The latest version had published in TF&SC. Please cite this article as: H.-C. Huang, et al., Contagion effects of national innovative capacity: Comparing structural equivalence and cohesion models, Technol. Forecast. Soc. Change (2010), doi:10.1016/j.techfore.2010.07.017
PICMET 2009 Proceedings, August 2-6, Portland, Oregon USA Š 2009 PICMET
National Innovative Capacity in the International Technology Diffusion: The Perspective of Network Contagion Effects Hung-Chun Huang, Hsin-Yu Shih National Chi Nan University, International Business Studies Dept., Taiwan Abstract--Effective promoting national innovative capacity performance tends to be a critical policy for a country. This study examines network contagion effects on international diffusion of embodied and disembodied technology by two different social network models: cohesion models, which are based on diffusion by direct communication, and structural equivalence models, which are based on diffusion by network position similarity. This study then utilizes the data of 42 countries from 1997 to 2002 to empirically examine their relational influences. The analytical results show international technology diffusion influences the performance of national innovative capacity through contagion effects; however, the mimetic behavior is predicted better by network position than by interactions with others. This result provides a broader consideration for science and technology policy.
I. INTRODUCTION Due to fierce global competition, developing or developed countries have experienced the pressure of competition; especially for developing countries, they must meet the intractable challenges of technological advancement and innovation from advanced countries. Technological innovation is an indispensable means for promoting national competitiveness, no matter what level the country in question currently occupies. Freeman et al.[1] theorize that national innovative capacity reflects more fundamental determinants of the innovation process, proposing the influence of national innovative capacity, offering countries recipes to affect national innovative capacity. Technology is highly related to cultural and social settings of organizations [2]. However, Furman & Hayes [3] suggest that a well-functioning innovation infrastructure is essential but not sufficient to support the environment required to achieve everlasting innovation at the world’s technological frontier. In addition, related R&D management literatures stress the necessity for interaction between developers and users of new technology to enhance the development and execution processes [4-7]. Therefore, the interaction among organizations brings forth the progress of technological innovation. So does the communication among countries. Countries make these interactions affect each other in the performance of economics, politics and culture, due to the development of information technology. So, while a country makes a decision or a direction of its policy on national technology development, it not only depends on its own situation, but may seek other countries’ advice or experience. Theories of interdependence support mutual interdependence between nations from close interactions, resulting in reciprocity and complicity in policies [8]. Koka et al. [9]
states trade and investment policies are influenced by trading partners and competitors. A focal country will be subject to policy influences from its cohesive partners and structurally equivalent competitors. Based on the previous literature on the influence of national innovative capacity, simply focusing on the internal environment in a nation cannot entirely affect the performance of national innovative capacity. This study examines social contagion effects, using cohesion and structural equivalence models to explore the critical influence mechanisms of a national innovative capacity. Amplifying the influence of national innovative capacity requires not solely reinforcing the internal elements of NIC but concentrating on the interaction with cohesive countries or the imitation of structurally equivalent competitors. Hence, the research objectives in this study are the following: Firstly, to evaluate the contagion effects on the performance of national innovative capacity through international diffusion of embodied technology and disembodied technology. Secondly, provide authority utilizing extensive consideration on the influence upon national innovative capacity to make a more perfectible policy toward magnifying national competitiveness. The rest of this study is organized as follows. Section II examines literature focusing on the concept of national innovative capacity, international technology diffusion containing embodied and disembodied form and social contagion effects, the cohesion model and structural equivalence model. Section III then proposes the research hypotheses in relation to the testing and comparison of the different contagion effects. Next, Section IV introduces the measurement and models of social network analysis used to investigate the mechanisms of international technology diffusion. Section V empirically tests the research hypotheses applying the sample of international technology diffusion on global structure, and discusses the theoretical and managerial implications. Finally, conclusion and remarks are shown in section VI. II. LITERATURE REVIEW This section introduces national innovative capacity and defines the international diffusion of technology involving two types of diffusion, embodied and disembodied. The final sub-section focuses on social contagion effects, exploring previous works discussing social network analysis. A. National innovative capacity National innovative capacity has been defined as the institutional potential of a country to sustain innovation.
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PICMET 2009 Proceedings, August 2-6, Portland, Oregon USA Š 2009 PICMET Numerous scholars (e.g. [10, 11] ) have clearly defined this concept and a suitable measure based on patenting rates. Therefore, patents are acknowledged to provide a reliable and unbiased indication of national innovation effort [12, 13]. One of the clearest indicators of innovation performance is the rate of take-up of patents issued by the US Patent and Trademarks Office (USPTO). Innovative capacity primarily depends upon the technological level and sophistication of an economy and the investments and policy choices of both institutions and the private sector [11]. Consequently, measuring national innovation output includes patents, publications in scientific journals, copyrights, trademarks, etc. All of these are products of innovation efforts, and copyrights and trademarks even represent direct indicators of innovative output[11]. However, this work, based on previous studies (e.g.[10, 11]) chooses patent output as innovative output. Additionally, Furman & Hayes [3] note that PATENTS correlated positively with the true level of new-to-the-world innovative output in their model, and that it appears to be the best available indicator for comparing national innovation output across countries over time. Trajtenberg [13] even considers international patents “the only observable manifestation of inventive activity with a well-grounded claim for universality.� Therefore, international patents is the most useful available measure for comparing innovation output across countries and over time [3]. Consequently, this study adopts USPTO patenting activities by sample countries to measure national innovative capacity. B. International Technology Diffusion Diffusion is a process that involves spreading certain innovation information by participants in a social system through particular channels [14]. Diffusion is an exceptional form of communication, and involves participants providing and sharing information. Diffusion thus can refer to the dissemination of knowledge, technology transfer or deployment [2]. Technology diffusion was influenced by innovations and technical updates over time. Based on technology diffusion, Vernon[15] argues international product life cycle theory; however, this theory focus upon production sites shifting process and trade flow rather than the influence of technology diffusion on innovation capacity. Countries acquire innovation technology in two main ways, enforcing domestic technology development and innovation capacity, and obtaining foreign advanced technologies via international technology diffusion. Griliches [16-18] divides international technology diffusion into rent spillover and pure knowledge spillover. 1. Embodied Technology Diffusion The type of rent spillover, referring to the price of new products for which innovation technology knowledge exists, cannot fully reflect the high quality of knowledge innovation in the process of commercialization. A country purchasing intermediate products at certain price that does not mirror their actual value can enjoy the benefits of R&D conducted
