements: institutional logics redundancy triggers cultural change challenges which can be overcome through management practices and communications; task redundancy facilitates knowledge sharing and collaboration, thus helping to deal with organisational change challenges. Finally, loose coupling in OI settings facilitates social interconnectedness among members through management practices, helping to face organisational and cultural change challenges. We provide managerial and theoretical implication to deal with the challenges of OI in relation to both organisational and cultural changes.