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Arho Suominen Notes on Emerging Technologies Turku Centre for Computer Science TUCS Dissertations No 141, November 2011 1. Introduction This dissertation focuses on the challenges in forecasting technological progres- sion. The work, by building a wide theoretical background in technology manage- ment and through a large case study, discusses the challenges of technological foresight. This discussion is, in addition to the sections included, based on the in- cluded original publication. In order to further elaborate on the overall context of the study, this introductory chapter explains the background, origins and motives, research question, research approach, and the structure of the thesis in individual sub-sections. 1.1. Background In the 1989 paper, The Future of Technological Forecasting Robert U. Ayres called for better methods of forecasting and planning for the future. Focusing espe- cially on quantitative methods of assessing technological development, Ayres thought that more accurate tools for decision making on a macroeconomic and microeconomic scale were needed. Building on previous work on long-range plan- ning and empirical measures of technological development, Ayers sought after 1. Introduction decision-making tools that would complement previously used qualitative methods of technological forecasting. Before and since the mentioned statement, an abundance of technology forecasting literature had been published. In the time before, work focused mostly on qualita- tive tools such as scenarios and long range planning (Gordon and Helmer 1964, H. A. Linstone 1978, Ayres 1969, Dalkey 1967, Dalkey and Helmer 1963) and since quantitative tools such as bibliometric, data mining and quantitative approaches have been used (Borgman and Furner 2002, Kajikawa, Yoshikawa, et al. 2008, Huang, Li and Li 2009, Tseng, Lin and Lin 2007, T. U. Daim, G. Rueda, et al. 2006, Kostoff, et al. 2001). Although being a rough categorization, the division into quantitative and qualitative approaches in foresight could be argued to be val- id, as seen from significant works on technology forecasting (Ayres 1969, Martino 1993, Porter, et al. 1991). This thesis, entitled Notes on Forecasting Emerging Technologies, draws from the abundance of technology forecasting and long-range planning literature and strives to create new insight on how qualitative and quantitative tools of technology fore- sight are applied in the context of technology management. The research question set for the study started from the fact that the rate of techno- logical change has increased. Straining our understanding on what possible, even elementary, development could be feasible within the time frame of 5 years, not to even talk about expanding the horizon to ten or twenty years, has made foresight a necessity. Challenges set by the increased speed of development into industry have made the identification of future development scenarios a question of survival (Day and Schoemaker 2005). In addition to identifying new technological options, the complexity of selecting between technical possibilities, correct or not, will require significant investment from both industry and governments. (Steensma and Fair- bank 1999). Studies have shown the challenges of selecting technologies (Torkkeli and Tuominen 2002), however, under turbulent environment survival is dependent on the ability to exploit new technologies through systematic foresight. (Mishra, Deshmukh and Vrat 2002) This has stressed the role of technology foresight in the management of technology (Henriksen 1997). However, while managers are aware of the need to foresight, the methods of conducting a foresight project has remained unclear. (Makridakis, Hodgsdon and Wheelwright 1974) – 3 – Notes on Emerging Technologies In addition to the challenges in applying foresight methods, cultural differences in how and to whom the responsibility to organize a foresight work differs signifi- cantly. Large national foresight efforts done in Europe (Keenan and Miles 2008, Cuhls 2008) and Japan (Kuwahara, Cuhls and Georghiou 2008) have tried to create a view on the direction of future research and development efforts. Taking a more macroeconomic view on how technological progression is managed, countries with large national foresight efforts strive towards a collective understanding of the future. Selecting technologies of the future is based on a somewhat collective un- derstanding on how things will evolve. In the Finnish context, we have seen efforts such as the FinnSight 2015 foresight project carried out during 2005-2006. Funded and lead by the Academy of Finland and TEKES, the Finnish Funding Agency for Technology and Innovation, the pro- gram strived to “lay the foundation for the Strategic Centers for Science, Technol- ogy and Innovation. Simultaneously, foresight will reinforce strategy work at the Academy of Finland and Tekes.” Comprising of ten twelve member panels, the Finnish foresight effort went through strategic areas of development and created a collective view on which factors will impact Finnish industry and society. Often going to detailed technological assump- tions, the process expanded from creating an overall view of the future to creating market expectations for specific technologies. For example with fuel cells, in the FinnSight report published in 2006 an argument was made