by other countries; that is, the purchasing country employs passive technology spillover or embodied technology diffusion [19] to supply their innovation capacity. The activities of the international diffusion of embodied technology are observable based on trade flows and foreign direct investment [17, 20]. Moreover, most related studies (for example [21-25]) demonstrate a significant positive relationship between total factor productivity and international trade for a given nation as evidence of international research spillover. New growth theory argues that the marginal profit from capital investment is not certain to decrease over time, and accumulated capital can sustain long-term GDP per capita; this theory also deems knowledge to be the public goods in the capital accumulation and the creation of an increasing rate of return via the spread of information. A nation benefits from spillover through trade partner investment knowledge. Consequently, knowledge capital and R&D activities benefit national economic growth. Smith & White [26] demonstrate a positive relationship between trade and national competitiveness using exploring the dynamic configuration of global economics through trade flows. Coe et al. [27] find it better to measure trade-related spillover using trade in capital goods rather than total trade. Hence, this work adopts imports of machinery and equipment for diffusing information on embodied technology to investigation. Countries exchanging goods through international trade generate rent spillover. 2. Disembodied Technology Diffusion The type of pure knowledge spillover, as well as the inherent knowledge simulated and adopted by others, emerge primarily by externalities in the form of flows of research and development (R&D) personnel, mobility of knowledge, dissemination via cooperation, international technology learning or the direct purchase of foreign technology knowledge. Such knowledge spillover makes leaders of enterprises or nations reluctant to accept unavoidable spread and diffusion via numerous noncommercial channels. Thus this kind of diffusion can be called active technology spillover or the disembodied form of international technology diffusion, measured in the form of formulas, blueprints, drawings, patent citations, and so on [28]. The advantages of innovation activities are reflected in the process of commercialization[19]; restated, an effective method of measuring national competitiveness in disembodied form is through patent citation frequency. Pure knowledge spillover results from disembodied knowledge flows, including licensing, patent citations, or outsourcing agreements. Griliches [17] suggests that patent citations can be measured as a disembodied form of diffusion. Moreover, Helleiner [29] indicates that based on the definition of a patent, technology includes not only legally guaranteed patents and trademarks but also the sophistication technique for tangible merchandise. According to Jaffe et al.[30], Eaton & Kortum[31], and Hu & Jaffe[32] international patenting is a proxy of the
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PICMET 2009 Proceedings, August 2-6, Portland, Oregon USA © 2009 PICMET channel for the international diffusion of disembodied technology. Patents can indicate intellectual property and measure technology innovation performance [33, 34]. Numerous researchers have taken frequency of patent citations as an indicator of national innovation competitiveness (e.g.[16, 35]) , with the importance of a patient increasing with frequency of citations. Patient citations thus are measurable innovation indicators of national competitiveness. Hence, this study adopts patent citations as a means of disembodied technology diffusion to investigation. Countries citing their patents to others generate pure knowledge spillover. C. Contagion Effects Lundvall [36] argues that the production and diffusion of new knowledge occurs in the mutual learning of members, and that is conducive to the development and diffusion of new technology. This if this study observes the influence of social proximity on national innovation performance, it can identify a similar mode of international interaction. Social influence occurs when actor behavior, attitudes, or beliefs involuntarily follow those of others in the same social system. Contagion is often used to describe the processes involved in social influence [37, 38]. Social influence theory involves two processes: communication and comparison [39].
2. Structural Equivalence Mechanism The other process of contagion is social comparison. In searching for a social identity, before the ego acts, it observes alters’ acts, and then corrects its actions. Ego compares himself with those alters who he sees as similar in network aspects [39]. The comparison is actuated if actors are competing [40]. Therefore, the comparison is most frequently operated using the concept of equivalence. Equivalent actors are similarly embedded in the network. The most comprehensive conception of equivalence is structural equivalence [43]. The concept of social equivalence exhibits another socialization process. The actors in the structural equivalence mode exhibit a similar pattern of relations to other actors in the social configuration [41], despite not necessarily having direct ties with one another. The similarity of patterns arising from social context creates powerful internalized pressures with which actors must comply [9]. Therefore individuals encountering uncertainty may refer to structurally equivalent actors to simulate appropriate responses. Burt [40] proposes that decision-makers are socialized via the symbolic role-playing of placing themselves in the position of others. This study thus applies the structural equivalence model to examine the influence national innovative capacity on performance. III. HYPOTHESES
1. Cohesion Mechanism Communication based on social influence involves direct contact between ego and alter [40]. Cohesion is the most common approach to operating a communication process in social network analysis. While the ego hesitates to make a decision, he will seek alters who he trusts for consultation, mostly owing to the relationship of cohesion between them. The more intimate and frequent interactions between ego and alter, the greater the influence of alter on the opinion and behavior of the ego [39]. The frequency, intensity, and closeness of interaction among cohesive actors leads to increased recurrence of action than it does among non-cohesive actors, not only increasing the opportunity to transmit social clues [41], but also resulting in network constraints among them. Some social network researchers interpret cohesion from a group perspective. Festinger [42] defines cohesion as “the result of all the forces acting on all members to remain in a group.” Actors in cohesive groups exhibit greater behavioral conformity and accordant relationship than those in less cohesive groups. Social structure is a configuration of social relations among actors where the relations involve exchange of cherished items that can be tangible (substance) or intangible (knowledge, information). Because of exchange, international trade yields increased opportunities for information sharing and thus government policies similarity between partner countries [9]. This study thus examine the influence of cohesion mechanism on national innovative capacity performance.
