Innovation ecosystem is an increasingly popular but all too often ambiguously utilized concept across academia, policy and business. In their recent well-argued critique of the concept, Oh et al. ( 2016) called it a "flawed analogy" that is potentially dangerous for its lack of rigor. This letter, we reflect on this critique and examine pathways to resolve some of the issues pointed out. We suggest that, at its best, the ecosystem analogy combines salient features from natural ecology to inform the design of system-level innovation management activities. This requires great deal of conceptual and empirical effort and rigor, and we outline a number of ideas for future research in this regard.

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For better or worse, digital technologies are reshaping everything, from customer behaviors and expectations to organizational and manufacturing systems, business models, markets, and ultimately society. To understand this overarching transformation, this paper extends the previous literature which has focused mostly on the organizational level by developing a multi-level research agenda for digital transformation (DT). In this regard, we propose an extended definition of DT as "a socioeconomic change across individuals, organizations, ecosystems, and societies that are shaped by the adoption and utilization of digital technologies." We suggest four lenses to interpret the DT phenomenon: individuals (utilizing and adopting digital technologies), organizations (strategizing and coordinating both internal and external transformation), ecosystems (harnessing digital technologies in governance and co-producing value propositions), and geopolitical frameworks (regulating the environments in which individuals and organizations are embedded). Based on these lenses, we build a multi-level research agenda at the intersection between the bright and dark sides of DT and introduce the PIAI framework, which captures a process of perception, interpretation, and action that ultimately leads to possible impact. The PIAI framework identifies a critical research agenda consisting of a non-exhaustive list of topics that can assist researchers to deepen their understanding of the DT phenomenon and provide guidance to managers and policymakers when making strategic decisions that seek to shape and guide the DT.

R&D Networks comprise different actors with various goals and motivations. Thus, such networks are filled with tensions that emerge from simultaneously existing, competing or contradictory organizing elements and demands. In this study, we examine the knowledge search and integration behaviour of firms participating in R&D networks in the Dutch aerospace sector. We find evidence of a multitude of tensions that have implications for knowledge processes of firms and within R&D networks. These tensions are grouped into dialectical and paradoxical tensions. In particular, paradoxical tensions require simultaneous attention to the different organizing elements, while dialectical tensions create either/or situations that need to be carefully managed. We find two types of dialectical tensions: openness of core knowledge exposure and inclusiveness of knowledge sharing behaviour; and three types of paradoxical tensions related to innovation goal alignment, coopetition, and actor interdependence. Overall, our results provide unique insights to how participants of R&D networks perceive tensions involved in knowledge search and integration, how the network role of the actors affects these perceptions, and what types of tension-resolving mechanisms are adopted in different types of networks.

Innovation ecosystems are built around new technologies, ideas, and innovations and their supporting actors and structures. However, the emergence of ecosystems is constrained by a host of institutional, system-level barriers in the existing organizational field that inhibit the legitimacy, resourcing, and growth of new initiatives. Through an empirical study in the Finnish energy sector, we find a strong and interdependent set of regulative, normative, and cultural-cognitive barriers that restrict the emergence of innovation ecosystems with new technologies. In particular, we identify a set of barriers and related field-sustaining mechanisms. The findings offer important implications for the theory and practice of innovation ecosystem emergence and related system-level barriers.