that “Within the next ten years, fuel cells will go commercial. In the last two years, significant efforts have been taken in Finland on the application of fuel cells, although the industry base for this has been limited. Core technologies exist in specific areas such as Polymer Exchange Membrane fuel cells and Solid Oxide Fuel Cells. Industry is however getting more and more excited 1 on the technology.” (Acedemy of Finland and Tekes 2006) 1 Original text in Finnish: Seuraavien kymmenen vuoden aikana polttokennot tulevat markkinoille. Suomessa on parin viime vuoden aikana panostettu varsin paljon polttokennojen sovelluspuoleen, mutta alan yrityskenttä on vielä suppea. Ydintek- nologiaa on eräillä alueilla, kuten PEM-teknologiassa (polymeeri-elektrolyyttinen – 4 – 1. Introduction Elaborating on how a specific technology would mature into a commercially viable technology within a specific timeframe. Clearly also including the assumption that in the near future efforts should be directed to the technologies mentioned. On the other end, technological foresight in the United States, although having different non-profit foresight organizations working on research policy, is more driven by a microeconomic view on the future. (Porter and Ashton 2008) National roadmaps on the development on, for example, light emitting diode technology can be found, but technology foresight is seen as a corporate level strategic tool, not so much an overall government lead effort. In this, Porter and Newman (2011) refer to Competitive Technological Intelligence (CTI) in explaining the significance of gathering information on the “who” and “what” of research and development out- side the organization. Emphasized by the adoption of open innovation (Chesbrough 2003) based development, managing technological trajectories outside the confines of a single organization would seem necessary. An apparent notion would be that there is a place for both, a macroeconomic fore- sight effort and a microeconomic effort. However, we often lack in the ability to create well-founded strategic foresight on either level, most significantly in a mi- croeconomics level (Coates 2010). 1.2. Origins and motives One could argue that in parts due to the Finnish national foresight effort (FinnSight 2015), in 2007 TEKES launched a program to fund research on fuel cell develop- ment in Finland. Making a significant national effort, TEKES started several pro- jects on three different focus points: stationary, transport, and portable fuel cells. Launched with the expectation of demonstrating fuel cell technologies, and by these means creating commercial applications and value networks that would fa- cilitate the creation of a fuel cell cluster in Finland, the program commenced as a seven-year effort in 2007. (Felt 2007) kenno) ja SOFC-systeemeissä (kiinteäoksidipolttokennot). Yrityskiinnostusta lö- ytyy kuitenkin yhä enemmän. – 5 – Notes on Emerging Technologies Simultaneously to the national research program being establish decision makers in the City of Salo were awakened by future challenges. For several years, the small region of only 50.000 inhabitants had the good fortune of having one of the world‟s largest mobile phone companies, Nokia, established there. However, as Nokia had grown to be a global company, the city needed to extend their industrial base from the dependency of the continuation of Nokia´s Salo factory to something else. To this end, different “think tanks” funded by the regional development agency were established. From one of these efforts, the establishment of a portable fuel cell cluster within the regional area of Salo was decided on. Having no prior industry using fuel cell technology, the decision was ultimately based on the significant expectations seen in the fuel cell technology. Initiated partly by the strong support by the city, the University of Turku had, with Turun ammattikorkeakoulu (a polytechnic school in Turku), a 2 year TEKES fund- ed project focusing on the productization and research of portable fuel cells. The research was carried out in the research organization´s Salo campus and focused on both explaining how this new knowledge created could be applied commercially as well as developing the portable fuel cell technology towards commercialization. The author worked in the project during its planning, funding application and im- plementation. Thus getting the opportunity to both plan and execute the research. Summarizing the origins and motives; in this thesis a case technology, portable fuel cells, is analyzed. Being instigated by the strong policy effort from TEKES, a sig- nificant amount of publicly funded Research and Development (R&D) was di- rected towards the fuel cell technology. Interested in this new technological oppor- tunity, several companies sought to apply this new opportunity to their business. Within this large national effort, the city of Salo strived to develop its own cluster of portable fuel cell industry. This resulted in the funding of a project called Porta- ble fuel cell Research and Productization. The project focused on applied research and evaluating the commercial possibilities of portable scale fuel cells. This in- cluded a significant foresight effort, which was done to ensure the validity of the technology as promising future market for the participating regional companies. – 6 – 1. Introduction 1.3. Research question Going back