• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.4
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• pp.167-178
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• 2021

The purpose of this study is to analyze the direct investment decision factors in the Kaesong Industrial Complex and Vietnam, and to contribute to the creation of domestic jobs and the revitalization of the inter-Korean economy. According to the analysis, most of the Kaesong Industrial Complex and Vietnamese investment companies are entering the complex for the purpose of utilizing cheap labor, cheap factory locations, sales/development of local markets, and bypass export production bases in third countries. This can be divided into production-efficient investors using differences in production price such as labor costs and market-oriented investors to sell and expand the local market, which seems to be consistent with global direct investment patterns such as Nike, Apple, and Amazon. However, even if the North Korea-U.S. denuclearization talks ease or lift sanctions, Vietnamese investors' willingness to invest in the North Korea has been most burdened by the possibility of closing special economic zones due to political risks. Last but not least, it is important to note that those willing to invest in North Korea are mostly smaller enterprises in textiles, sewing, footwear and leather industries-those that benefit from low-cost labor. Since their size is small, they need policy support in financing, especially in the early stages of their business. Even after they grow past the early stages, those without collateral would still need state guarantee letters to get financing. Thus, it is worth considering to use the Inter-Korean Cooperation Fund to compensate commercial banks for bad loan loss or for low-interest loans for smaller SMEs. The interviews with SMEs found that red-tape is one of the biggest difficulties they face. Thus, it is recommended that a one-stop service agency should be established to cover all processes and issues related to inter-Korean economic cooperation to eliminate redundancy and expediate government support for SMEs.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.5
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• pp.109-124
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• 2021

This study tried to verify the causal relationship that SMEs' organizational culture and self-efficacy would affect job crafting and job satisfaction. Unlike previous domestic studies that have been studied for organizational culture at the organizational level and self-efficacy at the individual level, this study tried to verify the interaction between job crafting and job satisfaction using different mechanisms as antecedent factors. In order to verify the research model of this study, questionnaires of 144 small and medium-sized enterprises (SMEs) workers located in Seoul and metropolitan areas were analyzed. Factor analysis and correlation analysis were performed to verify the reliability and validity of the research model on the relationship between variables, and empirical analysis was performed using regression analysis and mediation effect analysis to verify the hypothesis. The results of the study were first, that organizational culture and self-efficacy had a positive (+) effect on job crafting. On the other hand, relationship-oriented culture and hierarchical-oriented culture, which are sub-factors of organizational culture, were found to be insignificant. Second, organizational culture and self-efficacy were found to have a positive (+) effect on job satisfaction. On the other hand, it was found that market-oriented culture and hierarchical-oriented culture, which are sub-factors of organizational culture, were not significant. Third, job crafting was found to have a positive (+) effect on job satisfaction. On the other hand, it was found that the sub-factors of job crafting, disruptive job demands and social job resources, were not significant. This means that organizational culture partially affects job crafting and job satisfaction of SMEs, and job crafting also partially affects job satisfaction. The implications of this study are first, suggesting the meaning of SME organizational culture for stable and efficient human resource management for SMEs suffering from low productivity and high turnover rate. Second, it was meaningful to understand the possibility of introducing job crafting as an effective job management plan for SMEs. Third, in the current situation where there are few cases of practical introduction of job crafting, research on understanding job crafting for SMEs and improving job satisfaction is thought to be helpful in improving the productivity of SMEs.

• Management & Information Systems Review
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• v.37 no.4
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• pp.1-20
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• 2018

This study aimed to examine earnings quality of firms selected as Global Champs project which has been promoted by the government since 2013 to support small and medium sized enterprises, for the screening year(t-1) and selected year(t). Earing quality is measured as the value of discretionary accruals estimated by Dechow et al.(1995) adjusted Jones model and Kothari et al.(2005) model, respectively. I analyze the differences of earning quality between the Global Champ firms and the paired firms selected through criteria of the similar total assets and the same industry in the screening year and the selected year. This study is motivated by the needs of measurement of the performance of the Project from the accounting transparent point of view. As the results of this study, major findings are summarized as follows. Firstly the earnings quality of the selected firms was lower than that of the paired firms. This can be explained as a result of motivation of earnings management by companies eager to meet the requirements to be selected for the Project. Secondly, in the selected year, the earnings quality was proved to improve, comparing to the screening year. This can be explained by the efforts of companies to reinforce management innovation and transparent management, which in turn led to positive effects on the earnings quality. These findings were found to be consistent in the additional analyses, where the earning quality of the reconstructed sample with only selected companies was compared for the screening year and the selected year, based on the year before the screening year(t-2).

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.23-48
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• 2021

The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.

