• Economic and Environmental Geology
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• v.54 no.5
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• pp.573-580
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• 2021

This study analyzed the induced effects of the aggregate and stone sectors using the industry association table. First, the added value of the aggregate and stone sectors was summarized, and then the intermediate input structure and induced effect were analyzed. In terms of value-added structure, aggregate and stone showed a higher employee remuneration rate compared to the manufacturing industry, and a higher rate of operating surplus compared to other mining industries. The intermediate input structure summarizes the sector using aggregate and stone products as intermediate inputs and their input ratio. The proportion of the intermediate element input structure was confirmed. In addition, the main input sectors of ready-mixed concrete, the largest consumer of aggregate and stone, are also summarized. The production-inducing effect of aggregate and stone showed a higher influence coefficient than the sensitivity coefficient, confirming that they had a relatively large rear chain effect. The production inducement effect was reviewed by reconstructing the industry association table, and it was found to show a relative superiority in the influence coefficient, similar to the results derived according to the provisional classification of the Bank of Korea.

• Environmental and Resource Economics Review
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• v.26 no.4
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• pp.473-498
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• 2017

This study examines the effect of environmental regulation considering the endogeneity on the productivity of Korean manufacturing industry based on the Porter hypothesis using data from the Mining and Manufacturing Survey, Survey of Research and Development in Korea, and Environmental Statistics Portal from 2003 to 2013 with fixed effect model. In order to eliminate the bias of the missing variables that may occur in the existing studies, we analyze factors affecting productivity such as market competition, R&D investment as explanatory variables. And, in order to eliminate measurement error and inverse causality, we use instrumental variable approach. The main results are as follows. First, our findings that the environmental regulation improve the productivity of Korean manufacturing in the long-run support the Porter hypothesis. Second, our findings suggest that measurement error and reverse causality are main sources of the endogeneity, while omitted variable is not. Finally, environmental technology R&D has reduced productivity in the short-run.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.5897-5905
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• 2015

This paper investigates the differentials in productivity and growth performance between small and medium size and large size firms in Korean manufacturing industries. According to the empirical analysis based on the Mining and Manufacturing Survey of Statistics Korea, this paper finds the following facts. First, the level of contribution of capital deepening on the growth rate of output(value added) is relatively greater in the small and medium size firm group, while the level of contribution of total factor productivity on the growth rate is relatively greater in the large size firm group. Second, the productivity polarization among the firms has increased relatively greater in the large size firm group over the past decade.

• Journal of the Korean Geographical Society
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• v.28 no.4
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• pp.356-378
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• 1993

This study examines the competitiveness of urban industrial structure and its changing characteristics. Cluster analysis of Arizona towns based on economic functions revealed the changing characteristics of urban functions over time. The relationship between the changes of urban functions and industrial competitiveness was confirmed through shift-share analysis. The level of industrial specialization has become more closely related to urban size in terms of both population and employment, but the relationship between metropolitan location and specialization level is not clear. Also, it is validated that the economies of Arizona towns have become more diversified and, consequently, have tended to converge toward the state average in industrial structure over time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.492-498
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• 2021

This study examined how the emissions of pollutants affect the volume of traffic of freight vehicles in the transport sector. Multiple regression analysis was conducted considering several variables, including population by region, area of urban district, GDP, and the number of businesses by industry, e.g., agriculture, forestry, fishery, manufacturing, wholesale, and retail. These variables differ according to the characteristics of the freight vehicles (industry, by the ton). Therefore, it is essential to fully consider the volume of traffic of the specific freight vehicles by region before implementing relevant programs and policies, such as specific restrictions on the operation of vehicles. Some specific areas, in which logistic centers are located have heavy freight traffic, and these centers deserve extra consideration. Thus, in this study, different regional factors that affect the traffic of freight vehicles should be considered before determining the areas that will be subject to restrictions on the operation of these vehicles.

• Tunnel and Underground Space
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• v.32 no.1
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• pp.78-92
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• 2022

In this study, we proposed a diagnostics and assessment model for mining sites that can evaluate the smart mining technology level in a systematic and structured way. For this, the maturity of the smart mining was defined, and detailed assessment items of the diagnostics and assessment model for smart mining were derived by considering the smart factory diagnostics and assessment model (KS X 9001-3) used in the manufacturing industry. While maintaining the existing system, the existing 46 detailed assessment items were modified to be suitable for mining. As a result, a total of 29 detailed assessment items were derived in the areas of promotion strategy, process, information system and automation, and performance. Based on this, a questionnaire was designed to diagnose the level of smart mining technology, and assessment was performed by applying it to domestic iron mines. The level of smart mining technology in the study area was found to be level 2, and it could be inferred that it was about 40% lower than the average smart level of the general manufacturing industry. In addition, by using the developed model, it was possible to recognize the weak points of the mine at each stage of the introduction, operation, and advancement of smart mining, and to suggest investment and improvement directions.