to the theoretical background for the foresight effort, we as humans have an innate need, as well as an ability, to forecast and we do so with significant accuracy. Our everyday life includes forecasts made from practical things such as forecasts made on possible congestion on a specific highway within our commute to work. Our day-to-day forecasts are based on experience, word of mouth, or trust in the expertise of others, often relying on historical knowledge. We assume that spring would follow winter, but for an accurate forecast on tomorrow‟s weather we tend to turn towards professionals using elaborate mathematical models in their predictions. In a technological context, foresight is approached with different processes and methods than what would be used in our daily lives. Being able to accurately fore- cast the development of complex technology with an abundance of underlying causal relationships, differs significantly from what is done in a day-to-day basis. This has resulted in the creation of different structured approaches to evaluating technology and even an abundance of methodological options, or even a methodo- logical chaos. Reviewed in several works (Ayres 1969, Makridakis, Wheelwright and McGee 1983, Makridakis and Wheelwright 1989, 1978, Porter, et al. 1991, Martino 1993, Georghiou, et al. 2008), technological forecasting is done with a variety of meth- ods. Structured in different ways, such as normative and exploratory, or qualitative and quantitative methods, the abundance of forecasting methods should be ap- proached in a systematic way, while maintaining flexibility in selecting suitable methods in a case-by-case way (Makridakis, Hodgsdon and Wheelwright 1974). Within technological forecasting, we have historically relied on expert opinion and theoretical models of development. Having roots in military planning scenarios, expert opinion studies and mathematical models have been used to elaborate on possible technological futures. In forecasting, selecting methods is most often not a decision of selecting one suitable method, but rather selecting several suitable methods and using them in combination to approach a selected problem (Martino 1993). By using several methods, all of the relevant factors can be taken into con- – 7 – Notes on Emerging Technologies sideration (Makridakis, Hodgsdon and Wheelwright 1974), ultimately leading to better forecasts. Striving for more accurate predictions, the scientific community has developed methods of technological forecasting, some more accurate than others, but still having to deal with the unpredictability of life. This has resulted in an abundance 2 of mistaken forecasts , often based in nothing else than an opinion of a single per- son. This goes to show that forecasting, or foresight, is not an exact science. Fore- cast can often be seen as confining several foreseeable futures rather than elaborat- ing on one correct future. However, in an industry context we would have to be able to make an interconnec- tion between technology management, innovation, and product development. Cre- ating a link between the expected futures and company strategy and management, as such, an interconnection between technology management and foresight is more than apparent. From the background and origins of the study, the following research questions were made: What is the interconnection between technological foresight and technology management? Would a quantitative analysis of bibliometric technological tra- jectories enable sufficient strategic foresight? Would a combination of a qualitative and quantitative ap- proach add value to the trajectory based analysis? The questions proposed an interconnection between the existing culture of national level foresight to a microlevel foresight and between technology management and foresight. In addition the validation of quantitative, computer aided, methods called for by Ayres, for example, is suggested, simultaneously questioning if an analysis 2 Several authors have made a posteriori analysis on forecast made on the develop- ment of technology (Ayres 1969, Schnaars, Chia and Maloles 1993, Albright 2002, Armstrong 1978). Elaborating on the successes and mistakes made these studies give us a knowledge base for future work. – 8 – 1. Introduction of quantitative data could be the sole basis of foresight. Thus accepting the assump- tion that a mix of relevant methods, suggested for example by Makridakis et al. (1974), leads to better results. Finally in the context of the case study, the assumption is made that the national foresight effort, fuel cell program, and regional effort in Salo were the result of a well-founded view on technological progression and thus the results of this study would support the continuation of fuel cell development in the region. 