• Economic Analysis
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• v.27 no.4
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• pp.1-42
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• 2021

The outlook for Korea's consumer price inflation rate has a profound impact not only on the Bank of Korea's operation of the inflation target system but also on the overall economy, including the bond market and private consumption and investment. This study presents the prediction results of consumer price inflation in Korea for the next three years. To this end, first, model selection is performed based on the out-of-sample predictive power of autoregressive distributed lag (ADL) models, AR models, small-scale vector autoregressive (VAR) models, and large-scale VAR models. Since there are many potential predictors of inflation, a Bayesian variable selection technique was introduced for 12 macro variables, and a precise tuning process was performed to improve predictive power. In the case of the VAR model, the Minnesota prior distribution was applied to solve the dimensional curse problem. Looking at the results of long-term and short-term out-of-sample predictions for the last five years, the ADL model was generally superior to other competing models in both point and distribution prediction. As a result of forecasting through the combination of predictions from the above models, the inflation rate is expected to maintain the current level of around 2% until the second half of 2022, and is expected to drop to around 1% from the first half of 2023.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.2
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• pp.195-205
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• 2012

This study examines runaway youths at risk in a youths' shelter who are preparing for an independent life and both the facilitating and adverse factors to personal characteristics and independence of runaway youths at risk with the aim to grasp their recognition of independence and level of desire for it and find out necessary factors for a successful independence in multidimensional perspectives including the economic independence, educational independence, psychological independence, and social independence for their sound growth. This will provide the basis for desirable interventions for youths runaway youths at risk to prepare for an independent life. The findings of this study on the factors that affect the preparation for an independent life are as follows: First, as a result of analyzing the effect of micro-systematic factors on the preparation for an independent life, it turned out that problem-solving abilities and self-efficacy had influence on the preparation for a career Second, as a result of analyzing the effect of mesoscopic-systematic variables on the preparation for an independent life, it turned out that the preparation for a career were affected by whether to participate in independence preparation programs and institutional supports, and that career maturity of runaway youths at risk were affected only by the relationship with teachers and participation in independence preparation programs. Third, as a result of analyzing the effect of macro systematic variables on the preparation for an independent life, it turned out that the preparation for a career were affected by participation of the local community and service network, and that participation of the local community was an predictor variable that would affect a career maturity of runaway youths at risk. Fourth, as a result of analyzing ecological systematic variables that might affect the preparation for a career, it turned out that intervening variables and macro systematic variables had the most powerful influence on the preparation for a career among runaway youths at risk. It is necessary, therefore, to provide education programs organized by policies in order to develop problem-solving abilities and vocational capabilities so that runaway youths at risk, and to train and appoint more professional teachers at shelters. Programs for independence preparation need to be developed actively and practically in consideration of the characteristics of shelters, and the network with the local community for support also need to be established in utilization of the human resources and service programs of the community. With the understanding of leaving home of runaway youths at risk as the previous stage of an independence, there should be a housing support for their stable settlement in the perspective of housing welfare until become adults. In addition, there should be education specialized programs for occupation and careers to train runaway youths at risk as professionals including such areas as health, mentality, learning, and voluntary work for their sound growth.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.4
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• pp.193-216
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• 2020

Due to the recent mid- to long-term slump and falling growth rates in the global economy, interest in organizational structures that create new products or services as a new alternative to survive and develop in an opaque environment both internally and externally, and enhance organizational sustainability through changes in production methods and business innovation is increasing day by day. In this atmosphere, we agree that the growth of small and medium-sized venture companies has a significant impact on the national economy, and various efforts are being made to enhance the technological innovation capabilities of the members so that these small and medium-sized venture companies can enhance and sustain their performance. The purpose of this study is also to investigate how the technological innovation capabilities of small and medium-sized venture companies correlate with the performance of knowledge management and to analyze the role of network capabilities to organize the strategic activities of enterprise to obtain the resources and organizational capabilities to be used for value creation from external networks. In other words, research was conducted on the impact of technological innovation capabilities of small and medium venture companies on knowledge management performance by using network capabilities as parameters. Therefore, in this study, we would like to verify the hypothesis that innovation capabilities will have a positive impact on knowledge management performance by using network capabilities of small and medium venture companies. Economic activities based on technological innovation capabilities should respond quickly to new changes in an environment where uncertainty has increased, and lead to macro-economic growth and development as well as overcoming long-term economic downturns so that they can become the nation's new growth engine as well as sustainable growth and survival of the organization. In addition, this study was conducted by setting the most important knowledge management performance within the organization as a dependent variable. As a result, R&D and learning capabilities among technological innovation capabilities have no impact on financial performance. In contrast, it was shown that corporate innovation activities have a positive impact on both financial and non-financial performance. The fact that non-financial factors such as quality and productivity improvement are identified in the management of small and medium-sized venture companies utilizing their technological innovation capabilities is contrary to a number of studies by those corporate innovation activities affect financial performance during prior research. The reason for this result is that research companies have been out of start-up companies for more than seven years, but sales are less than 10 billion won, and unlike start-up companies, R&D and learning capabilities have more positive effects on intangible non-financial performance than financial performance. Corporate innovation activities have been shown to have a positive (+) impact on both financial and non-financial performance, while R&D and learning capabilities have a positive (+) impact on financial performance by parameters of network capability. Corporate innovation activities have been shown to have no impact on both financial and non-financial performance, and R&D and learning capabilities have no impact on non-financial performance. It could be seen that the parameter effects of network competency are limited to when R&D and learning competencies are derived from quantitative financial performance. It could be seen that the parameter effects of network competency are limited to when R&D and learning competencies are derived from quantitative financial performance.