Scientometrics (2014) 98:975–998 DOI 10.1007/s11192-013-1104-7
Dynamic patterns of technological convergence in printed electronics technologies: patent citation network Euiseok Kim • Yongrae Cho • Wonjoon Kim
Received: 18 March 2013 / Published online: 13 August 2013 Ó Akade´miai Kiado´, Budapest, Hungary 2013
Abstract The importance of the convergent approach to technology development has increased recently. Therefore, understanding the characteristics of technology convergence, which refers to the combination of two or more technological elements in order to create a new system with new functions, is an important issue not only for researchers in technology development, but also for company directors for their successful management of product competitiveness. Therefore, in order to investigate the patterns and the mechanism of technological convergence, we examine the printed electronics technology which has typical characteristics of technology convergence. Based on the printed electronicsrelated patents registered between 1976 and 2012, we perform network analysis of the technology components in order to identify key technologies which played a central role among the groups of convergence technologies and to examine their dynamic role corresponding to the development of technology convergence. The results show that control technologies which control the role of other technologies over the technology convergence process play significant role. The centrality value is highest in the case of control technology, and devices related technologies have the largest number of patents quantitatively, thereby confirming the results. In addition, the trajectory analysis of the centrality value reveals a co-evolution pattern in technology convergence. Keywords Network analysis Printed electronics Patent citation Technological convergence Mathematical Subject Classification (2010)
90B15
JEL Classification D85 O32 O33
E. Kim Y. Cho W. Kim (&) Graduate School of Innovation and Technology Management, KAIST, 335 Gwahangno, Yuseong-gu, Daejeon 305-701, Republic of Korea e-mail:
[email protected] Y. Cho e-mail:
[email protected]
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Introduction Accelerated innovation dynamics of recent decades have led to rapid changes in products in terms of complexity, miniaturization, digitalization, and changes in architecture (OECD 1993). These changes brought about the emerging phenomenon of technological convergence or fusion, creation of convergent products, resulting in inevitable structural transformation of the industries (No and Park 2010). In the early stages of this development, this phenomenon was described as ‘‘technological fusion.’’ (Kodama 1992; Kodama 1995) Research in this avenue investigated the effects of technological fusion in the mechatronics. Technological fusion, which refers to breakthroughs in existing technologies, is academically distinguished from technology innovation (Kodama 1995). Later, technological convergence was broadly defined as a form of technology innovation using more than two core technologies to create a new function, which the incumbent technologies did not possess (Bores et al. 2003; Islam and Miyazaki 2009). Also, technological convergence describes the current status of technological evolution. Consequently, our definition of the technological convergence is along the line with Kodama (1995)’s technological fusion that leads to breakthrough functions by combining at least two or more existing technologies into hybrid technologies. However, despite the increasing interest in technology convergence which requires inter-disciplinary approach in the development of technology, relatively little research has been done investigating the patterns and mechanism of technology convergence resulting in insufficient information on various facets of the technological convergence phenomenon. Some researchers (Hullmann and Meyer 2003; Miyazaki and Islam 2007; Takeda et al. 2009) analyzed some aspects of technological convergence in nanotechnology and biotechnology using a bibliometric methodology. Most of those studies utilized the number of journal publications or patents to determine the degree to which technologies in the main category contributed to technology convergence. Although they provided valuable information (e.g., identification of the core fusion technologies in nanotechnology/biotechnology and the countries/organizations that played a critical role in fusion technology), the characteristics of the technologies that played an important function in the technological convergence has not been well discussed. There are a number of reasons for these limitations. First, most of these studies concentrated on macro-level analysis of technology convergence in a wide range of technological areas, such as nanotechnology and biotechnology. Second, classification criteria for core technologies applied in these studies were mainly based on academic disciplines. Thus, the results could not explain the actual role and characteristics of technology convergence with the perspective of technology. To overcome the limitations of previous studies and to understand technology convergence more fundamentally, we examine the case of printed electronics technology using network analysis and identify the dynamic evolution of the relationship among the different component technologies over the convergence development. More specifically, we investigate how core technologies in printed electronics technology have evolved over time with different network structure and which core technologies have played a key role in the convergence phenomenon over the different phases of technological development. Here, we choose the printed electronics to examine the evolutionary characteristics of fusion technology. The printed electronics is a breakthrough technology in the area of the production of electronic circuits and semiconductors and uses electronic ink with electrical properties in patterning electronic circuits using printing process instead of traditional photolithography technology. The biggest difference between printed electronics and traditional electronics manufacturing is that the former uses an additive process and the latter
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employs a subtractive process in the traditional lithographic production of electronic circuits. The use of the additive process in printed electronics means it has the advantage of reducing the complexity of the processes, as well as manufacturing costs, compared to the traditional process. Another advantage of printed electronics is that it can be applied to a flexible substrate. Furthermore, it is more environmentally friendly compared to the traditional method (Kunnari et al. 2009; Leenen et al. 2009). Printed electronics were selected in this study because of the following reasons: First, printed electronics technology is a good example of convergence between a traditional printing technology and an electronic technology. More specifically, these two disparate technologies had different functions, different industry fields and different markets before the emergence of printed electronics technology (Aistrup 2009). In this context, printed electronics have the representativeness in that this technology can reveal the technological evolutions and fundamental mechanisms of convergence technologies. The case also can be generalized to other technology convergence cases where existing and new technologies are converged. Second, the component technologies can be easily differentiated and identified in printed electronics according to their characteristics and features, which allow us to track and investigate the development of convergence more easily. Third, printed electronics is expected to cover more various industries in the future. Its social impact may also increase over time since the electronics technology is expected to significantly supplant the lithography process (European Commission 2010). For example, BIS (Department for Business Innovation & Skills) of UK government forecasted that the value of the printed electronics market will rise from $2 billion today to $120 billion in 2020 (Mandelson 2009). The printed electronics have generally been classified into four core technologies in most key classifications—device, ink, substrate, and circuit. Additionally, control technology, which adjusts the integrated relationship among those four core technologies based on the aforementioned characteristics of printed electronics is considered (Harrop 2012; Igbenehi and Das 2012). Here, the device technology relates to printing machines or to related parts, whereas the ink technology relates to production technology regarding conductors, semiconductors, or insulator ink. The substrate technology relates to plastic substrates such as polyethylene terephthalate (PET) and polyethylene naphthalate (PEN), while the circuit technology pertains to the configuration of the circuits, considering the characteristics of the printing method. Finally, the control technology relates to controlling the physical properties of the core technologies involved in convergence (Perelaer et al. 2010; Chang et al. 2012). This research reclassifies the element technologies in printed electronics according to the technological characteristics as follows: Four core technologies which directly engage in the component technologies and one additional general technology (i.e., control technology) which converges the aforementioned four core technologies. In order to understand the technological convergence phenomenon, it is an important issue to study not only the core technologies of printed electronics but also the development patterns of the technologies that connect, control and integrate the core technologies with disparate technologies. In this perspective, patents are useful information sources to understand the patterns of convergence developments by identifying emerging technologies and core technologies (Cho and Shih 2011).1 Previously, the most common method of 1
Patents and patent statistics have long been employed as technological indicators and as representative proxies for technology analysis (Grilliches 1990; Trajtenberg et al. 1997). Patent management contributes to fundamental functions in technology management such as information protection and economic performance (Ernst 2003).
