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This paper estimates total factor productivity (TFP) growth and decomposes its contributing factors into technical efficiency change, scale component and technical progress for the Korean IT industry. The data set is the unbalanced panel of 293 IT firms listed in the KOSPI and KOSDAQ market for the period of 1980-2011. To compare the two markets, we apply the group-specific stochastic frontier production model, allowing for different groups of firms to have different patterns of technical efficiency over time. The empirical results are as follows; (1) The time-varing technical inefficiency exists significantly in Korean IT industry and its time-varing patterns are different each other in KOSPI and KOSDAQ. (2) The improvement of technical efficiency is major contributing factor to the TFP growth in both markets, but it has slowed down continuously over the sample period. (3) The scale component is larger in KOSPI than KOSDAQ, but it has trivial influences on the TFP growth in both markets. (4) The rate of technical progress is higher in KOSDAQ than KOSPI. Especially in KOSDAQ market, technical progress is also crucial factor on TFP growth. (5) The growth rate of TFP is higher in KOSDAQ than KOSPI, but it has slowed down continuously in both markets. Especially, TFP growth rate deteriorate rapidly in the late of 1990s(asian economic crisis) and 2000s(dot-com bubble collapse and global financial crisis). KOSDAQ is more sensitive to external shock than KOSPI. (6) In the case of KOSDAQ market, the technical progress is also as important factor as technical efficiency changes. It means that the speed of catch-up to the frontier technology is fast in KOSDAQ than in KOSPI.

This paper empirically explores the effects of various government policy instruments on innovation firms’ productivity using Korean 2008 and 2010 Community Innovation Survey data conducted by the STEPI. The empirical results summarized as follows. First, government policy variables are found to be endogeneous, which implies that simple OLS estimation of the productivity model should produce biased results and thus lead to inappropriate policy suggestions. Second, empirical results shows that most government technology promotion policies are positively associated with firm productivity directly, implying that the policies cause to correct market failure, rather than lead to government failure. This indirectly means that the government policies promote technology development activities, rather than crowd out them. Third, using the non-InnoBiz firm sample, only one policy variable is found to be statistically significant, but for the Inno-Biz firm sample, all estimated coefficients except two government policy variables are found to be significant. This implies that productivity effects of government policy can be mainly due to those from Inno-Biz firms.

As the development of the knowledge, technology and information for the industrial development was deepened, the securement of the workforce has been regarded as an important factor for firm's growth. Especially, the importance of skilled workers who can make full use of technology and knowledge is becoming larger. That is, the securement of the skilled workers has been considered an important factor for corporation's growth. In this respect, the shortage of industrial technology workforce also has been considered an major factor restricting corporations' competitiveness and performance. This thesis has analyzed the effect of the industrial technology workforce shortage on a corporation's performance based on panel data constructed by combining those of Korea Enterprise Data and the Ministry of Knowledge Economy data. Methodologically, in order to resolve the problem of selection bias the Propensity Score Matching using the Nearest Neighbor Matching has been applied to estimate the average treatment effect on the treated (ATT) of the shortage on a corporation's performance. Furthermore, the effect of the level of skills and the level of technology of the corporation on a performance has been examined. Upon the analysis, the shortage of industrial technology workforce displayed to have negative effects on both the technological as well as financial aspects, and the shortage appeared to have heterogeneity and threshold effect. That is, the effect of the shortage applied to mid- to high-tech groups than low-tech corporates, and the shortage of bachelor degrees appeared to have a greater effect. Therefore, government needs to consider the technology level of the firms when supporting the industrial technology workforce policy, and the current support program which is focusing to foster master's and doctorate degree also needs to be reconsidered.

This study analyzes the relative efficiency of chain stores according to regional characteristics and identifies its factors. In this study, the efficiency of 321 chain stores is measured by DEA model and its factors are identified by Tobit regression model. Three inputs(store size, number of items, and number of employees) and two outputs(sales and number of customers) are used for the DEA model. As a result, only 3 ∼6% of the stores are efficient and the average technical efficiency score is 0.5968 and the average pure technical efficiency score is 0.6457. The efficiency of metropolitan stores is higher than that of small town stores and the efficiency of residential and commercial area stores is higher than that of residential area stores. In Tobit regression model, the DEA efficiency scores are used as dependent variables and five variables, namely store age, number of items per store size, number of items per employee, trade area index, and number of competitors are used as independent variables. The results show that store age, number of items per employee, trade area index, and number of competitors play a significant role in influencing stores’ efficiency. All of five variables are statistically significant in metropolitan stores, but in small town stores so are two variables, namely store age and number of items per store size. In residential area stores number of items per store size, number of items per employee, and trade area index are statistically significant, but number of items per store size is not statistically significant in residential and commercial area stores. Managerial implications of the study are discussed.

Park Geun-hye administration initiated support policy for small and medium-sized enterprises as part of its “creative economy strategy” in order to rejuvenate the economy and improve the country’s competitiveness. Despite these efforts, the policy has made little impact on nurturing small and medium-sized enterprises until now. In this perspective, it is necessary to review the performance of the policy and modify the details of the policy based on the performance. This study empirically analyzed the performance of the World Class 300 project as the key part of Park Geun-hye administration's support policy for small and medium-sized enterprises in order to support policy for small and medium-sized enterprises by categorizing it into output and outcome according to the program logics model. For the output, the performance supported by the government and utilizing the project in the enterprises were examined, and for the outcome, changes in enterprises sales, exports, and employed personnel were examined after government support. Particularly for the outcome, the performance by year of government support and the difference between selected enterprises and disqualified enterprises using the quasi-experimental design were compared. The results showed that the growth rate of sales and exports increased until the third year and fell in the fourth year, and the employment rate steadily dropped until the fourth year. Also, the rates of increase in sales and employment were found to be higher in selected enterprises than disqualified enterprises on average, and this gap was statistically significant. In conclusion, though there were differences depending on the term of government support, it was founded that the government support has made some progress. However, this study proposed that continuous management is necessary to retain the performance made by support and to manage individual enterprise making sure there is not a big gap between them.

