• Knowledge Management Research
• /
• v.20 no.1
• /
• pp.27-43
• /
• 2019

This paper examines spillover effects of R&D investment in the ICT industry to other industries by analyzing panel data composed of 6 manufacturing industries for the period of 1983~2011. Major findings are as follows; (1) The increase of R&D investment in ICT industry has a significantly positive relationship with the increase in the value-added of the remaining 5 industries with 3~10 year lags, depending on the source of R&D funds and R&D stage. (2) More specifically, public R&D shows the spillover effects during 3~7-year lag periods, whereas private R&D started to exert spillover effects from 9-year lag. The result implies that the public R&D appropriately targets projects with more spillover effects. (3) Basic research, applied research, and development showed the spillover effects for the period of 9~10, 7~10, and 10-year lag, respectively. (4) The R&D investment in 5 other industries such as machinery, chemicals, and materials does not have positive spillover effects to the remaining industries. Few studies have been done to analyze the R&D spillover effects to other industries, with certain limitations. This study contributes to the existing literature by analyzing the spillover effects of the different R&D funds and R&D stages, and by considering various time-lag effects.

• World Technopolis Review
• /
• v.3 no.3
• /
• pp.122-138
• /
• 2014

The number of environment-related technologies has increased remarkably over the past two decades, as has the public's interest in effective resource use and ways to reduce the effects of global warming. Industries that are based on environment-related technologies are thus growing rapidly. Previous studies revealed that externalities derived from the population concentration in urban areas positively affect agglomerations of high-tech industries. Such externalities have been named the "knowledge spillover effect". The purposes of the present paper are to (1) give a thumbnail sketch of the locations of environment-related industries around the world, using the Organisation for Economic Co-operation and Development environment-related patent statistics, and (2) explicate the effects of the Marshall-Arrow-Romer (MAR) and Jacobs externalities, which result from population concentrations in urban areas, on the agglomeration of environment-related industries in Sweden. The analysis revealed that environment-related industries are located chiefly in urban areas across the globe, and that only the MAR externalities influenced positively on the agglomeration of these industries in Sweden.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.10 no.1
• /
• pp.86-93
• /
• 2007

The objective of this paper is to examine the structure of technology spillover from UAV(unmanned air vehicle) technology to other industries by applying patents analysis. The network analysis on patent data of USPTO(United Stated Patents and Trademark Office) from 1981 to 2000 was adopted to investigate the characteristic change of the technology spillover The results show that the influence of the UAV technology to other industries has grown over the twenty years period. For the weapon system development, this study provides a research basis to estimate the technology spillover effects on industries. Searching a structural niche from the inter-industrial knowledge flow structure might be a useful technique to find core technologies which generate large technology spillover on the other industries.

• Asian Journal of Innovation and Policy
• /
• v.6 no.1
• /
• pp.94-110
• /
• 2017

This paper approaches knowledge capital as social infrastructure and analyzes its impact on economic growth. To this end, we constructed a panel dataset for 120 countries for the years 2000-2014 and estimated the economic growth function using the panel analysis. As proxies for knowledge capital, we used the R&D expenditure per capita and the number of patent applications per thousand people in each country, both measured in stock. Economic growth was measured in terms of real GDP per capita and real value added per capita at the industry level. The empirical findings demonstrate that knowledge capital accumulated in a society significantly promotes economic growth. Especially R&D stock increases real value added per capita in all industries-not only manufacturing, but also services and agriculture-implying substantial inter-industry spillover effects. The findings of this study suggest that knowledge capital boosts economic growth as core social infrastructure.

• Journal of Technology Innovation
• /
• v.31 no.2
• /
• pp.263-301
• /
• 2023

This study analyzes whether the network characteristics lead to differences in innovation performance between inventors, using the case of Samsung Electronics and Hyundai Motor Company which have applied for the most patents in the electronics and automobile industries while showing significant differences in the degree of collaborative invention. The more inventors an inventor is connected with in the network, the higher innovation performance is achieved. While existing literature addressed intra- / interindustry, and intra- / inter- group spillovers at the organizational level, this study extends this discussion to the inventor level. This study newly introduces spillover pools from network components and then constructs spillover pools in three dimensions of the group, the industry, and the network component. The study analyzes the effects of each spillover pool on invention performance of an individual inventor and compares the effects between spillover pools. At the inventor level, the innovative effects of spillover pools were confirmed. The results of this study suggest that the inventor's network characteristics and spillover pools can be used to predict the inventor's innovation performance.

• Journal of Technology Innovation
• /
• v.8 no.1
• /
• pp.73-94
• /
• 2000

The main objective of this research is to examine the spillover effects of technological knowledge from IT industry to other industrial sectors and, based on empirical findings, to draw policy implications and suggest policy directions. To this end, we divide IT industry into IT equipment and IT service, assuming that these two sub-sectors are considerably different each other in terms of technology knowledge flow. Other industries are classified into 17 different sectors based on the KSIC of 1990. As the proxy measure of technological knowledge, the notion of R&D stock is employed. The Input/output(I/O) Table is used to define the inter-industrial flow pattern and to draw the knowledge flow matrix. As the research methodology, cost function model is employed to gauge the spillover effects of technological knowledge of IT industry. Based on the results of analysis, it is found that the economic impact of technology diffusion also exhibits a different pattern between IT equipment and IT service. The diffusion of IT equipment tends to show labor-substitution effect whereas IT service displays labor-creation effect. This fact should be considered in devising industry, education, and labor policy. The expectations from this research are as follows. First, the sectoral pattern, difference between IT equipment and service in particular, identified from this research may shed light on the sector-specific policy direction. It is emphasized that a sector-specific approach, rather than an aggregate approach, is relevant for formulating IT policy. Second, it is expected that the importance of technology diffusion programs and policy measures are recognized among policy makers in IT industry.

