• Journal of the Korean Regional Science Association
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• v.11 no.2
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• pp.41-51
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• 1995

It has been estimated the total factor productivity(TFP)of the city of Seoul. Average TFP growth rate during 1974-1992 has been estimated as 0.0602. TFP growth rate has been decreased from 0.0804 of 1970's to 0.0561 of 1980 and 1990's Factsro affecting the TFP are found to be core infrastructure, capital stock and land price growth rate. High land price growth rate depresses the TFP growth rate. During 1989, due to the high land price growth rate and extremely low building costruction permit TFP rate has been estimated as negative.

• 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.

• Food Science of Animal Resources
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• v.23 no.1
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• pp.80-85
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• 2003

This study was carried out to investigate antimicrobial and antitumoral activities of Candida kefyr TFP7 isolated from Tibetan fermented milk Strains of TFP1∼10 were isolated from Tibetan fermented milk by agar diffusion method using potato dextrose agar(PDA). Antimicrobial activities were examined against 18 microorganisms of food-related bacteria, yeast, algae, fungi and actinomycetes isolated from soil. Antitumor activities were examined against 9 human tumor cell lines. Strains of TFP2∼10 showed strong antimicrobial activities against Micrococcus luteus ATCC l1880, and strains of TFP6∼10 to actinomycetes, Streptomyces murinus JCM 4333. In antitumor test, all isolated strains(TEP1∼10) showed the growth inhibition of SNU-5 and SW-534 by 60% and 70%, respectively. Among those, the strain TFP7 showed the most antitumor activity, which was 77.5% for SNU-5 and 76.5% for SW-534. The strain was identified as Candida kefyr by use of API 20C AUX kit and scanning electron micrograph.

• KDI Journal of Economic Policy
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• v.37 no.3
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• pp.31-53
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• 2015

According to the macroeconomic allocation efficiency measure, particularly based on the methodology of Hsieh and Klenow (2009), Korea's allocation efficiency in the manufacturing industry deteriorated in the 2000s compared to that in the 1990s. This study compares the potential TFP gain when resource allocation is removed, an indicator of allocation inefficiency according to Hsieh and Klenow (2009), and the productivity dispersion in the Korean manufacturing industry. It finds that the TFP gain may be better explained by TFP dispersions rather than proxies related to factors of distortion. The findings imply that we should investigate the sources of TFP dispersion rather than the sources of distortion to explain increases in the TFP gain (or TFP loss), which is considered as allocation inefficiency in the literature.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.411-417
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• 2021

This study aims to estimate the production function and total factor productivity (TFP) of Vietnamese seafood processing firms. At the same time, the study analyses the impact of internal factors of firms and the quality of economic institutions on the TFP of the Vietnamese seafood processing industry. The study uses the Function Control (FC) approach in TFP estimation and the Feasible Generalized Least Squares (FGLS) regression model in the analysis of factors affecting TFP. The study was carried out on the census data of enterprises of the Vietnamese seafood processing industry collected by the Vietnamese General Statistics Office and Provincial Competitiveness Index data of Vietnam Chamber of Commerce and Industry in the period from 2013 to 2018. Estimated results from the models show that: i) Vietnamese seafood processing firms are, currently, mainly labor-intensive, the TFP contribution and output is only about 2.258. ii) Factors such as the firm's age, firm's size, and the firm's ownership affect TFP. In which, firms that have few numbers of years of operation, small and medium firms, and private firms have low TFP. iii) Institutional quality and the provincial business environment have a positive impact on the TFP of Vietnamese seafood processing firms in this period.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.6
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• pp.59-72
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• 2012

Since a protein displays its specific functions when disorder region of protein sequence transits to order region with provoking a biological reaction, the separation of disorder region and order region from the sequence data is urgently necessary for predicting three dimensional structure and characteristics of the protein. To classify the disorder and order region efficiently, this paper proposes a classification/prediction method using sequence data while acquiring a non-biased result on a specific characteristics of protein and improving the classification speed. The emerging patterns based EPs-TFP methods utilizes only the essential emerging pattern in which the redundant emerging patterns are removed. This classification method finds the sequence patterns of disorder region, such sequence patterns are frequently shown in disorder region but relatively not frequently in the order region. We expand P-tree and T-tree conceptualized TFP method into a classification/prediction method in order to improve the performance of the proposed algorithm. We used Disprot 4.9 and CASP 7 data to evaluate EPs-TFP technique, the results of order/disorder classification show sensitivity 73.6, specificity 69.51 and accuracy 74.2.