This work examines the performance of national innovative capacity using social contagion effects, via the cohesion and structural equivalence models, and through international diffusion of embodied and disembodied technology. Regarding the cohesion model, primarily the significant alter within a cohesive group influence actors who directly contact one another. In the structural equivalence model, the alter in the similarity of network position influence actors and they may not have direct interactions with. Hence, the hypotheses in this study employed the contagion model to examine embodied and disembodied technology diffusion. A. Cohesion Model The cohesion model centers on the interaction between ego and alter. When actors encounter tough questions or deal with something, their attitude and conduct will lean towards alters within the same group. This is the social influence process. The cohesion model incorporates the opinion, behaviors, attitudes, and policies connecting actors. Therefore, the policy making of a given country promptly follows the one of an alter country, since both share the common evaluation of the costs and benefits from interaction [40]. Hence, this study can assume that the countries within the same group through cohesion mechanisms can influence the innovative capacity performance of a certain country. Thus the hypotheses are: Hypothesis 1: The performance of national innovative capacity of a focal country is influenced positively and
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PICMET 2009 Proceedings, August 2-6, Portland, Oregon USA © 2009 PICMET significantly by those of other countries within a cohesive group formed through international diffusion of embodied technology. Hypothesis 2: The performance of national innovative capacity of focal country is influenced positively and significantly by those of other countries within a cohesive group formed through international diffusion of disembodied technology. B. Structural Equivalence Model Burt [44] argues that ego’s behavior is predicted more precisely by structural network position than interactions with others. Because of competition, ego’s making changes will be readily followed by competitors [39]. An actor will accept an innovation while perceiving others structurally equivalent to him applying it. Owing to similarity, actors would experience the awareness of competition, and then take others as the paradigm. Therefore, the more similar ego's structural position with others, the more possible that others would substitute for ego's positions [40]. According to the Burt's study, this study can figure out that actors in the structural equivalence model mean that they are competitive with each other. Burt applied the concept of structural equivalence to the study of industrial structures, and he also concluded that an actor's adopting behavior is triggered by others who are structurally equivalent in the network. Therefore, this study has the following hypotheses: Hypothesis 3: The performance of national innovative capacity of a focal country is influenced positively and significantly by those other countries at structurally equivalent levels defined through international diffusion of embodied technology. Hypothesis 4: The performance of national innovative capacity of a focal country is influenced positively and significantly by those of other countries structurally equivalent, defined through international diffusion of disembodied technology. C. Comparison Social contagion effects of the cohesion and structural equivalence models show theoretically fundamental difference of mechanisms. Although there may be two different contagion mechanisms in social proximity, many scholars all argue that ego’s behavior is more inclined to be affected by alter having the same network position than by alter interacting with each other [9, 40, 45, 46]. Hence, the contagion effect of structural equivalence model should be stronger than the cohesion model. The hypotheses of comparison on the performance of national innovative capacity are examined as the following: Hypothesis 5: In terms of international diffusion of embodied technology, the performance of national innovative capacity between countries with social proximity structural equivalence is more similar than those countries with social proximity of cohesion. Hypothesis 6: In terms of international diffusion of
disembodied technology, the performance of national innovative capacity between countries with social proximity structural equivalence is more similar than those countries with social proximity of cohesion. IV. METHODOLOGY A. Data This investigation employs a sample of 46 countries over the period from 1997 to 2002, ranked according to the Global Competitiveness Index of the World Competitiveness Databank. The social contagion effects dataset contains four categories: bilateral trade in exports and imports, frequency of patent citations, aggregate R&D Expenditure and international patents granted in year t+3. Trade flow data are mainly obtained from Global Trade Information Services, Inc.. However, data on imports are more accurate than those on exports [26, 47, 48], and this study adopts an importing dataset. Furthermore, Coe et al. [27] found that it is better to measure trade-related spillover using trade in capital goods than total trade. For frequencies of patent citations, the dataset of patents granted by the United States Patent and Trademark office, and frequencies of patent citations are obtained from the NBER Patent Citations Database [49]. Owing to technical difficulties in analyzing raw data, this investigation gathers data for the periods from 1997~2002 1 and contains frequencies of inter-country patent citing and cited. As for the total R&D expenditure of each country, this investigation refers to World Competitiveness databank, IMD. PATENTS represents the number of patents granted in year t+3 by USPTO due to the average lag between the application and approval accounted by USPTO and between the measures of innovative capacity and the observed realization of innovative output [11]. Considering the completeness of data collection, this investigation selects 42 countries as the sample owing to materials for some countries being absent. Appendix 1 lists the countries studied in this work. The initial levels of innovative productivity and the legacy of historical situations of each country represent different influences on the performance of national innovativeness [3], and thus Appendix 1 shows both embodied and disembodied diffusion countries. Appendix 2 lists variable sources and definitions. B. The International Technology Diffusion This work employs social contagion effects to examine spillovers in international technology diffusion. Since total national R&D expenditure is positively and significantly related to international technology diffusion, [18, 50], Xu & Wang[51] and Shih & Chang[48] propose that international technology diffusion is measured based on national R&D 1 The original data in NBER was collected until 1999, and Hall, Jaffe and Trajtenberg continue updating the project and collected data until 2002.
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PICMET 2009 Proceedings, August 2-6, Portland, Oregon USA © 2009 PICMET expenditure, which must be multiplied by a weighted coefficient, this study considers total national R&D expenditure when measuring the degree of international technology diffusion. Equation (1) shows the formula used to calculate international technology diffusion. ITDij = rij × RDi (1)
ITDij represents the degree of technological
Here,
knowledge diffusion from country i to country j, RDi is the R&D expenditure of country i; and
rij represents the
fraction of knowledge spillover from country i to country j. Distinguishing embodied and disembodied forms of technology diffusion requires establishing two weighting formulas, rE ,ij ,t and rD ,ij ,t . This study defines the embodied form of diffusion as
rE ,ij ,t =
rE ,ij ,t [48].
M ij ,t l
i ≠ j,
l
∑∑ M i =1 j =1
i, j, l = 1,2 … ,42
(2)
ij ,t
Mij,t represents country j importing capital goods from country i during year t; l stands for numbers of countries, from 1 to 42. Regarding trade flows in this study, the quantity of machinery and equipment imports in one country is multiplied by total R&D expenditure in another country, and it imports from 42 countries while they export to this country so it forms 42 by 42 matrix. Hence, this study assumes that if a certain country imports more capital goods from other country, the net importer nation will benefit through embodied technology diffusion. Regarding the disembodied technology diffusion, patent citations represent the linkage to prior knowledge; restated, the frequencies with which a certain country cites patents from another country represent the density of pure knowledge spillovers between the two countries. Thus, the weight of disembodied technology diffusion is rD,ij,t, defined as:
rD ,ij ,t =
Cij ,t l
i ≠ j,
l
∑∑ C i =1 j =1
i, j, l = 1,2 … ,42
(3)
affected by the opinions and behaviors of significant others belonging to the cohesive group or occupying a position of structural equivalence. This influence process is the contagion effect. Burt [40] designed a theoretical framework for the contagion effects of cohesion and structural equivalence in the social network by observing the diffusion of medical innovation proposed by [52]. Thus, this study adopts the social contagion model devised by Burt [40] to forecast international technology diffusion among countries. yi is defined as the patent output in country i, and represents the realization of national innovative activities in country i. y*i denotes the expected patent output in country i based on the response to other countries and ε represents the residual term. Weight wij is the crucial term in this study, which can recognize the contagion effects of cohesion and the structural equivalence model by operating wij, and it measures the social proximity of country i to country j relative to its social proximity to other countries, except that country i reveals the degree of closeness between countries i and j compared to other countries within the network. The contagion effects equation is as follows: ⎛ ⎞ yi = ρ ⎜⎜ ∑ wij y j ⎟⎟ + ε ⎝ j ⎠
j≠i
( )
or yi = ρ yi* + ε , j ≠ i
Here, yi* = ∑ wij y j , j ≠ i j
( proximity i to j ) v , k ≠ i wij = ∑ ( proximity i to j)v
(5)
k
The magnitude of exponent v can be measured as the degree to which country i is reactionary in relying on other countries [40, 46]. This work operates the contagion effects of the cohesion and structural equivalence models via wij., and thus the two models can measure the social proximity of contagion effects by equation Eqs. (4) and (5). If social proximity is measured by trade flows or frequency of patent citations between countries i and j, then wij represents the cohesion model. On the other hand, if social proximity is measured via the similarity of relation between country i and country j, then wij represents the structural equivalence model. Since y * = w y , the meaning of ∑ ij j i
ij ,t
(4)
yi* is different from the
j
Cij,t denotes the frequencies of country j citing patents from country i during year t; l represents individual countries by number, from 1 to 42. Patent citations are measured by the citation frequencies and owing to the reference, a given country cites patents from 42 countries while they are cited by this country, it also constitutes 42 by 42 matrix. This study thus assumes that when a given country cites more patents from other countries, the patent citing nation will benefit from disembodied technology diffusion. C. Contagion Effects Numerous researchers are interested in the contagion process of the innovations diffusion[45, 46]. Actors tend to be
relationship between actors. Consequently, if wij is measured using the cohesion model, then
yi* represents the degree to
which country i responds to the performance behavior of trading or citation partners. Conversely, if wij is measured using the structural equivalence model, then
yi* denotes the
response of country i to the performance of competitors. The relationship between
yi and yi* represents the degree to
which social contagion process influences international technology diffusion.