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patent analysis was to simply count patents and to compare how many patents had been assigned to each entity (Wartburg et al. 2005). However, the current study goes further beyond simple identification of trends in patents statistics. We analyze the evolution of its network structure, the structure of technology knowledge relationship (patents) in printed electronics related technologies, by utilizing bibliometric information such as patent citations. This approach shows larger picture of the overall knowledge structure and the internal/external linkages of the technologies, thereby shedding light on the patterns of technology convergence. Therefore, we identify important technologies by examining citation links among the different patents in a technology network using patent codes [e.g., those used by the United States Patent and Trademark Office (USPTO) or the International Patent Classification (IPC)] to analyze and to predict core technologies or promising technologies (Cho and Shih 2011; Gay and Dousset 2005; Lee et al. 2009; No and Park 2010; Shin and Park 2010). These studies revealed that network analysis can be effectively employed to measure technological knowledge flows among actors in a patent citationbased network (Lee et al. 2009; Park et al. 2005). Other literature on innovation also addressed challenges related to knowledge flows within a patent citation network by defining technological trajectories from the perspectives of industry (Fontana et al. 2009; Verspagen 2007). The novelty of this paper is threefold: First, it identifies technology convergence patterns and their underlying mechanisms, consequently providing empirical evidence and ground for further theoretical development regarding the phenomenon of technology convergence. Second, it explicitly verifies the evolutionary patterns of technology convergence by linking the knowledge level to the artifact level via citation networks. Patents are particularly suitable for these tasks because they provide detailed information on the invention and on its background (Martinelli 2012). Third, it validates an increasingly applied quantitative method used to analyze technological changes by factoring out the engineering heuristics of the patents in the trajectories of the technological convergence.
Methodology Data This study attempted to identify the core technologies at particular time periods and the technologies that played a central role in convergence among different core technologies with regard to printed electronics as well as the related technologies. Therefore, we collected data on patents related to printed electronics that were registered by USPTO from 1976 to 2012 including patent bibliographic and citation information. We analyzed bibliographic information pertaining to the patents including the main technological terms used and a combination or a composite of individual words in printed electronics-related abstracts. The development of search words for the patents was carried out collaboratively with experts studying printed electronics technology. Following the keywords extraction method, we extracted 6,439 patents initially and finally selected 2,689 patents by eliminating bibliographic information not related to printed electronics. Citation information was then extracted for each patent, yielding a total of 95,036 cases of citation information from the patents.2 In total, 75,443 citations were extracted from the 2,689 bibliographic references. 2
If the patents cited were not registered in the USPTO but registered in other overseas offices, they were removed from the analysis.
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Two-step process was adopted to establish technological characteristic/periodic standard prior to conducting network analysis. First, the citation information data were reclassified according to the characteristics of technology, and the IPC listing of each patent was utilized to classify the extracted patent information into the core technologies of printed electronics. The IPC system divides patents into a section, class, subclass, main group, and subgroup. The patents used in this study were classified into 51 main groups according to the IPC classification. The main groups belong to the five core technologies of printed electronics mentioned earlier (see Table 1), taking the definitions of the main groups according to 8th edition of IPC and the attributes of the patents in each group into account. The topological clustering approach in the citation network of technologies also shows that taxonomies according to application technologies as well as fundamental technologies have statistically meaningful results (Takeda et al. 2009). In Appendix 2, the IPC definitions of the main groups are provided and representative patents of those in the main groups are listed to show which type of patents were included in each core technology. Second, the patent information was reorganized according to the time periods, taking into consideration the technological development and the characteristics of the fusion at each time period into consideration. The citation information extracted earlier was divided into five periods in compliance with the classification of the core printed electronics technologies. The periodical classification process in this study follows two steps. First, we divided the whole sample based on the year of 2000 because there was a technological breakthrough in printed electronics for technological convergence. Specifically, ink-related technology went through a radical innovation enhancing conductivity of conductive ink as nanoparticle was introduced (Iijima 1991; Ridley et al. 1999; Garnier et al. 1994). Accordingly, year 2000 is considered as an important periodical basis for the first classification of the time periods (1976–1999 and 2000–present). Second, a total of three periods (1976–1989, 1990–1994 and 1995–1999; two periods of 2000–2005 and 2006–present) were used to observe technological evolutions and changes in network structure. 5 or 10 year intervals are generally used in many previous studies on network analysis (Bekkers and Martinelli 2012; Grupp 1990; No and Park 2010; Lei et al. 2013; Porter and Rafols 2009). As a result, 5-year interval was selected for network analysis: 1976–1989, 1990–1994, 1995–1999, 2000–2005, 2006–present. Then, patent information and relevant citation information for each period and core technologies were reconfigured for an empirical study. Table 1 Element technologies and IPC main group codes of printed electronics technology Element technology
IPC main group
Device
B05C017, B21D053, B41C001, B41F005, B41F007, B41F013, B41F015, B41F031, B41F035, B41J002, B41J003, B41J023, B41J029, B41L013, B41M001, G01D018, G01N027, G03C001, G03C005, G03F007, G03G005, G03G009, G03G013, G03G015, H05B001, H05B003
Ink
C08F002, C08K003, C09D011, C09K011, H01B001
Substrate
B32B003, B32B009, B32B027, B32B031, B41M005
Circuit
