• The Journal of the Korea Contents Association
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• v.14 no.8
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• pp.394-405
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• 2014

Purposes of this study are to find difference in efficiency, productivity change and determinants on efficiency of life insurance industry between pre and post-execution of capital market law on the basis of pre(2005-2008) and post-execution(2009-2012) data. Main results of this research are as follows. First, there was no significant difference of mean value for efficiency between pre and post execution of capital market law. Second, difference of mean value for malmquist index between pre and post execution of capital market law was statistically significant at 5% level. This imply increase in productivity for post-execution of capital market law. Third, one of the important determinant for efficiency was the weight of life planner in both pre and post-execution of capital market law. The weight of life planner had significant positive effect on efficiency.

• Journal of Korean Society for Quality Management
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• v.44 no.4
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• pp.771-784
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• 2016

Purpose: The purpose of this study is to analyze the efficiency and productivity of the quality by integrating the product quality and service quality of global automobile brands from the customer's perspective. Methods: In this study, the data from JD Power and GoodCarBadCar.net were used to analyze the efficiency and productivity of a total of 24 automobile brands (10 luxury brands and 14 mainstream brands) between 2009 and 2013. For this, DEA (Data Envelopment Analysis) and MPI (Malmquist Productivity Index) were used. Results: The mean efficiency of the quality of global automobile brands were 0.725 for luxury brands and 0.587 for mainstream brands, which suggests generally higher efficiency for luxury brands. The productivity of the quality of global automobile brands increased by 16.1% for luxury brands while it decreased by 3.1% for mainstream brands. Conclusion: The study provides a theoretical implication in that it emphasized the efficiency of the quality viewed from the customer's perspective, and investigated the quality of the product and that of service in an integrative manner. In addition, this study provides also a practical implication in that it suggests how to set the sales goal by the brand and how to manage according to the characteristics of the brand to the managers of automobile manufacturers.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.10
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• pp.109-117
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• 2021

This study investigates the effects of FDI and other macroeconomic variables on Total Factor Productivity (TFP) in selected ASEAN+3 countries from 1981 till 2016. Total Factor Productivity (TFP) for each ASEAN+3 country was constructed using the Malmquist productivity index method. Then, a panel ARDL framework (dynamic heterogeneous panel), namely Pooled Mean Group (PMG), Mean Group (MG), and Dynamic Fixed Effect (DFE) are employed in examining the effects of FDI and other controlling variables on TFP. The new findings show that FDI has a significant and positive impact on TFP in the long run and the short run in ASEAN+3 countries. Besides, the results also reveal that in the long run, other variables such as the average number of years of schooling and the ratio of high-skilled to low-skilled labor also have a significant and positive effect on TFP. However, economic openness, government expenditure on R&D, and interaction between countries and FDI have a negative and significant impact on TFP. These findings implied that the recipient countries must ensure their political stability and offer various incentives to attract more investors. Furthermore, the influx of foreign investors, especially large ones and lower costs, should be encouraged by each country as FDI inflows can boost their TFP growth.

• Journal of Korea Trade
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• v.23 no.5
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• pp.27-44
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• 2019

Purpose - The purpose of this paper is to analyze the net effect of the green total factor productivity (GTFP) of China's manufacturing industry from the China-Korea Free Trade Area (China-Korea FTA) quantitatively. Design/methodology - Firstly, the Global Malmquist-Luenberger (GML) index based on the SBM directional distance function is used to measure the GTFP of China's manufacturing and analyze the driving force for its growth. Secondly, the regression discontinuity quantitative analysis is used to determine the impact of the China-Korea FTA on China's manufacturing GTFP. Findings - Our main findings can be summarized as follows: the China-Korea FTA has promoted the GTFP of China's manufacturing with an effect evaluation mainly resulting from green technology progress. And there is industry heterogeneity in the policy effect on the manufacturing GTFP due to the China-Korea FTA. Namely, policy promotion from the China-Korea FTA is more effective on the GTFP of equipment manufacturing than it is on those of other industries. Originality/value - First, an evaluation and analysis of the GTFP development of China's manufacturing that employs GML index based on SBM directional distance function. Second, a quantitative estimate of China-Korea FTA's net effect on China's manufacturing industrial GTFP that uses regression discontinuity analysis, which is considered to be the closest method to natural experiments and superior to other causal inference methods. Third, an in-depth discussion of the practical steps that China's manufacturing can take to improve GTFP development and integrate China-Korea FTA construction into economic development.