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PICMET 2009 Proceedings, August 2-6, Portland, Oregon USA © 2009 PICMET 1. Cohesion Model This study employs the two types of diffusion mechanism, cohesion and structural equivalence models. As for the cohesion model, the weight matrix W is measured using the row data, representing the effects of social contagion on national innovative capacity of importing or patent citing countries. In this study ITDij denotes the degree of technological knowledge diffusion via export value or frequency of patent citations from countries i to j; conversely, if the weight matrix W is measured using the normalized column data, this operation exhibits the effect of social contagion to national innovation performance from exporting or cited countries. The degree of technological knowledge diffusion via import value or frequency of patent citations from countries i to j is represented by ITD ji . Summing the row ( ITDij ) and column data ( ITD ji ) can investigate the
⎡ ⎛ ITD ITD jk ik d ij = ⎢∑ ⎜ − ⎜ Rj ⎢ k ⎝ Ri ⎣
2
⎞ ⎛ ITDkj ⎟ + ∑ ⎜ ITDki − ⎟ ⎜ Cj k ⎝ Ci ⎠
⎞ ⎟ ⎟ ⎠
2
1
⎤ 2 , i ≠ k ≠ j (7) ⎥ ⎥ ⎦
After identifying the structural equivalence between countries i and j, this study applies the value of Euclidean distance d ij to the weight wij. The weight wij of the structural equivalence defined by Burt [40].
d max i
represents the maximum distance between country i and other countries in the global network. Shih [46] suggests that the proximity of sector i to j can be represent as the extent to which d ij is smaller than d max i . Similarly, if the extent to
d ij is smaller among countries than d max i , it
which
demonstrates the proximity of country i to j. (d max i − dij )v , k ≠ i SE wij =
v ∑ (d max i − dik )
(8)
influence on the performance behavior of national innovative capacity of the degree of technological knowledge diffusion via trading or citing partners. According to Burt [40], the exponent v frames the scope of the influencing process on ego conception, and a high value indicates a strong relationship between the closet alters. The weight of influence wij is constituted as follows: (ITDij + ITD ji )v , k ≠ i (6) wijC = v ( ) ITD + ITD ∑ ik ki
This study examines national innovation capacity using social contagion effects, the cohesion model and the structural equivalence model via international diffusion of embodied and disembodied technology. This section presents the results of global technology contagion effects.
2. Structural Equivalence Model As for the structural equivalence model, measuring the extent to which country i and country j requires examining Euclidean distance, which is the most common method used by sociologists to measure degree of structural equivalence, the value of which ranges between zero and one. In this particular case, when this distance equals zero it means that the two actors are precisely structurally equivalent. Since the structural equivalence model measures the relations of the actors in terms of trading or patent citations, row data and column data are included in the Euclidean distance equation. Here, Ri denotes the summation of the degree of technological knowledge diffusion via export values or frequency of patent citation to each country in row i, and Ci represents the summation of the degree of technological knowledge diffusion via import values or frequency of patent citation i. If from each country in column ITDik ITD jk and ITDki ITDkj , then countries i and j are = = Ci Cj Ri Rj structurally equivalent, demonstrating that the degree of technological knowledge diffusing occurring through their exports or patent are cited the duplicate proportions of outcomes to every other country; and the degree of technological knowledge diffusion occurring through their imports or patent cite the duplicate proportions of input from each country. Consequently, the following is used to measure Euclidean distance.
A. Contagion effects Equation (4) tests contagion effects, and this study examines the intensity of such effects on national innovative capacity at the global level, as follows: Equation (6) is applied in Eqn. (4) to examine the cohesion model; Eqn. (7) and (8) are incorporated into Eqn. (4) to analyze the structural equivalence model. This part represents the contagion effects, cohesion model and structural equivalence model through international diffusion of embodied and disembodied technology on NIC performance, specifically patent output. This study observes 42 countries during 1997 to 2002. Owing to time lag of innovative realization, this study focuses on patent output during 2000 to 2005. Table 1 reveals that all models are significant. As for the relations between the contagion effects and patent output in each country as demonstrated by models 1 and 3, the cohesion mechanism exhibits unexpected negative effects via embodies and disembodies technology diffusion. However, regarding the structural equivalence mechanism, models 2 and 4 demonstrate positive and significant relationships between the contagion effects and NIC performance in each country. This study infers that countries lean more towards influencing national innovative capacity through mimicking the behavior of competitors than that of communication partners. Furthermore, comparison of the contagion effects in Table 1 reveals that the structural equivalence mechanism through embodied technology diffusion outperforms the
k
V. RESULTS AND DISCUSSION
k
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PICMET 2009 Proceedings, August 2-6, Portland, Oregon USA Š 2009 PICMET cohesion mechanism in terms of influencing national innovative capacity, supporting hypothesis 5. Regarding disembodied technology diffusion, the structural equivalence mechanism remains more positive and significant than the
cohesion mechanism in terms of influencing national innovative capacity, supporting hypothesis 6. Thus, the study findings support hypotheses 3, 4, 5 and 6, and do not support hypotheses 1 and 2.