H01K003, H01L029, H01R012, H05K001
Control
B05D001, B05D003, B05D005, B44C001, C25D001, C25D005, G01D015, H01L021, H01R009, H04N001, H05K003
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Indicators for network analysis Network analysis is a technique derived from graph theory and originally visualizes various aspects of a network by analyzing the relationship between nodes quantitatively. However, it can quantitatively determine influences on the relationships between actors and the extent of these influences using network indexes. The interactive characteristics between nodes, which are represented visually, can provide a variety of information via quantitative indexes. In the current network analysis, the individual patents are represented by actors or nodes, and patent citations are denoted as knowledge flows, with edges referring to interactions among the nodes (Gelsing 1992; Jaffe et al. 2005; Lee et al. 2009; Martinelli 2012). In addition, citations provide good evidence on links between innovations and their technological ‘‘antecedents’’ and ‘‘descendants’’ (Trajtenberg et al. 1997). For example, backward citation is used to measure the inflow knowledge from other technologies, and forward citation is used to measure the inventive quality in terms of technological and/or economic values (Jaffe et al. 2005; Henderson et al. 1998). These unique linking properties of citations provide vital information when studying technology fusion, which is greatly influenced by relationships between other technologies (No and Park 2010). Among various indices of network, centrality is a typical index used in network analysis. It is subdivided into degree centrality, closeness centrality, and betweenness centrality (Scott 2003; Wasserman and Faust 2006). In the current study, these three measures were used to represent the impacts on the relationship with the other nodes within the network and to represent their intermediary roles in this relationship. The degree or the extent of the connection between a single node and the other nodes implies that related technological information flows exist. In this respect, degree centrality and closeness centrality are widely used measures in the network graph theory. The former measures direct ties only as a role of local centrality, whereas the latter takes into account indirect ties and thereby allows the impacts and potential capabilities of the technology to be determined. Closeness (global) centrality represents indirect, as well as direct, linkages in network theory (Scott 2003). Therefore, we utilized closeness centrality to help examine the global centrality of patents in technological knowledge networks. 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: " #1 n X dij ; Ci ¼ j¼1
where the sum is the total distance that i is from all the other actors. The closeness centrality is the inverse of the average shortest path between a node and all the other nodes in the network. Thus, high closeness centrality values depict technologies with a strong influence on other technologies (Robinson and Miyazaki 2013). In the case of Betweenness centrality, it is an indicator of the extent of a node’s role as brokerage. It gauges a node’s capabilities to control communication within the network. In terms of network theory, this value indicates the ‘‘intermediary’’ role and thus is a central component of the network (Scott 2003). Thus, betweenness centrality is considered a measure for determining the convergence of technologies, research coordination, and arbitration capabilities (Lee et al. 2012). When gjk is the number of the shortest paths existing between two certain nodes (j, k), and gjk (i), and the number of stops at i is a point
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existing between the points j and k, the node betweenness centrality of node i is the sum of the estimated probabilities for all the pairs of actors, not including the ith actor " # X gjk ðiÞ ; Ci ¼ gjk j\k where i is distinct from j and k. Therefore, this index counts how ‘‘between’’ each of the actors is and sums the probabilities (Wasserman and Faust 2006). The betweenness centrality depicts the extent to which a node lies on the shortest path between the pairs of nodes in the network. This centrality value determines the locational quality of the technology. Usually, those with high betweenness centrality tend to be located closer to the center of the network (Robinson and Miyazaki 2013). In sum, closeness centrality was analyzed in relation to technological impacts, and betweenness centrality was analyzed in relation to the technological intermediary role at different time points. By adopting this quantitative approach and using a network-centric perspective, the fusion of the core technologies over time was identified, in addition to unique and idiosyncratic changing patterns in the core technologies over time.
Results Descriptive statistical analyses In the 51 main groups in the IPC patent classification, of the 2,689 patents, the largest portion was devices comprising of 56.64 % (1,523), and then 24.84 % (668) for control technology, followed by 8.55 % (230) for ink, 5.21 % (140) for circuits, and 4.76 % (128) for substrates. Among the device technology group, there were 898 (33.4 %) patents for B41J-002 (typewriters or selective printing mechanisms characterized by the printing or marking process for which they were designed), the largest main group compared to the total number of patents. On the other hand, there were 195 control technology patents (IPC code H01L-02; processes or apparatus specially adapted for the manufacture or treatment of semiconductor or solid state devices or of parts thereof), 99 (3.68 %) ink technology patents (IPC code C09D-011) followed by 40 (1.49 %) substrate technology patents (IPC code B32B-003; layered products essentially comprising a layer with external or internal discontinuities or unevennesses or a layer of nonplanar form) and 72 (2.68 %) circuit technology patents (IPC code H05K-001; printed circuits). Table 2 shows the high ranking of the patent cases per IPC main group code for each core technology. Figure 1 shows the changes in the number of patents per element technology from 1976 to 2012. Overall, the numbers of patents in all areas related to printed electronics technology increased steadily. In particular, there was a significant change in the total number of patents since 1990s. The increase can be explained by the rapid progress in the development of nanotechnology in the 1990s and the consequent impact on ink materialrelated patents using nanoparticle technology. Furthermore, the numbers of patents in the device technology area increased rapidly since 1995. This can be attributed to the important role of printing devices, which are responsible for printing jobs in printed electronics, in the implementation of fusion technology. Thus, the pace of development in the device technology area occurred in parallel with that of the other element technologies. Meanwhile, the number of patents for circuit technology and substrate technology does not show typical increasing patterns. There are fluctuations in patent counts since 2000 in these
