• The Journal of Fisheries Business Administration
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• v.14 no.2
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• pp.15-68
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• 1983

From the economic point of view the fishing port is the complex of installations on land, organized to serve the fishing fleet and its cargo, and is the main link in the production chain of all components of the fishing industry, with the aim of achieving the planned targets with the minimum cost. Fishing port investment decisions have had significant impact on the development aims of Korean fisheries. Fishing port investments in Korea are made mostly by public or semipublic port authorities. Such investments should be judged not purely on the basis of financial profitability but rather on the extent to which they serve the development aims of the fishing industry. This makes the economic appraisal process more complex and presents certain problems in correctly quantifying the economic costs and benefits of the fishing port projects. This study concentrates more on the theoretical economic appraisal models than on the purely financial aspects of fishing port investments and points out the difference between the two approaches. In the result, there is clearly an element of judgment as to whether or not a shadow price needs to be used in estimating economic benefits and costs. From this viewpoint, some attempts are made to provide definitions of the possible economic benefits and costs, and methods for estimating and evaluating them in Part III and IV. Especially queueing theory is applied in the calculation of economic benefits. When a project is contemplated and analysis shows it to Lave a positive NPV, one question that arises is whether it should be implemented now or delayed. In this paper, the first year rate of return method is regarded as a more concise way of solving the timing of investment, At the end of Part IV, risk analysis of fishing port investments is considered. It can be handled in a number of ways, ranging from informal judgment to complex statistical analyses involving large-scale computer models, This paper recommends that evaluators of fishing port investments use the sensitivity analysis indicating exactly how much NPV will change in response to a given change in an input variable, other things held constant. Decisions regarding the amount of capacity to provide must be made in fishing port investments. Providing too much service would involve excessive capital costs. On the other hand, not providing enough service capacity would cause the waiting line of fishing vessels to become excessively long at times. Therefore, in Part V, the optimal number of berths and berth productivity in fishing port are defined as follows: Minimize E(TC) ＝ E(WC)＋E(SC) The minimum of this function is the solution and that is the optimal number of berth and berth productivity in fishing port.

• Korean small business review
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• v.42 no.2
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• pp.117-137
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• 2020

We examine the current status of smart factory deployment and diffusion programs in Korea, and seek to promote manufacturing innovation from the perspective of SMEs. The main conclusions of this paper are as follows. First, without additional market creation and supply chain improvement, smart factories are unlikely to raise profitability leading to overinvestment. Second, new business models need to connect "manufacturing process efficiency" with "R&D" and "marketing" in value chain in smart factories. Third, when introducing smart factories, we need to focus on the areas where process-embedded technology is directly linked to corporate competitiveness. Based on the modularity-maturity matrix (Pisano and Shih, 2012) and the examples of U.S. Manufacturing Innovation Institute (MII), we establish the new smart factory deployment policy measures as follows. First, we shift our smart factory strategy from quantitative expansion to qualitative upgrading. Second, we promote by each sector the formation of industrial commons that help SMEs to jointly develop R&D, exchange standardized data and practices, and facilitate supplier-led procurement system. Third, to implement new technology and business models, we encourage partnerships, collaborations, and M&As between conventional SMEs and start-ups and business ventures. Fourth, the whole deployment process of smart factories is indexed in detail to identify the problems and provide appropriate solutions.

• Korea Trade Review
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• v.41 no.2
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• pp.203-229
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• 2016

Korean general trading companies had started their business to benchmark and to adopt the successful new business models of the Japanese ones. Nevertheless, the strategic gaps between Korean and Japanese GTCs, Sogo-Shosha, still exist, including financial profitability and managerial competencies. In this regard, it is academically and practically required to find out the differences between Korean and Japanese GTCs. This study overviews the previous researches and the business cases to understand the features of GTCs and to get recent and meaningful factors which are related with the rebirth of Sogo-Shosha. Thereafter, in-depth interviews with industry experts and scholars and subsequent investigations were also conducted to suggest meaningful implications for both academicians and practitioners with the found factors. This study suggests four fundamental differences between the Korean and Japanese GTCs: ① the origin and growth path, ② business ownership, governance strategies and contracts management, ③ availabilities of investment portfolio and risk management, ④ business operation system and organizational culture. This study suggests meaningful implications for Korean GTCs to apply the experiences and lessons learned from Japanese Sogo-Shosha into their own business.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.121-139
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• 2014