TABLE 1. RESULTS OF REGRESSION ANALYSIS Dependent variable=(PATENTS)j,t+3 Model 1 Embodied spillover via Cohesion mechanism
Model 2
Model 3
Model 4
-0.463 (-8.273)
Model 5
Model 6
-0.189 (-3.580)
Embodied spillover via Structural equivalence mechanism Disembodied spillover via Cohesion mechanism Disembodied spillover via Structural equivalence mechanism Significance
0.000
0.000
0.000
0.000
0.000
0.000
R2
0.214
0.268
0.412
0.842
0.304
0.851
0.517 (9.568)
0.518 (9.804) -0.642 (-13.257)
-0.120 (-3.843) 0.917 (36.533)
0.844 (27.070)
Note: Numbers represent standardized beta coefficients; t-values are in parentheses; all standardized coefficients are significant at the 0.001 level.
These empirical results confirm that the contagion effect in this study seems not entirely consistent with prior works [9, 40, 45, 48]. Therefore, this study will discuss the reasons for these results, providing broader perspectives on exploring the influence of national innovative capacity through two mechanisms of the contagion effect.
B. The effects of Contagion on NIC performance 1. Embodies forms International technology diffusion in the cohesion mechanism, the embodied technology diffusion negatively influences national innovation capacity performance, which appears inconsistent with previous research. Theoretically, international technology diffusion positive affects both ego and alter countries [24, 53]. However, in this study, international technology diffusion negatively affects innovative capacity; that is, the more interact its partner countries, the more the innovation capacity of those countries is reduced. The reverse effects are observed when this investigation include developed and developing countries and those countries develop new-to-the-world technology differently[11]. On the one hand, developing countries import embodied technologies form developed countries to upgrade their productivity and increase efficiency [54]; furthermore, developed countries export numerous types of machinery and equipment to developing countries, while developed countries increase a positive effect to developing countries innovative capacity. Therefore, lower innovative capacity countries achieve economic growth and changes in productivity efficiency through the embodied technology of the more innovative capacity partner. However, the rent of embodied technology transfers to domestic innovative capacity, and is affected by import country absorptive capabilities[55]. Products just partially contain essential
knowledge and techniques on manufacturing[56], and it cannot learn the technology completely. Acquiring knowledge involves not simply purchasing or trading goods, but rather systematic and purposeful knowledge-based learning and construction [57]. Developing countries do not exert a valid influence on innovative activity via the embodied technology of developed partner countries, but such technology does increase their production efficiency [54, 58]. At the global level, the several higher innovative capacity countries flow their technology into numerous lower innovative capacity countries, leading to technology diffusion negatively impacting cohesion mechanism based on NIC performance. Additionally, the technological-gap theory[59] and product life cycle theory[15] regard technological diffusion as hierarchical diffusion. According to international technology diffusion with global stratification patterns [15, 21, 27, 48, 60, 61], the findings of this study are consistent with those of previous works. Contrarily, the structural equivalence mechanism via embodied technology significantly and positively influences NIC performance. Model 2 represents countries that are more inclined to utilize mimicking behavior with structurally equivalent competitors through trading embodied technological commodities. This mechanism demonstrates that a ego countries and the alter countries are competitors; restated, they may not communicate directly via embodied technology exchanges, but their similar network position leads them to communicate indirectly by trading with third parties [40]. Owing to the existence of structural equivalence, a given country can mimic the technology of a competitor country with a similar network position, thus influencing their national innovative capacity. On the one hand, countries with similar network positions employ similar capabilities to acquire new technologies. On the other hand, while trade
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PICMET 2009 Proceedings, August 2-6, Portland, Oregon USA Š 2009 PICMET action from competitors results in more innovative outputs, and owing to competition, a focal country has a similar reaction and then increases its innovative output, thus influencing national innovative capacity. This study compares two contagion mechanisms, namely cohesion versus structural equivalence, to determine whether national innovation capacity performance is more similar between countries with social proximity and structural equivalence than between those with social proximity of cohesion, as stated in Hypothesis 5. A standard error is calculated for the difference between two standardized coefficient estimates of structural equivalence and cohesion models, with a t test applied to assess the significance of the difference. The standardized coefficient estimate measured by the structural equivalence model significantly exceeds that measured by the cohesion model, and the R2 of the former model is significantly larger than that of the latter model. The analytical results support Hypothesis 5, indicating that the structural equivalence model exerts a more significant contagion effect than does the cohesion model on the diffusion of embodied technology affecting global NIC structures. Restated, NIC performance is triggered more by the influence of competitors than that of cohesion partners. In terms of embodied diffusion, countries prefer to learn from the experiences of others with a similar network position, since such learning can positively influence national innovation performance; countries can react to competitors who are structurally equivalent in terms of embodied technology diffusion. Policy-making as a means of influencing innovative capacity cannot be performed in isolation and decisions of other cohesive or structurally equivalent countries should be considered in policy-making. This result is consistent with that of Koka et al. [9], namely that countries seeking to develop a profitable trading policy must ensure their policies fit those of other related countries. 2. Disembodied forms For diffusion of disembodied forms, the standardized coefficient of the cohesion model is negative and significant. Like embodied technology diffusion, disembodied technology is significantly diffused with global stratification patterns, and this result can be discussed from two perspectives. First, this investigation at the global level included developing countries and developed countries; it may exhibit the reverse effect of cohesion mechanism due to the large differences in innovative capacity between developing and developed countries. Second, as discussed above, owing to low innovative capacity and insufficient intellectual property, developing countries must cite more cohesive partner’s disembodied technology from to apply their R&D and promote their technological advances[54]. Consequently, at the global level, the strong relationship within cohesive groups has side effects on innovative capacity. Therefore, the effect of disembodied technology diffusion among countries within a cohesive group exerts a negative influence on innovative capacity.