• The Journal of Fisheries Business Administration
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• v.50 no.2
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• pp.41-56
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• 2019

The aim of this study is to analyze the productivity change of pollock enterprise by applying a mutually quadratic hyperbolic model and a bootstrapping model. This study used 20 units of pollock firms data (from 2013 to 2017). As a result of total productivity analysis of twenty pollock enterprises, total factor productivity was estimated to have decreased by 24.9% over the last five years (2013~2017). The main cause of this productivity decline was analyzed by technical change. In terms of annual productivity change, it showed decrease 3.0% in 2013~2014, 7.8% in 2014~2015, 4.5% in 2015~2016 and 4.7% in 2016~2017 respectively. In the analysis of productivity by corporation type, total factor productivity showed a significant decrease in both general corporation and external corporation, and productivity decrease (-29.3%) was larger than general corporation (-23.0%). In the productivity analysis by type of business, total factor productivity decreased significantly in the order of wholesale and commodity brokerage (-26.3%), food manufacturing (-25.1%) and fisheries (-15.3%). This decrease in productivity was caused by the technological change which indicates a downward shift in the production curve that is significant in all sectors.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.361-374
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• 2021

The purpose of this study is to analyze the efficiency and productivity of technological innovation activities of companies certified as innovative pharmaceutical companies by the government to diagnose their competitiveness and derive measures to strengthen them. This study collected pharmaceutical input (R&D expenditures and number of employees) and output (sale, operating profit and patent) data between 2017 and 2019 for 38 innovative pharmaceutical companies. This study analyzed them using the data envelopment analysis (DEA) method, Tobit model and the Malmquist Productivity Index (MPI). First, the DEA result of the innovative pharmaceutical companies show that between the value of the CCR model of the scale efficiency and the value of the BCC model to diagnose the internal operation efficiency is differences. Second, efficiency does not differ between corporate characteristics. Third, Tobit model shows that number of patents held have positive effects on efficiency. Forth, overall MPI is 0.89. This can be interpreted as the rate of TECI decreased 3%p and TCI has increased 4%p. The results of this study can be used as decision-making data for response strategies to improve efficiency by identifying the cause of inefficiency and presenting target values.

• Journal of Technology Innovation
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• v.19 no.1
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• pp.1-27
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• 2011

This paper aims to measure and analyze R&D productivities and efficiencies of 17 major OECD countries including Korea over the 1984-2008 period by using the Malmquist Productivity Index and Data Envelopment Analysis, classifying R&D performance into an output and outcome aspects. It also searches the Korea's current status and characteristics in each R&D stage to enhance Total Factor Productivity (TFP) compared with other developed countries. Our major findings are the followings: (i) Korea's productivity index of R&D input vis-a-vis R&D output is very high (13.39% annual growth rate) compared with those of major advanced countries, whereas the annual average of efficiency index is very low (0.33), i.e. Korea's technical efficiency index has risen to 0.83 at the last time series started at 0.10 point and come up to the level of major advanced countries. (ii) the Korea's productivity index of R&D output vis-a-vis R&D outcome is very low (14.02% annual reduction rate) compared with those of major advanced countries, whereas the annual average of efficiency index is very high (0.22), i.e. Korea's integrated frontier technical efficiency index has dropped to 0.057 at the last time series started at 1.00 point and coming up to the level of major advanced countries. (iii) The productivity of R&D input vis-a-vis R&D outcome is positively correlated with that of R&D output vis-a-vis R&D outcome and the growth of R&D input factors. In a nutshell, it implicates that the effort to take advantage of R&D outputs, namely establishing the diffusion and commercialization system of technical knowledge to the level of developed countries, should be strengthened over that on the growth of R&D investment and output for enhancing R&D productivity and efficiency in Korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.532-542
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• 2020