• Resources Recycling
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• v.31 no.5
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• pp.67-76
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• 2022

The furniture industry has a high possibility to create value-added and a high potential to create new occupations due to the characteristics of the industry, which mainly consists of small and medium-sized enterprises (SMEs). However, the used furniture, which has sufficient reuse value, is also crushed and used as solid refuse fuel (SRF) recently. Besides, the number of waste treatment companies continues to decrease, and it occurs congestion of wood waste. As a way to solve the issue, a business model development of remanufacturing used furniture can be suggested as an alternative due to its high circular economic efficiency. Remanufacturing business including furniture industry creates positive effects in various aspects such as economic, environmental and job creation. In other words, remanufacturing is an effective recycling way to reduce input resources and energy in the production process. The results of economic analysis show that the expected annual revenue from the single worker furniture remanufacturing site was 104 million won which is 3.11 times more than the average income of a single-worker household in Korea and its B/C ratio was estimated about 30 which means high business feasibility. Revenue through furniture remanufacturing also showed 320 times higher than that of SRF production from the perspective of weight. In addition, it is shown that the GHGs reduction from the furniture remanufacturing is 2.2 ton CO₂-eq. per year, which is similar to the amount of GHGs absorption effect of 937 pine trees or 622 Korean oak trees annually. Thus the results of this study demonstrate that it is important to adopt an appropriate recycling method considering the economic and environmental effects at the end-of-life stage.

• 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.

• Korea Trade Review
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• v.48 no.3
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• pp.43-68
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• 2023

In this study, in relation to "Chapter 3 Support for Priority Purchase of Technology Development Products" of the 「Market Channel Support Act」, this study investigated the positive growth impact of technology development products subject to preferential purchase on small and medium sized enterprises. The data used for empirical verification is for 371 companies that obtained certification for technology development products subject to preferential purchase in 2016 and Data from SMEs were collected from 2017 to 2021, Sales, operating profit, and net profit was identified, and empirical verification. And conducted through statistical analysis to determine whether it had a positive effect on the growth factors of SMEs. In addition, data from 225 technology development product certification companies were collected, and empirical testing was conducted through t-test analysis on the change in growth factors before and after acquiring certification. As a result of statistical analysis, it was found that the total assets, certified sales, operating profit, and net profit, which are the growth factors of a company, are all positively affected according to the type of technology development product certification. However, in the case of authentication types, some authentications showed significant negative results. In addition, significant results were derived that after acquiring certification had a positive effect on growth factors than before acquiring certification. Consistent with this conclusion, I think that it is effective for technology development-based SMEs to enter the public procurement market and utilize the technology development product priority purchase policy for market exploitation and corporate growth. And the government should strengthen the market support policy to create demand so that SMEs can enter the procurement market and actively utilize the preferential purchase system, and come up with an improvement plan so that public institutions can actively utilize the preferential purchase system.

• Journal of Venture Innovation
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• v.3 no.2
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• pp.41-76
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• 2020

This study confirmed factors affecting smart factory technology acceptance through empirical analysis. It is a study on what factors have an important influence on the introduction of the smart factory, which is the core field of the 4th industry. I believe that there is academic and practical significance in the context of insufficient research on technology acceptance in the field of smart factories. This research was conducted based on the Unified Theory of Acceptance and Use of Technology (UTAUT), whose explanatory power has been proven in the study of the acceptance factors of information technology. In addition to the four independent variables of the UTAUT : Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions, Government Assistance Expectancy, which is expected to be an important factor due to the characteristics of the smart factory, was added to the independent variable. And, in order to confirm the technical factors of smart factory technology acceptance, the Task Technology Fit(TTF) was added to empirically analyze the effect on Behavioral Intention. Trust is added as a parameter because the degree of trust in new technologies is expected to have a very important effect on the acceptance of technologies. Finally, empirical verification was conducted by adding Innovation Resistance to a research variable that plays a role as a moderator, based on previous studies that innovation by new information technology can inevitably cause refusal to users. For empirical analysis, an online questionnaire of random sampling method was conducted for incumbents of domestic small and medium-sized enterprises, and 309 copies of effective responses were used for empirical analysis. Amos 23.0 and Process macro 3.4 were used for statistical analysis. For accurate statistical analysis, the validity of Research Model and Measurement Variable were secured through confirmatory factor analysis. Accurate empirical analysis was conducted through appropriate statistical procedures and correct interpretation for causality verification, mediating effect verification, and moderating effect verification. Performance Expectancy, Social Influence, Government Assistance Expectancy, and Task Technology Fit had a positive (+) effect on smart factory technology acceptance. The magnitude of influence was found in the order of Government Assistance Expectancy(β=.487) > Task Technology Fit(β=.218) > Performance Expectancy(β=.205) > Social Influence(β=.204). Both the Task Characteristics and the Technology Characteristics were confirmed to have a positive (+) effect on Task Technology Fit. It was found that Task Characteristics(β=.559) had a greater effect on Task Technology Fit than Technology Characteristics(β=.328). In the mediating effect verification on Trust, a statistically significant mediating role of Trust was not identified between each of the six independent variables and the intention to introduce a smart factory. Through the verification of the moderating effect of Innovation Resistance, it was found that Innovation Resistance plays a positive (+) moderating role between Government Assistance Expectancy, and technology acceptance intention. In other words, the greater the Innovation Resistance, the greater the influence of the Government Assistance Expectancy on the intention to adopt the smart factory than the case where there is less Innovation Resistance. Based on this, academic and practical implications were presented.