For structural equivalence mechanisms, the standardized coefficient is positive and significant. Due to the multi-collinarity between patent output and patent citation, the structural equivalence model has higher explanatory power. However, the diffusion of the structural equivalence mechanism remains an important issue requiring discussion. A country that is structurally equivalent not only has a similar network position to a competitor but also similar technological capabilities to acquire the knowledge of their competitors; disembodied technology via structurally equivalent mechanism is more easy to diffuse. Since disembodied technology diffusion is termed an active technology spillover, direct learning or purchase of foreign technological knowledge involves explicitly using disembodied knowledge in the form of patent applications. While the actions of competitor countries stimulate increased patent output and raise national competitiveness, a ego country in the same network position performs similar and active R&D to increase their innovation activity. When other countries remain in a position of structural equivalence with a ego country, their conduct positively affects innovation capacity. Consequently, alter countries, as the role of competition in the same network position, provide a ego country with positive feedback regarding national innovation capacity performance via international technology diffusion. By comparing two contagion mechanisms of disembodied technology diffusion, as presented in Hypothesis 6, this investigation applied a t test to assess the significance of the difference. The standardized coefficient estimate measured using the structural equivalence model significantly exceeds that measured using the cohesion model, and the R2 of the former model significantly exceeds that of the latter model. Analytical results still support Hypothesis 6, indicating that the structural equivalence model yields more significant contagion effect than the cohesion model on the diffusion of disembodied technology affecting NIC in a global structure. That is, national innovative capacity performance is influenced more by competitive countries than cohesion partner countries. In terms of disembodied diffusion, the alter countries with similar network positions remain the main influences on national innovative capacity of ego countries. However, international pure knowledge spillover proves effective not only when technology is obtained from abroad for less than the original cost to domestic inventors, but also when a country can absorb and apply technology from abroad. Additionally, direct learning regarding explicit knowledge of foreign competitors increases domestic technological capability and can be actively adopted for innovation efficiency. 3. Comparison for embodied and disembodied technology diffusion Empirically, embodied and disembodied diffusion are not easily distinguishable, but the measurement in terms of empirical data can capture and differentiate either embodied
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PICMET 2009 Proceedings, August 2-6, Portland, Oregon USA Š 2009 PICMET or disembodied diffusion. Comparing Models 1 and 3, involving the coefficient of cohesion mechanism, or Model 2 and Model 4, involving the coefficient of structural equivalence mechanism, demonstrates that disembodied diffusion influences national innovative capacity significantly more than embodied diffusion does. This result indicates a difference in spillover rigidity between embodied and disembodied technology diffusion. Notably, rent spillovers resulting from embodied technology diffusion are more rigid than pure knowledge spillovers resulting from disembodied technology diffusion. Utilizing specialized and advanced intermediate products that have been invented overseas demonstrates the implicit usage of technological knowledge embodied in foreign intermediate goods for producing final output. Furthermore, the technological knowledge embodied in trading intermediates is not available to domestic inventors. Embodied technology diffusion is thus considered a passive technology spillover that primarily influences changes in productivity efficient [54]. Restated, embodied technology diffusion is rigid to knowledge spillover, which is a relatively weak form of international technology diffusion that influences national innovative capacity. Direct acquisition of foreign technological knowledge involves explicitly using disembodied knowledge in the forms of formulas, blueprints, drawings, and patent applications [62]. Pure knowledge spillover occurs internationally if technological knowledge is obtained from overseas for less than the original cost to domestic inventors. Direct learning regarding foreign technological knowledge increases the domestic technological stock of knowledge that can be actively adopted for innovation and that influences technical change. Disembodied technology diffusion is less rigid for knowledge spillover, and is termed active technology spillover. More specifically, disembodied technology diffusion influences national innovation capacity more significantly than does embodied technology diffusion. VI. CONCLUSION AND REMARKS Since globalization, many forms of international cooperation, such as global supply chains and globalized R&D, heterogeneously promote a country towards achieving technological progress and driving economic growth through international technology diffusion. So does the need to understand the mechanisms characterizing international technology diffusion, to identify major influences upon the performance of national innovative capacity. This study examines the influence upon national innovative capacity by network contagion effects of cohesion mechanisms and structural equivalence mechanisms through international diffusion of embodied and disembodied technology. Patents are not only acknowledged as providing a reliable and unbiased indication of the innovation effort being expended by a country, but also regarded as a country’s R&D performance. Two types of potential knowledge generated by
R&D activities are rent spillovers and pure knowledge spillovers. Rent spillovers occur through embodied knowledge flows; pure knowledge spillovers are performed via disembodied knowledge flows. However, heterogeneous potential knowledge is affected by the network structure of technology diffusion within the international economy. Two different diffusion mechanisms, the cohesion mechanism and the structural equivalence mechanism, exist to examine the contagion effects of two actors that are social proximate, so that one actor's performance of innovative capacity can be expected to trigger the other actor's performance. The cohesion mechanism, which is based on diffusion by direct contact and communication, measures the influence upon innovative capacity performance by cohesion partners. Conversely, the structural equivalence mechanism, which is based on diffusion by similarity of network position, measures the imitation between competitors as a result of conformity to prevalent norms within structurally similar sectors. This study employed the two contagion effects to examine the international technology diffusion via two social contagion mechanisms, and empirically tested and compared the two mechanisms by studying a sample of international technology diffusion taken from global economic structures. Social network analysis has been successfully applied in studying the contagion effects of international technology diffusion to demonstrate the usefulness of the proposed methodologies and to find the contagion effect that most accurately predicts mimetic behavior. From the empirical results, this study finds the distinguishable influence upon the performance of national innovative capacity between countries with different technological diffusion forms and social proximity. Embodied or disembodied technology diffusion through structural equivalence mechanisms has significant influence on the performance of national innovative capacity. However, a country is affected more by its structurally equivalent competitors than by its cohesion partners. In other words, countries are more inclined to take competitors as a paradigm through international technology diffusion based on their developing environment. Therefore, while the leader of a given country makes policies on technology development via international cooperation, a country can depend on its internal capability and deliberate the action of its competitors to accurately shift its policy. Moreover, embodied or disembodied technology diffusions through cohesion mechanisms have negative affects on the performance of national innovative capacity, which can be regarded as international technology diffusion via global stratification patterns. In other words, merely utilizing a cohesion partner’s technology without absorbing the embodied or disembodied technological rent spillover into domestic innovation activity will more deeply embed a country into a large exchange system. Embodied and disembodied technology diffusions distinguishably influence the performance of national innovative capacity. Embodied technology diffusion is more
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PICMET 2009 Proceedings, August 2-6, Portland, Oregon USA © 2009 PICMET rigid to knowledge spillover and more strongly influences productivity changes than the performance of national innovative capacity. Relatively, disembodied technology diffusion is less rigid to knowledge spillover and which increases the domestic technological stock of knowledge that can be actively adopted for innovation and affects technical change. In terms of international technology diffusion, policy makers should refer to their development plans to tune these technology diffusion mechanisms. Participating in international cooperation deploys their “international relationship” strategy to influence their innovative capacity. Furthermore, the expenditure of research and development for a country can be regarded as a country’s intention to develop a national specific capability in technology. However, without considering their global network position, the effectiveness of this expenditure is likely to decrease. The limitations of this study should be acknowledged in order to identify directions for future research. This study provides some suggestions for further studies to investigate. Suggestions are the following for further study: The ego’s behavior and opinions are not merely determined by heterogenous mechanisms (others’ behavior and opinions), but also by endogenous mechanisms (reaction to various other constraints and opportunities granted by the ego's conditions). Such a process is typically modeled in sociology as an autocorrelation model. Owing to the lack of the endogenous mechanism, this study points out the need for future research to examine the autocorrelation model of international technology diffusion to consider both heterogenous and endogenous mechanism simultaneously. Second, this study explores the social contagion effect at the global level, but does not investigate the actions at the block level of focal countries individually (e.g. Core, semi-periphery and periphery). With global stratification patterns, it will be more specific if researchers can focus on certain countries interacting with others. Finally, this study centers on social contagion effects and does not utilize other social network analysis. If researchers can apply more indicators and the conceptions of social network analysis to analyze the data, that would be beneficial. ACKNOWLEDGMENTS
[3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23]
The authors would like to thank Les Davy, National Chi Nan University Department of computer Science and Information engineering, for his editorial assistance. Also, this research was supported by a grant from the National Science Council of Taiwan for financially supporting this research under Contract No. 97-2410-H-260-011-MY3. This support is gratefully acknowledged.
