106
Int. J. Technology Management, Vol. 67, Nos. 2/3/4, 2015
Strategy transformation under technological convergence: evidence from the printed electronics industry Yongrae Cho Division of Vice President, Science and Technology Policy Institute (STEPI), Building B, Sejong National Research Complex 370, Sicheong-daero, Sejong-si, 339-907, Korea and Graduate School of Technology and Innovation Management, Hanyang University, Research Building, Wangsimni-ro 222, Seongdong-gu, Seoul, 133-791, Korea Fax: +82-44-287-2068 Email:
[email protected]
Euiseok Kim Korea Minting, Security Printing and ID Card Operating Corp., 80-67 Gwahangno Yuseong-gu, Daejeon 305-713, Korea Fax: +82-42-862-7631 Email:
[email protected]
Wonjoon Kim* Department of Business and Technology Management, Graduate School of Innovation and Technology Management, 335 Gwahangno, Yuseong-gu, Daejeon 305-701, Korea Fax: +82-42-350-4340 Email:
[email protected] *Corresponding author Abstract: Radical technological innovations have transformed competition in high-tech markets. One result of innovation is technological convergence, whereby different technologies are integrated and businesses become more complex, thus blurring industry boundaries. We examine the evolution of firms’ strategic positions under technological convergence. Specifically, we analyse the printed electronics industry using patent-centric network indexes and reveal technological intensity using firm-based networks of patent citations. We labelled firms that own core-functional (ink) technology core functional leaders in the patent network of the printed electronics industry. Additionally, we labelled firms that own control-related (device) technology technology integrators and those involved in application-related (electronics) technology application pioneers. Furthermore, we constructed a strategic quadrant framework that categorises firms according to their strategic positioning and
Copyright © 2015 Inderscience Enterprises Ltd.
Strategy transformation under technological convergence
107
evolutionary patterns. We also identified the idiosyncratic patterns of firms’ strategic behaviours in each dimension in relation to industrial leadership and regime changes in technological convergence. Keywords: dynamic evolution; network analysis; patents; patent citation analysis; printed electronics; strategic positions; technological convergence; technological leadership; United States Patent and Trademark Office; USPTO. Reference to this paper should be made as follows: Cho, Y., Kim, E. and Kim, W. (2015) ‘Strategy transformation under technological convergence: evidence from the printed electronics industry’, Int. J. Technology Management, Vol. 67, Nos. 2/3/4, pp.106–131. Biographical notes: Yongrae Cho is an Associate Research Fellow in Science and Technology Policy Institute (STEPI). He holds a PhD in Technology Management from Korea Advanced Institute of Science and Technology (KAIST). His research interests focus on innovation strategy and technological convergence. Euiseok Kim is a Senior Researcher at Korea Mining, Security Printing and ID Card Operating Corp. He holds a PhD in Technology Management from Korea Advanced Institute of Science and Technology (KAIST). His research interests mainly focus on the innovation theory, technological convergence and its dynamics. Wonjoon Kim is an Associate Professor at the Department of Business and Technology Management, Korea Advanced Institute of Science and Technology (KAIST). He holds a PhD in Economics from Seoul National University. His research topics focused on economics of innovation, innovation strategy and policy.
1
Introduction
High-tech industries have recently experienced rapid and accelerating radical technological innovation and this trend has markedly changed the competitive business environment. Particularly, this phenomenon has accelerated product miniaturisation and digitalisation (Hacklin et al., 2013; No and Park, 2010). Eventually, this phenomenon entails changes in product architecture through the combination/reconfiguration of existing components and materials to reflect changed technological knowledge (Hacklin et al., 2013; Henderson and Clark, 1990; Kodama, 2009). Accordingly, the last decade has seen increasing overlapping of technologies and the associated technological convergence has created a decisive opportunity to realise industrial development and technological breakthroughs (Kodama, 1995). A recent comparative study examined technological convergence and technology fusion from an industrial perspective (Curran and Leker, 2011). Convergence between disparate technologies has also become a factor in strategic alliances and inter-firm networking focused on technological innovation and such activity often involves different industries (Harianto and Pennings, 1994). Technological convergence thus has been identified as a key catalyst for sharing industryspecific knowledge (Hacklin, 2008) and creating dynamic innovation networks (Kodama,
108
Y. Cho et al.
2009). Technological convergence thus gradually blurs and erodes industry boundaries in a turbulent and complex business environment. Therefore, investigation of the changes in the industrial leadership and the resulting evolution of the competitive landscape in terms of technological convergence is an important research issue. Existing research has focused on analysing firm strategic choices and directions with regard to industrial convergence (Hacklin, 2008; Hacklin et al., 2013) and on further discussion of technology strategy. However, the role of underlying technological convergence in firm strategic choices remains unexplored. Additionally, rather than adopt an integrated perspective, previous studies on technological convergence and related firm strategy treated the two separately. For example, studies on technological convergence (No and Park, 2010; Curran et al., 2010; Curran and Leker, 2011; Kim et al., 2014) focused on technological convergence itself without considering firm strategy at the industry level, while other studies (Lei, 2000; Nyström, 2008) examined firm strategic choices related to industry convergence at the market and industry levels. Technology-level or patent-level empirical studies and discussions of firm strategy are still required. Therefore, this study investigates firm strategic choices regarding technological convergence. In doing so, we also examine and suggest the categorisation of converging technologies according to their functional roles in a specific industry, namely printed electronics. We thus examine the roles in technological convergence of companies that own core and peripheral technologies and suggest firm-specific dynamic evolution patterns of their strategic choices regarding technologies. This study thus analyses firm patent citation networks and conducts comparative analysis using network indicators to measure technology strategic behaviours. Consequently, this study not only examines which companies have played a central role in technological convergence of printed electronics, but also the trajectory of their technological leadership roles. Theoretically, this study expands the current limited perspectives and discussions on technological convergence into a discussion of firm technology strategy based on detailed patent analysis. The underlying interactions and dynamic evolution of firm technological knowledge during technological convergence have not been revealed at the level of the firm. Therefore, we can identify the interdependent knowledge structure of firms and its evolution, which corresponds to the dynamics of technological convergence. This also enables firms to find strategic opportunities at the technology level and suggests strategic directions for firms currently facing turbulence associated with technological convergence. Methodologically, this study suggests a new analytical approach using patent analysis to map the network of patent-holding firms. This approach allows the clear identification of firm knowledge flow and strategic direction in relation to firm technology development. The new approach presented in this study thus can identify firm strategic implications at the technology level based on analysis of the dynamics of firm technological convergence. For example, this study can identify companies that are key players that own core technologies, or that connect, adjust and integrate core and disparate technologies to develop technological convergence. Additionally, we can use technology intensity on converging technologies to identify a firm’s strategic positioning in patent network structure. To fulfil the research aims, Section 2 examines existing studies on the significance of technological convergence and patent data to measure convergence from a technological knowledge perspective. Additionally, we deal with issues of network-centric
Strategy transformation under technological convergence
109
technological and industrial analysis using patent information. This section also discusses the concept of printed electronics technology and the meaning of technological convergence. Section 3 introduces the data collection, network-centric methodology and relevant indicators. Additionally, we reclassify companies according to the technological fields relevant to printed electronics. Section 4 presents network visualisation and strategic group maps intended to reveal companies’ technology strategic position and summarises analytical results together with related inferences. Finally, Section 5 presents some discussion and draws conclusions.
