技术创新面临的障碍外文文献翻译.docx

1、技术创新面临的障碍外文文献翻译技术创新面临的障碍外文翻译2019-2020英文Barriers to the international diffusion of technological innovationsSanjesh Kumar，Baljeet SinghAbstractThis paper examines the role of diffusion barriers in explaining differences in technological innovation across countries through an index of economic complex

2、ity. The barriers are captured by genealogical distance from the worlds technology frontier. We hypothesize that greater the genetic distance between a countrys population and the technology innovator the lower will be levels of technological innovations. Utilizing data for 100 countries, our empiri

3、cal estimates offer solid support for the negative influence of genetic distance from the global frontier on innovation. A number of sensitivity checks also confirm that our findings are robust. Overall, the evidence lends strong support to the barriers effect of genetic distance from the frontier w

4、hereby it prevents the diffusion of productivity enhancing innovations across countries by affecting the countrys capability to imitate and adopt frontier innovations and technologies.Keywords：Genetic distance，Innovation，Economic complexityIntroductionThis paper seeks to bring forth empirical eviden

5、ce to highlight the significance of barriers that hold back technological innovations from spreading across countries. In particular, it focuses on human barriers which are measured using genetic distance between a laggard country and the global technology frontier. To this end, the study analyses t

6、he influence that genetic distance has on country specific economic complexity index (ECI). FollowingSweet and Eterovic Maggio (2015), we used ECI as proxy of innovation because an improvement in ECI implies that a country is improving its production capacity as well as creating innovation that is e

7、ssential for its prosperity (Hausmann etal., 2013). More importantly, innovation is an accumulative process, which is obtained by accumulation of both “tacit” and “explicit” knowledge; using patent as an indicator of innovation reflects only the “explicit” component of innovative activities (Nelson,

8、 2005;Sweet and Eterovic Maggio, 2015). On the contrary, genetic links promotes progressive accumulation of “tacit” knowledge through a series of social relationships and networks. Hence, the impact of genetic distance on innovation could be more effectively captured through ECI as a measure of tech

9、nological progress compared to any other indicator.Technological innovation is essential for supporting economic growth and development (Romer, 1986;Lucas, 1988). Recently, a number of studies have tried to explore the determinants of innovation in developed as well as developing countries (Aghion a

10、nd Howitt, 1998;Guloglu etal., 2012;Ang and Kumar, 2014;Chen etal., 2018;Zhou etal., 2019). Some of these studies suggest that factors such as organizational ability of a firm, resources available for research purpose and spillover across business entities and nations as well as quality of instituti

11、ons are crucial for innovation. While other studies argue that factors such as interest rates, foreign capital, and domestic income are important determinant of innovation. Despite the extensive literature, there is lack of consensus on what limits the diffusion and adaptation of productivity-improv

12、ing technologies across different societies.More recently, a stream of researchers on innovation, such asLundvall (1988)andAlvarez etal. (2013)argue that creative and innovative learning takes place through interactive activities. Studies such asJovanovic and Rob (1989),Ang (2018)andAzis (2019)attri

13、bute formulation of new innovation to interaction between agents with diverse prior knowledge.Cattani and Ferriani (2008)andBuera and Oberfield (2016)argue that social networks shape an individuals ability to generate creative outcomes.Mejia (2018)using a case study of Colombia demonstrates that ind

14、ividuals that have better capacity to engage with different components of social web have better chances of emerging as industrial entrepreneurs in the initial stage of industrialization. Likewise,Dudley (2012)finds similar evidence for the British industries. However, a series of literature identif

15、y genetic link as an important factor in formulation of a social network among individuals. According to the inclusive fitness theory (Hamilton, 1964), people are generally able to detect those who have similar traits as themselves and prefer to interact with those that resemble themselves. Individu

16、als and societies prefer to form social networks and they are willing to cooperate with other people or groups that share similar genetics. This literature highlights that genetics and a series of social relationships are highly related.Moreover, there is ample evidence to show that some countries s