• Journal of Technology Innovation
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• v.28 no.2
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• pp.63-100
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• 2020

This study analyzes the effectiveness of government supported R&D program for SMEs by measuring TFP improvements. We estimate TFP for Korean companies from 2011 to 2018 using Levinsohn and Petrin (2003) method which reduces endogenous problem. Then government R&D beneficiary companies were extracted from the NTIS and linked to TFP estimates. The empirical results are as follows. First, as a result of estimating production function, the contribution of TFP to value-added is more important than in the past. Second, the TFP gap between large firms and SMEs continues to wide and there is no sign of easing.(from 3.72 times in 2011 to 5.23 times in 2018). Third, SMEs beneficiaries show higher TFP level than non-beneficiaries. However their TFP was on the decline until government support. After government supported R&D program, it reverses upward. Fourth, although one-year TFP improvement of beneficiaries is bigger than non-beneficiaries, it is smaller than the control group through PSME. Because SMEs participating in government R&D programs had showed downward trend of TFP until R&D program, it is necessary to examine whether there is a fundamental discordance between the demand of SMEs for R&D program and governments policy goal. More sophisticated program design will be required to escape the recognition that government R&D programs for SMEs are just charity.

• Spatial Information Research
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• v.19 no.2
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• pp.71-76
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• 2011

In this paper, for using emerging patterns to define and analyze the significant difference of safe and non-safe power load lines, and identify which line is potentially non-safe, we proposed an incremental TFP-tree algorithm for mining emerging patterns that can search efficiently within limitation of memory. Especially, the concept of pre-infrequent patterns pruning and use of two different minimum supports, made the algorithm possible to mine most emerging patterns and handle the problem of mining from incrementally increased, large size of data sets such as power consumption data.

• KDI Journal of Economic Policy
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• v.43 no.1
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• pp.53-80
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• 2021

The main objective of this study is to determine whether there have been TFP increases in the Korean manufacturing sector due to trade liberalization since the 1990s. Based on the methodology proposed by Pavcnik (2002), which focuses on the channel through which trade liberalization measures enhance overall industrial productivity by triggering the exit of low-productivity firms, this study tests the following two hypotheses: first, the TFP increase in the Korean tradable industry is not higher than that in the non-tradable industry, and second, plants with lower TFP levels did not exit from the tradable industry. Through the rejection of these two hypotheses, it is possible to infer indirectly the effect of trade liberalization on firm productivity rates in Korea since the 1990s. First, this analysis reveals that since the 1990s, the TFP of the tradable sector compared to the non-tradable sector presented a statistically meaningful increase only in the 2000s, when China joined the WTO and trade increased sharply between Korea and China. Secondly, TFP growth in the tradable sector was positively affected by exits, as it was plants with lower TFP levels that ceased to exist.

• The Journal of Industrial Distribution & Business
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• v.8 no.7
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• pp.13-20
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• 2017

Purpose - Performance appraisal has a significant influence on the development of low-carbon tourism distribution. Research design, data, and methodology - Data of this study are collected from 27 provinces (cities) of China. SBM-Malmquist model is used to measure the TFP and its dynamic changes of low-carbon tourism distribution; TOBIT model is used to discuss the factors of TFP of low-carbon tourism distribution. Results - The results show that, there are obvious differences among regional TFP of low-carbon tourism distribution, the average change tends to grow positively in general, and the western region grows fastest on average due to the improvement of technical efficiency and technical progress, while there are technical efficiency improvement but technical regresses in eastern and central regions. The economic scale, economic strength, structure of energy consumption, location quotient and government regulation have a significant positive effect on the TFP of low-carbon tourism; energy intensity, industrial structure and opening degree have a negative effect; investments in fixed assets, intensity of R&D fund and urbanization rate have no significant influence on the TFP of low-carbon tourism. Conclusions - Improving the productivity of low-carbon tourism and reducing regional differences are effective ways to develop low-carbon tourism and enhance tourism competitiveness.