Predicting corporate failure has been an important topic in accounting and finance. The costs associated with bankruptcy are high, so the accuracy of bankruptcy prediction is greatly important for financial institutions. Lots of researchers have dealt with the topic associated with bankruptcy prediction in the past three decades. The current research attempts to use ensemble models for improving the performance of bankruptcy prediction. Ensemble classification is to combine individually trained classifiers in order to gain more accurate prediction than individual models. Ensemble techniques are shown to be very useful for improving the generalization ability of the classifier. Bagging is the most commonly used methods for constructing ensemble classifiers. In bagging, the different training data subsets are randomly drawn with replacement from the original training dataset. Base classifiers are trained on the different bootstrap samples. Instance selection is to select critical instances while deleting and removing irrelevant and harmful instances from the original set. Instance selection and bagging are quite well known in data mining. However, few studies have dealt with the integration of instance selection and bagging. This study proposes an improved bagging ensemble based on instance selection using genetic algorithms (GA) for improving the performance of SVM. GA is an efficient optimization procedure based on the theory of natural selection and evolution. GA uses the idea of survival of the fittest by progressively accepting better solutions to the problems. GA searches by maintaining a population of solutions from which better solutions are created rather than making incremental changes to a single solution to the problem. The initial solution population is generated randomly and evolves into the next generation by genetic operators such as selection, crossover and mutation. The solutions coded by strings are evaluated by the fitness function. The proposed model consists of two phases: GA based Instance Selection and Instance based Bagging. In the first phase, GA is used to select optimal instance subset that is used as input data of bagging model. In this study, the chromosome is encoded as a form of binary string for the instance subset. In this phase, the population size was set to 100 while maximum number of generations was set to 150. We set the crossover rate and mutation rate to 0.7 and 0.1 respectively. We used the prediction accuracy of model as the fitness function of GA. SVM model is trained on training data set using the selected instance subset. The prediction accuracy of SVM model over test data set is used as fitness value in order to avoid overfitting. In the second phase, we used the optimal instance subset selected in the first phase as input data of bagging model. We used SVM model as base classifier for bagging ensemble. The majority voting scheme was used as a combining method in this study. This study applies the proposed model to the bankruptcy prediction problem using a real data set from Korean companies. The research data used in this study contains 1832 externally non-audited firms which filed for bankruptcy (916 cases) and non-bankruptcy (916 cases). Financial ratios categorized as stability, profitability, growth, activity and cash flow were investigated through literature review and basic statistical methods and we selected 8 financial ratios as the final input variables. We separated the whole data into three subsets as training, test and validation data set. In this study, we compared the proposed model with several comparative models including the simple individual SVM model, the simple bagging model and the instance selection based SVM model. The McNemar tests were used to examine whether the proposed model significantly outperforms the other models. The experimental results show that the proposed model outperforms the other models.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.3
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• pp.1-15
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• 2016