• Journal of Venture Innovation
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• v.6 no.2
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• pp.41-65
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• 2023

This study was conducted to empirically analyse the factors that influence SMEs' intention to adopt ESG. For this purpose, we first derived the variables of usefulness of ESG and ease of adoption. In addition, we adopted CEO's will because of the importance of CEO's role in decision-making in SMEs. In addition, we added customer's request, government support, and credit evaluation reflection as institutional factors for ESG management. To examine the mediating role of attitudes and employees' innovation resistance in these relationships and how they affect ESG adoption, we set up a research model. These factors were used in the empirical analysis with 368 valid responses from the survey. Hierarchical regression analysis method using SPSS 24.0 was used for statistical analysis, and Process Macro 4.0 based on SPSS 24 was used for mediation and moderation effects. The results of the empirical analysis of this study showed that the usefulness of ESG adoption, ease of adoption, CEO's will, customer's request, government support, and credit evaluation reflection all had a positive and significant effect on the intention to adopt ESG management. In particular, among the variables affecting ESG adoption, CEO's will was found to be the most influential. Attitudes were also found to play a mediating role between the influencing factors and intention to adopt ESG management, as well as the mediating effect of employee' innovation resistance. The academic implications of this study include the identification and empirical testing of each of the influencing variables of ESG management adoption in the scarce literature on ESG in SMEs, and the prioritisation of the influence of these factors on adoption intention, which can be used to promote the adoption of ESG management. In terms of practical implications, it is important for SMEs to have a win-win relationship with large corporations, an ecosystem such as government support, in order to improve CEO awareness and motivate the CEO's will, and for smooth introduction of ESG management, it is necessary to find ways to reduce resistance through sufficient communication with organizational members to make them aware of the need.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.185-196
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• 2023

This paper investigates the effects of entrepreneurs' cognitive biases on business opportunity evaluation, given their strong entrepreneurial spirit, which is characterized by innovation, proactivity, and risk-taking. When making decisions related to business activities, entrepreneurs typically make rational judgments based on their knowledge, experience, and the advice of external experts. However, in situations of extreme stress or when quick decisions are required, they often rely on heuristics based on their cognitive biases. In particular, we often see cases where entrepreneurs fail because they make decisions based on heuristics in the process of evaluating and selecting new business opportunities that are planned to guarantee the growth and sustainability of their companies. This study was conducted in response to the need for research to clarify the effects of entrepreneurs' cognitive biases on new business opportunity evaluation, given that the cognitive biases of entrepreneurs, which are formed by repeated successful experiences, can sometimes lead to business failure. Although there have been many studies on the effects of cognitive biases on entrepreneurship and opportunity evaluation among university students and general people who aspire to start a business, there have been few studies that have clarified the relationship between cognitive biases and social networks among entrepreneurs. In contrast to previous studies, this study conducted empirical surveys of entrepreneurs only, and also conducted research on the relationship with social networks. For the study, a survey was conducted using a parallel survey method using online mobile surveys and self-report questionnaires from 150 entrepreneurs of small and medium-sized enterprises. The results of the study showed that 'overconfidence' and 'illusion of control', among the independent variables of entrepreneurs' cognitive biases, had a statistically significant positive(+) effect on business opportunity evaluation. In addition, it was confirmed that the moderating variable, social network, moderates the effect of overconfidence on business opportunity evaluation. This study showed that entrepreneurs' cognitive biases play a role in the process of evaluating and selecting new business opportunities, and that social networks play a role in moderating the structural relationship between entrepreneurs' cognitive biases and business opportunity evaluation. This study is expected to be of great help not only to entrepreneurs, but also to entrepreneur education and policy making, by showing how entrepreneurs can use cognitive biases in a positive way and the influence of social networks.