2
Theoretical foundation
2.1 The distinctive characteristics of technological convergence Technological convergence has two distinctive characteristics. First, contrary to homogeneous technology development, technological convergence can cause radical and discontinuous innovation in a market or industry. New technologies develop interdependently and technology integration and substitution can introduce a new technological paradigm, i.e., radical innovation (Freddi, 2009). Interacting technologies develop complementary relations and maintain their interaction through technological convergence. Within this process, technological convergence drives change in organisational strategy and triggers radical innovations that are new to market or product (Chandy and Tellis, 1998). From the industrial perspective, sustaining competitive advantage in rapidly converging industries requires high intra-firm and inter-firm coordination to learn and build new sources of knowledge, skills and insights, which results in technological convergence and, ultimately, radical innovation (Lei, 2000; Kim and Lee, 2009). However, technological convergence is also significantly related to incremental innovation. For example, the recent management environment, known as ‘complex product industries’, comprises countless heterogeneous, interrelated and interdependent forms of technological knowledge (Bekkers and Martinelli, 2012; Kim and Kim, 2014), i.e., incremental innovation, under a continuous process of integration, i.e., technological convergence. Therefore, technological convergence is also important in the gradual development of technology in the current market and industry environment. Second, co-evolution among disparate technologies under technological disequilibrium is a characteristic of technological convergence. As Rosenberg (1982) pointed out, imbalance occurs in the combination of two disparate technologies when one underperforms the other. On the one hand, an improvement in a specific technological field can hinder full technological integration (Rosenberg, 1982). On the other hand, significant delay in improvements in a technological field can hamper technological convergence. When innovations involving leading or even following technologies can solve this imbalance, technological convergence can succeed by introducing significant innovation to a market or industry. The responsible company can then influence the subsequent development of converged technological areas. Therefore, identifying technological leaders in the development of technological convergence enables the prediction of upcoming competitive market leaders in immature industries where significant players have not emerged.
110
Y. Cho et al.
2.2 Patent data as an indicator of technological knowledge and corporate strategy Patents provide useful information for examining the convergence between disparate technologies and the dynamics of changing patterns, identifying future promising technologies and establishing firm technological strategy. Many scholars use patent data to establish national technological policies, as well as for technological and industrial analysis (Cho et al., 2012; Cho and Shih, 2011; Choi et al., 2004; Park et al., 2005). In fact, statistical information related to patents provides one of the most representative proxies and indicators of technological analysis (Chang et al., 2009; Griliches, 1990; Trajtenberg et al., 1997). Moreover, patent citations are an important indicator for predicting convergence (Karvonen and Kässi, 2013). Numerous studies have emphasised the importance of patent management for both information protection and technological improvement (Ernst, 2003; Ernst and Omland, 2011). Overall, the research on patents comprises two streams. The first stream examines a patent as disembodied technological knowledge and focuses on the technological analysis of bibliographic information. Recent studies have adopted network analysis based on citation information (Choi et al., 2004; Park et al., 2005). Specifically, patent citation information has been utilised to analyse and predict technological development and pathways. Researchers conducted network analysis of numbers of patent citations according to specific classification systems such as the United States Patent Classification (USPC) and International Patent Classification (IPC) (Chang et al., 2009; Cho and Shih, 2011; Gay and Dousset, 2005; Lee et al., 2009; No and Park, 2010; Shin and Park, 2010). Second, a stream of research exists that uses patent information to establish firm technological strategies. Specifically, such research uses patent information as a key indicator of competitive advantage and business performance (Ernst, 2003; Ernst and Omland, 2011). Particularly, research that draws a positioning group map using patent information provides important clues regarding firm technological strategies. To summarise, patent information can understand the technological linkage structure and analyse strategic portfolios in presenting rapid changes in the technology market represented by technological convergence.
2.3 Network analysis for technological convergence As already mentioned, the level of interdependence and integration between disparate technologies is a complex phenomenon that includes not only the relative importance of individual technologies but also their interaction (Freddi, 2009). While such technological convergence is possible through technological collaboration with external partners, in fact it largely depends on in-house research. The reason is that where new technologies are highly integrated into traditional ones, internal corporate capabilities that enable the real absorption of new technologies become important (Freddi, 2009). Therefore, higher performance is associated with a focus on downstream activities and operational capability, as well as on technological diversification (Gambardella and Torrisi, 1998). Also, organisations able to manage different standards and platforms can effectively implement product strategy (Park et al., 2012). The success of the combination of disparate technologies can be said to depend on
Strategy transformation under technological convergence
111
the absorptive capacity of an organisation. To summarise, “a firm’s ability to integrate new ideas from diverse fields has competitive advantages in the converging trends among technologies and markets” (Yoffie, 1997). Nonetheless, companies should constantly seek external knowledge through the combination of disparate technologies. In this process, collaboration, such as networking and forming strategic alliances with other organisations, should be pursued (Harianto and Pennings, 1994). To understand such complex, interrelated and cumulative technological changes, as well as the resulting patterns of competition and collaboration among companies, the analysis of patent information as an indicator of technical knowledge remains important. Previously, the most common method of patent analysis was to simply compare entities based on the number of patents assigned to them (von Wartburg et al., 2005). However, the recent trend involves introducing methodologies for more precise analysis of technological knowledge flows, such as patent citations, using bibliometric information. Such analysis increases the importance of showing the big picture of the overall structure and internal/external linkage of technologies (Lee et al., 2009; Kim et al., 2014). From this perspective, network analysis is derived from graph theories and is an appropriate methodology for visual analysis of the relationship between technologies or companies. Network analysis also has the advantage of quantitatively deriving and using network indicators that can be used to judge the extent and influence of the relationships between objects. If network analysis is used for technology analysis, it can visualise and quantify both core technologies and the technologies that link networks together (Cho and Shih, 2011; Shin and Park, 2007). For instance, analysis of patent citation is an area where network analysis is effectively employed to measure technological knowledge flows among actors (Lee et al., 2009). Patent data also publicly provide citation information on all the other areas involved in technology-driven industrial convergence (Curran et al., 2010). Following this methodological approach, patents as technological knowledge can be transformed into potential for technological innovation, allowing inter-industry knowledge spillover to facilitate new technological combinations (Hacklin, 2008; Hacklin et al., 2009). Business network analysis based on mergers and acquisitions and strategic linkages between companies is particularly significant (Phelps, 2010; Schilling and Phelps, 2007). Nevertheless, few studies have applied patent network analysis to business network studies. For example, studies using patent citation information have established patent-owning firms as nodes and analysed the structure of the links among them and their knowledge positions (von Wartburg et al., 2005). However, an important yet overlooked fact is that such analysis has failed to demonstrate the evolution of technological trajectory and the dynamic technological relationships between companies. Of course, numerous factors besides patent citations influence the linkages among companies. Therefore, attempting to infer a company’s technological strategy using a patent citation network involves using only a subset of the possible knowledge-based links among firms. Despite this drawback, this type of network analysis offers meaningful insights into the relative position of a firm in the technological knowledge space (Bekkers and Martinelli, 2012). Moreover, network analysis can reveal not only the role of technologies or related firms in knowledge flows, but also firm-specific industrial leadership changes and trajectories (Fontana et al., 2009; Verspagen, 2007; Oh et al., 2015).
