• The Southeast Asian review
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• v.28 no.3
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• pp.159-212
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• 2018

This paper is focused on analyzing the social environment of a rapidly changing on Vietnamese company. The key analysis of this study is on the change of perception in Vietnam and the regional difference of CSR acception. The social acceptance research of CSR is centered on the comparative analysis of Korean, Japanese and Chinese companies Social Activities in Vietnam. In addition, This paper seek to way of contribute to the sustainable development of Korean companies, and its harmonious cooperation with Vietnamese society through reviewing the CSR activities and direction of their CSR expectation. In the paper, linkage analysis was conducted with the results of the study on CSR value development process in Vietnam society and analysis of social responsibility values obtained from empirical studies. Through this, finally, we trying to search the value of social responsibility in Vietnam and its future directions. When we understand Vietnam's CSR, based on 'locality' of Vietnam, Northern and Southern can be understand on its different backgrounds. And it can be analyzed by their CSR characteristics of acception. As the result of this research, In the North, Foreign companies' CSR is understanded to be viewed from the corporate economic income and distribution. In the South, there is a strong tendency to understand CSR activities of foreign companies as marketing activities. On the whole, In northern Hanoi, there was a strong expectation in terms of 'employment improvement' and 'workers' working conditions'. In the South, there was a greater interest in improving the 'quality of life of residents' and 'consumer protection'. This is due to the influence of the economic system experienced during the process of different colonization, modernization and communization between the two regions. Since the Reform and Opening of Vietnam, Social Awareness of CSR seems that the regional differences were formed by the pace of economic development and the economic environment has played a role. In particular, the social acceptance of CSR values showed a slight difference in recognition between the North and South regions, but as both regions showed common hope for 'intervention in the role of government'. Therefore, Social Awareness of Vietnam's CSR is based on relation of 'government-society' formed from the 'Communitarianism'. As foreign investment flows more, CSR awareness and expectations in Vietnam's society will increase further. And the CSR expectations of local governments and stakeholder will be more complicated. It is time to check the needs of Vietnamese society in relation to locality of the social responsibility activities.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.2
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• pp.109-121
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• 2021

With the recent increase in senior retirement, and senior start-ups are becoming more active due to high interest in start-ups. Research on young entrepreneurship, including college students, is being actively conducted, but most of the preceding research on senior entrepreneurship was conducted mainly on personal characteristics and social environment, and there were not many empirical studies on the influencing factors of entrepreneurship support policies. In this study, research and discussion on the entrepreneurial support policy and entrepreneurial competence as the influencing factors of senior entrepreneurship. As the independent variable of this study, the founder's competency was adopted as two factors: technical competence and creative competency, and the entrepreneurial support policy was divided into education support and funding support. Mentoring was set as a controlling variable and entrepreneurial intention was set as a dependent variable. A total of 232 questionnaires collected from seniors in their 40s or older were empirically analyzed. To verify the hypothesis of the study, SPSS 23 was used for exploratory factor analysis and regression analysis, and Process 3.4 was used for moderation effect. As a result of the study, it was found that the factors of technical competence, creative competence, educational support, and funding all have a significant influence on the will of entrepreneurship. It was found that creative competency(𝛽=.318), funding support(𝛽=.188), educational support(𝛽=.152), and technical competence(𝛽=.139), in this order, influenced the entrepreneurial intention. It was verified that the moderating effect of mentoring was significant between technical competence, creative competence, and entrepreneurial intention, but the moderating effect of mentoring between educational support, funding and entrepreneurial intention was not. The implications of this study will contribute to the research of senior start-up support policies, institutional supplementation, and differentiated start-up support programs by studying the factors of senior start-up capabilities and start-up support policies. It is also believed that it will contribute to the search for ways to increase creative capabilities that have a high influence on the willingness to start a business and the expansion of mentoring functions.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• Maritime Security
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• v.1 no.1
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• pp.273-310
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• 2020

This study aims at empirically analyzing the overall mechanism of the "Gray Zone Strategy", which has begun to be used as one of Chinese major maritime security strategies in maritime conflicts surrounding the South China Sea and East China Sea since early 2010, and comparing the resulting conflict patterns in those reg ions. To this end, I made the following two hypotheses about Chinese gray zone strategy. The hypotheses that I have argued in this study are the first, "The marine gray zone strategy used by China shows different structures of implementation in the South China Sea and the East China Sea, which are major conflict areas.", the second, "Therefore, the patterns of disputes in the South China Sea and the East China Sea also show a difference." In order to examine this, I will classify Chinese gray zone strategy mechanisms multi-dimensionally in large order, 1) conflict trends and frequency of strategy execution, 2) types and strengths of strategy, 3) actors of strategy execution, and 4) response methods of counterparts. So, I tried to collect data related to this based on quantitative modeling to test these. After that, about 10 years of data pertaining to this topic were processed, and a research model was designed with a new categorization and operational definition of gray zone strategies. Based on this, I was able to successfully test all the hypotheses by successfully comparing the comprehensive mechanisms of the gray zone strategy used by China and the conflict patterns between the South China Sea and the East China Sea. In the conclusion, the verified results were rementioned with emphasizing the need to overcome the security vulnerabilities in East Asia that could be caused by China's marine gray zone strategy. This study, which has never been attempted so far, is of great significance in that it clarified the intrinsic structure in which China's gray zone strategy was implemented using empirical case studies, and the correlation between this and maritime conflict patterns was investigated.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.1
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• pp.147-159
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• 2021