1.4. Research approach The research was approached as a case study on portable fuel cell technology. Using, similarly to Flyvbjerg (2006), the definition in the Dictionary of Sociology, a case study is defined as “The detailed examination of a single example of a class of phenomena, a case study cannot provide reliable information about the broader class, but it may be useful in the preliminary stages of an investigation since it provides hypotheses, which may be tested systematically with a larger number of cases. (Abercrombie, Hill, & Turner, 1984, p. 34 in Flyvbjerg 2006) Following the arguments made by Flyvbjerg (2006) the value of a case approach is seen much broader than what would be understood from the definition. It can be argued that a case study is not just a poor surrogate for large scale statistical studies on a specific research question. The value of case studies can be found from its ability to study a specific case extensively such creating value by 1) either by prov- ing that there truly are “black swans”, and as such questioning the status-quo or 2) by using the proven force of an example to challenge current knowledge. Arguing that “One can often generalize on the basis of a single case, and the case study may be central to scientific development via general- ization as supplement or alternative to other methods. But for- mal generalization is overvalued as a source of scientific devel- – 9 – Notes on Emerging Technologies opment, whereas “the force of example” is underestimated .” (Flyvbjerg 2006) In the context of this thesis a case study is used, not as a method but as a research strategy. As suggested by Hartley, (2004) a case study can be viewed as a research strategy comprised of several methodologies seen fitting to the case. As such, methodologically the research planned was designed as a four-phased research project: literature review, quantitative phase, expert opinion study, and a conclud- ing scenario phase. The literature review phase was seen as creating the conceptual understanding on the interconnection between technological foresight and man- agement. In addition, the required baseline knowledge on the case study was stud- ied. In the quantitative phase, the case study was approached with computer- assisted tools which were seen as testing if a purely quantitative approach to fore- sight would give significant insight into the case. This was further complemented by a quantitative study, done in the form of a Delphi study, creating an expert based view on the development. These efforts were concluded in a subsequent scenario phase where the qualitative and quantitative studies done were combined to form a holistic view of developments. 1.5. Structure of the thesis 3 The dissertation is structured as follows. The following section, Section 2 , focuses on building the foundation for the study. It elaborates on managing technology through innovation, new product development, and management of technology. This could be seen as a different approach from previous literature, which seldom makes a connection between concepts as far apart. In this thesis, the second section is written as it is seen to elaborate on the context to which forecasts are made. Em- phasising innovation, managing our technological world and managing uncertain- ties are often mentioned in New Product Development literature as significant chal- 3 Section two has been published partly in the authors earlier pre-doctoral degree of Licentiate of Science (Technology). The theses form a continuum in which the earlier thesis focused to understand the conseptualisation focusing on product de- velopment. Section two has however been partly rewritten due to the authors fur- thered understanding in the theoretical background. – 10 – 0. lenges. As well, Fuzzy Front Ends call for better insight on the future of our tech- nological surroundings. In addition Technology Management (TM) emphasises the identification and selection of new opportunities as key activities. However, this literature, as seen in section 2, does not make an explicit connection to foresight. Section 3 elaborates on the theoretical background of Technology Foresight (TF). Focusing on the rough categorization to quantitative and qualitative tools in fore- sight, the Section explains the theoretical background of the subject. The section reviews significant literature within the context of TF and creates an understanding of the concepts found to be significant The concluding Section 4 discusses the theoretical background and draws conclu- sions from the previously published original publications included in this thesis. The publications are also reviewed in short in Section 4. In the final section the implications and future research possibilities are also introduced. – 11 – 2. Technology Management When attempting to analyze the concepts relating to this thesis it is seen as im- portant to limit the work to a specific scope. As Ayers (1969) has noted technology is created, either in response to societal changes or needs or by the second-order effects created by technology itself. It is important to create this context to this thesis as well. The way creating new products or taking advantage of innovations is understood in the confines of this thesis is at the very heart of technological fore- casting, as it lays the foundation to what it is that we are attempting to forecast. We have seen that the management of our increasingly technological world is im- portant, but in what context. By creating a background of TM, the author elaborates on the context in with TF is analyzed in. From this analysis, the scientific back- ground has been confined to describe and analyze several terms. These are innova- tion, Fuzzy Front End (FFE), New Product Development (NPD), and Management of Technology (MOT). This section is divided into four self-containing sub-sections reviewing individual concepts. In the first sub-section, innovation as a term and process is reviewed. This is followed by FFE, which is analyzed in a smaller detail than innovation. 