Dr Richard Tee

Reflecting the emergence of new organizational forms and hybrid organizations, this edited collection explores the processes of exchange, collaboration and technological management that have changed organizational structures. By investigating the impact that inter-organizational collaboration can have on the production and implementation of ideas within new firms, this study contributes to the growing field of innovation and responds to the need for a greater understanding of renewed processes. The authors argue that collaborations need to go beyond existing practices to create emerging paths such as bricolage, experimentation, effectuation and learning. Drawing together a diverse body of literature on the internal dynamics that drive organizational change, Learning and Innovation in Hybrid Organizations presents multiple perspectives on combining organizational flexibility with learning and innovation, and provides implications for future practice. 

Open governmental data available via platforms like data.gov have earned a place in the innovation agenda of governments and local authorities alike. To successfully make use of these sources, governments around the world experiment with competitive virtual contests or challenges to ignite the creativity of developers and hackers and motivate them to turn this data into novel digital applications. However, such efforts don’t seem to be sustainable. Applications developed in such contests regularly fail to ignite the continuous use by the end users. We argue that governments need to adopt an ecosystem perspective facilitating cocreation within the diverse open data innovation ecosystems of developers, producers, and users in order to foster the generativity needed for continuous value creation. However, various tensions among actors appear along the way. Taking a paradoxical view towards ecosystem tensions, we propose a socio-technical infrastructure that supports ecosystem generativity by addressing latent tensions in the “breeding zone” of an open data innovation. The infrastructure supports generative responses to these tensions in three ways: creating virtual trading zones, supporting the duality of stable and dynamic roles, and providing technological affordances for fluidity. This framework could set the stage for future research, encouraging system designers and policymakers to foster cocreation in open data innovation ecosystems.

What factors and processes drive value appropriation and value creation in interdependent industry ecosystems? This paper explores this issue through a case study comparing the deployment of the i-mode mobile Internet service in two countries, seeking the reasons behind its contrasting fortunes: spectacular success in Japan vs failure in Europe. The comparison between network operators NTT Docomo in Japan and KPN in the Netherlands suggests that differences in the underlying industry architectures explain why similar platform strategies led to such different outcomes. The paper contributes to the literature on industry architecture by unpacking the interaction between evolutionary processes, industry architecture, and business strategies. It also contributes to the platforms literature, by positing that firms' ability to successfully pursue platform strategies depends on industry architecture.

The construct of generativity is increasingly adopted to describe system innovation in digital contexts. We systematically review this construct, investigating its antecedents, processes and outcomes in management studies. We draw on different theoretical perspectives to develop an integrative conceptual framework. We argue that generativity is a sociotechnical system where social and technical elements interact to facilitate combinatorial innovation, and where generative fit and governance play a central role. Based on our bibliometric and qualitative analysis, we identify seven components of generativity: generative architecture, generative governance, generative community, generative fit, combinatorial innovation, generative outcomes and generative feedback. We integrate these components into a conceptual framework that describes the relationships among the components and how they collectively result in ecosystem innovation. We also elucidate future research directions for management scholars.

Collaboration in large-scale projects introduces challenges involving both coordination (the ability to collaborate) as well as cooperation (the willingness to do so). Existing research has shown how modular designs can improve coordination by locating interdependencies within rather than between different modules. Based on an in-depth case study of collaboration in a large-scale infrastructure project, our study highlights an effect of modularity on collaboration that previously has been overlooked. Specifically, we show that while modular designs may help overcome coordination challenges by reducing interdependencies between modules, they can in turn hamper collaboration by emphasizing specialization within modules. Therefore, though existing work typically perceives modularity and integration as opposites, we clarify how they can also act as complements. In particular, we show how firms need to complement modular designs with integrating practices that stimulate cooperation. Overall, we contribute to the literature on collaboration and modularity by explaining when and how organizations can combine modularity and integration.

Open governmental data available via platforms like data.gov have earned a place in the innovation agenda of governments and local authorities alike. To successfully make use of these sources, governments around the world experiment with competitive virtual contests or challenges to ignite the creativity of developers and hackers and motivate them to turn this data into novel digital applications. However, such efforts don’t seem to be sustainable. Applications developed in such contests regularly fail to ignite the continuous use by the end users. We argue that governments need to adopt an ecosystem perspective facilitating cocreation within the diverse open data innovation ecosystems of developers, producers, and users in order to foster the generativity needed for continuous value creation. However, various tensions among actors appear along the way. Taking a paradoxical view towards ecosystem tensions, we propose a socio-technical infrastructure that supports ecosystem generativity by addressing latent tensions in the “breeding zone” of an open data innovation. The infrastructure supports generative responses to these tensions in three ways: creating virtual trading zones, supporting the duality of stable and dynamic roles, and providing technological affordances for fluidity. This framework could set the stage for future research, encouraging system designers and policymakers to foster cocreation in open data innovation ecosystems.

Existing work has shown how, in platform ecosystems, firms can capture above-average rents by controlling hard-to-replace segments. However, initial conditions can have a lasting effect on a platform owner's ability to capture value as the ecosystem in which it operates evolves. We develop a theoretical framework that first considers the role of bargaining power and industry life cycle stage, showing how these shape initial governance arrangements and the platform owner's subsequent ability to capture value based on the rigidity of these arrangements. We then develop propositions, focusing on contingencies that moderate this degree of governance rigidity in platform ecosystems. Our framework helps understand the combined effects of initial conditions and governance rigidity as key drivers of a platform owner's ability to capture rents. Once we consider these dynamics , controlling a hard-to-replace segment may neither be sufficient nor necessary to obtain a large share of the value created by an ecosystem.