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Table 2 The rankings of the number of patent main groups by element technologies of printed electronics Element technology Device
Ranking
Main-group
1
B41J-002
898
B41J-029
141
5.24
3
B41M-001
39
1.45
4
G03G-015
39
1.45
5
B41F-015
35
1.30
Others
Total
42.84
371
13.80
C09D-011
99
3.68
H01B-001
94
3.50
3
C08F-002
13
0.48
4
C08K-003
13
0.48
5
C09K-011
11
0.41
230
8.55
1
B32B-003
40
1.49
2
B32B-009
30
1.12
3
B41M-005
26
0.97
4
B32B-031
18
0.67
5
B32B-027
14
0.52
128
4.76
1
H05K-001
72
2.68
2
H01L-029
32
1.19
3
H01K-003
21
0.78
4
H01R-012
15
0.56
140
5.21
1
H01L-021
195
7.25
2
G01D-015
124
4.61
3
H05K-003
102
3.79
4
B05D-005
100
3.72
5
H04N-001
34
1.26
Subtotal
555
20.64
Others
113
4.20
2,689
100.00
Subtotal Control
1,152
1
Subtotal Circuit
33.40
2
Subtotal Substrate
%
2
Subtotal Ink
Number of patent output
element technologies. In the case of circuit technology, the number of patents decreased during 2003–2007 and again decreased during 2008–2010. However, the number of substrate technology shows a relatively consistent decreasing pattern from 2000 to 2012. In the case of the control technology, which adjusts, integrates, and controls other core technologies for convergence, it showed a prominent advancement. It was not until the 2000 that scientists could make compatible ink for printed electronics. Since then, many companies began to attempt the commercialization of printed electronics technology. In addition, the control technology which adjusts, integrates and controls other technologies for convergence played a key role in convergence (Mihm 2000; Jacobson 2001; Leenen et al. 2009). In this context, the control technology played a key role in convergence since
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the 2000s and led to the current commercialization of printed electronics. On the other hand, the level of substrate technology-related patents showed no major change, a finding probably due to the lack of need for a great deal of technology innovation in the existing substrate technology. Network analysis and technological trajectory The values of the centrality indexes for the five technology areas were calculated using network analysis of the patents. As explained earlier, the closeness centrality and the betweenness centrality trends were analyzed and compared for each period, as well as for each technology area. First, we statistically analyzed group differences across different element technologies such as substrate, ink, circuit, device, and control, and different time periods with the intervals. Accordingly, we conducted two-way ANOVA because two-way ANOVA determines the statistical significance of both main effect and interaction effect as well (Bordens and Abbott 2008). Our initial proposition stated that there are group differences in centrality indexes across different element technologies and periods. To test this proposition, we performed two-way ANOVA with centrality indexes (closeness, betweenness) of each patent as dependent variables to assess whether there are any differences in variances of each different group. Table 3 shows the two-way ANOVA results for closeness centrality. As shown in Table 3, there is a significant interaction between the effects of the two group factors on dependent variable of closeness centrality, F = 5.053, p = 0.000. We also compared the betweenness centrality for the two different types of groups. The ANOVA results given in Table 4 show a significant main effect according to group type as well as interaction effects (F = 3.257, p \ 0.000). These results suggest that network centralities differ across the element technologies and different time periods. Table 5 shows the results of the analysis. The control technology showed the highest closeness centrality value (average = 0.2209) over all the periods, and the ink technology showed the highest betweenness centrality value (average = 0.0302). Especially, the control technology showed a high propensity for impacts on other technologies, with active
Fig. 1 The trends in USPTO patent counts by issued year and element technologies in printed electronics
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Table 3 Tests of between-subjects effects (dependent variable: closeness centrality) Source
Type III sum of squares
Corrected model
0.004a
24
0.000
18.157
0.000
Intercept
0.005
1
0.005
585.116
0.000
Period
0.001
4
0.000
40.768
0.000
Tech. char.
0.001
4
0.000
31.305
0.000
Period 9 tech. char.
0.001
16
4.209E–5
5.053
0.000
Error
0.038
4600
8.331E–6
Total
0.049
4625
0.042
4624
Corrected Total a
2
df
Mean square
F
Sig.
2
R = 0.087 (adjusted R = 0.082)
Table 4 Tests of between-subjects effects (dependent variable: betweenness centrality) Source
Type III sum of squares
Corrected model
1.306E–8a
24
5.441E–10
6.468
0.000
Intercept
1.083E–8
1
1.083E–8
128.733
0.000
Period
4.636E–9
4
1.159E–9
13.781
0.000
Tech. char.
2.902E–9
4
7.255E–10
8.625
0.000
Period 9 tech. char.
4.383E–9
16
2.739E–10
3.257
0.000
Error
3.869E–7
4600
8.411E–11
Total
4.117E–7
4625
4.000E–7
4624
Corrected total a
2
df
Mean square
F
Sig.
2
R = 0.033 (adjusted R = 0.028)
knowledge flows serving as a hub and aiding integration within the technology network. This empirical results support the technological characteristics of printed electronics. Printed electronics involves a process of adhering electronically functional materials to various substrates such as flexible polymer and plastic. Therefore, the key element of printed electronics is high performance ink since ‘electronically functional materials’ is the role of the ink (Kantola et al. 2009). For high performance ink is limited in several ways due to sintering process (to form large particles or masses from metallic particles by applying heat). The sintering step that is necessary to render the precursor compounds conductive typically requires [30 min and higher temperatures ([250 °C). However, the long sintering time is not scalable to Roll-to-roll production lines3 and the high sintering temperatures are not compatible with common polymer substrate (Perelaer et al. 2010). Although several scientists knew the fact that the sintering temperature has decreased as the particle size decreased, it was not until 2000 that they could reduce particle size with the help of micro/nano technology (Buffat and Borel 1976; Huang et al. 2003; Smith et al. 2006). Since then, developing various types of inks and controlling the properties of each technology have been the main challenge of printed electronics (Leenen et al. 2009). Therefore, from 2000, the importance of control-related technology has been highlighted throughout the industry. 3
Roll-to-roll production line: a kind of rotary printing technique that allows target material surface to move constantly during the printing process thus increasing cost-efficiency.