2. Technology Management NPD is reviewed in the third sub-section. The analysis, as well as for innovation, hopes to elaborate the definition and process of NPD, but also makes notions on NPD success mostly following the work of Cooper (1994). The analysis on NPD is followed by analysis on MOT, which is seen as a tool for the leadership and man- agement of innovation and NPD. The chapter is seen as giving a basic understanding on the terms presented. The work is written with the understanding that the work does not cover all of the as- pects in the vast scope of the terms presented, but rather lays the foundation to understand the context of the work. The undertone selected, based on the context of the study, is to focus on technology or knowledge-driven development scenarios. This could also be defined, as Rothwell (1994) has done, as technology-push de- velopment. 2.1. Innovation Innovation has been an increasingly researched subject, but not a new concept to humans as such. As (Fagerberg 2006) has pointed out there is something innate in humans need to think of new and improved ways of doing things. As seen from Figure 2.1 the number of scientific articles relating to innovation has increased in recent years. 3500 3000 2500 2000 1500 1000 500 0 4 Figure 2.1: Articles analysis from the term innovation by years. 4 Source: ISI web Of Science Citation Index. – 13 – Notes on Emerging Technologies This sub-section focuses on the term innovation. It strives to elaborate the defini- tion of the term as well as what is seen as being an innovation process. The section also includes an elaboration of the sources and types of innovation. 2.1.1. Definition of Innovation As Fagerberg (2006) noted innovation is innate to humans. Innovations are born from humans working towards new and improved ways of doing things. It can be easily argued that innovation starts from the work of a network or single human working towards depicting the born idea. Earlier innovation was seen as the result of the individual actions of a researcher, but the current understanding emphasizes the role of network of innovators working in a problem-solving process. (Dosi 1992). Innovation is manifested in the interaction of interdependent actors, learning and exchanging information, in a system. (Edquist 2006) A distinction between idea, invention and innovation can be seen as demonstrating 5 the need for an innovation process. An idea is a change, incremental or revolution- ary to the status-quo. It can be a change in thinking, processes or products, but the 6 change has no concrete manifestation. In comparison, invention is the concrete manifestation of an idea. From this, we can see that innovation is the successful application of an invention (Mckeown 2008). Fagerberg (2006) has used the dis- tinction that innovation is seen as the first occurrence of an idea, innovation how- ever is invention carried out in practice. Innovation as such is defined as “The eco- nomic application of a new idea. Product innovation involves a new or modified 5 “(Product) idea” An idea for a possible product that the company can see itself of- fering to the market. If the idea is pursued, the product enters its development stage. - A Dictionary of Business and Management. Ed. Jonathan Law. Oxford University Press, 2009. Oxford Reference Online. Oxford University Press. Turku University. 30 July 2009 http://www.oxfordreference.com/views/ENTRY.html?subview=Main&entry=t18. e5052 6 “Invention” is the idea of a new product, or a new method of producing an existing product. This is distinguished from an innovation, which is the development of an invention to the stage where its use becomes economically viable. - A Dictionary of Economics. John Black, Nigar Hashimzade, and Gareth Myles. Oxford Univer- sity Press, 2009. Oxford Reference Online. Oxford University Press. Turku Uni- versity. 30 July 2009 http://www.oxfordreference.com/views/ENTRY.html?subview=Main&entry=t19. e1684 – 14 – 2. Technology Management product; process innovation involves a new or modified way of making a product. Innovation sometimes consists of a new or modified method of business organiza- 7 tion.” Innovation is similarly defined in scientific literature as “An innovation is an idea, procedure or object perceived as new by an individual or another unit of adoption, e.g., a firm” (Rogers 1995), although lacking in the economic compo- nent. A distinction has to also be made between creativity and innovation. These terms, which are also used as synonyms, have a clear distinction. Creativity is by defini- tion used to depict the ability to produce ideas, on the other hand innovation, as seen earlier is tightly linked to the concept of having a concrete and successful application of an idea. (Davila, Epstein and Shelton 2006) The definition of an innovation is also greatly affected by its context. In arts some- thing innovative means a radical change to the current state, however in economics and innovation is defined by the capability to increase value for customer, product 8 or organization. In an organizational perspective, innovation can be seen the “…successful imple- mentation of creative ideas within an organization.” (Amabile, et al. 1996) Innova- tion is seen as starting from the innovative individuals in the organization. When creative individuals, which can form innovative teams, use their insight on a given subject to create something new that makes a difference and can be successfully implemented an innovation might occur. Innovation is the combination and/or syn- thesis of knowledge within the organization that creates new processes, products or services. (Luecke and Katz 2003). Studied by several scholars (Bowman and Helfat 2001, Subramaniam and Youndt 2005), the knowledge, or intangible factors owned by the company, are the most significant factors affecting the innova- tiveness of a company. 