112
Y. Cho et al.
2.4 Printed electronics in technological convergence We use the example of printed electronics technology to examine technological convergence. Printed electronics is an innovative technology through which microchips can be manufactured in the same manner as printed matter such as newspapers, magazines and posters. Specifically, this alternative to photolithography produces electronic circuits and semiconductors through a printing process that uses inks with electrical properties. Printed electronics is selected to examine the evolutionary characteristics of convergence technologies for the following reasons. First, as an exemplar of technological convergence, printed electronics is symbolic as it involves the convergence of long-established technological knowledge, namely printing, with electronics, a high-technology. Additionally, the technological development of printed electronics is heavily indebted to nanotechnology, widely regarded as a new paradigm1. However, this revolutionary technology also results from an underlying knowledge convergence involving other existing technologies (Hacklin, 2008; Hacklin et al., 2009). Second, the elementary components of this technology may be clearly differentiated. Third, printed electronics is a disruptive technology that involves a revolutionary substitution of the lithography process used to manufacture electronic circuits (European Commission, 2010). This technology exerts a strong ripple effect on all present and future industry and is increasingly socially important (Das and Harrop, 2012)2. The biggest differences between printed electronics and traditional electronics manufacturing are as follows. Printed electronics uses an additive method while the lithography process used in traditional electronic circuit manufacture involves a subtractive method. This difference provides printed electronics the advantages of greater simplicity and lower manufacturing costs. Other major advantages of printed electronics are its suitability for use with flexible substrates and its greater eco-friendliness compared with existing manufacturing methods (Kunnari et al., 2009; Leenen et al., 2009). Figure 1
Value chain of the printed electronics industry
Source: Das and Harrop (2012)
Elementary components of printed electronics are clearly differentiated into substrate, ink and device technologies. Additionally, electronics (application) technology involves application in electronic products (see Figure 1, Das and Harrop, 2012). Here, substrate technology relates to plastic substrates such as polyethylene terephthalate and polyethylene naphtha-late used for semiconductor printing and ink technology involves the manufacture of the conductors, semi-conductors and insulators that comprise circuits. Device technologies involve the printing machines or parts that control the characteristics of each technological element and integrate them into printed electronics processes. Last,
Strategy transformation under technological convergence
113
electronics technologies are product-related technologies that apply printed electronics processes to electronic products (Perelaer et al., 2010). To summarise, based on the literature on network-centric patent analysis and an overview of the element technological fields in printed electronics, this study attempts to analyse patent citation relationship patterns. Particularly, we attempt to transform data on specific aspects of technologies into an understanding of the companies that own the four component technologies involved in the convergence of printed electronics technologies.
3
Methods
3.1 Sample and data collection This study examines the technological linkages among firms using network analysis based on patent citation information. We collected patents related to printed electronics registered with the United States Patent and Trademark Office (USPTO) from 1976 to 2012. More specifically, search operators and search periods were set and bibliographic information was extracted for each year. The data included citation information, which incorporates patent number (and the relevant assignee firm), as well as antecedent or descendant patent citations. We analysed bibliographic information in patent abstracts, including compound and individual technological terms related to printed electronics. The major keywords and search expressions of element technologies were jointly developed and verified with academic and industry experts in printed electronics. Through this process, we set the search words listed in Table 1. Table 1
Keywords and their sources in patent information
Information sources Title, abstract, claims, specification
Keywords Printed electronics, flexible electronics, gravure print, offset print, flexo print, screen print, ink jet, conductive ink, CNT (carbon nano tube), graphene, metallic ink, silver ink, copper ink, stretchable substrate, printed circuit board
This keyword-based searching method extracted the first 3,677 patents as bibliographic information. We then unified the assignees according to associated business names and divided the business types according to the North American Industry Classification System (NAICS). Using number of patent registrations as a filter, we excluded companies with fewer than ten patents, though this group comprised relatively little of the data. Finally, 1,598 items of bibliographic information on 43 companies were analysed. Citation information between patents included in this bibliographic information was extracted and information on 72,718 cases was obtained. Patents registered with overseas patent offices rather than USPTO were excluded from the citation analysis. These procedures selected 5,277 citations from 1,598 bibliographic data entries. Two analytical strategies were employed. The first was to reconstruct the classification system by considering the characteristics of printed electronics technology. Based on the NAICS, we classified companies based on their product and service classifications among the four technological fields of printed electronics presented in the previous section (see Appendix). The second strategy was the reclassification of patent information according to technology period. We conducted extensive work to classify the
114
Y. Cho et al.
citation information extracted by search words on component technology in the printing area into two phases, as follows: the first phase was assumed to comprise the period during which each individual technological element of printed electronics, particularly nanoparticle technology, developed independently (1976 to 1999). The second phase was assumed to run from the real start of technological convergence to the present (i.e., 2000 to 2012). We then reconstructed patent and citation information for each period and component technology at the business level.
3.2 Firm-level indicators of network centrality and strategic position Assessment of small patent portfolios, for example to understand firm technological strategy, can be performed using in-depth expert valuation techniques. However, assessment of large patent portfolios, such as to understand technological convergence or compare technological strategies between firms, requires other indicators. Thus, merely comparing patent quantity, such as by using patent count data, is insufficient to value the competitive impact of patent portfolios (Ernst and Omland, 2011). In this context, we follow Ernst and Omland (2011) who assessed the quality dimension using certain patent indicators such as citations. Using patent citations in network analysis, individual patents are represented by nodes and citations are denoted as knowledge flows whose edges indicate inter-nodal interactions (Bekkers and Martinelli, 2012; Gelsing, 2010; Jaffe and Trajtenberg, 2002; Lee et al., 2009). Basically, patent citation analyses are based on ‘backward’ and ‘forward’ measures, which provide evidence regarding technological innovation links between ‘antecedents’ and ‘descendants’ (Trajtenberg et al., 2002). Similarly, ‘cited’ patents are studied to understand knowledge inflows from other technologies, while ‘citing’ patents are studied (typically using simple counts of patent citations) to measure invention quality using technological or economic value (Henderson et al., 1998; Jaffe and Trajtenberg, 2002; Trajtenberg et al., 1997). These unique linking properties of patent citations provide information vital in studying technological convergence, which is strongly influenced by relationships among technologies (No and Park, 2010). Transforming our focus from the technological to the firm level, the nodes represent individual firms and the edges represent the accumulated citations used to measure patent quality in the technology portfolios. Essentially, patents cited denote backward citations whereby technological knowledge is absorbed from other firms, while patents citing denote forward citations whereby technological knowledge is sent to other firms (Bekkers and Martinelli, 2012). In network analysis, the traditional index is centrality (Scott, 2003; Wasserman and Faust, 2006). The degree of connectivity between a given node and others implies the extent of related technological information flows. Widely used measures of connectivity include degree centrality and closeness centrality. The former measures direct ties only as a role of local centrality, while the latter considers both indirect and direct ties. Closeness thus serves as a measure to determine the impact or influence of a certain technology, as well as its potential technological capabilities. Restated, closeness (global) centrality represents both indirect and direct linkages in the network theory (Scott, 2003). Additionally, following the concept of closeness centrality, nodes that are ‘shallow’ to other nodes (i.e., those that tend to have short geodesic distances to other nodes within the network) have higher closeness. In centrality analysis it is preferable for closeness to mean shortest-path length, as it assigns higher values to more central nodes (Belussi et al., 2012).