Due to abnormal weather conditions such as high temperature, the management of greenhouse rose farms is getting worse. In order to enhance the competitiveness of these farms, new measures are needed to improve their management performance. Therefore, this study suggests alternatives to improve the efficiency and productivity by identifying the causes of inefficiency of greenhouse rose farms in terms of management performance analysis through DEA analysis and MPI analysis. As a result of DEA analysis, the average TE of farmers increased from 0.867('16) to 0.905('17), but decreased to 0.850 in 2018, indicating that it was inefficient. In order to increase the management efficiency of farmers, efforts to preferentially reduce the costs (equipment, employment labor, fertilizer, facilities, seeds) that cause inefficiencies are needed. As a result of MPI analysis, TECI decreased from 1.044(T2) to 0.939(T3), which was the cause of the MPI decrease, and the TCI was rather increased from 0.958(T2) to 0.969(T3). In other words, it means that the decrease in productivity is due to insufficient utilization of potential production technology rather than the slowing of technological progress. This implies that it is important to provide technical guidance on utilization after technology dissemination.

• Journal of Digital Convergence
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• v.18 no.1
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• pp.35-44
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• 2020

The purpose of this paper is to investigate various factors affecting the efficiency of China IC industry, reflecting the resource utilization and overall development level of China IC industry. In this paper, three input indicators (R&D Expenditure, Cash paid to and for employees, Total fixed assets) and two output indicators (Net profit, Sales revenue) were selected for 17 listed companies in the IC industry with operating profit of less than 1 billion yuan in 2018 and applied the technology efficiency theory and DEA analysis method to analyze the relative efficiency of the output base. The study found that one of the 17 companies analyzed was efficient, two were inefficient on an inadequate scale, and the rest were inefficient due to insufficient production technology, scale and management level. This study argues that enterprises should reduce resource input appropriately and strengthen scientific and technological innovation management to maximize resource utilization efficiency. Therefore, this study has important practical significance for improving the efficiency of IC enterprises. The Malmquist method will be used to study the total factor productivity of small and Medium-sized companies in IC industry.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.2 no.4
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• pp.71-102
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• 2007

There were many comprehensive analyses conducted within the existing research activities wherein factors affecting technology progress including investment in R&D vis-${\Box}$-vis their influences act as the determinants of TFP. Note, however, that there were few comprehensive analysis in the industrial research performed regarding the impact of the economy of scale as it affects TFP; most of these research studies dealt with the analysis of the non -parametric Malmquist productivity index or used the stochastic frontier production function models. No comprehensive analysis on the impacts of individual independent variables affecting TFP was performed. Therefore, this study obtained the TFP increase rate of each industry by analyzing the factors of the existing growth accounting equation and comprehensively analyzed the TFP determinants by constructing a comprehensive analysis model considering the investment in R&D and economy of scale (smallness by industry) as the influencers of TFP by industry. First, for the TFP increase rate of the 15 industries as a whole, the annual average increase rate for 1993${\sim}$ 1997 was approximately 3.8% only; during 1999${\sim}$ 2000 following the foreign exchange crisis, however, the annual increase rate rose to approximately 7.8%. By industry, the annual average increase rate of TFP between 1993 and 2000 stood at 11.6%, the highest in the electrical and electronic equipment manufacturing business and IT manufacturing sector. In contrast, a -0.4% increase rate was recorded in the furniture and other product manufacturing sectors. In the case of the service industry, the TFP increase rate was 7.3% in the transportation, warehousing, and communication sectors. This is much higher than the 2.9% posted in the electricity, water, and gas sectors and -3.7% recorded in the wholesale, food, and hotel businesses. The results of the comprehensive analysis conducted on the determinants of TFP showed that the correlations between R&D and TFP in general were positive (+) correlations whose significance has yet to be validated; in the model where the self-employed and unpaid family workers were used as proxy variables indicating the smallness of industry out of the total number of workers, however, significant negative (-) correlations were noted. On the other hand, the estimation factors of variables surrogating the smallness of scale in each industry showed that a consistently high "smallness of scale" in an industry means a decrease in the increase rate of TFP in the same industry.