After the 2020 Corona 19 pandemic, consumers' online consumption is increasing rapidly, and non-store online retail channels are showing high growth. In particular, social media is gaining its status as a social media market where direct transactions take place in the means of promoting companies' brands and products. In this study, changes in consumer behavior after the Corona 19 pandemic are different in choosing online shopping media such as existing online shopping malls and SNS markets that can be classified into open social media and closed social media when purchasing agri-food online. We tried to find out what type of product is preferred in the selection of agri-food products. For this study, demographic characteristics of consumers, perceived risk of consumers, and dietary lifestyle were set as independent variables to investigate the effect on online shopping media type and product selection. The summary of the empirical analysis results is as follows. When consumers purchase agri-food online, there are significant differences in demographic characteristics, consumer perception risks, and detailed factors of dietary lifestyle in selecting shopping channels such as online shopping malls, open social media, and closed social media. Appeared to be. The consumers who choose the open SNS market are higher in men than in women, with lower household income, and higher in consumers seeking health and taste. Consumers who choose the closed SNS market were analyzed as consumers who live in rural areas and have a high degree of risk perception for delivery. Consumers who choose existing online shopping malls have high educational background, high personal income, and high consumers seeking taste and economy. Through this study, we tried to provide practical assistance by providing a basis for judgment to farmers who have difficulty in selecting an online shopping medium suitable for their product characteristics. As a shopping channel for agri-food, social media is not a simple promotional channel, but a direct transaction. It can be differentiated from existing studies in that it is approached as a market that arises.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.256-266
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• 2022

Empirical models including the Angstrom-Prescott (AP) model have been used to estimate solar radiation at sites, which would support a wide use of crop models. The objective of this study was to estimate two sets of solar radiation estimates using the AP coefficients derived for climate zone (AP_Frere) and specific site (AP_Choi), respectively. The daily solar radiation was estimated at 18 sites in Korea where long-term measurements of solar radiation were available. In the present study, daily solar radiation and sunshine duration were collected for the period from 2012 to 2021. Daily weather data including maximum and minimum temperatures and rainfall were also obtained to prepare input data to a process-based crop model, CERES-Rice model included in Decision Support System for Agrotechnology Transfer (DSSAT). It was found that the daily estimates of solar radiation using the climate zone specific coefficient, SFrere, had significantly less error than those using site-specific coefficients S_Choi (p<0.05). The cumulative values of S_Frere for the period from march to September also had less error at 55% of study sites than those of S_Choi. Still, the use of S_Frere and S_Choi as inputs to the CERES-Rice model resulted in slight differences between the outcomes of crop growth simulations, which had no significant difference between these outputs. These results suggested that the AP coefficients for the temperate climate zone would be preferable for the estimation of solar radiation. This merits further evaluation studies to compare the AP model with other sophisticated approaches such as models based on satellite data.

• Land and Housing Review
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• v.14 no.1
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• pp.47-66
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• 2023

This study reviews prior studies on the residential environment characteristics, residential satisfaction, residential ownership consciousness and housing movement of MZ generation and analyze the structural equation models using the 2020 Korea Housing Survey data. Using 14 residential characteristics based on three classifications, we explore the effects on residential satisfaction, residential ownership consciousness, and housing movement. The empirical results are summarized as follows. First, based on factor analysis with Varimax of principal component analysis, parking facility items were excluded from the analysis by hindering validity, and as a result, KMO was 0.925 and Bartlett's test result showed a significant probability of less than 0.01. This indicates that the factor analysis model was suitable. Second, the results of the structural equation analysis for the MZ generation show that the surrounding environment, which is a potential variable of the residential environment characteristics, was statistically significant, but the accessibility and convenience were not statistically significant. Third, we find that the higher the satisfaction with the accessibility of commercial facilities, the more significant the sense of housing ownership appears. This suggests that the younger generation such as the MZ generation has a stronger desire for consumption. Fourth, the overall housing satisfaction of the MZ generation was significant for housing movement, but not for housing ownership. Compared to the industrialized generation, the baby boom generation, and the X generation, MZ generation shows distinct factors for housing satisfaction, housing ownership, and housing movement. Therefore, the residential environment characteristics of the residential survey should be improved and supplemented following the trend of the times. In addition, the government and local governments should prioritize actively participating in the housing market that suits the environment and characteristics of the target generation. Finally, our study provides implications regarding the need for housing-related research on how differ in special temporal situations such as COVID-19 in the future.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.375-384
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• 2022