Strategy transformation under technological convergence
115
Therefore, we utilise closeness centrality to help examine the role of a patient as a global centrality in the technological knowledge networks. Closeness enables the determination of the role of each node (firm) as a key influencer of the relationship with other firms within the network for technological convergence. If the shortest distance of the path linking two nodes i and j is dij, it depicts the number of lines in the geodesic linking the two actors. Therefore, the closeness centrality of node i can be written as: ⎡ Ci = ⎢ ⎢⎣
⎤ dij ⎥ ⎥⎦ j =1 n
∑
−1
where the sum is the total distance of i from all other actors. Closeness centrality entails the inverse of the average shortest path between a given node and all others in the network. High closeness centrality values thus indicate the most influential problem areas (Ávila-Robinson and Miyazaki, 2013). We need additional information to infer firm technological strategies. Patent indicators used in the existing research on patent portfolios were adapted and developed to this end. Ernst (2003) formed the patent portfolio using patenting indicators such as technology share (patent strength), shown along the abscissa and patent growth (attractiveness), shown along the ordinate. The size of a circle indicates the R&D emphasis in this portfolio of the matrix form and thus reveals the importance of each technological field within a company’s R&D portfolio (Ernst, 2003). Firm R&D emphasis is calculated from the number of its patent applications in given technological fields. The ratio of patents in printed electronics to total patents for each firm thus indicates its technological intensity in printed electronics. Here, the concept of technological intensity for printed electronics is quantified as: PI i =
PAiF Ni
where Ni is the total number of patent applications for firm i and PAiF (also called PA: patent activity) is the number of patent applications of firm i in the printed electronics field. Thus, this index shows firm technological intensity and weight on printed electronics, which represents their specific related strategies. Using the two indicators, we identify companies that played a central role in each phase of the technological convergence and integration of disparate technologies. Simultaneously, we attempt to find unique and idiosyncratic patterns in the technology strategies. This study uses closeness centrality to understand the technological impacts and influences of each company and also considers technological intensity on printed electronics from the perspective of firm strategy.
4
Analytical results
4.1 Descriptive statistical analyses Table 2 lists numbers of patents held by individual firms, for a total of 1,598 patents from 1976 to 2012. The company with the most patents is Hewlett-Packard (276), followed by Samsung Electronics (210) and Xerox (119). Firms that own device-related patents
116
Y. Cho et al.
account for the largest portion of the sample (48.44%), followed by those with patents related to electronics (34.67%), ink (11.20%) and substrate (4.32%) (see the Appendix for a classification of each firm according to its technological characteristics). Table 2
List of firms with over 10 patent registrations
Corporate name
Counts of patents
Corporate name
Counts of patents
Hewlett-Packard Company
276
General Electric Company
17
Samsung Electronics Co., Ltd.
210
Dai Nippon Printing Co., Ltd.
17
Xerox Corporation
119
Motorola, Inc.
17
Canon Kabushiki Kaisha
86
Mitsubishi Denki Kabushiki Kaisha
17
Eastman Kodak Company
73
NEC Corporation
16
Seiko Epson Corporation
66
Sony Corporation
16
International Business Machines Corporation
60
Hitachi, Ltd.
15
Cabot Corporation
47
Konica Minolta Holdings, Inc.
15
Samsung Electro-Mechanics Co., Ltd.
40
Westvaco Corporation
14
Fujifilm Corporation
36
BASF Aktiengesellschaft
13
E Ink Corporation
35
Nanosolar, Inc.
13
Semiconductor Energy Laboratory Co., Ltd.
35
Kovio, Inc.
13
E. I. Du Pont de Nemours and Company
30
Alps Electric Co., Ltd.
13
Industrial Technology Research Institute
26
LG Chem, Ltd.
12
Siemens Aktiengesellschaft
26
Robert Bosch GmbH
12
Brother Kogyo Kabushiki Kaisha
25
Nippon CMK Corp.
11
Sumitomo Metal Mining Co., Ltd.
25
Toppan Printing Co., Ltd.
11
Kabushiki Kaisha Toshiba
22
Samsung Mobile Display Co., Ltd.
11
Sharp Kabushiki Kaisha
20
Cambridge Display Technology Ltd.
11
Fuji Xerox Co., Ltd.
19
Hitachi Displays, Ltd.
10
Ricoh Company, Ltd.
19
Asahi Glass Company, Ltd.
10
3M Innovative Properties Company
19
Total
1,598
The line chart depicts patent count for each of the four technological components of printed electronics. The category with the highest patent count was device, followed by electronics. Notably, whereas patent registrations in the device category rapidly increased after the mid-1990s and then decreased after the mid-2000s, patent registrations in the electronics category actually increased after the mid-2000s. In other words, the quantitative increase of patents related to the integration of component technologies (devices) was immediately followed by an increase in application into final products (electronics) and this latter phenomenon continues.
Strategy transformation under technological convergence Figure 2
Rends of patent counts by technological category registered during 1976 to 2012 (see online version for colours)
Figure 3
Firm network of printed electronics by technological category during 1976 to 1999 (see online version for colours)
117
4.2 Network analysis We conducted firm-level network analysis by substituting patent nodes with company nodes3 to show firm patent citation structures related to printed electronics. Based on citation direction and with links shown as arcs, companies that cited other companies’ patents were visualised as receiving inflows of technological knowledge, while those
118
Y. Cho et al.
whose patents were cited by others were visualised as providing outflows of technological knowledge (Bekkers and Martinelli, 2012). Figures 3 and 4 show firm-specific patent networks related to printed electronics technologies. The size of the nodes indicates the total number of patent applications. Figure 4
Firm network of printed electronics by technological category during 2000 to 2012 (see online version for colours)
Figure 3 shows active knowledge outflows and inflows, with the companies that owned device technologies being main players in printed electronics during 1976 to 1999. Overall, we found certain companies led the technological convergence and influenced other firms. Figure 3 shows that device-related companies occupy the centre of the network, while other types of companies, including electronics-related companies, occupy the periphery. Additionally, knowledge generally flows from device-related technology to other types of technologies. For example, HP strongly influenced Xerox and Samsung Electronics, as suggested by the tendency of the latter to cite its patents. Similar patterns characterise the cases of Xerox and Seiko Epson. Particularly, Xerox intensively passed knowledge to Cabot. Throughout the network structure, Xerox and Seiko Epson are clearly key players and linkers in both global and local terms. The patent-specific business network (Figure 4) exhibits a more complex structure from the 2000s. Specifically, the technological linkage structure becomes more complex and many companies occupied the centre of the network. Particularly, compared with the previous period (1976 to 1999), device-related companies remained central to the network structure and their patent citation actively occurred with electronics-related companies. In other words, leading companies that play a central role in technological
Strategy transformation under technological convergence
119
convergence consistently influence other firms in terms of knowledge flow regardless of network period. Additionally, a strong link between Cabot and Xerox continues. However, unlike in the previous period Cabot acts as a receiver of technological knowledge and simultaneously links with other ink-related firms. Additionally, links became more scattered and complex than in the first period. Samsung Electronics not only increased its overall number of patents during this period but also the flow of technological knowledge. The company diversified its network during this period to include ink- and substrate-related companies and actively cited patents of other electronics companies. From this we infer that during this period Samsung Electronics changed its position in technological capabilities that differed from those used in the previous period.
