• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.595-605
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• 2021

The objectives of this research are to see if the phenomena of "demand following" and "supply leading" exist in the business cycle, as well as to look at how liquidity and output react to changes in credit risk, investment-saving gap, inflation, exchange rate, and growth rate of real national output. Employing quarterly data of Maluku and North Maluku (2008-2019), this study utilizes VAR/VECM for inferential analysis. This research found three important findings. First, liquidity and output growth influenced each other in the long run. Second, the determinants of output growth for Maluku are liquidity, investment-saving gap, and inflation, while the determinants of liquidity are output-growth, the gap of investment-saving, and inflation. Third, the determinants of output growth for North Maluku are liquidity, credit risk, investment-saving gap, inflation, exchange rate, and the national output-growth, while the determinants of liquidity are output-growth, credit risk, investment-saving gap, inflation, exchange rate, and national output-growth. The findings of this study supported the hypothesis of demand following and supply leading theory in the Maluku and North Maluku business cycles. This study concludes that economic development would improve if supported by liquidity adequacy through increased deposit growth.

• Journal of Korea Technology Innovation Society
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• v.6 no.3
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• pp.328-344
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• 2003

This paper is aimed at analyzing the effect of Information Technology (IT) investment on the output growth and Total Factor Productivity (TFP) of Korean stock industry. Data on 24 stock firms for the eleven years (1991-2001) are used for the analysis. It is identified that there are both direct and indirect impacts of IT investment of the Korean stock industry on output growth. The total effect on output growth is 1.34 percentage point per year, which divided into a direct effect of investment in IT on the output growth is 1.97 and an indirect effect on the TFP is -0.63 percentage points per year. Results show that IT investment cannot contribute to increased stock industry productivity. Therefore, the Korean stock industry has not benefited from increased investment on IT in increasing productivity, implying the so-called productivity paradox has existed during the period.

• Asia-Pacific Journal of Business
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• v.10 no.3
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• pp.1-16
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• 2019

This paper examines how firm's investment has been affected by offshoring and financialization in Korea over the period 2000-2014 by using industry-level data collected from World Input Output Database (WIOD) and firm-level data collected from the KIS-Value Database. The findings are summarized as follows. First, offshoring index as expected shows a negative relationship with real investment. This negative impact is stronger in a large firm group. Second, there is a positive relationship between dividend payments and real investment. The positive relationship is greater in a small & medium-sized firm group. Third, the purchase of financial assets and the income generated from financial assets are positively related to real investment. The positive relationship is stronger in the small & medium-sized firm group. The empirical results show that firm size is a factor that effectively affects firm's real investment. This paper suggests that the influence of financialization and offshoring on firm's real investment should be assessed in various contexts rather than in a unilateral context.

• Environmental and Resource Economics Review
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• v.16 no.2
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• pp.313-336
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• 2007

The paper is concerned with, firstly, estimating the North Korean input-output table in which energy sectors like electricity and petro products are specified and, secondly, computing the effect of an investment in the energy sector on North Korean economy, by using the estimated input-output table and applying CGE analysis. The 4,000 million dollar investment on North Korean electricity industry produces 368 million dollar worth of output and 156 million dollar worth of value added. The 150 million dollar investment on petro industry creates about 20.5 million dollar worth of output and 9.65 million dollar worth of value added in North Korea.

• The Journal of Information Systems
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• v.29 no.3
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• pp.159-178
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• 2020

Purpose The purpose of this study is to demonstrate the relationship between ICT(Information & communication technology) infrastructure, investment environment, and innovation performance from a national perspective. Design/methodology/approach We derived 5 hypotheses based on the literature review. To measure each concept, We converted the scores of each country provided by the Global Innovation Index into a 7 Likert scale and performed a regression analysis. Findings According to the empirical analysis result, this study confirmed that knowledge and technology output mediated the relationship between ICT infrastructure and creative goods and services. In addition, this study confirmed that the investment environment has a moderating effect between ICT infrastructure and knowledge and technology output.