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Table 5 The averages of network centrality indexes of the element technologies in printed electronics by time periods Technology characteristics Device
Ink
Substrate
Circuit
Control
Periods
Closeness centrality
Betweenness centrality
1976–1989
0.0841
0.0045
1990–1994
0.1915
0.0308
1995–1999
0.1186
0.0150
2000–2005
0.0825
0.0054
2006–2012
0.0452
0.0034
Average
0.1044
0.0118
1976–1989
0.2890
0.0100
1990–1994
0.2710
0.0292
1995–1999
0.2985
0.0819
2000–2005
0.1025
0.0234
2006–2012
0.0456
0.0065
Average
0.2013
0.0302
1976–1989
0.1967
0.0210
1990–1994
0.3162
0.1001
1995–1999
0.2452
0.0222
2000–2005
0.0832
0.0039
2006–2012
0.0498
0.0018
Average
0.1782
0.0298
1976–1989
0.1690
0.0277
1990–1994
0.2753
0.0436
1995–1999
0.1628
0.0340
2000–2005
0.0997
0.0079
2006–2012
0.0663
0.0211
Average
0.1546
0.0269
1976–1989
0.3025
0.0287
1990–1994
0.4025
0.0646
1995–1999
0.2158
0.0172
2000–2005
0.1074
0.0183
2006–2012
0.0765
0.0184
Average
0.2209
0.0294
In this context, the ink technology shows intermediary characteristics of knowledge flows, which connects disparate technologies and helps other technologies keep pace with each other, maintaining technological interactions. Also, considering aforementioned technological background, the role of the ink technology in convergence of core technologies was enabled by outstanding advancements in micro/nano technologies. For this technology advancement, something had to play the role of an intermediary or a facilitator to actively accept or to absorb other technologies and to aid dissemination of the technologies. According to the descriptive statistics, the device technology had the highest counts, which also showed an explosive increase of the amount. In contrast, both the closeness centrality and the betweenness centrality showed the smallest values, which can be due to the control technology facilitating fusion of the disparate technologies and the device technologies concentrating on implementation. Thus, the importance of the device
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technology was lower in the entire technology network with respect to the level of technological difficulty and the capability or influence of a combination of disparate technologies. Tables 6 and 7 shows the results of the comparative analysis for the five patent technology fields for each period and the closeness and betweenness centrality values. In terms of closeness centrality, the technology area had the highest ranking and was found mainly in the control technology, followed by the circuit and substrate technologies, which ranked second and third, respectively. Thus, the most influential technology per technology area based on the average number of patents as discussed in the previous section was mainly the control technology, followed by the ink, substrate, and circuit technologies in terms of their influence on the network. In relation to betweenness centrality, technologies that played an intermediary role changed over time through the periods. Up to the middle of the 1990s, control and substrate technologies had an important role in the network. On the other hand, up to the middle of the 2000s, the ink technology, followed by the circuit technology, played important roles. In the case of the control technology, it was ranked No. 2 and maintained that position. This meant that in addition to playing an important role in influencing the technology network, the control technology also functioned as an intermediary of knowledge flows with the other technologies by combining disparate technologies. In other words, for advanced and developed core technologies to be converged, an appropriate adjustment in the technology level was required. To this end, the control technology not only advanced into one of the core technologies but also contributed to technological convergence. These results focusing on the network-centric analysis emphasize the importance of the technology which takes a role of integration and recombination of existing and prior component technologies in the technological change using evolutionary analogies (Henderson and Clark 1990; Utterback 1996). Our results confirm this perspective by finding that a particular patented technology combines existing technologies in convergence phenomenon. In addition, we detected the emergence of this mediating technology, although network analysis has intrinsic drawbacks in the time lag to identify phenomena of technological changes more precisely by reflecting accumulation of citations (E´rdi et al. 2013). The circuit technology also ranked No. 1 or No. 2, which indicated that it played an important intermediary role in the convergence of the technologies. The analysis of the dynamical evolution of network according to periods shows meaningful results. We analyze not only the dynamics of the indexes, but also the characteristics of the time period, thereby providing important implications for technology innovation theories. This is important because patent citation network observes the
Table 6 Comparative analysis of the patent citation network index: closeness centrality by periods Ranking
Closeness centrality 1976–1989
1990–1994
1995–1999
2000–2005
2006–2012
1
Control
Control
Ink
Control
Control
2
Ink
Substrate
Substrate
Ink
Circuit
3
Substrate
Circuit
Control
Circuit
Substrate
4
Circuit
Ink
Circuit
Substrate
Ink
5
Device
Device
Device
Device
Device
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Table 7 Comparative analysis of the patent citation network index: betweenness centrality by periods Ranking
Betweenness centrality 1976–1989
1990–1994
1995–1999
2000–2005
1
Control
2
Circuit
3 4 5
2006–2012
Substrate
Ink
Ink
Circuit
Control
Circuit
Control
Control
Substrate
Circuit
Substrate
Circuit
Ink
Ink
Device
Control
Device
Device
Device
Ink
Device
Substrate
Substrate
Fig. 2 The trajectories in the averages of centrality indexes of element technologies in printed electronics by time periods
dynamics of cluster formation and disappearance over time and described these dynamics systematically in terms of birth, death, growth, shrinking, splitting and merging of clusters, analogous to the cluster dynamical elementary events (E´rdi et al. 2013). Figure 2 shows the visualization of the individual core technologies shown in Table 3 per period. Figure 2 shows how the trajectory of each coordinate value moved on the basis of the average value of the dotted line when the closeness centrality was set as abscissa and the betweenness centrality was set as the ordinate. The trajectory analysis of the centrality indexes revealed a new aspect of the evolution and the advancement of the technology that cannot be shown in existing trend analyses, which perform only description-level analysis. All the technology areas showed increasing centrality indexes before 2000 and then exhibited a decreasing trend after 2000. The consistent trend in the change in the centrality
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values highlights the pattern of technology convergence. All the core technologies, showing the increase of the centrality values in 1990s to raise influence and association between the technologies, seemed returning to the state again before the convergence took place when integration and convergence were completed between the technologies. Then, they showed individual development and advancement on their own. Overall, each technology advanced individually and then underwent integration and convergence. Once the convergence was more or less achieved, individual advancement of the technologies occurred until they reached a certain level with another convergence, showing co-evolution of technology convergence. In other words, the convergence between different technologies become stronger and the general trend of inter-disciplinarity also converges in the long run, although the degree of this convergence depends greatly on the indicators what we choose (Wang et al. 2013).