4.3 Strategic group map To better understand the evolution of the strategic positions of companies within the patent network, we constructed a strategic group map based on firm patent portfolios. Specifically, strategic group maps were drawn for the two periods, with closeness centralities indicated on the abscissa and technological intensity on the ordinate (Figures 5 and 6). This enables us to understand both firm strategic interest in printed electronics and firm strategic behaviours, such as changes in network positions. Additionally, the distributions of firms on the two dimensions of this strategic group map suggest the strategic characteristics of the technology-based firms (Podolny et al., 1996). The size of each circle in the map represents the total count of patent applications by each company. Two lines on each positioning map can be used to create a scatter plot to indicate the average values of indicators (vertical: closeness centrality, horizontal: technological intensity on printed electronics) (Okamura and Vonortas, 2006). According to the plotting of our sample along these two dimensions, we identify four quadrants of technological convergence. The first quadrant identified, occupying the upper-right partition – high technological intensity on printed electronics and high centrality in the firm networks – is associated with both strong technological concentration on printed electronics and strong technological influence. Firms in this quadrant are technological leaders in the printed electronics industry and likely to maintain their leadership in the future. The second quadrant, which occupies the lower-right corner partition – low intensity on printed electronics and high status in the firm networks – is associated with strong technological influence in printed electronics but a weaker focus on the associated technology. Firms in this quadrant are successful in strategically targeting the most important technologies in the industry. These firms have high potential to become technological leaders in the industry as they concentrate more on printed electronics. Firms in the third quadrant, occupying the upper-left corner – high intensity and low status – concentrate their R&D efforts on printed electronics, but have yet to become leaders in the technology network. Although centrality in the patent network does not strictly correspond to the potential market value of a patent, firms that occupy such central positions appear to be technological followers and accumulate related technological knowledge in printed electronics. Positioning in the third dimension can be also interpreted to mean that “their technologies may be at the cutting edge, leading to future innovation opportunities but not yet taken up” (Okamura and Vonortas, 2006). Finally, firms in the fourth quadrant, occupying the lower-left corner, have low levels of both technological intensity and network status. Firms in this quadrant do not
120
Y. Cho et al.
pay great attention to printed electronics technology and thus have low technological leadership. Figure 5
Strategic group map by technological category during 1976 to 1999 (see online version for colours)
During the first phase, from 1976 to 1999 (Figure 5), device-related companies occupied high positions in both closeness centrality and intensity, with Canon and Sharp being two notable exceptions. Meanwhile, electronics-related companies ranked relatively low in terms of intensity. Specifically, companies like HP, Seiko, Epson and Xerox showed relatively high intensity and closeness centrality. From this it may be inferred that companies with device-related technological knowledge fully concentrated their technological capabilities on printed electronics. Additionally, such activities are reflected in patent quantity, as shown by high citation frequency. Particularly, Cabot and Nippon CMK had relatively high technological intensity, suggesting they engaged in technological activities intended to increase their technological capabilities in printed electronics. During the second period, from 2000 to 2012, electronics- and ink-related companies changed their positioning to increase the patent intensity of printed electronic technology (Figure 6). Restated, as technological convergence developed, companies changed their strategic positions by changing their technological intensity in the direction of technology convergence. For example, device-related companies moved in the upper right direction,
Strategy transformation under technological convergence
121
meaning they reinforced technological strategies on printed electronics. Particularly, the closeness centrality of ink-related companies moved toward the high intensity region. This is supported by the rapid increases in nanoparticle patents in the 1990s, which achieved epochal development through combination with micro/nanotechnologies. It can be inferred that such technological progress was based on the dissemination of technological knowledge into other technologies through their active accommodation and absorption. Therefore, in the patent citation network, the movement towards a desired strategic position occurred as key players integrated disparate technologies, especially in the case of electronics and ink technology related companies in printed electronic technology. Additionally, in terms of patent portfolio, the intensity of printed electronics-related patents to total patents of ink and electronics-related companies was heightened, thus concentrating firm technological capabilities. Figure 6
Strategic group map by technological category during 2000 to 2012 (see online version for colours)
Comparison of the first and second phases reveals changes in companies’ strategic position, as follows. First, certain companies moved towards higher centrality or higher intensity, such as Canon, GE and Samsung Electronics. Canon exhibited low close centrality and technological intensity during the first period (1976–1999). However, the second phase saw Canon move to a higher position within the strategic group map. Restated, among the entire networks, Canon grew its centrality as a device business by
122
Y. Cho et al.
increasing its influence on other companies and strengthened its strategic position in printed electronics. Meanwhile, GE moved its position from low centrality to high, although its printed electronics patents decreased in number and intensity. Samsung Electronics intensified its strategic position by increasing its total number of patents. Second, the second phase saw the emergence of numerous new entrants, such as E-Ink, Hitachi, Kovio, LG Chemical, NEC, Samsung Elec-Mechanics/Display, Siemens and Sony. Technologically these firms are heavily focused on electronics, except for a few ink- and device-related firms. Also, these firms are quite evenly distributed along the intensity axis. The focus of these new entrants on the electronics area suggests the emergence of technological convergence issues involving the application of disparate technologies since the 2000s. In this context, the printed electronics industry is attracting more companies to commercialise related technologies, constructing industrial ecosystems of technological convergence with high market potential. Third, we can also find that the overall distribution of companies moved towards the high centrality region, which suggests increased complexity of technological convergence. In other words, convergence made technologies more interdependent. One group to note is those companies involved in ink-related technologies, such as E-Ink, Cabot, Sumitomo Metal and LG Chemical. These companies mostly have high patent intensity on printed electronics, except for Asahi Glass, which suggests they are specialised firms focused on specific components of printed electronics technology, i.e., ink-related technology. That is, unlike other components of printed electronics, ink-related technology has unique characteristics that require companies to specialise in that technology rather than maintaining large technology portfolios and simultaneously developing other aspects of printed electronics technology. The network analysis in the previous section shows an increase in technological inflow, which suggests increased company absorptive capacity and corresponding increased outflow of technology knowledge. Simultaneously, we find that their position has been moved to high centrality position and the technological intensity also increased in general. This result indirectly suggests that firm internal capabilities, rather than technological focus or business type, are most important, which is consistent with previous studies (Cohen and Levinthal, 1989; Freddi, 2009; Harianto and Pennings, 1994).
5
Discussion and conclusions
5.1 Firms’ strategic choices in technological convergence Based on the results, we can categorise firms into three groups. First, firms such as Cabot and E-ink, which are specialised in Ink technology, are core functional leaders that provide core technological solutions related to technology convergence and proactively contribute to it realisation. As mentioned in the previous section, Ink-related firms provided key impetus for the materialisation of the printed electronics industry by developing nano-particle technology and also entered the market early and made strategic choices focused on appropriate technological specialisations. Second, firms specialised in device technology are technology integrators and attempt to exploit market opportunities resulting from emerging technologies. These firms leverage their own competences to establish new technological platforms by integrating other elemental technologies. Device
Strategy transformation under technological convergence
123
technology integrates disparate technological components and eventually completes overall technological convergence, in this case resulting in printed electronics. Therefore, device-related firms such as Canon, Sharp, HP and Seiko Epson are platform providers that aggregate different services and product components in the printed electronics industry. Third, electronics-related firms are application pioneers and lead the application of integrated technology to new products by developing the converged technology into more market-oriented forms. In the printed electronics industry, firms such as Samsung Electronics, 3M and IBM apply and commercialise electronic products and related services. Such corporate activities indispensably require understanding of both technological characteristics and market environment. Based on the strategic positions and trajectories of firms, we can suggest evolutionary patterns of their strategic behaviours related to technological convergence. Figure 7 shows four such patterns for each group of firms. Figure 7
Four quadrants representing corporate strategies and behavioural patterns in the strategic map of technological convergence
First, evolutionary pattern A describes firms that moved from dimension 3 to dimension 4 in the strategic group map. Technology integrators, such as Sharp and Canon and application pioneers, such as GE, followed this trajectory during the second period (2000–2012). From this it can be interpreted that firms following this trajectory maintained a similar level of technological focus on printed electronics technology and their technological leadership increased over time. These firms thus increased their strategic capability during the technological convergence. Second, evolutionary pattern B describes firms that moved from dimension 4 to dimension 1, such as Eastman Kodak and Samsung Electronics. These companies concentrated their technological resources on printed electronics while maintaining their strong technological leadership in patent networks. These firms thus are expected to maintain a lead in related technological development and hence occupy the highly competitive technological frontier in the printed electronics industry. Third, pattern C describes firms that have maintained their initial positioning. Firms that belong to this evolutionary type are located in dimension 1 (device-related firms such
