New Technology-Based Firms in the New Millennium: Volume 7

The presentation of papers in this volume follows the logical and chronological process in which knowledge produced by universities is subsequently exploited. Beginning with a consideration of the business idea recognition process Lucas, Cooper, and Rodriguez-Falcon in Chapter 2 seek to understand the psychological mechanisms that trigger the recognition of science and technology-based opportunities for new ventures. By a number of qualitative interviews at the University of Sheffield, and a survey of science and engineering students at four UK universities, this topic is explored as a major component of opportunity recognition. In Chapter 3, Warren conducts an in-depth examination of the nature and extent of work carried out by a PhD engineer involved in various phases of a high tech university “spin-off.” Through a qualitative case study she addresses the important impact that the creation of a university spin-out has on the career development of engineering researchers, which can hinder the spin-out process if not managed effectively.

This chapter seeks to understand the psychological mechanisms that support entrepreneurial opportunity recognition. That recognition is treated here from the perspective of Kirzner's (1979) entrepreneurial alertness, a perspective that calls attention to the unconscious processes of discovery. It begins with the proposition that a substantial fraction of opportunities recognised by nascent entrepreneurs are not conscious in the sense that they are not found through a process that is driven by rational search or even by the conscious focusing of one's attention. A cognitive theory of unconscious recognition and discovery is considered that might then explain this phenomenon, based on the proposition that individuals develop a directed attention through interest and experience to quite specific domains.

The purpose of this chapter is to explore the creation and maintenance of entrepreneurial identity during the establishment of a high-tech university spin-out (USO) company in the United Kingdom. The chapter is based on a case study of a mature PhD student working initially in a research team, and later in a spin-out company, in a UK university; he then founds his own company. The study tracks his understanding and development of different aspects of his professional identity as he works towards shifting career goals in different formal and informal learning settings. The chapter commences with a discussion of the career tensions that might arise during the spin-out process. The next section argues that purposeful construction of entrepreneurial identity may be a significant element in supporting successful career transformation. The third section presents the case in detail. Following a discussion, conclusions are presented. The practical implications of the study are that better understanding of these processes can be used by educators and support staff in classroom settings and in incubators. Theoretically, the chapter adds specifically to the growing literature on entrepreneurial identity, extending it to the realm of science and engineering; the importance of the dynamic between engineering identity and entrepreneurial identity during the transition from engineer to entrepreneur is examined in depth. Most significantly, the case demonstrates how a complex reworking of what it means to be an entrepreneur and what it means to be an engineer takes place that is enormously significant in the crafting of a personal career trajectory.

Academic knowledge can be put to use in a commercial environment in several ways. One such mechanism to transfer knowledge to the market place is the start of a new, separate company, termed an academic spin-off company, with the aim to commercially develop and exploit the knowledge generated in the university (Fontes, 2003). In 1999, the Dutch Ministry of Economic affairs published a paper stating that the number of high-tech start-ups in the Netherlands lags behind compared to other EU countries and the United States. Subsequently, initiatives were started to stimulate commercial exploitation of knowledge generated within universities. A specific initiative by the Dutch government in the area of the Life Sciences was the so-called Biopartner programme. This was started in 2000 with the objective to enhance the business climate for start-ups in the Life Sciences and to realize 75 start-ups within 5 years (Dutch Ministry of Economic Affairs, 1999). Actions were directed toward increasing awareness, stimulating starters, establishing facilities like a seed fund and academic incubators, and promoting the commercialization of academic knowledge within universities. A few years later, the Technopartner program and the Valorization Grant were implemented with similar instruments aiming at scientists in universities (Dutch Ministry of Economic Affairs, 2003).

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.

Conventional models for the business valuation of technology are usually financially oriented and only measure economic value. Several of these financially oriented approaches have been reviewed by Leloux and Groen (2007). Current monetary (financial) valuation methods for technology include cost-based methods, income-based methods and market-based methods (Martin, 1999; Goldheim, Slowinski, Joseph, Edward, & John, 2005).

This chapter addresses the introduction of a post-project market review, which is based on the concept of post-project reviews to stimulate commercialisation. It will start with a brief description of the case-company. After this, the motives of the research will be clear, and the research methodology will be explained in Chapter 2.