This study has analyzed predication capabilities leveraging multi-variate model, logistic regression model, and artificial neural network model based on financial information of medium-small sized companies list in KOSDAQ. 83 delisted companies from 2009 to 2012 and 83 normal companies, i.e. 166 firms in total were sampled for the analysis. Modelling with training data was mobilized for 100 companies inlcuding 50 delisted ones and 50 normal ones at random out of the 166 companies. The rest of samples, 66 companies, were used to verify accuracies of the models. Each model was designed by carrying out T-test with 79 financial ratios for the last 5 years and identifying 9 significant variables. T-test has shown that financial profitability variables were major variables to predict a financial risk at an early stage, and financial stability variables and financial cashflow variables were identified as additional significant variables at a later stage of insolvency. When predication capabilities of the models were compared, for training data, a logistic regression model exhibited the highest accuracy while for test data, the artificial neural networks model provided the most accurate results. There are differences between the previous researches and this study as follows. Firstly, this study considered a time-series aspect in light of the fact that failure proceeds gradually. Secondly, while previous studies constructed a multivariate discriminant model ignoring normality, this study has reviewed the regularity of the independent variables, and performed comparisons with the other models. Policy implications of this study is that the reliability for the disclosure documents is important because the simptoms of firm's fail woule be shown on financial statements according to this paper. Therefore institutional arragements for restraing moral laxity from accounting firms or its workers should be strengthened.

• Journal of Venture Innovation
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• v.1 no.1
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• pp.1-14
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• 2018

The 4th Industrial Revolution is making a big change for our company like the tsunami. The CPS system, which is represented by the digital age, is based on the data accumulated in the physical domain and is making business that was not imagined in the past through digital technology. As a result, the business model of the 4th Industrial Revolution era is different from the previous one. In this study, we analyze the trends and the issues of business innovation theory research. Then, the business innovation model of the digital age was compared with the previous period. Based on this, we have searched for a business model suitable for the 4th Industrial Revolution era. The existing business models have many difficulties to explain the model of the digital era. Even though more empirical research should be supported, Michael Porter's diamond model is most suitable for four cases of business models by applying them. Type A sharing outcome with customer is a model that pay differently according to the basis of customer performance. Type B Value Chain Digitalization model provides products and services to customers with faster and lower cost by digitalizing products, services and SCM. Type C Digital Platform is the model that brings the biggest ripple effect. It is a model that can secure profitability by creating new market by creating the sharing economy based on digital platform. Finally, Type D Sharing Resources is a model for building a competitive advantage model by collaborating with partners in related industries. This is the most effective way to complement each other's core competencies and their core competencies. Even though numerous Unicorn companies have differentiated digital competitiveness with many digital technologies in their respective industries in the 4th Industrial Revolution era, there is a limit to the number of pieces to be listed. In future research, it is necessary to identify the business model of the digital age through more specific empirical analysis. In addition, since digital business models may be different in each industry, it is also necessary to conduct comparative analysis between industries

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.585-591
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• 2020

In accordance with the government's expansion of solar power generation, the installation of solar panels is expected to expand in Korea. On the other hand, policy discussions on the establishment of a domestic post-management system for waste from photovoltaic power are insufficient. This study estimated the benefit-cost of solar PV Panel recycling and derived the implications for the photovoltaic waste policies in Korea. Overall, the profitability of the recycling project is very low when the project execution period is 10 years. On the other hand, the economic efficiency of the project can be sufficiently high when the duration of the solar panel recycling project is extended to 20 years. In the short term, it is challenging to expect voluntary companies to enter this recycling business because of low economic efficiency. Therefore, it is necessary to prepare various policies to improve the economic efficiency of the recycling business. In conclusion, the following policy implications for PV panel recycling activation are proposed: i) legislation for the recycling of waste solar photovoltaic panel, ii) designation of Association for Solar Panel waste monitoring, and iii) expansion of R & D and the development of various business models related to solar recycling.