124
Y. Cho et al.
as HP, Seiko Epson and Xerox), dimension 4 (Ricoh, E. I. Dupont, IBM and Toshiba) and dimension 3 (BASF). These firms have maintained their technological intensity and technological status throughout the development of technological convergence and appear to maintain a consistent strategic direction together with their technological development. Finally, pattern D indicates that new entrants are mostly located in dimension 1. During the first phase (1976–1999), dimension 1 was occupied by core functional leaders, such as ink-related firms and technology integrators, such as device-related firms. Many new core functional leaders and application pioneers also occupy dimension 1. These firms are interesting because they became technological leaders immediately after entering the industry as printed electronics-oriented firms. These firms have other technological assets such as electronics and ink technology, but entered the printed electronic industry when nano-technology changed its technological landscape. In other words, they modified their technological capabilities to make them suitable for application to the printed electronics industry. Based on the above corporate evolutionary patterns in the printed electronics industry, we can find some strategic choices related to technological convergence. First, two types of technological strategies can be defined, namely horizontal and vertical innovation strategies. A horizontal innovation strategy involves moving from dimension 2 to 1 or from dimension 3 to 4. During this strategic movement, firms maintain their technological R&D focus, but strategically target important technologies. This enables them to acquire technological leadership with their limited technological development assets. In the case of vertical innovation strategy, firms move from dimension 3 to 2 or from 4 to 1. Restated, firms can increase their technological concentration on specific industry targeting, although their technological leadership does not change accordingly. However, this innovation strategy allows firms to accumulate technological knowledge and keep up with frontier technological assets as they reach a certain level. This vertical innovation strategy can be appropriate for late-comers in an industry when they lack leadership capability. Based on these new strategic innovation concepts, two main innovation trajectories can be described for firms in an industry with technological convergence. First, for a firm considering entering this emerging industry, an appropriate strategic movement can be a ‘vertical-to-horizontal strategy’, that involves moving from dimension 3 to 2 and finally from 2 to 1. As firms follow this trajectory, they must first accumulate technological assets (in order to move from dimension 3 to 2 through horizontal innovation), before they introduce a leading technology to their industry (in order to move from dimension 2 to 1 through vertical innovation). This trajectory can become the most natural path for a new firm that is entering an industry with technology convergence when that firm lacks related technological capability. Second, a more appealing strategy is to move from dimension 3 to 4 and then to dimension 1, a ‘horizontal-to-vertical strategy’. This strategy is demonstrated by evolutionary pattern A, shown above, in which firms increased their technological leadership without increasing their technological intensity on printed electronics. In this case, firms require high strategic capability to select and develop technologies with high technological potential. From this perspective, it would be valuable and interesting to examine firms such as Sharp and Canon and GE, which exhibit evolutionary pattern A, to obtain important strategic insights into the strategic technology selection processes. Overall, the strategic map of technological convergence gives valuable and important insights into how to understand firms’ strategic behaviours and opportunities in the face of technological convergence.
Strategy transformation under technological convergence
125
5.2 Conclusions Technological convergence is crucial to realising technological breakthroughs and industrial development and ultimately significantly affects industry evolution and severely disrupts firm capacities (Hacklin et al., 2013). This study thus examines companies that have played a core role in technological convergence and focuses particularly on printed electronic technology. Indeed, convergence can be understood as an evolutionary process of technological knowledge spillover that can eventually lead to the merging of heterogeneous industries (Hacklin et al., 2010). By reinterpreting the patent network structure from a business network perspective, we found that the technological categories to which companies belong decide their roles in technological convergence. Particularly, we found that companies that own control-related (device) and application-related (electronics) technologies act as key players in technology commercialisation through the integration of disparate technologies. Ink-related firms that own the core-functional technologies for manufacturing the conductors, semi-conductors and insulators from which circuits are built are also key players. Based on patent citation networks, key players integrated disparate technologies and this was especially so for device- and electronics-related firms. Additionally, those key players have increased both the technological intensity of printed electronics and their own influence on other companies. Particularly, we attempted to find different groups of companies that showed unique strategic behaviours in technological convergence. To this end, this study constructed a framework that formalises and generalises different strategic positioning groups of firms and their evolutionary patterns in technological convergence. This study makes three main contributions: first, it expanded the network analysis by transforming patent citation networks into firm networks and suggested technological convergence as a new perspective on firm technology strategic positioning. Correspondingly, we could understand the evolution of the strategic positions and movements of companies centrally involved in technological convergence in relation to printed electronics. Second, the analysis of the structure of the network among companies from the perspective of technological convergence allows us to engage in reverse inference regarding company technological strategies. The patent-centric network methodologies and portfolio analysis techniques using relevant indexes conducted in this study can be applied to other research to understand leadership changes in different industrial and technological areas, as well as important phenomenon like technological convergence. Third, owing to the technological disequilibrium observed in association with technological convergence, that convergence occurs at a level below the maximum capacity of each component technology. Therefore, knowing the role of each technological field and the strategic behaviours of firms involved in technological convergence is vital to establish corporate technology strategies. Additionally, this knowledge enables policy makers to determine the industry policy based on consideration of the pace of technological development. In this regard, it is important to investigate the technologies and players central to the technological convergence process. This characteristic can be observed in printed electronics technology and we identified core technologies and players that lead technological convergence. The results of this study reveal important aspects of the recent convergence occurring in many technological areas. Restated, companies involved in the control or application of disparate technologies have played a central role in technological convergence and have focused their technological innovation strategies on printed electronics. Also, the
126
Y. Cho et al.
generalisation and formalisation of firms’ strategic choices and behavioural patterns by constructing strategy quadrant provided interesting and valuable implications for strategy research. More specifically, we found idiosyncratic patterns of firm strategic behaviours in each dimension associated with issues of industrial leadership and regime change. On a business level, this suggests important strategic insights into how to build a technology strategic portfolio during technological convergence. Additionally, the fact that the position of the core technology changes during technological convergence suggests the need to approach R&D strategy and policy using a dynamic perspective that is responsive to the development phase of technological convergence. Restated, firm strategy and relevant industrial policy on technological convergence should be developed using different perspectives to those associated with more homogeneous technology development. Future research should examine the causality of the effect of the convergence activities of companies on business performance. Additionally, the relationship between R&D investment and patent influence from the perspective of technological convergence is another important issue that merits investigation. Moreover, technological competition considering the dynamic evolution of patents and R&D investment among competing firms would be an interesting area to examine in an environment characterised by rapidly changing management and technological convergence. This study suggests an initial view and approach to interpreting and understanding the emerging phenomenon of technological convergence that can help answer both important questions regarding technology strategy and fundamental questions about patterns of technological convergence.
Acknowledgements This work was supported by National Research foundation (NRF) of Korea funded by Korean Government (NRF-2012-S1A3A-2033860).
References Ávila-Robinson, A. and Miyazaki, K. (2013) ‘Dynamics of scientific knowledge bases as proxies for discerning technological emergence — the case of MEMS/NEMS technologies’, Technological Forecasting and Social Change, Vol. 80, No. 6, pp.1071–1084. Bekkers, R. and Martinelli, A. (2012) ‘Knowledge positions in high-tech markets: trajectories, standards, strategies and true innovators’, Technological Forecasting and Social Change, Vol. 79, No. 7, pp.1192–1216. Belussi, F., Baglieri, D. and Orsi, L. (2012) ‘When do alliance partners become attractive targets?’, Paper presented at 2012 DRUID Academy Conference, 19–21 June, Copenhagen, Denmark. Chandy, R.K. and Tellis, G.J. (1998) ‘Organizing for radical product innovation: the overlooked role of willingness to cannibalize’, Journal of Marketing Research, November, Vol. 35, No. 4, pp.474–487. Chang, S.B., Lai, K.K. and Chang, S.M. (2009) ‘Exploring technology diffusion and classification of business methods: using the patent citation network’, Technological Forecasting and Social Change, Vol. 76, No. 1, pp.107–117. Cho, T.S. and Shih, H.Y. (2011) ‘Patent citation network analysis of core and emerging technologies in Taiwan: 1997–2008’, Scientometrics, Vol. 89, No. 3, pp.795–811.
