The keen interest in emerging technology stems from both a competitive advantage standpoint as well as a societal need point of view (Myers et al., 2002; Ray & Ray, 2011; van der Valk, Moors & Meeus, 2009; Walsh, 2007). Emerging technologies are assisting in the solution of the most challenging problems of the twenty-first century, including issues regarding water, health, energy, food and environmental concerns (Chan, 2008; Tierney, Hermina & Walsh, 2013). Many people from developing and developed nations (Pandza, Wilkins & Alfoldi, 2011; Thukral et al., 2008), including former Swedish Prime Minister Göran Persson (Persson, 2012) seek to embrace emerging technologies as a problem solution vector. Counterintuitively, they fear the continued use of traditional technologies, which have often created or contributed to the global challenges the world faces today.
Technologies, and especially emerging technologies, either improve or have the potential to improve gross domestic product (Freeman, 1982; Solow, 1957). The interest in creating scientific research and development in emerging technologies is extreme, but what is the state of the management and policy knowledge that must accompany such interest? The management interest in emerging technologies is also growing. Indeed they are the foundations of Kondratieff or Schumpeterian economic cycles (Kondratieff, 1935; Schumpeter, 1937). They are the true ‘winds of creative destruction’ (Abernathy & Clark, 1985).
Similarly, the term ‘emergent technology’ is a management designation, yet the term is more often used by the technical community than the managerial community (see Figure 1). Even here, the necessary managerial, policy and societal (Hung, Gao & Hu, 2009) considerations are lagging the scientific development by a great amount. Still countries fund and generate emerging technology-based product portfolios at an ever increasing rate (Walsh, 2001). Energy, one of the twenty-first century's biggest problems, has had few managerial publications (Kajikawa et al., 2008) compared to the thousands of technological articles related to energy development based on emerging technologies. Management techniques focused on emerging technologies as a whole, as well as any one specific emerging technology in particular, are immature.
Figure 1 does not project the true disparity between the research from social scientists and that of the physical scientists. Today's emerging technologies include computational sciences, micro-electro-mechanical systems (MEMS), nanotechnology, mobile technologies, bio-fuels and others (Cordero, Walsh & Kirchhoff, 2005; Elders, Spiering & Walsh, 2001; Kautt, Walsh & Bittner, 2007). Yet, if we simply plot the number of economics, finance, business management and indeed any non-technical articles compared to just one of these emerging technology fields, the true disparity is revealed. MEMS, for example, is an emergent technology. In Figure 2 we plot all non-technical articles on both MEMS and all non-technical articles on emerging technology to the single technical field of MEMS. Figure 2 shows that there is an over 100-fold higher publication rate for technologists than all social sciences combined.
The relative lack of insight into issues associated to the managerial, policy and societal impact of emerging technologies is of great concern because of their potential. Our task, here, is to improve the ‘tool box’ that managers and policy makers have to responsibly and successfully develop emerging technology-based innovations (Marquis, 1969). Emerging technologies are often used to develop radically new products with exceptional benefits to society (Allarakhia & Walsh, 2011; Barras, 1986). Managerial techniques are needed that would help managers determine the value of emerging technologies. Emerging technologies are at once often overvalued by the technologist (Gillier & Piat, 2011) and underappreciated by managers (Linton & Walsh, 2008a, 2008b).
Again, either figure illustrates how the managerial, policy, entrepreneurial and social impacts are clearly trailing scientific investigation. There is a need and opportunity for social sciences to do their share in adding value to this process. Managers are as a whole uncomfortable with the strategic importance of technology (Christensen, 1997; Linton & Walsh, 2013). The notion of the unknown risk that emerging technologies pose often causes large firm strategic managers, already uncomfortable with the importance of technology, to default the commercialization process of the even higher risk emerging technology-based products to entrepreneurs (Kassicieh et al., 2002; Kirchhoff & Walsh, 2002). One technique that could be used to diminish these fears is roadmapping. Roadmaps research that addresses portions of this concern are in critical need (Cowan, 2013; Tierney, Hermina & Walsh, 2013; Walsh, 2004).
This special issue contributes to this need in a number of different ways. One example of such progress is the improvement in understanding learning curves (Linton & Walsh, 2013) focusing on the technological development nature of emerging technologies. Another would be to create a deeper understanding of the development of ‘patient’ venture capital often required by emerging technology-based firms (Mahto & Khanin, 2013). Still others search for value that open innovation (Chiaroni, Chiesa & Frattini, 2011) or consortia can bring to the management of the use of emerging technologies (Allarakhia & Walsh, 2012; Park & Kang, 2013; Ritala & Hurmelinna-Laukkanen, 2009). We provide a brief summary of the authors' contributions below.
Linton and Walsh (2013) extend learning curve theory to encompass the entire development process, from design through supply chain and life cycle management. They develop a framework that illustrates the complex series of events underlying the seemingly parsimonious learning curve. This is of exceptional value for firms large and small, desperately trying to reduce risk in embracing emerging technology development. By integrating learning curve theory, it is possible to see how they can reduce cost while creating markets for emerging technology-based products.
Saner and Stoklosa (2013) embrace the definitional problems which hamper the understanding and commercialization of all emerging technology bases. They speak directly to the adage that if you cannot manage it you cannot measure it and you cannot measure it if you cannot define it, as discussed in our practitioners introduction (Martinez, 2013). This is especially the case for the emerging technology field of nanotechnology and its subfields, where populist ideas and non-convergent technology definitions add to the social unease associated with its use. The authors address nanotechnology and add to the literature by providing a pathway for the development of a definition of emerging technology. They provide the precision essential to advance rational dialogue, decision making, regulation, policy and ethics on emerging technologies.
Wu and Haak (2013) provide insights into large firm development of emerging technologies through the use of their corporate R&D centres. They lean heavily on the competency-based and resource-based strategic views of the firm in doing so. They suggest that large firms are trying to differentiate themselves through R&D development of new differentiating technological competencies which are often emerging technologies. They show both how developed and developing countries are creating their corporate R&D centres for the advance of emerging technologies.
Park and Kang (2013) examine the utility of alliances for emerging technology development and commercialization. Large firms often seek to gain advantage from emerging technologies by partnering with firms that are developing them in alliances. They show that this tried and true managerial pathway to incorporate emerging technologies into their innovative product development often limits firm risk, but does not always positively affect innovative performance. Specifically, they propose that firms should adopt technology alliance with due consideration of its negative aspects and their firms' limited resources.
Cowan (2013) deeply integrates legislation and policy into a roadmapping process so necessary for many emerging technologies to advance. Here, he presents a regional ‘smart grid’ process that focuses on the world problem of energy manufacture and distribution. He presents the drivers of the need for creating a smarter grid. He focuses on the unique regulatory and market structure that challenges its implementation. The author roadmap technique integrates key technology, business and policy concerns into an emerging technology roadmapping process.
Mahto and Khanin (2013) address one of the major commercialization hurdles for emerging technology-based entrepreneurial enterprises – ‘patient capital acquisition’. Traditional wisdom would suggest that emerging technology-based entrepreneurial firms, which often are lead by technologists with limited prior interaction or reputation with venture capitalists, would find difficulties in both obtaining access to and acquiring capital in a timely manner from these venture capitalists. Here the authors utilize empirical techniques to analyse data from 140 Internet-based firms to examine the effect that founder reputation has on an enterprise's ability to swiftly obtain financing. Their results suggest that founder reputation expedites ventures' quick access to public but not to private financing. This provides information useful in entrepreneurial team development for emerging technology-based firms.