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In a dynamic environment where underlying competition is “for the market,” this chapter examines what happens when entrants and incumbents can instead negotiate for the market. For instance, this might arise when an entrant innovator can choose to license to or be acquired by an incumbent firm (i.e., engage in cooperative commercialization). It is demonstrated that, depending upon the level of firms’ potential dynamic capabilities, there may or may not be gains to trade between incumbents and entrants in a cumulative innovation environment; that is, entrants may not be adequately compensated for losses in future innovative potential. This stands in contrast to static analyses that overwhelmingly identify positive gains to trade from such cooperation.

Commercialization of research projects at the university, in particular, its efficiency and performance, have attracted little attention in the empirical literature to date. This despite the fact that commercialization of university knowledge is increasingly seen as a third task of universities and understanding of what enhances and what blocks the processes involved, is virtually lacking, particularly on the project level. The purpose of this chapter is therefore to identify factors that influence the performance of university-driven knowledge projects, including efficiency, in the context of commercialization of knowledge at universities. In this context, the study employs Data Envelop Analysis combined with Rough-Set Analysis on a sample of 42 projects in the Netherlands. The major factors influencing overall performance in commercialization turn out to be years of collaboration with large firms and efficiency in use of resources in the projects, but the affinity of the project managers at university with the market also plays a role. The best overall results in commercialization (introduction to market in a relatively short time) are gained with a longer period of collaboration with large firms (5–10 years) and a medium level of efficiency. There are also some contradictory trends. The chapter concludes with implications of the results, as well as some future research paths.

As a company that has continuously achieved business innovation, Apple in the United States has successfully applied strategic knowledge creation to produce a series of products that integrate various digital devices as well as diverse contents and applications, such as the iPod, iPhone, and iPad, based on a corporate vision of a digital hub concept. At the same time, the redefining of corporate boundaries that expanded Apple’s business in a horizontal direction from the Macintosh PC business to the delivery of music, smartphones, and tablets is also an indication of the evolution of a corporate vision involving Apple’s strategic transformation. This chapter presents the strategic and creative processes that enabled practitioners, including the late Steve Jobs, to demonstrate “strategic innovation capability” by “holistic leadership” at every level of management at Apple and successfully achieve a business ecosystem strategy through “creative collaboration” across diverse boundaries within and outside the company.

Universities have a new role in the commercialisation of knowledge (Etzkowitz, 1998). The new role began with science parks and increased collaboration in 1980s and, with other forms of commercialisation, broadened to licensing and spin-off creation in 1990s, which also involved students (Rasmussen, Moen, & Guldbransen, 2006). Commercialisation has led to a situation where a complex web of relations exists between higher education, spin-offs created by them and large firms. All together the progress has been important because the ‘commercialisation of knowledge connects the higher education to the users of the knowledge’ (Etzkowitz, 1998). The rise of the knowledge-based society also brings the creation of knowledge-intensive firms into focus. The aim of the chapter is to create more understanding how small technology-based Knowledge Intensive Business Service (KIBS) firms can have a new role in knowledge commercialisation. In this chapter, the innovation chain is considered as a continuum from basic research through applied research to product development and finally commercialisation. There still exists a ‘valley of death’ between research and commercialisation (Markham, 2002). Spin-offs are one means to cross it.

This chapter explores the extent to which an innovator is able to capture innovation rents. After examining the two main drivers of such rents, the strength of the appropriability regime and the ownership of specialized complementary assets, the chapter examines how their interaction is so critical in affecting imitation, commercialization options, and firm performance. After reviewing the underlying conceptual framework and empirical evidence, and using a perspective that cuts across both time and industries, the authors then discuss the implications of innovation profits for the resources to be devoted to the discovery of new or improved product and processes.

Since the 1980s, US universities have greatly increased attention given to innovation and entrepreneurship out of a genuine commitment to enhancing American competitiveness. Although regional innovation and entrepreneurship can be enhanced by universities in multiple ways, the primary metrics of “success” remain patenting, licensing rates, and university spin-outs. While these metrics can be a useful proxy for the entrepreneurial university they tend to understate the many important contributions universities, including non-research intensive universities, make to their regional economies. In this chapter, we introduce a framework of capabilities that are essential to nurturing ecosystems of innovation and entrepreneurship at the regional level. We then describe the varied ways in which universities can support the development of these capabilities. Finally, we provide a framework of metrics, which can more comprehensively capture the value that universities represent to innovation and entrepreneurship in their regions.

Many corporations have annual expenditures in research and development in the range of billions of U.S. dollars. Senior managers have often been frustrated by the lack of innovation in their organizations and have been looking for better ways to implement an innovation strategy. To provide initial evidence on this significant topic, we conduct an empirical examination and contribute to the existing literature in two important areas. First, we examine how managers choose what measures to pay attention to in managing the innovation process – defined as the process of creative definition, development, and commercialization of substantially new products, services or businesses. We find that managers use measures about specific phases of the innovation process together. For example, measures that inform about the execution stage of the innovation process are grouped together rather than being grouped with measures informative about other phases of the innovation process, such as market performance. This pattern “focused” around specific phases is in contrast to the alternative “balanced” pattern where managers would use measures from various phases of the process together. This result provides the first empirical test of how managers combine measures to filter information about business processes. It also provides important new evidence on the use of measures and provides guidance to the design of measurement systems. Second, this paper provides empirical evidence on the relationship between innovation strategy and the use of measures. Though previous studies have linked innovation strategy and the use of management control systems in general, there is little empirical data on the relationship of strategy and the use of measures and on the innovation process. We find that different dimensions of strategy are positively associated with how managers use different types of measures.

This study assess how governments can nurture innovation activities by supporting the research of individual companies, establishing new networks for innovation activities, and by contributing to the general contextual factors supporting innovative behavior.

This chapter analyzes alternative possibilities for the governance of innovation support and develops a framework to evaluate the governance of innovation support activities provided by a national innovation agency.

The framework is developed by analyzing how the governance principles in various national innovation systems have emerged when the countries have pursued low-carbon innovation strategies.

This chapter empirically shows a need to broaden the perspective on what can be expected from an adaptive innovation system, as well as the new types of arrangements facing public-private innovation collaboration.

This chapter explores new opportunities for the research community to further the understanding of how to apply various governance mechanisms in different contexts of innovation support especially relating to multi-level governance and co-governing.

We extend the literature on scientific discovery and commercialization by examining entrepreneurial action by university-based scientists. Specifically, we investigate the decision process and the paths to commercialize academic technologies. University-based technology transfer involves multiple stakeholders with competing interests; hence, we believe researchers should apply a multilevel theoretical lens, which starts with the disclosure of discoveries made by scientists in their labs. We build a multilevel framework that views the scientists’ choice to first disclose viable discoveries to pursue entrepreneurial action as a function of three factors: (i) a scientist's rent orientation, (ii) a university's rent doctrine, and (iii) the rent doctrine of the scientific field in which the scientist conducts research. We suggest that commercial disclosure most often occurs when there is alignment between these three factors. Lastly, we advance an agenda for future empirical research by developing specific propositions about the key constructs and relationships concerning university-based entrepreneurial action.

This chapter explores the extent to which an innovator is able to capture innovation rents. After examining the two main drivers of such rents, the strength of the appropriability regime and the ownership of specialized complementary assets, the chapter examines how their interaction is so critical in affecting imitation, commercialization options, and firm performance. After reviewing the underlying conceptual framework and empirical evidence, and using a perspective that cuts across both time and industries, the authors then discuss the implications of innovation profits for the resources to be devoted to the discovery of new or improved product and processes.