Strategy transformation under technological convergence
127
Cho, Y., Lee, S. and Kim, W. (2012) ‘The role of funding source for commercializing university patents: network analysis on technology – industry linkage patterns’, IEEE IEEM 2012: Proceedings of the IEEE International Conference on Industrial Engineering and Engineering Management Conference, IEEE, pp.727–731. Choi, C.W., Shin, J.S., Yoon, B.G., Lee, W.Y. and Park, Y.T. (2004) ‘On the linkage between industries and technologies: patent citation analysis’, Engineering Management Conference, 2004: Proceedings of the 2004 IEEE International, IEEE, Vol. 2, pp.576–578. Cohen, W.M. and Levinthal, D.A. (1989) ‘Innovation and learning: the two faces of R&D’, The Economic Journal, Vol. 99, No. 397, pp.569–596. Curran, C.S. and Leker, J. (2011) ‘Patent indicators for monitoring convergence-examples from NFF and ICT’, Technological Forecasting and Social Change, Vol. 78, No. 2, pp.256–273. Curran, C.S., Bröring, S. and Leker, J. (2010) ‘Anticipating converging industries using publicly available data’, Technological Forecasting and Social Change, Vol. 77, No. 3, pp.385–395. Das, R. and Harrop, P. (2012) Printed, Organic & Flexible Electronics Forecasts, Players & Opportunities 2012–2022, IDTechEX, Cambridge. Ernst, H. (2003) ‘Patent information for strategic technology management’, World Patent Information, Vol. 25, No. 3, pp.233–242. Ernst, H. and Omland, N. (2011) ‘The patent asset index – a new approach to benchmark patent portfolios’, World Patent Information, Vol. 33, No. 1, pp.34–41. European Commission (2010) Focus Report 2010: Printed Electronics – Observatory NANO, Focus Report, European Commission [online] http://www.observatorynano.eu/project/ filesystem/files/ObservatoryNanoFocusReport_PrintedElectronics.pdf (accessed April 2010). Fontana, R., Nuvolari, A. and Verspagen, B. (2009) ‘Mapping technological trajectories as patent citation networks. An application to data communication standards’, Economics of Innovation and New Technology, Vol. 18, No. 4, pp.311–336. Freddi, D. (2009) ‘The integration of old and new technological paradigms in low-and mediumtech sectors: the case of mechatronics’, Research Policy, Vol. 38, No. 3, pp.548–558. Gambardella, A. and Torrisi, S. (1998) ‘Does technological convergence imply convergence in markets? Evidence from the electronics industry’, Research Policy, Vol. 27, No. 5, pp.445–463. Gay, B. and Dousset, B. (2005) ‘Innovation and network structural dynamics: study of the alliance network of a major sector of the biotechnology industry’, Research Policy, Vol. 34, No. 10, pp.1457–1475. Gelsing, L. (2010) ‘Innovation and the development of industrial networks’, in Lundvall, B.A. (Eds.): National Systems of Innovation: Toward a Theory of Innovation and Interactive Learning, Anthem Press, London. Griliches, Z. (1990) ‘Patent statistics as economic indicators: a survey’, Journal of Economic Literature, Vol. 28, No. 4, pp.1661–1707. Hacklin, F. (2008) Management of Convergence in Innovation: Strategies and Capabilities for Value Creation beyond Blurring Industry Boundaries: Contributions to Management Science, Springer, Berlin. Hacklin, F., Battistini, B. and Krogh, G. (2013) ‘Strategic choices in converging industries’, MIT Sloan Management Review, Vol. 55, No. 1, pp.65–73. Hacklin, F., Marxt, C. and Fahrni, F. (2009) ‘Coevolutionary cycles of convergence: an extrapolaration from the ICT industry’, Technological Forecasting and Social Change, Vol. 76, No. 6, pp.723–73. Hacklin, F., Marxt, C. and Fahrni, F. (2010) ‘An evolutionary perspective on convergence: inducing a stage model of inter-industry innovation’, International Journal of Technology Management, Vol. 49, No. 1, pp.220–249. Harianto, F. and Pennings, J.M. (1994) ‘Technological convergence and scope of organizational innovation’, Research Policy, Vol. 23, No. 3, pp.293–304.
128
Y. Cho et al.
Henderson, R. and Clark, K.B. (1990) ‘Architectural innovation: the reconfiguration of existing product technologies and the failure of established firms’, Administrative Science Quarterly, Vol. 35, No. 1, pp.9–30. Henderson, R., Jaffe, A.B. and Trajtenberg, M. (1998) ‘Universities as a source of commercial technology: a detailed analysis of university patenting, 1965–1988’, Review of Economics and Statistics, Vol. 80, No. 1, pp.119–127. Jaffe, A.B. and Trajtenberg, M. (2002) Patents, Citations, and Innovations: A Window on the Knowledge Economy, MIT Press, Cambridge. Karvonen, M. and Kässi, T. (2013) ‘Patent citations as a tool for analysing the early stages of convergence’, Technological Forecasting and Social Change, Vol. 80, No. 6, pp.1094–1107. Kim, E., Cho, Y. and Kim, W. (2014) ‘Dynamic patterns of technological convergence in printed electronics technologies: patent citation network’, Scientometrics, Vol. 98, No. 2, pp.975–998. Kim, W. and Kim, M. (2014) Reference Quality-Based Competitive Market Structure for Innovation Driven Markets, SSRN, doi:10.1016/j.ijresmar.2014.10.003 [online] http://ssrn.com/abstract =2519039. Kim, W. and Lee, J-D. (2009) ‘Measuring the role of technology-push and demand-pull in the dynamic development of the semiconductor industry: the case of the global DRAM market’, Journal of Applied Economics, Vol. 12, No. 1, pp.83–108. Kodama, F. (1995). Emerging Patterns of Innovation: Sources of Japan’s Technological Edge, Harvard Business Press, Boston. Kodama, M. (2009) Innovation Networks in Knowledge-Based Firms, Edward Elgar, Massachusetts. Kunnari, E., Valkama, J., Keskinen, M. and Mansikkamäki, P. (2009) ‘Environmental evaluation of new technology: printed electronics case study’, Journal of Cleaner Production, Vol. 17, No. 9, pp.791–799. Lee, H., Kim, C., Cho, H. and Park, Y. (2009) ‘An ANP-based technology network for identification of core technologies: a case of telecommunication technologies’, Expert Systems with Applications, Vol. 36, No. 1, pp.894–908. Leenen, M.A., Arning, V., Thiem, H., Steiger, J. and Anselmann, R. (2009) ‘Printable electronics: flexibility for the future’, Physica Status Solidi (a), Vol. 206, No. 4, pp.588–597. Lei, D.T. (2000) ‘Industry evolution and competence development: the imperatives of technological convergence’, International Journal of Technology Management, Vol. 19, Nos. 7/8, pp.699–738. No, H. and Park, Y. (2010) ‘Trajectory patterns of technology fusion: trend analysis and taxonomical grouping in nanobiotechnology’, Technological Forecasting and Social Change, Vol. 77, No. 1, pp.63–75. Nyström, A-G. (2008) Understanding Change Processes in Business Networks: A Study of Convergence in Finnish Telecommunications 1985–2005, ÅBO Akademi University Press, Finland. Oh, C., Cho, Y. and Kim, W. (2015) ‘The effect of a firm’s strategic innovation decisions on its market performance’, Technology Analysis & Strategic Management, Vol. 27, No. 1, pp.39–53. Okamura, K. and Vonortas, N.S. (2006) ‘European alliance and knowledge networks’, Technology Analysis & Strategic Management, Vol. 18, No. 5, pp.535–560. Park, Y., Hong, P. and Moon, G. (2012) ‘Implementation of product strategy with differentiated standards’, International Journal of Technology Management, Vol. 57, No. 1, pp.166–184. Park, Y., Yoon, B. and Lee, S. (2005) ‘The idiosyncrasy and dynamism of technological innovation across industries: patent citation analysis’, Technology in Society, Vol. 27, No. 4, pp.471–485. Perelaer, J., Smith, P.J., Mager, D., Soltman, D., Volkman, S.K., Subramanian, V., Korvink, J.G. and Schubert, U.S. (2010) ‘Printed electronics: the challenges involved in printing devices, interconnects, and contacts based on inorganic materials’, Journal of Materials Chemistry, Vol. 20, No. 39, pp.8446–8453.