7 "innovation" A Dictionary of Economics. John Black, Nigar Hashimzade, and Gareth Myles. Oxford University Press, 2009. Oxford Reference Online. Oxford University Press. Turku University. 29 July 2009 http://www.oxfordreference.com/views/ENTRY.html?subview=Main&entry=t19. e1609 8 For further discussion on innovation terminology refer to Linton (2009) – 15 – Notes on Emerging Technologies Historical discussion on innovation has started as early as 1800´s by Say (Say 1836) and later, purely in an economic context one of the first definitions of inno- vation is given by Schumpeter (Schumpeter and Backhaus 2003) as: 1. “The introduction of a new good” 2. “The introduction of a new method of production” 3. “The opening a new market in which a particular branch has not previously enters.” 4. “The conquest of a new source of supply of raw materials” 5. “The carrying out of a new organization of any industry” Drawing from the work of Kondrantieff (1935), Schumpeter described innovation as the disruption in the regular flow of economics caused by the introduction of novelties. The legacy of Schumpeter has since sprung the birth of Neo- Schumpeterian economics. Neo-Schumpeterian, in addition to basing itself on Schumpeter‟s work, is based on Evolutionary economics, Complexity economics, Change and Development, and System theory. Evolutionary economics is focused on the emergence and diffusion of novelties based, as well as in the biological evo- lution, on creation, selection and retention. Complexity economics is based on the interaction between agents in the knowledge creation and diffusion processes. As we can easily see, innovation driven economies, working with novelty are complex systems. Change and development incorporates laws of motion and industry devel- opment and finally systems theory introduces the competence building systems, which incorporate several factors such as firms, universities, and regions to the innovation process. (Hanusch and Pyka 2007) In this thesis, the focus is kept on technological innovation. Making a distinction between social and technological innovations the focus is kept on a micro level technological innovation, although accepting that the role of social innovations in a macro or micro level are significant enablers of technological development (Kuz- nets 1979, Abernathy and Clark 1985). OECD (1991 in Garcia and Calantone 2002) has defined technological innovation as an iterative process, which is initiat- ed by the possibility of introducing an innovation, or an improvement to an existing innovation, in the context of the industrial arts, engineering, and basic and applied research. As Garcia and Calatone (2002) have pointed out this definition made by the OECD includes two significant points. Firstly, technological innovation is seen as a process, which is iterative in nature. Secondly, the process works through it- – 16 – 2. Technology Management eration towards an innovation being successful in the market. The iteration can be also seen as including the possibility of reintroducing existing innovation as they evolve in the innovation process. Technological innovation processes are further discussed in the next chapter. 2.1.2. Innovation process As described earlier innovation is the end product of a process. The starting point, idea and invention, is through a process molded to an innovation as defined earlier. Innovation has by this definition taken place when the original invention has passed successfully through a process of research, production and marketing and been proven on the market place (Mckeown 2008). Working with innovation, or following with an innovation process, is described as a technological change process where from a novel solution something tangible is developed. The change process follows a path of recognizing needs, creating novel solutions for discovered needs, as well as then developing solutions and imple- menting them in a wider scale. The process models presented for innovation follow this abstract pathway to some extent, although not following a linear process of R&D to commercial innovation as argued by Freeman & Soete (1997). Pavitt (2006) has also analyzed the innovation process, partly through the work of Mowery and Rosenberg (1979), and has presented a framework of two aspects: 1. “Innovation processes involve the exploration and exploitation of opportuni- ties for new or improved products, processes or services, based either on an advance in technical practice („know-how‟), or a change in market demand or a combination of the two.” 2. Because of the high degree of uncertainty in innovation, innovation processes involves a process of learning through experimentation or theory. The capital- ist market is also seen as experimentation through competition. From this framework, Pavitt (2006) constructs innovation into three overlapping processes seen in Figure 2.2. Pavitt in some