• KDI Journal of Economic Policy
• /
• v.34 no.1
• /
• pp.87-133
• /
• 2012

This paper consists of two parts. The first part introduces a simple endogenous growth model. It is based on Romer(1990), but extends the original model by incorporating individual workers skill heterogeneity. Based on the heterogeneity, the model has a labor allocation mechanism between skilled (research) and unskilled (production) sectors. Different from Romer(1990), the labor allocation is determined by both demand and supply conditions of the economy. The endogenous growth model presented in this paper shows how the shape of the distribution of human capital affects on the labor allocation, hence on the employment structure, wage profile and economic growth. The model can be extended to an open economy. With the heterogeneity, the extended model explains distributional effect as well as growth effect of the economic openness. The second part provides empirical evidence in support of the extension part of the model presented in the first part. Based on the endogenous growth framework as proposed by Romer(1990) and Rivera-Batiz and Romer(1991), the model explains how economic openness affects labor allocation between skilled and unskilled sectors. According to the model, economic openness can affect labor allocation through two channels; knowledge spillover and specialization. First, the openness promotes knowledge spillover and hence increases the productivity of workers in the skilled sectors. This makes the economy employs more workers in the skilled sector. On the other hand, the openness causes global specialization which leads more employment in the skilled sector for the developed countries but at the same time, leads less employment in the skilled sector for the developing countries since the developing countries have comparative advantages in the unskilled sector. The empirical results obtained using cross country panel data in this paper support these two effects of knowledge spillover and specialization.

• International Commerce and Information Review
• /
• v.11 no.3
• /
• pp.191-215
• /
• 2009

This study extends the previous research into the effects of knowledge spillovers on innovation and regional exports growth by more clearly distinguishing, both theoretically and empirically, two different types of knowledge spillovers, namely product and market knowledge spillovers. More importantly, this research provides insights on their role of knowledge spillovers in shaping regional innovative activities and, eventually, regional export growths. Furthermore, this research makes an important contribution to the understudied market knowledge spillovers by developing two variables that could be used to assess the flow of market knowledge spillovers at the regional level: localization economies and export consulting advice. Using secondary data on eight 2-digit manufacturing industries in ten New Zealand regions over a seven year period, this research found that regional competition, localization economies and the availability of export consulting advice have positively and significantly impact on the regional export growth in New Zealand.

• International Commerce and Information Review
• /
• v.2 no.1
• /
• pp.3-24
• /
• 2009

This study extends the previous research into the effects of knowledge spillovers on innovation and regional exports growth by more clearly distinguishing, both theoretically and empirically, two different types of knowledge spillovers, namely product and market knowledge spillovers. More importantly, this research provides insights on their role of knowledge spillovers in shaping regional innovative activities and, eventually, regional export growths. Furthermore, this research makes an important contribution to the understudied market knowledge spillovers by developing two variables that could be used to assess the flow of market knowledge spillovers at the regional level: localization economies and export consulting advice. Using secondary data on eight 2-digit manufacturing industries in ten New Zealand regions over a seven year period, this research found that regional competition, localization economies and the availability of export consulting advice have positively and significantly impact on the regional export growth in New Zealand.

• Knowledge Management Research
• /
• v.10 no.3
• /
• pp.115-132
• /
• 2009

This paper makes an analysis of economic spillover effects of credit guarantee by linking the remainder of guarantee according to industries from 2003 to 2006 in this study. Specifically, total remainder of guarantee in 2006 is approximately 3922 billion and 600 million won on the basis of unchangeable price in 2003, and each funds becomes the input of the last demand in 27 industries over the cow1try and, thereby, induces production, added value, and the effect of employment. The last demand according to industries shows that a lot of funds have been supported to the manufacturing industry for about 1200 billion won, the wholesale and retail for about 1299 billion and 500 million won, food and lodging industry for about 144 billion and 100 million won, education and health care industry for about 132 billion and 600 million won, and social and other service industry for about 339 billion and 300 million won. The spillover effect about the remainder of guarantee in 2006 classified by industries over the country on the basis of production shows the high effects on the manufacturing industry for 37.8%, 2625 billion and 90 million won, the wholesale and retail for 20.7%, 1439 billion and 290 million won, food and lodging industry for 9.4%, 654 billion and 570 million won, real estate and business service industry for 9.2%, 637 billion and 310 million won, social and other service industry for 5.3%, 369 billion and 90 million won, and education and health care industry for 2.9%, 199 billion and 300 million won of the effect causing production over the country, 6945 billion won in order. The effect causing added value shows high spillover effect on the wholesale and retail for 36.7%, 1186 billion and 830 million won, the manufacturing industry for 25.8%, 831 billion and 500 million won, food and lodging industry for 14.9%, 480 billion and 980 million won, social and other service industry for 9.3%. 300 billion and 160 million won, and real estate and business service industry for 4.2%, 135 billion and 36 million won of the effect causing added value over the country in order. Finally, the effect causing employment shows a lot of employment have occurred in the wholesale and retail for 37.4%, 23,060 people, the manufacturing industry for 18.9%, 11,637 people, food and lodging industry for 13.7%, 8,429 people, social and other service industry for 7.9%, 4,866 people, and real estate and business service industry for 5.6%, 3,429 people of 61,617 people in order.