Strategy transformation under technological convergence
129
Phelps, C.C. (2010) ‘A longitudinal study of the influence of alliance network structure and composition on firm exploratory innovation’, Academy of Management Journal, Vol. 53, No. 4, pp.890–913. Podolny, J.M., Stuart, T.E. and Hannan, M.T. (1996) ‘Networks, knowledge, and niches: competition in the worldwide semiconductor industry, 1984–1991’, American Journal of Sociology, Vol. 102, No. 3, pp.659–689. Rosenberg, N. (1982) Inside the Black Box: Technology and Economics, Cambridge University Press. Schilling, M.A. and Phelps, C.C. (2007) ‘Interfirm collaboration networks: the impact of largescale network structure on firm innovation’, Management Science, Vol. 53, No. 7, pp.1113–1126. Scott, J. (2003) Social Network Analysis: A Handbook, 2nd ed., SAGE Publications Ltd., London. Shin, J. and Park, Y. (2007) ‘Building the national ICT frontier: the case of Korea’, Information Economics and Policy, Vol. 19, No. 2, pp.249–277. Shin, J. and Park, Y. (2010) ‘Evolutionary optimization of a technological knowledge network’, Technovation, Vol. 30, No. 11, pp.612–626. Trajtenberg, M., Henderson, R. and Jaffe, A.B. (1997) ‘University versus corporate patents: a window on the basicness of invention’, Economics of Innovation and New Technology, Vol. 5, No. 1, pp.19–50. Trajtenberg, M., Henderson, R. and Jaffe, A.B. (2002) ‘University versus corporate patents: a window on the basicness of invention’, in Jaffe, A.B. and Trajtenberg, M. (Eds.): Patents, Citations, and Innovations: A Window on the Knowledge Economy, MIT Press, Cambridge. Verspagen, B. (2007) ‘Mapping technological trajectories as patent citation networks: a study on the history of fuel cell research’, Advances in Complex Systems, Vol. 10, No. 1, pp.93–115. von Wartburg, I., Teichert, T. and Rost, K. (2005) ‘Inventive progress measured by multi-stage patent citation analysis’, Research Policy, Vol. 34, No. 10, pp.1591–1607. Wasserman, S. and Faust, K. (2006) Social Network Analysis: Methods and Applications, 14th ed., Cambridge University Press, New York. Yoffie, D.B. (1997) Competing in the Age of Digital Convergence, Harvard Business Press.
Notes 1
2
3
Hacklin (2008) and Hacklin et al. (2009) argued that, “recent scientific developments around nanotechnologies show that nanoscale science will act as a similar catalyst for entailing convergence between technologies, and for action as fundamental platform technology spanning a wide range of existing scientific and techno-scientific fields”. According to IDTechEX, a market survey institution, the printed electronics market reached US$4.6 billion in 2012 and is expected to reach US$10 billion in 2014 and US$160 billion in 2025, at which point it will be half the size of the current semiconductor market and more than 20 times its current size (Das and Harrop, 2012). Pajek 64 3.09 (2013 version) was used for the analysis.
130
Y. Cho et al.
Appendix Matrix of firms engaged in the printed electronics industry and their activities by technological characteristics and industrial classification codes Technological focus Substrate
Ink
Device
Firm name
Industrial classification
E. I. Du Pont de Nemours and Company
Agricultural chemical manufacturing
Industrial Technology Research Institute
Instruments and related products manufacturing for measuring, displaying and controlling industrial process variables
BASF Aktiengesellschaft
Plastics and resins
Cabot Corporation
Carbon black and specialty chemicals manufacturing
E Ink Corporation
Computer display and projector manufacturing
LG Chem, Ltd.
Automobile parts manufacturing
Sumitomo Metal Mining Co., Ltd.
Printing machinery and equipment manufacturing
Fujifilm Corporation
Office machines, machinery manufacturing
Westvaco Corporation
Pulp and paper mills
Asahi Glass Company, Ltd.
Plastic and rubber product manufacturing
Hewlett-Packard Company
Electronic computer manufacturing
Toppan Printing Co., Ltd.
Electrical products manufacturing
Seiko Epson Corporation
Printing and imaging equipment manufacturing
Canon Kabushiki Kaisha
Printing and imaging equipment manufacturing
Eastman Kodak Company
Photographic equipment and supplies
Sharp Kabushiki Kaisha
Photographic equipment and supplies
Xerox Corporation
Information technology services
Konica Minolta Holdings, Inc.
Printing and imaging equipment manufacturing
Dai Nippon Printing Co., Ltd.
Commercial lending
Fuji Xerox Co., Ltd.
Legal services
Ricoh Company, Ltd.
Semiconductors and related devices
Sony Corporation
Semiconductor manufacturing
Robert Bosch GmbH
Plastics materials and resins
Brother Kogyo Kabushiki Kaisha
Copper rolling, drawing, extruding and alloying
Strategy transformation under technological convergence
131
Matrix of firms engaged in the printed electronics industry and their activities by technological characteristics and industrial classification codes (continued) Technological focus Electronics
Firm name
Industrial classification
Samsung Mobile Display Co., Ltd.
Pharmaceutical manufacturing
NEC Corporation
Computer hardware manufacturing
Hitachi, Ltd.
Computer networking equipment manufacturing
Samsung Electro-Mechanics Co., Ltd.
Computer peripheral equipment manufacturing
Nippon CMK Corp.
Computers, peripherals and software
International Business Machines Corporation
Computer integrated systems design
Samsung Electronics Co., Ltd.
Semiconductors and related devices
Mitsubishi Denki Kabushiki Kaisha Satellite and broadcast network equipment manufacturing Alps Electric Co., Ltd.
Electronic component manufacturing
Motorola, Inc.
Electrical apparatus and equipment
Nanosolar, Inc.
Electronic parts and equipment
Hitachi Displays, Ltd.
Electronic parts and equipment
General Electric Company
Commercial printing, lithographic manufacturing
Electronics for Imaging, Inc.
Printing and imaging equipment manufacturing
3M Innovative Properties Company
Printing and imaging equipment manufacturing
Cambridge Display Technology Ltd.
General and industrial loan institutions
Siemens Aktiengesellschaft
Scientific research and development services
Kovio, Inc.
Semiconductors and related devices
Semiconductor Energy Laboratory Co., Ltd.
Integrated circuits, semiconductor networks