Search results

Platform, open/user innovation, and ecosystem strategies embrace and enable interactions with external entities. Firms pursuing these approaches conduct business and interact with environments differently than those pursuing traditional closed strategies. This chapter considers these strategies together highlighting similarities and differences between platform, open/user innovation, and ecosystem strategies. We focus on managerial and organizational challenges for organizations pursuing these strategies and identify four institutional logic shifts associated with these strategic transitions: (1) increasing external focus, (2) moving to greater openness, (3) focusing on enabling interactions, and (4) adopting interaction-centric metrics. As mature incumbent organizations adopt these strategies, there may be tensions and multiple conflicting institutional logics. Additionally, we consider four strategic leadership topics and how they relate to platform, open/user innovation, and ecosystem strategies: (1) executive orientation and experience, (2) top management teams, (3) board-management relations, and (4) executive compensation. We discuss theoretical implications, and consider future directions and research opportunities.

This chapter adopts a problem-solving perspective to analyze the competitive dynamics of innovation ecosystems. We argue that features such as uncertainty, complexity, and ambiguity, entail different knowledge requirements which explain the varying abilities of focal firms to coordinate the ecosystem and benefit from the activities of their suppliers, complementors, and users. We develop an analytical framework to interpret various instances of coupling patterns and identify four archetypical types of innovation ecosystems.

Innovation ecosystems consist of independent and yet interdependent enterprises and actors. This constitutes a challenge for innovation leadership to set the direction to pursue UN SDGs. Enhanced insights and understandings of how collaborative innovation leadership can be conducted in practice are revealed in two cases conducted using a participatory action research approach. Hereby theory and practice are linked by the ecosystem participant actions to reach competitiveness of the offshore wind energy ecosystem compared to traditional/other renewable energy sources pursuing UN SDG number 7 of ‘affordable and clean energy’. The two cases are situated in ports in offshore wind energy innovation ecosystems, respectively in the Baltic Sea and in the North Sea. The first case contains complementary ecosystem participants with both leadership and expert positions. The second case contains both complementary and competitive ecosystem participants with leadership positions. The findings note that both cases can use collaborative innovation leadership through the point of origin in the guiding star of the value proposition at ecosystem level to go beyond their own enterprise self-interest. Next, collaborative innovation leadership is based in heterogeneities of both knowledge domains and individual and organisational behaviours for the innovative imagination of future needed initiatives for collaborative design-based sensemaking. A short-term challenge is present from reduced revenue in own enterprise from future needed initiatives. This short-term impact needs to be addressed for enhanced long-term robustness. The findings are summarised in a model for dissemination of collaborative innovation leadership in ecosystems to pursue UN SDGs in practice.

Healthcare innovations for bottom-of-pyramid populations face considerable risks and few economic incentives. Can entrepreneurial innovators provide new solutions for global health? This chapter examines how a technology enterprise built a collaborative network and supportive ecosystem making it possible to steer an innovation for TB patients through discovery, development, and delivery. Ecosystem resources were mobilized and upstream and downstream co-innovation risks were mitigated to commercialize a new diagnostic test. Detailed evidence on this innovation for TB care uses ecosystem analysis to clarify core issues in the context of joint value creation. The case study shows how resources from private and public partners can be leveraged and combined by the focal firm to build joint value and to lower execution, co-innovation, and adoption risks in healthcare ecosystems combating diseases of poverty.

The purpose of this chapter is to explore the phenomenon of innovation in a particular setting in Japan, and more specifically to trace a local initiative toward the creation of an “innovation ecosystem” in a large city and its surrounding region in Western Japan, with the aim of fostering entrepreneurship and economic revitalization.

The analysis in this chapter is based on ethnographic fieldwork, including participant-observation in meetings and events held to promote entrepreneurship and collaboration in the region, as well as interviews with city officials, managers, and entrepreneurs related to the activities of the creation of the “innovation ecosystem.”

In the chapter, I show how the emergence of the ecosystem metaphor for business innovation informs practices and imaginaries in which relations, co-creation, and natural growth become central as models of and for innovation processes in a context of crisis, in ways that generate not only innovation but the ecosystem itself.

The chapter provides historical and social context to the metaphor of the innovation ecosystem that is receiving increasing interest globally, and provides insights into how innovation activities and the enacting of the “innovation ecosystem” take place in practice.