Knowledge theories have developed over the past 30 years (Polanyi, 1966). However, it is only recently that knowledge has become regarded valuable asset in corporate boardrooms. Knowledge acquisition has become a critical resource for creating and sustaining competitive advantage as the competitive environment continues to intensify (Hitt, Ireland, & Lee, 2000). As with other corporate assets, the processes surrounding the creation and transfer of knowledge must be managed with significant insight to derive the most value from knowledge investments (Bhagat, Kedia, Harveston, & Triandis, 2002; Conner & Prahalad, 1996; Davenport & Prusak, 1998; Edvinsson & Malone, 1997; Stewart, 1997). The purpose of this chapter is to examine the significance of managing knowledge both within firm (internal knowledge) and across the value chain (external knowledge) for small and large firms. First, we review the literature on knowledge management systems and propose some hypotheses for internal and external knowledge management. Next, we present the data and follow this with the results. Discussion of the results follows, and the chapter closes with a number of managerial implications, limitations, and suggestions for future research.

Given the numerous government initiatives in existence improving the transfer of knowledge to high-tech small- and medium-sized enterprises (HTSMEs) appears to be a highly relevant topic (Bougrain & Haudeville, 2002). For example, governments provide subsidies, give training, found knowledge-brokering institutes, websites, and support collaboration between HTSMEs and research institutes (Jetter, Kraaijenbrink, Schröder, & Wijnhoven, 2005). Although government initiatives are undoubtedly helpful in supporting the transfer of knowledge into HTSMEs, they are not the only way to support them. An alternative way to support HTSMEs is by providing them with the Methods and Software Tools (MSTs) they need to identify, acquire, and utilize external knowledge. This process of identifying, acquiring, and utilizing knowledge from their environment is termed external knowledge integration (EKI) in this chapter.

Since the onset of the industrial revolution in England during the late 18th century, it has become increasingly clear how advances in technology have played a pivotal role in delivering wealth-creating economic growth, ranging from major advances in the generation of industrial power, initially through steam engines (e.g. successively by Nucomen, Watt and Trevithick), to the design of labour saving industrial machinery and working practices (Smith, 1776; Marx, 1867; Solow, 1957; Denison, 1967; Mansfield, 1968; Freeman, 1982). These advances have not merely resulted in industrial progress but have triggered changes in industrial location (e.g. water powered to coalfield sites in the cotton textile industry) (Riley, 1973), dictated population distributions and fixed the positions of major industrial cities within national and world regions. Indeed, perhaps, the most ambitious attempt to establish the major impact of revolutionary technological change on macro-level industrial performance was the explanation by Schumpeter of Kondratiev's ‘long wave’ industrial cycles (Kondratiev, 1925) in which upswings in world economic activity were linked to the introduction of pervasive new technologies caused by their ability to reduce unit prices, increase efficiency and be broadly applicable across large sectors of industry (e.g. stream and electric power) (Schumpeter, 1939; Freeman, 1986).

The recent failure to deliver the Lisbon agenda has led to much soul-searching within Europe (cf. The Sapir Group, 2005). This failure has enlarged the gulf between the limited number of successful knowledge regions, and those regions for whom globalisation has brought further anxiety, job losses and economic restructuring. More recent Lisbon-inspired policies have therefore attempted to build linkages between successful ‘knowledge islands’ and other, outlying and peripheral places, so that all these areas can benefit from concentrations of European knowledge and innovativeness.

Over the years, the above advantages have gained wide recognition in such a way that fostering spin-offs has become part of most universities’ and research centers’ policy. Among the many ways of accelerating the growth of USOs, perhaps the most captivating one is establishing incubator organizations. The networks of incubators have been built gradually in industrialized regions such as the United States and in Western Europe over the past two decades and now have reached maturity (Lalkaka, 2003). The first generation of incubators in the 1980s essentially only offered affordable office facilities to potential new ventures, including shared services, and soft loans. As time progressed, it was realized that the needs of spin-offs included more than just physical and financial support. This situation has challenged some incubators to change into providers of “added-value support,” such as business skills training and connecting the entrepreneurs to various networks.

Global technological competition has made technology transfer from academia to firms an important public policy issue (Rahm, 1994). Academia and individual academic institutions are a primary source of new knowledge production and innovation (Brennan & McGowan, 2007). It is widely acknowledged that the commercialization of scientific and technological knowledge produced in public funded research institutions, including universities and research centres, into the marketplace have a fundamental role to play in wealth creation, supporting economic growth and technological innovation, and plays a significant role in new venture creation, growth of existing firms, and new job creation (Mansfield, 1991; Harmon et al., 1997; Ndonzuau, Pirnay, & Surlemont, 2002; Siegel, Waldman, Atwater, & Link, 2003b; Steffensen, Rogers, & Speakman, 1999; Walter, Auer, & Ritter, 2006; Perez & Sanchez, 2003). Research by Acs, Audretsch, and Feldman (1992), Jaffe (1989), Mansfield (1991, 1998), and others indicates that technological change in important segments of the economy has been significantly based on knowledge that spin-off from academic research.