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The relationship between market structure and productivity is explored in this paperusing disaggregated industry data for the Korean economy. A structural VAR model isemployed to estimate the effects of a rise in market concentration on labor productivityas well as on employment and production. The sectoral analysis in this paper covers tenmanufacturing industries as well as five non-manufacturing industries such as electricity,gas and water supply; construction; and three major service sectors. Estimation results for ten manufacturing industries show that higher concentration inproduct markets leads to an increase in labor productivity in most of manufacturingindustries, which supports the Schumpeterian view on this issue. In contrast, it induces afall in employment. Moreover, output decreases except for a few industries. Thus higherconcentration rather has a negative impact on the growth of manufacturing industries. Compared to manufacturing industries, more heterogeneity is found for fivenon-manufacturing industries. Higher concentration enhances labor productivity except fortwo industries. For construction, higher concentration reduces labor productivity, whichimplies that the Arrowian view is valid for this sector. For transport, storage andcommunications, higher concentration does not have a significant effect on laborproductivity. The effect of higher concentration on production also varies substantially across non-manufacturing industries. Output increases in the sectors of electricity, gas andwater supply; and finance, insurance, real estate and business services. Output in theconstruction sector decreases. Output does not change much in the sectors of wholesaleand retail trade, restaurants and hotels; and transport, storage and communications. Focused on the output effect, empirical results of this paper suggest that by and largeproductivity-enhancing measures that lead to higher concentration in product markets maynot be so effective in raising the growth potential of each industry.

This purpose of this study is to examine the interaction effects of planned change ontrust affecting innovation and the mediated moderation of interaction effects throughorganizational communication. This study uses HCCP 2011 (Human Capital Corporate Panel) data to analyze themediated moderation. This study follows the mediated moderation model analysis used byMuller et al.(2005). The statistical analysis indicates that planned change moderates the relationship betweentrust and innovation. In addition, planned change also moderates the relationship betweentrust and organizational communication. The analysis also shows that these moderatingeffects are mediated by organizational communication. Particularly, these interactioneffects of planned change are found in both paths of mediated effect (trust →organizational communication, organizational communication → innovation). This results have means any of the following. The results of this study contributes to positive outcome of planned change byempirical analysis and proves that many researchers need not only to focus on themediating and moderating effect but also the mediated moderating effect.

The purpose of the study is to verify the presence of congestion in the operations ofpublic hospitals in South Korea. Moreover, the differences in congestion and efficiencyamong the types(foundation type/treatment function) of public hospitals are analyzed. Todo these, a DEA model is developed and “the 2013 National Public Hospital Guidance”that was provided by the Public Health Support Unit of National Medical Center isutilized. For the DEA model of congestion and efficiency, the following five inputs areselected: number of doctors, number of nurses, number of medical technicians, number ofadministrative staffs and number of sick-beds. As for the outputs for the analyses ofcongestion and efficiency, number of hospitalized patients, number of outpatients andmedical profits are considered. The summary of the major results of the study is asfollows. First, we find that there are congestions in the operations of public hospitals. For eachinput, public hospitals generally show a high rate of congestion occurrence as well as alarge size of congestion in the operations. There are some differences in the congestionamong the foundation types of public hospitals. The national hospitals are found to havea larger occurrence rate and the size of congestion than the special corporate hospitalsand geriatric hospitals with respect to every input except for the number of medicaltechnicians. As for the types of treatment function, the special medical treatment-centric (diseases) hospitals are found to have a larger size of congestion than the general medicaltreatment-centric hospitals and elderly-specialized hospitals in all the inputs. Second, in the case of the differences in the efficiency among the foundation types ofpublic hospitals, the special corporate hospitals show the highest efficiency, followed bythe geriatric hospitals and the national hospitals. As for the types of treatment function,the general medical treatment-centric hospitals are found to have a higher degree ofefficiency than the elderly-specialized hospitals. The followings state the contributions of the study. First, in this research, thecongestion of public hospitals of South Korea is measured and the existence of thecongestion is verified for the first time by leveraging the congestion DEA model whichwould measure the special case of an inefficient situation. These results provide thepractical implication that could help determine the priority of management by comparingthe congestion for each input. Second, the differences in the efficiency among the types of foundation and treatmentfunction are also analyzed. This achievement helps to establish a foundation which couldenhance the understanding of the public hospitals by the environmental factors.

Input congestion is present when reducing some inputs causes some outputs. Suchphenomenon is likely to be present in Korean universities. But previous studies measuringthe efficiencies for Korean universities did not take the input congestion into account. Hence, this study revisited the efficiency of Korean universities with consideration ofinput congestion by employing T-S model(SBM DEA). T-S model divided the inputcongestion into strong congestion and weak congestion. This study measures the weak congestion because the definition of strong congestion istoo restrictive. Strong congestion implies weak congestion, but weak congestion does notimply strong congestion. Number of full time teaching staffs, number of non-teaching staffs, and number ofstudents are used as outputs and employment rate, domestic publication index, andinternational publication index as outputs. Inputs congestions are estimated for 39research-oriented universities in 2012. 20 universities have been diagnosed with inputcongestion and an excessive number of students is the main sources of input congestion,Based on this study, the congested inputs are required to be removed from the inputs. The outputs augmentation such as employment rate, domestic publication index, andinternational publication index could have been achieved by the reduction in number offull time teaching staffs, number of non-teaching staffs, and number of students. In addition, the above unexpected input congestion from full time teaching staffs mightbe indicative of institutional inefficiency. Further research is necessary to examine theinstitutional inefficiency.