The time is right for a theory on strategic entrepreneurial ecosystems and business model innovation. Both topics have increased substantially during the past couple of years due to their strategic nature. This means they are uniquely placed to provide practical advice but also theoretical development. This chapter discusses the theory in terms of how it bridges strategic planning, innovation management, and entrepreneurship literature. Thereby propelling the field of entrepreneurial ecosystems further by suggesting it has both a strategic and business model perspective. This chapter argues the reasons for a new theory to be developed in order to maintain the relevance and practicality of the entrepreneurial ecosystem literature.

The diffusion and adoption (D&A) of innovation propels today's technological landscape. Crisis situations, real or perceived, motivate communities of people to take action to adopt and diffuse innovation. The D&A of innovation is an inherently human activity; yet, artificially intelligent techniques can assist humans in six different ways, especially when operating in fifth generation ecosystems that are emergent, complex, and adaptive in nature.

Humans can use artificial intelligence (AI) to match solutions to problems, design for diffusion, identify key roles in social networks, reveal unintended consequences, recommend pathways for scaling that include the effects of policy, and identify trends for fast-follower strategies. The stability of the data that artificially intelligent systems rely upon will challenge performance; nevertheless, the research in this area has positioned several promising techniques where classically narrow AI systems can assist humans. As a result, human and machine interaction can accelerate the D&A of technological innovation to respond to crisis situations.

In this paper, we seek to understand how changes in product architecture affect the innovation performance of firms in a complex product ecosystem. The canonical view in the literature is that changes in the technological dependencies between components, which define a product’s architecture, undermine the innovation efforts of incumbent firms because their product development efforts are built around existing architectures. We extend this prevailing view in arguing that component dependencies and changes in them affect firm innovation efforts via two principal mechanisms. First, component dependencies expand or constrain the choice set of firm component innovation efforts. From the perspective of any one component in a complex product (which we label the focal component), an increase in the flow of design information to the focal component from other (non-focal) components simultaneously increases the constraint on focal component firms in their choice of profitable R&D projects while decreasing the constraint on non-focal component firms. Second, asymmetries in component dependencies can confer disproportionate influence on some component firms in setting and dictating the trajectory of progress in the overall system. Increases in such asymmetric influence allow component firms to expand their innovation output. Using historical patenting data in the personal computer ecosystem, we develop fine-grained measures of interdependence between component technologies and changes in them over time. We find strong support for the empirical implications of our theory.

This chapter describes the transition from single-helix roadmap innovation to Open Innovation 2.0 (OI 2.0), based on Quadruple Helix innovation processes. Innovation is intended to make things happen in new and better ways, but actual take-up is always an essential aspect of successful innovation. A change of mindset to be in accord with the behaviour and processes in innovation ecosystems is crucial for an understanding of the interdependencies and complexity management that lead to impact. OI 2.0 is a ‘mash-up’ parallel process in which the public policy maker needs to create a safe framework for this interaction (mash-up) to take place. OI 2.0 is genuinely intersectional, as innovation increasingly happens at the crossroads of technologies and applications – it is not the linear extrapolation of the past. To speed up scalability, all stakeholders need to co-create solutions and find innovations together in real-world settings. Only then do we have a strong driver to create new markets and services and scale up successes rapidly: There is inherent buy-in in this kind of innovation environment. At the same time, by involving end users as co-creators up front and seamlessly, less successful experiments and failing prototypes are rapidly revealed as such: ‘failing fast, scaling fast’ is one of the strongest advantages of OI 2.0. All this leads to the Quadruple Helix innovation model, which supplements the Triple Helix model (research, industry, public sector) with the additional component of the people. In the Quadruple Helix, citizens are not the passive objects of new products or services but active agents contributing to the whole innovation process.

Sport entrepreneurial ecosystems are part of the international business environment and help to determine the competitiveness of a place. While the origins of entrepreneurial ecosystems derive from the economic geography field, increasingly international business theories are being used as a way to engage with the cultural and societal context. This means it is important for scholars to take an interdisciplinary perspective on how to define and conceptualize an ecosystem from an entrepreneurial point of view. This chapter reviews the current body of literature on sport entrepreneurial ecosystems and extends it to a more international business perspective by focusing on knowledge spillovers. This will enable sport managers and practitioners to utilize entrepreneurial ecosystems as a way to foster their internationalization efforts.