Recently, farmers' training has been expanding to ensure the competitiveness of agriculture and enhance their expertise in the agricultural workforce. The purpose of this study is to identify the effects of farmers' training on job satisfaction. In addition, this study aimed to verify the moderating effect of psychological capital being to be a major variable factor in the educational effect. Therefore, a survey was distributed to 250 farmers in Ulsan area. From April 1, 2015 the survey was conducted up to 14 days. Excluding defective data, 155 copies were used for final analysis. The training were divided into six groups, such as crops (animal feeding) technology, agricultural products processing, technical experts, agricultural management, information, and culture training. The study results are as follows: First, Cultural training has significant positive effects on job satisfaction. In Previous studies, either educational participation or training expenses of employees have a significant relationship between positive effects on job satisfaction. But in this case, crops (animal feeding) technology, agricultural products processing, technical experts, agricultural management, and information training do not affect on job satisfaction. However cultural training is satisfied cultural needs and assists founding of female farmers. And an intensive cultural training program increases intimacy among students. These things can be considered for such a reason. Second, psychological capital such as self-efficacy, hope, resilience ,and optimism has a positive effect on job satisfaction. It means that running a course or program to improve the psychological capital of the farmers improve the job satisfaction of farmers. Third, psychological capital plays the moderating role on the agricultural technical training between job satisfaction. The technical training is similar to that on the type of hands-on training of enterprise. Farmers believed in themselves and looked to the future with a view to positive are the more educational participation, the higher job satisfaction. In conclusion, farmers' training with the process of improving psychological capital are able to increase job satisfaction of farmers.

This study measures total factor productivity (TFP) of Korean manufacturing enterprises and decomposes it into technological change and scale effect terms for the period of 2001-2011 by using an abundant firm-level data set. Main findings are as follows: 1) the scale component plays an important role in enhancing productivity of the Korean enterprises, and 2) the size of a firm and TFP growth has a positive relationship. Although many previous studies found that the technological change is the main contributor to the TFP growth to a large extent, this study provides evidence that scale effects have a positive relationship with TFP growth as a whole. Policy implications are developed based on the empirical results. Growth in sales and employees is effective in enhancing performance of Koran manufacturing enterprises, which requires a different explanation on the polarization across Korean enterprises. This finding also demands a new policy paradigm along with the traditional two-track policy strands; to protect SMEs and to regulate conglomerates. For further development of policymakings, supports for Korean small giants or hidden champions are required in order for SMEs to have continuous growth.

This paper analyzes the relationship between labor productivity and team performance by using the National Football League (NFL) data between 1994-1995 and 2008-2009 seasons. In order to do this, we collect statistical data from two major web-sites as of nfl.com and pro-football-reference.com, and utilize a methodology of Poisson regression model because we have count data. The dependent variable is a winning percentage and independent variables are player performance in offense and defense indicating labor productivity. From the empirical analysis, we found the number of independent variables has positive impacts on team performance. Thus, we can conclude that there exists a positive relationship between labor productivity and team (organizational) performance. In addition, we can conclude that the quarterback’s performance is a statistically significant determinant of team performance.

The global financial crisis in 2008 was spreading to object economy through financial institutions, thus at that time many domestic construction companies whose abilities to meet debt obligations were worried became financially distressed. The distress of the construction and real estate industry caused domestic banks’ deteriorating of financial soundness. Also it influenced to domestic economy by direct and indirect production decrease and reduced employment. During recession, as bankruptcy rate increases financial intermediaries need more funds thus they reduce loan offerings. After all recession increases macro economic crisis. Procyclicality by financial intermediaries is mainly due to the limit of measuring firms’ credit risk. Recently major domestic construction firms with high volume of overseas plant business began to reflect large scale losses in settling accounts from 2013 and their financial condition has not improved. This kind of accounting method, treating cumulative loss in certain financial year, is called Big Bath. Such accounting methods by the order-receiving industries set limits to credit management for financial intermediaries by bankruptcy detecting model using firms’ past financial data for measuring a firm’s default. In this study we modify Moody’s KMV model to apply to the domestic construction industry debt structure and calculate default distance and empirical EDF. And we analyzed lead-lag relation of construction macro-economic indexes using VAR model and conducted impact response analysis of each macro-economic index as 1 standard deviation change of EDF model using VECM model. By this analysis we test empirically whether EDF model can evaluate industry risk in advance. We reviewed literature related to construction cycle and construction firms’ default prediction and chose indicators that can diagnose construction cycle. And we empirically analysed the relation between the chosen indexes and the construction industry EDF. The study results show that EDF lead the leading and the coincident index of construction cycle, which means EDF is useful as a measure for analysing an industry, especially the construction industry. Also these study results can help financial institutions that have financial relations with the construction industry to control the relations in advance. Due to the these characteristics of the construction industry, financial institutions need to know the information and criteria to evaluate the related information to make appropriate decisions in advance. Otherwise considering the size of the construction industry and the size of the loans to the industry from domestic financial institutions, the economy of this country may be in trouble under inappropriate decisions. In this study we focused on the construction industry. Considering the fact that each industry can have its own customary practice regarding financial statement, financial institutions should be vigilant to find and apply the most appropriate method to evaluate the firms in the industry.