• Journal of Korea Technology Innovation Society
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• v.7 no.2
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• pp.325-349
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• 2004

This paper tried to evaluate an economic analysis about research and development far areas of renewable resource in Korea. To evaluate this validity, we tried to calculate the spillover effect of R＆D investment through input-output table. In the first stage of spillover effect, we simply calculate the rate of return on R＆D investment for renewable energy resources in Korea through the input-output model, which can calculate the value added as well as output based upon the price of 2000 year. According to the first stage calculation, the rate of return on R＆B investment in solar heat is higher than any other renewable energy. In the second stage we tried to calculate the second round of spill over effect, which derives from the additional amount of supply of renewable resources due to the R＆D investment. The overall evaluation of R＆D invesment including the first stage as well as second stage spillover effect shows that bio-energy and waste energy generate 14 times as well as 2.5 times in the rate of return respectively.

• Journal of Information Technology Services
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• v.15 no.2
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• pp.51-63
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• 2016

In this study, we conducted a comparative analysis of R&D investment efficiency and operational efficiency of IT firms using Data Envelopment Analysis (DEA). We categorized thirteen sample firms into two groups-IT manufacturing and IT service-after an extensive literature review on IT industry classification. We adopted an output-oriented two-stage DEA model suggested by Banker et al. (1984) with total asset and R&D investment as input variables. Then, we constructed investment efficiency and operational efficiency by using Return on Equity (ROE) and Return on Asset (ROA) as intervening variables and operating income and Earnings Per Share (EPS) as output variables. The outcome of the analysis is summarized as follows. First of all, IT manufacturing firms were more efficient (57% on average) than IT service firms. To be specific, IT service firms showed decreasing returns to scale (DRS) with diseconomy of scale. In contrast, IT service firms showed higher operational efficiency (81.5% on average) than IT manufacturing firms. Also, we conducted a Mann-Whitney U test to compare the output of IT service firms and IT manufacturing firms. Lastly, we found a negative correlation ($R^2$ = -.754) between R&D investment efficiency and operational efficiency which infers the trade-off between two constructs

• Journal of Technology Innovation
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• v.15 no.1
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• pp.203-233
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• 2007

This study investigates how characteristics in the value-chain industrial cluster affect the R&D investment and the output of firms in each industries. For this, we try to extract the inter-industrial networking structure from the input-output table in which 17 manufacturing sectors are included. In particular, we will give shape to the "unit structure" which shows the intermediary flows of goods and services between industries in order to get an unit of final demand in a certain industry. Using this "unit structure", we can try the inter-industrial networking analysis and get some indices of centrality and centralization related to the characteristics of each industries in the value-chain industrial cluster. The results show that the centrality in the value-chain industrial cluster does not have any consequence for the R&D investment and the output in each industries. However, there is a correlation between the centralization in the value-chain industrial cluster and the R&D investment and the output of firms in each industries. These results may be very suggestive in bringing up a new frame of industrial cluster policy in a macro level.

• International Area Studies Review
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• v.15 no.2
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• pp.51-76
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• 2011

Since Japanese government took reformative measures of public investment in the period of 2000s, this paper investigates how the economic effects of public investments has improved in the period of 2000s. The empirical findings do not show that the output elasticity with respect to public capital has been higher in the 2000s than that of 1990s. Rather, some output elasticity estimates for 2000s has lowered after the advent of year 2000. In addition, the impact of public capital on the productivity of private capital has not improved in the 2000s compared with that of 1990s in Japan. Another major finding shows that the crowding-out effect of public investment has been stronger in the 2000s than before. Those findings imply that the reforms done by Japanese government in the 2000s regarding public investment do not spread out into the private aggregate production and investment.

• Journal of the Korean Professional Engineers Association
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• v.32 no.6
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• pp.40-43
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• 1999

The R&D productivity has the same meaning as that of general meaning. Its input includes budget, facility, schedule, idea and target, and its output includes patent, paper, technological innovation and revenue increase and technology accumulation influenced by these factors. The choice of R&D item which will have the large effectiveness after customization, resource input of proper level, application of efficient development schema, effective usage of development output, objective appraisal for the R&D output and extension for the future project are the main factors for which is suggested to enhance the R&D productivity. The management's expectation for R&D can be represented as the innovativeness of output and potential influence to outsiders. The speedy output, even if incremental investment more than planning happens, will eventually result in the productivity enhancement of the enterprise, and managers must not encounter the opportunity loss in return for the excessive investment control.