Conclusions In this study, we analyze the patterns of technology convergence in the case of printed electronics, which is a typical fusion technology, utilizing bibliometric information such as patent citations. Based on the classification of each core technologies involved in technology convergence according to the role and characteristics of the technology, we investigated how these core technologies developed as the technology convergence between the core technologies took place and identified the core technologies that have played a central role in each phase of the convergence. We used data on patents relating to printed electronics that were registered between 1976 and 2012 and this patent information was summarized and divided into five groups—device, ink, substrate, circuit, and control. In addition, the network analysis was divided into five periods in order to identify which technological component has been a core technology and which played a linker role in each period. The results of the analysis generated the following conclusions: First, among the five core technologies, the device (printing machine or related parts) accounted for the most of the patents in printed electronics, followed by control, ink, circuit, and substrate. In the IPC main group classification, the number of patents relating typewriters or selective printing mechanisms dominates the most portions of total patents. These results show that the quantitative development in the area of printed electronics concentrated on the development of devices. Second, we conducted network analysis to find the role of each element technology in the technological network structures. The value for the closeness centrality, which represents the centrality of a core technology, demonstrates that control had the highest value, followed by ink, substrate, circuit, and device. This result is in contrast with the simplified quantitative results for the patents. In other words, the control technology which controls and adjusts many other core technologies involved in convergence was the core element and. The analysis of betweenness centrality, which indicated the degree of the relationships between the technologies, showed that ink, which was related to various materials and chemical technologies, had the highest value, and followed by substrate, control, circuit, and device. Thus, the ink technology area played as the important linker in that it helps the control technology as a general technology links and integrates four core element technologies. Third, based on the results of the analysis of the centrality value for each core technology per convergence period in printed electronics technology, the control technology
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played a key role through all the periods, except between 1995 and 1999. During that period, conductive ink technology was developed that utilized nanoparticles, and efforts to apply the technology increased rapidly as a result of the development of nanotechnology in the 1990s. When the linker roles were reviewed according to the time period, in the early periods, the control or the substrate technologies facilitated connections between the technologies. From 1995, the ink technology took on this role, followed by the circuit technology. Since 2006, major convergence and commercialization of printing and electronics technologies have taken place. These results have important implications for the convergence phenomenon, which has taken place in all technology areas. The results show that the control technology or the matching between disparate technologies is the key aspect in fusion technology. Although the number of patents in the control technology was lower than that of the other technologies, it has played an important role in technological convergence. These findings can aid policy decision making at the national level or strategies at the firm level when we consider which technologies should receive assistance to facilitate convergence. The taxonomic structure of technologies and their converging patterns obtained by our analysis can offer an implication on the framework of research funding (Takeda et al. 2009). Our results provide a policy direction to support technological development from the perspective of technology convergence. On the other hand, it will be more insightful if future research demonstrates that converging technology becomes more mature, simplified, and codified, as technological convergence proceeds and technological standardization reaches at a certain level (Wang et al. 2013). The finding that core technologies or linker technologies changed over time with regard to technology convergence indicates that technology convergence should not be seen as a single static R&D result. Flexible and dynamic policies or strategies are needed to advance technology convergence because technology convergence showed a constant co-evolutionary trajectory of dynamic patterns, which are different from those observed in the advancement of a single technology or an R&D strategy. In addition, the results of this study suggest research institutes, industries, and academia clear directions for research and funding focus on the important technology fields which play integrating role in technological innovation even from the national level (Cho and Shih 2011). Acknowledgments This work was supported by National Research Foundation (NRF) of Korea funded by Korean Government (Ministry of Education, Science and Technology: NRF-2012-S1A3A-2033860, NRF-2011-013-B00051).
Appendix 1 See Table 8.
Table 8 Keywords and their sources in patent information Information sources
Keywords
Title, abstract, claims, specification
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
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Appendix 2 See Table 9.
Table 9 The descriptions and examples of 51 IPC main groups and classification of element technologies IPC (main group)
Technology
Example (patent title)
IPC description
B05C017
Device
Screen printing apparatus
Hand tools or apparatus using hand-held tools, for applying liquids or other fluent materials to, for spreading applied liquids or other fluent materials on, or for partially removing applied liquids or other fluent materials from, surfaces
B05D001
Control
Method and composition for ink jet printing on a nonabsorbent substrate
Processes for applying liquids or other fluent materials
B05D003
Control
Method and compositions for printing substrates
Pretreatment of surfaces to which liquids or other fluent materials are to be applied
B05D005
Control
Processes for forming photovoltaic conductive features from multiple inks
Processes for applying liquids or other fluent materials to surfaces to obtain special surface effects, finishes or structures
B21D053
Device
Method for manufacturing an ink jet head
Making other particular articles
B32B003
Substrate
Edge connectors for printed circuit boards comprising conductive ink
Layered products essentially comprising a layer with external or internal discontinuities or unevennesses, or a layer of non-planar form
B32B009
Substrate
Multilayer printed wiring board and method of making same
Layered products essentially comprising a particular substance not covered by groups
B32B027
Substrate
Stabilized porous, electrically conductive substrates
Layered products essentially comprising synthetic resin
B32B031
Substrate
Method of manufacturing a packaging substrate
Layered products characterized by particular properties or particular surface features, e.g. particular surface coatings
B41C001
Device
Method for making lithographic plates using an ink-jet printer
Forme preparation
B41F005
Device
Flexographic rotary platen printing press
Rotary letterpress machines
B41F007
Device
Offset printing machine
Rotary lithographic machines
B41F013
Device
Cylinder for a rotary press
Common details of rotary presses or machines
B41F015
Device
Printing apparatus utilizing flexible metal sleeves as ink transfer means
Screen printers
B41F031
Device
Method and device for influencing ink-trapping behavior
Inking arrangements or devices
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Table 9 continued IPC (main group)