[24] [25] [26] [27] [28]
REFERENCES [1]
[2]
Adler, P. S., and S. W. Kwon, “Social capital: Prospects for a new concept.,” Academy of Management Review, vol. 27, no. 1, pp. 17-40,
[29]
2708
2002. Tornatzky, L., and M. Fleisher, The Processes of Technological Innovation, Lexington, MA: Lexington Books, D.C. Heath and Company., 1990. Furman, J. L., and R. Hayes, “Catching up or standing still? National innovative productivity among ‘follower’ countries, 1978-1999,” Research Policy, vol. 33, pp. 1329-1354 2004. Aoki, M., and N. Rosenberg, The Japanese Firm as an Innovating Institution: CEPR Publication, Center for Economic Policy Research, Stanford University, 1987. Marquis, D., The Anatomy of Successful Innovations: Ballinger Publishing Co., 1988. Tushman, M., “Managing Communication Network in R&D Laboratories,” Sloan Management Review, pp. 37-49, 1979. von Hippel, E., The Sources of Innovations, New York: Oxford University Press, 1988. Staniland, M., What is political economy? A study of social theory and under-development, New Haven, CT: Yale University, 1985. Koka, B. R., J. E. Prescott, and R. Madhavan, “Contagion Influence on Trade and Investment Policy: A Network Perspective,” Journal of International Business Studies, vol. 30, no. 1, pp. 127-147, 1999. Hu, M.-C., and J. A. Mathews, “China's national innovative capacity,” Research Policy, 2008, DIO:10.1016/j.respol.2008.07.003. Furman, J. L., M. E. Porter, and S. Stern, “The determinants of national innovative capacity,” Research Policy, vol. 31, no. 6, pp. 899-933, 2002. Griliches, Z., “Patent Statistics as Economic Indicators: A Survey,” Journal of Economic Literature, vol. XXVIII, pp. 1661-1707, December 1990, 1990. Trajtenberg, M., Patents as Indicators of Innovation, Cambridge (MA): Harvard University Press. , 1990. Rogers, E. M., Diffusion of Innovations, New York: Free Press, 1985. Vernon, R., “International Investment and International Trade in the Product Cycle,” Quarterly Journal of Economics, vol. 153, pp. 190-207, 1966. Griliches, Z., “Issues in assessing the contribution of research and development to productivity growth,” The Bell Journal of Economics, vol. 10, no. 1, pp. 92-116, 1979. Griliches, Z., “Market value, R&D, and patents,” Economics Letters, vol. 7, pp. 183-187, 1981. Griliches, Z., "Productivity and technological change: some measurement issues," Technology and Productivity: The Challenge for Economic Policy, pp. 229-231: OECD, 1991. Bascavusoglu, E., "Patterns of technology transfer to the developing countries: differentiating between embodied and disembodied knowledge," TEAM and CNRS Working Papers, 2004. Papaconstantinou, G., N. Sakurai, and A. Wyckoff, “Domestic and international product-embodied R&D diffusion,” Research Policy, vol. 27, pp. 301-314, 1998. Coe, D. T., and E. Helpman, “International R&D spillovers,” European Economic Review, vol. 39, pp. 859-887, 1995. Eaton, J., and S. Kortum, “Trade in capital goods,” European Economic Review, vol. 45, no. 7, pp. 1195-1235, 2001. Keller, W., "The geography and channels of diffusion at the world’s technology frontier," National Bureau of Economic Research Working Paper No. 8150, 2001. Keller, W., “International technology diffusion,” Journal of Economic Literature, vol. XLII, pp. 752-782, 2004. Grossman, G., and E. Helpman, Innovation and Growth in the World Economy, Cambridge, MA: MIT Press, 1991. Smith, D. A., and D. R. White, “Structure and dynamics of the global economy: network analysis of international trade, 1965-1980,” Social Forces, vol. 70, pp. 857-893, 1992. Coe, D. T., E. Helpman, and A. W. Hoffmaister, “North-South R&D spillovers.,” The Economic Journal, vol. 107, pp. 134-149, 1997. Maskus, K. E., Encouraging International Technology Transfer, Geneva, Switzerland, 2004. Helleiner, G. G., “The Role of Multinational Corporation in Less Developed Countries’ Trade in Technology,” World Development, vol. 3, pp. 161-189, 1975.