17、hare close genetic links while there is significant genetic distances among other countries. In line with inclusive fitness theory, countries that share similar genetic links with frontier countries will most probably have high levels of social interaction and collaboration with frontier countries w

18、hich is likely to transfer innovation more easily to laggard countries. Moreover, genetically linked countries are expected to cooperate more because of similar language, comparable commercial operation, common economic and social interest (Chaudhry and Ikram, 2015). In contrast, populations which a

19、re very different genetically from each other incline to differ in many of these attributes, which can potentially hold back the free flow of technology and knowledge because it imposes costs on adaptation and imitation. Moreover, a laggard country which is not genetically close to a frontier countr

20、y is likely to receive less social interaction and cooperation from firms and citizens of a frontier country, and hence their overall innovation will be less. Generally, there can be a lack of trust between firms and citizens of frontier country and laggard country whose citizens do not share simila

21、r cultural and genetic traits.Using the insight from the above literature, we hypothesize that dissimilarities in these genetic attributes between societies limit the sharing and communication of new ideas. Limited flow of ideas lowers the prospects for learning, copying and embracing new technology

22、, thereby serving as an obstacle to the dissemination of technology from the frontier to laggard countries. Contrarily, countries that share similar genetic characteristics with the technology leader can facilitate the dissemination of knowledge more effectively as there is more significant interact

23、ion between genetically similar countries due to common ethnic and cultural characteristics, languages, beliefs and practices. Effective social interaction between frontier and laggard countries facilitate greater flow of ideas and innovation from the frontier country which increases product innovat

24、ion in the laggard country.Using data on the index of economic complexity from 2000 to 2015 for 100 countries, we find genetic distance from the technological frontier (that is, USA) exerts a significant negative influence on innovations across countries. Our results hold even after controlling for

25、many other variables which are found influential in the literature on innovation. Moreover, additional analysis using cross-country panel data further confirm the consistency of the evidence provided. In general, our results lend strong support to the notion that the diffusion barrier effect of gene

26、tic distance from the frontier reduces innovation.Literature reviewGenetic distance and technological innovationA growing number of studies investigate the underlying drivers of technological innovation. The initial studies suggest that increasing investment in new technology is vital to ensure cont

27、inuous improvement in countrys technological advancement (Schumpeter, 1942;Abramovitz, 1956;Solow, 1956;Romer, 1990;Jones, 2002;Rath and Hermawan, 2019). Few studies have recently examined the capacity of nations to create and market a series of new innovation over the years (e.g.,Wu etal., 2017;Fur

28、man etal., 2002;Furman and Hayes, 2004;Hu and Mathews, 2005). The insight from this strand of literature is that in addition to financial and human resources invested in innovation, factors such as innovative environment in a countrys industrial sector, the linkage between common innovative infrastr

29、ucture and strength of relationships between a nations industrial sector are essential for improving a countrys creativity and technological advances (Porter and Stern, 2002;Furman and Hayes, 2004).On the other hand, scholars such asLundvall (1988)andSweet and Eterovic (2019)highlight that innovatio

30、n partly takes place through the tacit learning process. These studies further emphasize that collaboration, a series of social relationships and social networks are essential drivers of the tacit learning process.Cattani and Ferriani (2008)argue that social networks shape individuals ability to gen

31、erate creative outcomes. However, there is conclusive evidence in the literature that genetic link is a critical determinant of the strength of social relationships between individuals. According to Kin-selection theory, animals improve their wellbeing more by cooperating with their relations than t

32、o non-relations.Hamilton (1964)in an animal study shows that individual animals identify close relations through a number of channels such as familiarity and imprinting self on others.Hamilton (1975)extended his study to humans and deduced that level of cooperation between persons is to a large exte

33、nt determined by genetic relatedness. Hamiltons theory is generally known as “inclusive-fitness theory.” More recently, some studies applied inclusive-fitness theory to human studies and broadly find conclusive evidence that individuals maximize their inclusive fitness by engaging with those that have sim