Technology
Example (patent title)
IPC description
B41F035
Device
Device for cleaning screen plate used in screen printing
Cleaning arrangements or devices
B41J002
Device
Inkjet printer and ink dryer
Typewriters or selective printing mechanisms characterised by the printing or marking process for which they are designed
B41J003
Device
Electroresistive printing apparatus
Typewriters or selective printing or marking mechanisms characterised by the purpose for which they are constructed
B41J023
Device
Displaceable print cartridge chute
Power drives for actions or mechanisms
B41J029
Device
Inkjet printing apparatus and ink ejection control method
Details of, or accessories for, typewriters or selective printing mechanisms not otherwise provided for
B41L013
Device
Rotary silk screen printing machine
Stenciling apparatus for office or other commercial use
B41M001
Device
Screen process printing method and screen printing machine
Inking and printing with a printer’s forme
B41M005
Substrate
Gloss coated multifunctional printing paper
Sheet materials for use therein
B44C001
Control
Method of patterning conductive films
Processes, not specifically provided for elsewhere, for producing decorative surface effects
C08F002
Ink
Printing inks containing zirconium or titanium compound
Processes of polymerization
C08K003
Ink
Ink and coating compositions containing silicon-treated carbon black
Use of inorganic ingredients
C09D011
Ink
Polymeric dispersants used for aqueous pigmented inks for ink-jet printing
Inks
C09K011
Ink
Screen printable electroluminescent polymer ink
Luminescent, e.g. electroluminescent, chemiluminescent, materials
C25D001
Control
Process for the preparation of screen printing stencils by an electroplating method
Electroforming
C25D005
Control
Process for electrochemically roughening aluminum for printing plate supports
Electroplating characterized by the process
G01D015
Control
Droplet control aspects-ink evaporation reduction
Component parts of recorders for measuring arrangements not specially adapted for a specific variable
G01D018
Device
Nozzle test apparatus and method for thermal ink jet systems
Testing or calibrating apparatus or arrangements provided for in groups
G01N027
Device
Detection of erroneous ink-jet printing
Investigating or analyzing materials by the use of electric, electro-chemical, or magnetic means
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Table 9 continued IPC (main group)
Technology
Example (patent title)
IPC description
G03C001
Device
Flexographic printing plate having a vanadium oxide antistatic coating layer
Photosensitive materials
G03C005
Device
Offset printing plate
Photographic processes or agents therefor
G03F007
Device
Litho strip and method for its manufacture
Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printed surfaces
G03G005
Device
Photoconductive printing master
Recording-members for original recording by exposure e.g. to light, to heat, to electrons
G03G009
Device
Liquid developer for electrostatic photography
Developers
G03G013
Device
Printing plate and process for preparing the same
Electrographic processes using a charge pattern
G03G015
Device
Digital plate maker system and method
Apparatus for electrographic processes using a charge pattern
H01B001
Ink
Electroconductive carbon fibril-based inks and coatings
Conductors or conductive bodies characterised by the conductive materials
H01K003
Circuit
Method of producing circuit board
Apparatus or processes adapted to the manufacture, installing, removal or maintenance of incandescent lamps or parts thereof
H01L021
Control
Screen printing light-emitting polymer patterned devices
Processes or apparatus specially adapted for the manufacture or treatment of semiconductor or solid state devices or of parts thereof
H01L029
Circuit
Printed TFT and TFT array with selfaligned gate
Semiconductor devices specially adapted for rectifying, amplifying, oscillating or switching and having at least one potential-jump barrier or surface barrier
H01R009
Control
Electronic part fabricated by intaglio printing
Structural associations of a plurality of mutually-insulated electrical connecting elements, e.g. terminal strips, terminal blocks
H01R012
Circuit
Printed circuit board for straddle mount electrical connector and method for pasting the same
Structural associations of a plurality of mutually-insulated electrical connecting elements, specially adapted for printed circuits, e.g. printed circuit boards (PCBs), flat or ribbon cables, or like generally planar structures, e.g. terminal strips, terminal blocks
H04N001
Control
Printing process using lithographic plates made from toned amplitude modulated magnetic images
Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
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Table 9 continued IPC (main group)
Technology
Example (patent title)
IPC description
H05B001
Device
Method of manufacturing an integrated thermal printing head
Details of electric heating devices
H05B003
Device
Method of manufacturing a thermal fluid jetting apparatus
Ohmic-resistance heating
H05K001
Circuit
Printed circuit board and electronic component device
Printed circuits
H05K003
Control
Multilayer thick-film hybrid circuits method and process for constructing same
Apparatus or processes for manufacturing printed circuits
Appendix 3 Tables 10 and 11 shows the detailed post hoc test results of two-way ANOVA for element technologies and different time periods. The results show that the mean of control technologies and the period of 1990–1994 have relatively high closeness centrality than any other element technologies and periods respectively. However, the mean of circuit technology shows no difference statistically. Tables 12 and 13 shows the detailed post hoc test results of two-way ANOVA for element technologies and different time periods in the case of betweenness centrality. The ink technology shows high betweenness centrality than other element technologies. In terms of time period comparisons, 1990–1994 and 1995–1999 have statistically significant differences than other periods. Table 10 Multiple comparisons: Scheffe post hoc test results for differences of element technology Closeness centrality Scheffe (I) Tech. char.
(J) Tech. char.
Mean difference (I - J)
Std. error
Sig.
95 % confidence interval Lower bound
Circuit
Control
Control
-0.000645150
0.0002124788
0.056
-0.001299897
Device
0.000389901
0.0002016131
0.442
-0.000231364
0.001011165
Ink
-0.000339443
0.0002395989
0.734
-0.001077760
0.000398873
Substrate
Ink
0.000009597
-0.000375686
0.0002736468
0.757
-0.001218920
0.000467549
Circuit
0.000645150
0.0002124788
0.056
-0.000009597
0.001299897
Device
0.001035050a
0.0001036544
0.000
0.000715642
0.001354458
Ink
0.000305707
0.0001658433
0.494
-0.000205335
0.000816748 0.000922990
Substrate Device
Upper bound
0.000269464
0.0002120824
0.806
-0.000384061
Circuit
-0.000389901
0.0002016131
0.442
-0.001011165
0.000231364
Control
-0.001035050a
0.0001036544
0.000
-0.001354458
-0.000715642
Ink
-0.000729344a
0.0001516728
0.000
-0.001196719
-0.000261969
Substrate
-0.000765586a
0.0002011953
0.006
-0.001385564
-0.000145609
Circuit
0.000339443
0.0002395989
0.734
-0.000398873
0.001077760
Control
-0.000305707
0.0001658433
0.494
-0.000816748
0.000205335
0.0001516728
0.000
0.000261969
0.001196719
0.0002392474
1.000
-0.000773476
0.000700991
Device Substrate
0.000729344a -0.000036242
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Table 10 continued Closeness centrality Scheffe (I) Tech. char.
(J) Tech. char.
Mean difference (I - J)
Std. error
Sig.
95 % confidence interval Lower bound
Substrate
Upper bound
Circuit
0.000375686
0.0002736468
0.757
-0.000467549
0.001218920
Control
-0.000269464
0.0002120824
0.806
-0.000922990
0.000384061
Device
0.000765586a
0.0002011953
0.006
0.000145609
0.001385564
Ink
0.000036242
0.0002392474
1.000
-0.000700991
0.000773476
Based on observed means The error term is mean square (error) = 8.33E–006 a
The mean difference is significant at the 0.05 level
Table 11 Multiple comparisons: Scheffe post hoc test results for differences of technological period Closeness centrality Scheffe (I) Period
(J) Period
Mean difference (I - J)
Std. error
Sig.