PICMET 2009 Proceedings, August 2-6, Portland, Oregon USA © 2009 PICMET [30] Jaffe, A. B., M. Trajtenberg, and R. Henderson, “Geographic localization of knowledge spillovers as evidenced by patent citations,” Quarterly Journal of Economics, vol. 108 no. 3, pp. 577-98, 1993. [31] Eaton, J., and S. Kortum, “International patenting and technology diffusion: theory and measurement,” International Economic Review, vol. 40, pp. 537-570, 1999. [32] Hu, A. G. Z., and A. B. Jaffe, “Patent citation and international knowledge flow: the cases of Korea and Taiwan,” International Journal of Industrial Organization, vol. 21, pp. 849-880, 2003. [33] Mogee, M. E., “Using Patent Data for Technology Analysis Planning,” Research Technology Management, vol. 34, no. 4, pp. 43-49, 1991. [34] OECD, Oslo Manual, Proposed Guidelines for Collecting and Interpreting Technological Innovation Data: OECD, 1997 [35] Austin, D., “An Event Study Approach to Measuring Innovative Output: The Case of Biotechnology.,” American Economic Review, vol. 83, pp. 253-258, 1993. [36] Lundvall, B.-A., National Systems of Innovation: Towards a Theorem of Innovation and Interactive Learning, 1992, Ed. ed., London: Pinter Publications, 1992. [37] Leenders, R. Th. A. J., Structure and Influence: Statistical Models for the Dynamics of Actor Attributes, Network Structure and Their Interdependence, Amsterdam: Thela Thesis Publishers, 1995. [38] Leenders, R. Th. A. J., Longitudinal behavior of network structure and actor a tributes: modeling interdependence of contagion and selection, New York: Gordon and Breach, 1997. [39] Leenders, R. Th. A. J., “Modeling social influence through network autocorrelation: constructing the weight matrix,” Social Networks, vol. 24, pp. 21-47, 2002. [40] Burt, R. S., “Social contagion and innovation, cohesion versus structural equivalence.,” American Journal of Sociology, vol. 92, pp. 1287-1335, 1987. [41] Rice, R. E., and C. Aydin, “Attitudes towards new organizational technology: Network proximity as a mechanism for social information processing,” Administrative Science Quarterly, vol. 36, pp. 219-44, 1991. [42] Festinger, L., S. Schachter, and K. Back, Social Pressures of an Informal Groups: A Study of Human Factors of Housing, New York: Harper, 1950. [43] Lorrain, F., and H. C. White, “Structural equivalence of individuals in a social network,” Journal of Mathematical Sociology, vol. 1, pp. 49-80, 1971. [44] Burt, R. S., "A note on cooptation and definitions of constraint," Social structure and network analysis, P. V. Marsden and N. Lin, eds., Beverly Hill: Sage Publications., 1982. [45] Harkola, J., and A. Greve, “Diffusion of technology: cohesion or structural equivalence?,” in Academy of Management Meeting., Vancouver, 1995, pp. 422–426. [46] Shih, H.-Y., “Contagion effects of electronic commerce diffusion: Perspective from network analysis of industrial structure,”
[47] [48]
[49] [50] [51] [52] [53] [54] [55] [56]
[57] [58]
[59] [60] [61] [62]
Technological Forecasting & Social Change, vol. 75, no. 1, pp. 78-90, 2008. Kim, S., and E.-H. Shin, “A longitudinal analysis of globalization and regionalization in international trade: a social network approach,” Social Forces, vol. 81, no. 2, pp. 445-470, 2002. Shih, H.-Y., and T.-L. S. Chang, “International Diffusion of Embodied and Disembodied Technology: A Network Analysis Approach,” Technological Forecasting & Social Change, 2008, DOI: 10.1016/j.techfore.2008.09.001. Hall, B. H., A. B. Jaffe, and M. Trajtenberg, "The NBER patent citations data file: lessons, insights and methodological tools," National Bureau of Economic Research Working Paper No. 8498., 2001. Griliches, Z., R&D and Productivity, the Econometric Evidence, p.^pp. 382, Chicago and London: University of Chicago Press, 1998. Xu, B., and J. Wang, “Capital goods trade and R&D spillovers in the OECD,” Canadian Journal of Economics, vol. 32, pp. 1258-1274, 1999. Coleman, J. S., E. Katz, and H. Menzel, Medical Innovation: A Diffusion Study., New York: Bobbs Merrill, 1966. Eaton, J., and S. Kortum, “Engines of growth: domestic and foreign sources of innovation,” Japan and the World Economy, vol. 9, pp. 235-259, 1997. Kim, J. W., and H. K. Lee, “Embodied and disembodied international spillovers of R&D in OECD manufacturing industries,” Technovation, vol. 24, pp. 359-368, 2004. Cohen, W., and D. Levinthal, “Absorptive capacity: A new perspective on learning and innovation,” Administrative Science Quarterly, vol. 35, pp. 128-152, 1990. Breiger, R., S. Boorman, and P. Arabie, “An algorithm for clustering relation data with applications to social network analysis and comparison with multidimensional scaling,” Journal of Mathematical Psychology, vol. 12, pp. 328-383, 1975. Teece, D. J., “Capturing value from knowledge assets: the new economy, markets for knowhow, and intangible assets,” California Management Review, vol. 40, no. 3, pp. 55-79, 1998. Özçelik, E., and E. Taymaz, “Does innovativeness matter for international competitiveness in developing countries?: The case of Turkish manufacturing industries,” Research Policy, vol. 33, no. 3, pp. 409-424, 2004. Posner, M. V., “ International trade and technical change.,” Oxford Economic Papers, vol. 13, pp. 323-341, 1961. Kojima, K., Direct Foreign Investment: a Japanese Model of Multinational Business Operations, London: Croom Helm press., 1978. Geroski, P. A., “Models of technology diffusion,” Research Policy, vol. 29, pp. 603–625, 2000. Gong, G., and W. Keller, “Convergence and polarization in global income levels: a review of recent results on the role of international technology diffusion,” Research Policy, vol. 32, pp. 1055-1079, 2003.
APPENDIX 1 COUNTRIES OF INTERNATIONAL TECHNOLOGY DIFFUSION Argentina Canada Finland Hungary Italy New Zealand Russia Sweden United Kingdom
Australia Chile France Iceland Japan Norway Singapore Switzerland United States
Austria China Germany India Malaysia Philippines South Africa Taiwan
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Belgium Colombia Greece Indonesia Mexico Poland South Korea Thailand
Brazil Denmark Hong Kong Ireland Netherlands Portugal Spain Turkey
PICMET 2009 Proceedings, August 2-6, Portland, Oregon USA Š 2009 PICMET APPENDIX 2 VARIABLES AND DEFINITIONS Variable Innovative output
Full variable name Patents j,t+3
Definition
Source
International patents granted in year t+3
All types of patents granted by USPTO patent database USPTO in country j in year (t+3)
Aggregate R&D Expenditure
Total R&D expenditures
ITD R&D $ j,t Contagion effects 1 Cohesion (embodied)
Interaction within cohesive Interaction within cohesive group group via embodied form of via trade flows diffusion. Cohesion (disembodied) Interaction within cohesive Interaction within cohesive group group via disembodied form of via patent citations diffusion. Structural equivalence Relation in Structural Relation in Structural equivalence (embodied) equivalence via embodied form via trade flows of diffusion. Structural equivalence Relation in Structural Relation in Structural equivalence (disembodied) equivalence via disembodied via patent citations form of diffusion. 1. Trade flow data are based on imports of capital goods; Patents are granted by USPTO.
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IMD World Competitiveness Report Global Trade Information Services, Inc. (GTI) NBER Patent Citations Database Global Trade Information Services, Inc. (GTI) NBER Patent Citations Database