sense criticizes the distinction of in- novation processes as stages or gates, by this clearly referring to NPD processes. – 17 – Notes on Emerging Technologies The production of scientific and technological knowledge. The Responding to translation of and knowledge influencing into working market artifacts demand Figure 2.2: Innovation divided into three overlapping processes (Pavitt 2006). Pavitt (2006) sees the production of scientific and technological knowledge as a major trend. Pushed by the industrial revolution, the increased production of highly focused scientific and technological knowledge is affecting the framework present- ed by Pavitt. He sees the possibilities of rapid development offering opportunities for commercial exploitation. By coordination of specialization, these opportunities can be taken advantage of. Pavitt also follows in describing three forms of speciali- zation: 3. Development in R&D departments of large companies producing knowledge for commercial exploitation. 4. The small firms improving “producers` goods” 5. The “division of labor” in public/private knowledge development With the translation of knowledge into working artifacts, Pavitt (2006) troubled with the increased number of scientific knowledge, which theory is insufficient in guiding technological practice. This is underlined by the increased complexity in technological systems. Pavitt (2006) turns the focus of managers working with the endeavor of turning science and technology knowledge into products to take in account possibilities for government funding, system integration, techniques of managing uncertainty and “technological trajectories and scientific theories”. By this Pavitt hopes to elaborate that an innovation process is partly a diverse effort of handling vast spectrum of specific knowledge as well as being able to use the spe- cific knowledge on a high abstraction level. – 18 – 2. Technology Management In any case, the process of innovation involves matching the working artifacts with the user‟s needs. This includes the effort of coping with radical change as well as surviving the “tribal war” with existing technological solutions. Innovation, which is the commercial application of an idea, is significantly linked to the ability to facilitate the exploitation of an invention. The arguments made by Pavitt (2006) are clearly visible in the publications. In publication I the rapid increase in scientific knowledge on fuel cells is apparent. Keeping in mind that the technology has been invented over 100 years ago, the number of science produced has grown exponentially. Methods of structuring this knowledge are of significant value. As Nonaka and Takeuchi have pointed out, the innovation process can be seen as an intensive knowledge management process (Nonaka and Takeuchi 1995). In comparison to the overlapping trichotomy process described by Pavitt (2006) a linear representation of the innovation process is given by Rothwell (1994). Roth- well has described the evolution of the innovation process. In the 1950‟s and 60‟s the innovation process was seen as a technology push-model seen in Figure 2.3 (a). The process had as a starting point the production of new scientific knowledge through basic research. This new knowledge produced in universities and other organization doing basic research were then moved through applied research and research and development efforts to the market. This makes the idea of manufac- turer innovation and the novelty of end-user innovation, which are discussed in detail in the section 2.1.3, understandable. A technology push, or science push, based innovation can be seen in Figure 2.3 (b). This easily points out how the voice of the customer was forgotten and ideas or invention developed inside the company was pushed to the marketing department, which then selected the “via- ble” ideas to be launched. (Rothwell 1994) To answer the need for more market involvement in the innovation process a mar- ket pull type model was increasing in popularity in the 1970‟s. Market was seen as producing viable ideas or even inventions, which could be in a R&D process turned to products. As such, the market pull process, presented in Figure 2.3 (b), can be seen as the opposite of technology push. The new market pull innovation process was seen as being in tune with the needs of the market. It made possible by compa- – 19 – Notes on Emerging Technologies nies‟ production capabilities, which made it possible to adjust products to customer needs and follow the trends on the market. (Rothwell 1994) Figure 2.3: First (Technology push) and second (Market pull) generation innovation process (Rothwell 1994, Adopted). The evolution from the linear and static technology-push and market-pull models accounted to the birth of more versatile models. It was seen that either a market driven or a technology driven innovation process by itself would explain how the innovation process works. It was understood that markets and technology was in- terlinked through the lifecycle of an innovation. By this, the interaction in during the life cycle of the innovation will hold a key on explaining the innovation pro- cess. The interaction innovation model, presented in the 1980‟s took into consider- ation the interactions between technology development, society and markets as well as the development process. Figure 2.4 presents the interaction model. (Rothwell 1994) – 20 –