95 % confidence interval Lower bound
00–05
06–12
76–89
90–94
95–99
06–12
0.000362632a
0.0001124040
0.034
0.000016263
0.000709002
76–89
-0.000891493a
0.0001406589
0.000
-0.001324930
-0.000458057
90–94
-0.001866154a
0.0001545244
0.000
-0.002342316
-0.001389991
95–99
-0.000713662a
0.0001257181
0.000
-0.001101059
-0.000326265
00–05
-0.000362632a
0.0001124040
0.034
-0.000709002
-0.000016263
76–89
-0.001254125a
0.0001399763
0.000
-0.001685458
-0.000822793
90–94
-0.002228786a
0.0001539032
0.000
-0.002703034
-0.001754538
95–99
-0.001076294a
0.0001249539
0.000
-0.001461336
-0.000691252
00–05
0.000891493a
0.0001406589
0.000
0.000458057
0.001324930
06–12
0.001254125a
0.0001399763
0.000
0.000822793
0.001685458
90–94
-0.000974660a
0.0001756032
0.000
-0.001515776
-0.000433544
95–99
0.000177831
0.0001508766
0.846
-0.000287090
0.000642753
00–05
0.001866154a
0.0001545244
0.000
0.001389991
0.002342316
06–12
0.002228786a
0.0001539032
0.000
0.001754538
0.002703034
76–89
0.000974660a
0.0001756032
0.000
0.000433544
0.001515776
95–99
0.001152492a
0.0001638798
0.000
0.000647501
0.001657482
00–05
0.000713662a
0.0001257181
0.000
0.000326265
0.001101059
06–12
0.001076294a
0.0001249539
0.000
0.000691252
0.001461336
76–89
-0.000177831
0.0001508766
0.846
-0.000642753
0.000287090
90–94
-0.001152492a
0.0001638798
0.000
-0.001657482
-0.000647501
Based on observed means The error term is mean square (error) = 8.33E–006 a
The mean difference is significant at the 0.05 level
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Table 12 Multiple comparisons: Scheffe post hoc test results for differences of element technology Betweenness centrality Scheffe (I) Tech char. Circuit
Control
(J) Tech char.
Mean difference (I - J)
Substrate
95 % confidence interval Lower bound
Upper bound 0.00000178
Control
-0.00000030
0.000000675
0.995
-0.00000238
0.00000141
0.000000641
0.302
-0.00000056
0.00000339
Ink
-0.00000045
0.000000761
0.987
-0.00000279
0.00000190
Substrate
-0.00000024
0.000000870
0.999
-0.00000292
0.00000244
Circuit
0.00000030
0.000000675
0.995
-0.00000178
0.00000238
Device
0.00000171a
0.000000329
0.000
0.00000070
0.00000273
0.000000527
0.999
-0.00000177
0.00000148
-0.00000015
Substrate
Ink
Sig.
Device
Ink Device
Std. error
0.00000006
0.000000674
1.000
-0.00000201
0.00000214
Circuit
-0.00000141
0.000000641
0.302
-0.00000339
0.00000056
Control
-0.00000171a
0.000000329
0.000
-0.00000273
-0.00000070
Ink
-0.00000186a
0.000000482
0.005
-0.00000335
-0.00000038
Substrate
-0.00000165
0.000000639
0.155
-0.00000362
0.00000032
Circuit
0.00000045
0.000000761
0.987
-0.00000190
0.00000279
Control
0.00000015
0.000000527
0.999
-0.00000148
0.00000177
Device
0.00000186a
0.000000482
0.005
0.00000038
0.00000335
Substrate
0.00000021
0.000000760
0.999
-0.00000213
0.00000255
Circuit
0.00000024
0.000000870
0.999
-0.00000244
0.00000292
Control
-0.00000006
0.000000674
1.000
-0.00000214
0.00000201
Device Ink
0.00000165
0.000000639
0.155
-0.00000032
0.00000362
-0.00000021
0.000000760
0.999
-0.00000255
0.00000213
Based on observed means The error term is mean square (error) = 8.41E–011 a
The mean difference is significant at the 0.05 level
Table 13 Multiple comparisons: Scheffe post hoc test results for differences of technological period Betweenness centrality Scheffe (I) Period
(J) Period
Mean difference (I - J)
Std. error
Sig.
95 % confidence interval Lower bound
00–05
06–12
Upper bound
06–12
0.00000014
0.000000357
0.998
-0.00000096
0.00000124
76–89
-0.00000051
0.000000447
0.861
-0.00000189
0.00000087
90–94
-0.00000366a
0.000000491
0.000
-0.00000517
-0.00000215
95–99
-0.00000123a
0.000000399
0.049
-0.00000246
0.00000000
00–05
-0.00000014
0.000000357
0.998
-0.00000124
0.00000096
76–89
-0.00000065
0.000000445
0.715
-0.00000202
0.00000072
90–94
-0.00000379a
0.000000489
0.000
-0.00000530
-0.00000229
95–99
-0.00000137a
0.000000397
0.018
-0.00000259
-0.00000015
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Table 13 continued Betweenness centrality Scheffe (I) Period
76–89
90–94
95–99
(J) Period
Mean difference (I - J)
Std. error
Sig.
95 % confidence interval Lower bound
Upper bound 0.00000189
00–05
0.00000051
0.000000447
0.861
-0.00000087
06–12
0.00000065
0.000000445
0.715
-0.00000072
0.00000202
90–94
-0.00000315a
0.000000558
0.000
-0.00000487
-0.00000143
95–99
-0.00000072
0.000000479
0.685
-0.00000220
0.00000075
00–05
0.00000366a
0.000000491
0.000
0.00000215
0.00000517
06–12
0.00000379a
0.000000489
0.000
0.00000229
0.00000530
76–89
0.00000315a
0.000000558
0.000
0.00000143
0.00000487
95–99
0.00000242a
0.000000521
0.000
0.00000082
0.00000403
00–05
0.00000123a
0.000000399
0.049
0.00000000
0.00000246
06–12
0.00000137a
0.000000397
0.018
0.00000015
0.00000259
76–89
0.00000072
0.000000479
0.685
-0.00000075
0.00000220
90–94
-0.00000242a
0.000000521
0.000
-0.00000403
-0.00000082
Based on observed means The error term is mean square (error) = 8.41E–011 a
The mean difference is significant at the 0.05 level
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