• Journal of Distribution Science
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• v.13 no.7
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• pp.85-90
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• 2015

Purpose - Global trends play a part to change the structure of the fashion industry. In particular, companies attempting to conduct innovative marketing centering on such products as SPA brands are growing into global companies. SPA stands for "Specialty Store Retailer of Private Label Apparel", meaning its activities are fully integrated from manufacturing through sales, including material procurement design, product, distribution, inventory management, and final sales. For this reason, more understanding of individual corporate profitability is very sensitive to consumer's attitudinal changes. The effects that corporate marketing activities on customer lifetime value through brand attitude were analyzed based on a structural equation model. Rust suggested value equity, brand equity, and relationship equity as customer equity driver. The study examines Chinese consumer because China is the fastest growing fashion market in the world. Research design, data, and methodology - The survey targeted Chinese college student age 20s. Only respondents who had purchased SPA brands in the past year were included for this research. A total of 303, except for 47 missing data of 350 distributed questionnaires were included in this research. The questionnaire is consists of six part to measure value, brand, relationship equity, attitude toward brand, purchase intention and demographic characteristics. This research conducted exploratory factor analysis and reliability test. To verify research hypotheses, structural equation model test was conducted. As for customer equity, diversified models in consideration of the scope of acquisition data, a method of collection of data, influencing factor, and predictability were suggested based on a net present value model. However, the history of customer equity study is relatively short, and sufficient empirical analyses have not been conducted, so more integrated analysis is required. In this study, the concept of driver suggested by Rust was applied to figure out the effects that consumer's attitude has on customer equity. The customer equity driver suggested by them consists of brand equity, value equity, and relationship equity. Results - This study reveals that value equity and brand equity have a positive influence on relationship equity. And, relationship equity has a positive influence on purchase intention through brand attitude. However, value equity and brand equity do not influence on brand attitude. Conclusion - The results of this research generated following implications. First, SPA brands need to take advantage of their value equity such as perceived low price and up-to-date fashion style to attract Chinese young consumer. Second, strong brand equity promises dominants position in the competitive market. As Chinese fashion market grows rapidly, SPA brands can consider branding strategy such as flagship store and celebrity marketing enhancing brand image. Third, the core concept of customer equity strategy is to maintain a relationship with their expecting and existing customers. The relationship equity is built by brand equity and value equity. When SPA brands serves product and service meet with individual customers, customers have intimacy to the brands.

• Journal of Korean Society of Transportation
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• v.28 no.2
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• pp.135-150
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• 2010

This paper focuses on finding out which covenants are different among the concession agreements of Korean BTO projects and how these influenced IRR(Internal Rate of Return). That is, to figure out the political and economical determinants of IRR by analyzing the concession agreements which are the basic contract of implementing projects. As IRR is an index of profitability, so spread is an indicator of risk to collect debts. That's the reason why the analysis of spread is included. For the empirical analysis, the data of concession agreements for 75 projects and financial models are used. These 75 concession agreements are contracted from 1995 to 2008. The dependent variables are after tax nominal IRR and the spread of long term interest rates of 75 BTO projects. The independent variables are project's proceeding factors, the feasibility variables, the variables related to financial character and the variables related to covenants or the government's policy. The analysis shows that IRR has been influenced by the equity level of financial investors, the national government managed projects, the projects with minimum revenue guarantee (MRG), etc. And the equity level of financial investors, the national government managed projects and the implementation of supplementary project have an effect on spread also.

• Korean Journal of Soil Science and Fertilizer
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• v.34 no.1
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• pp.42-54
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• 2001

The use of nitrogen fertilizer in intensive agricultural production is of major concern due to its role on agricultural productivity and water quality. Crop production inputs on farm are usually applied at a uniform rate across an entire field. However, actual input requirements often vary within fields. The field variations in yield potential, soil moisture, soil N status, and the efficiency of fertilizer use, uniform application of crop production inputs does not allow optimum efficiency or profitability. This occurs because uniform application often results in areas of over- and under-application which may affect water quality and crop yield. This study used biophysical and economic models to assess the economic feasibility and water quality benefits of site specific nitrogen management for 10 soil types and 35 sample fields in Goodwater Creek watershed located near Centralia, Missouri. Results showed that the economic feasibility and water quality benefits of variable rate application were sensitive to the distribution of soil types within a field. Variable rate(VR) application was not uniformly more profitable than uniform rate(UR) application for the four agricultural systems evaluated and the water quality benefits were insubstantial relative to uniform application of N.