The shipping industry is cyclically impacted by complex variables such as various economic indicators, social events, and supply and demand. The purpose of this study was to analyze the operating profit of 13 Korean liner companies over 30 years, including the financial crisis of the late 1990s, the global financial crisis of the late 2000s, and the COVID-19 global pandemic. This study was conducted to also identify factors that impacted the profit ratio of Korea's liner shipping companies according to economic conditions. It was divided into ocean-going and short-sea shipping, reflecting the characteristics of liner shipping companies, and was analyzed by hierarchical multiple regression analysis. The time series data are based on the Korean International Financial Reporting Standards (K-IFRS) and comprise seaborne trade volume, fleet evolution, and macroeconomic indicators. The outliers representing the economic downturn due to social events were separately analyzed. As a result of the analysis, the China Container Freight Index (CCFI) positively impacted ocean-going as well as short-sea liner shipping companies. However, the Korean container shipping volume only impacted ocean-going liners positively. Additionally, world and Korea's GDP, world seaborne trade volume, and fuel price are factored in the operating profit of short sea liner shipping. Also, the GDP growth rate of China, exchange rate, and interest rate did not significantly impact both groups. Notably, the operating profitability of Korea's liner shipping shows an exceptionally high rate during the recessions of 1998 and 2020. It is paradoxical, and not correlated with the classical economic indicators. Unlike other studies, this paper focused on the operating profit before financial expenses, considering the complexity as well as difficulty in forecasting the shipping cycle, and rendered conclusions using relatively long-term empirical analysis, including three economic shocks.

• Korean Journal of Culture and Social Issue
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• v.22 no.4
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• pp.523-541
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• 2016

Both the child's and defendant's testimonies play crucial roles in the court's ruling of a child abuse case. Thus, empirical studies examining a child's truthful report, that is, disclosure, of his or her experience and recantation of the disclosure have manifold practical implications. The objective of the present study was to examine how easily a child recants his or her testimony after witnessing and disclosing an adult engaging in a small mistake. Furthermore, this study examined whether the child's age and emotional support from his or her caregiver predict the recantation of the child's testimony. Children of age 5-8 years played with dolls with the experimenter and witnessed the experimenter breaking the doll mask. The experimenter asked the children to keep it a secret. Then the children had the first memory interview, during which the interviewer induced the child to disclose the incident. Based on the treatment conditions, some children were provided supportive feedback while other received unsupportive feedback from their primary caregivers (mother) regarding the disclosure, then were interviewed for the second time. First, the author of this study examined whether the children would recant their disclosure (whether they would deny the incident after telling the truth of about what happened to the doll), and also examined the features of the child's voluntary reports, that is, the degree of their honesty. The findings of the experiment indicated that there were age-specific differences in the frequency of recantation, meaning that older children (8-9-year-olds) showed a stronger tendency to maintain their recantation in the second interview than relatively younger children (6-7-year-olds). Furthermore, children who received supportive responses from their mothers regarding the disclosure demonstrated more honest reports compared to those who received unsupportive responses from their mothers. The findings of this study assist the understanding of the effects of social-motivational factors on the process of children disclosing the truth when voluntarily recalling a negative incident that they had experienced and provide practical implications in legal aspects.

• Economic Analysis
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• v.26 no.1
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• pp.1-33
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• 2020

Recent discussions about a minimum wage increase (MWI) and its influence on the economy have mainly focused on the quantitative aspects, such as labor costs and employment. However, concerning the qualitative aspects, an MWI could have positive effects by enhancing firm productivity and crowding out marginal firms from the market. These positive effects of an MWI can offset, to some extent, its potential negative effects - increasing labor costs and decreasing employment, among others. In this regard we empirically examine the impact of an MWI on firm productivity (total factor productivity). Using firm level panel data from the manufacturing industry in Korea, we calculate the influence rates of a minimum wage by sector and by firm size (number of workers), and analyze its effects on firm productivity. In particular, the production functions of the firms are estimated by taking into account endogeneity among the input factors, in order to resolve the drawbacks of existing studies - underestimating the capital factor coefficient and overestimating the labor factor coefficient. This study finds that the influences of an MWI on wages, employment, and productivity are substantially different across sectors and firm sizes. While an MWI has shown to have positive influences on productivity growth in the manufacturing industry as a whole, each sector demonstrates a different direction of effect, and the degree of productivity change also varies by sector. The impacts of an MWI on firm productivity are generally estimated to be more negative for smaller firms, but in some sectors the effects are found to be positive. In addition, the wage increases resulting from an MWI seem to cause a productivity enhancement across all sectors in the manufacturing industry. The policy implications of this study are as follows. Considering the empirical findings that an MWI causes an increase in productivity in many sectors of the manufacturing industry, it would be desirable to take into consideration not only the negative side effects but also the positive effects of an MWI when designing any future minimum wage policy. Moreover, in spite of there being a uniform minimum wage, this study finds that the diverse influence rates of a minimum wage across firms have different impacts on wages, employment, and productivity across sectors or firm size. This finding could be conducive to discussions about differentiation among minimum wage schemes by sector or firm size.