R&D performance in Korea has been grown remarkably owing to the governmentsupport policy. However, the revenue of technology transfer to private enterprise bypublic research institutions in Korea is insignificant compared to the foreign developedcountries. Korean government has reviewed with multilateral on the efficient technologycommercialization, and then legislated research institute company law in 2006 as asupport policy to maximize technology commercialization success rate. A lot of researchinstitute companies have been operating these days. However, the business performancesof research institute companies are still not so prominent. In order to suggest methods toincrease the success rate of research institute companies, the research on the researchinstitute company is needed. This paper is to suggest right directions to activate technology commercialization inpublic research institutions. And it suggests methods to lead the research institutecompanies as prominent companies based on the case study of the four representativetechnology investment institutes and four research institute companies.

The goal of this study is to develop policy suggestions in order to increase theefficiency of entrepreneurship. First, regression analysis is carried out to examine howinput variables affect output in each phase of startup development. Then, dataenvelopment analysis(DEA) estimates efficiency in each development process in 26countries and identifies where South Korea locates herself in terms of entrepreneurialefficiency. The empirical results in the regression analysis implies the following. First, in terms ofentrepreneur, more young people should become self-employed to achieve businessopportunities in the market. Second, in terms of regulatory environment, governmentprogrammes should be diversified and differentiated in order to meet the various needs ofstartup companies. Third, in terms of market, startups should be tenacious, equipped withglobal competencies to survive. Fourth, in terms of financial support, it should be easierfor startups to enter into market with accessible unsecured loans. Fifth, in terms ofknowledge infrastructure, it is critical to encourage substantial investments on R&D. Sixth, in terms of education/training, vocational and lifelong education/training producesmore effective result than the one at universities. Last, in terms of cultural environment,society needs to show more respects to entrepreneurs, and media should pay moreattention to their entrepreneurship. DEA addresses benchmark countries for South Korea to improve efficiency in eachstage of development phases. While the efficiency of Korean startups is above average inthe phase of pre-startup, early-stage startup, and growth, it is far below average in thephase of failure/recovery. Among the entrepreneurship in benchmark countries on theefficiency frontier, it is highly suggested that the one in China should be extensivelyanalysed to carry implications to Korea.

This paper empirically explores the links between environmental and green innovation and labor productivity of innovative firms as a proxy for economic performance using firm level data based on Korean 2010 CIS(Community Innovation Survey) data created by the STEPI. To examine the effects of various modes of green innovation in manufacturing sector on firm performance, the paper controls for endogeneity of the innovation, using two stage Predictor Substitution and 2 Stage Residual Inclusion procedures as well. In the first stage, the probit model for each innovation variable is estimated by MLE using instrument variables such as lagged sale and worker variables, Then in the second stage, the firm’s productivity model include the predicted values of the innovation variable or residuals obtained from the probit model as an explanatory variable. The empirical results show, first, that green innovation intended for both firm and customer benefits has a positive effect on labor productivity. Firms need to implement firm-oriented environmental innovation as well as customer-oriented environmental innovation in order to increase their performance. Thus, the more the investment in the green product and process innovation was, the stronger the corporate competitive advantage was. Second empirical results also show that there are significant differences in aggregate green innovations depending on different firm sizes and industries.

Traditional corporate bankruptcy prediction methodology basically relies on financial accounting data to objectively reflect the status of companies. However, since financial accounting data is difficult to immediately reflect changes in the status of companies, real-time financial data such as stock and bond prices are also used in order to make up for the shortcomings. In this study, we use news text information which is a typical real-time information to study the corporate bankruptcy prediction models. In the past, news text information was difficult to use in quantitative analysis but not any more due to the recent advances of information processing technology and text-mining techniques. For bankruptcy prediction using news information, we collect news text for six months before the bankruptcy events of companies actually occur and study the possibility of bankruptcy prediction based on the data by utilizing text-mining techniques. Results indicate that we can not get such a high level of predictability as that of existing corporate bankruptcy prediction models, but that there exists a high potential of this approach enough to increase the predictability of bankruptcy models. Further research on bankruptcy prediction model using news text information will be promising.

The purpose of this study is to identify relationships among the TVET(Technical and Vocational Education and Training) service quality, training satisfaction, and employability of unemployed vocational trainees who participate in the national infrastructure and strategy industries training. In addition, this research tried to examine the mediating effects of training satisfaction in the relationship between TVET service quality and employability. The result of review were as follows. First, the level of training satisfaction(4.51), TVET service quality(4.41), and employability (4.32) of the unemployed vocational trainees showed above average based on five-point Likert scale. Second, the level of employability of trainees who were teenage male students showed higher relatively. Third, main factors influencing on both of training satisfaction and employability of trainees among several TVET service factors showed training contents, training methods, trainers, and employment support, in which training contents and training methods influenced the most on training satisfaction and employability. Finally, training satisfaction of trainees had mediating effects on the relationship between the TVET service quality and employability.

This study evaluates the predictive accuracy of expert (judgmental) forecasting and system (statistical) forecasting that provided two types of predictions on the NFL regular season games during 2000 and 2001 season. Then, we empirically investigate whether there exists a statistically significant difference in the predictive accuracy within the four groups of experts and systems respectively. From this, we implicitly investigate whether there is any prediction that has a better productivity. For this, we use the methodology of ‘Analysis of Variance by Ranks’ as an analytical tool. Our study finds that there is a statistically significant difference in the predictive accuracy within the group of experts as well as the group of systems who predicted the game winners. Meanwhile, we do not find a statistically significant difference within the group of experts as well as the group of systems who predicted against the betting line. In conclusion, it would not be the model of forecasting but the type of prediction that may induce a difference in the predictive accuracy.