• The Journal of Asian Finance, Economics and Business
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• 제9권6호
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• pp.69-79
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• 2022

The purpose of the study is to look into the likelihood of private sector enterprises going bankrupt due to COVID-19 pandemic-related issues. The data for this study was taken from the World Bank's Enterprise Survey, which was intended to assess the impact of the COVID-19 pandemic on the business sector. This study uses the Ordinal Logit Method to analyze the model with dependent variables having ordinal values. The determinants reflect business performance, innovation, business relationships, and government support. According to the estimation results, a lower probability of business closures, illiquidity, and payment delays are found in businesses that maintain sales growth, operating hours, temporary workers, product portfolio, consumer demand, and input supply. Meanwhile, the increase in online business activities and receiving support from financial institutions and the government do not help businesses reduce the risk. Moreover, higher survival is found in manufacturing and developing countries. This implies the fragility of businesses in the retail and service sectors, especially for mega-enterprises in developed countries. In addition, the negative impact of the COVID-19 pandemic on businesses in Europe and West Asia is less severe than in other regions. The results imply policies to support the private sector during the pandemic, such as increasing labor market flexibility or rapidly implementing supportive policies.

• The Journal of Asian Finance, Economics and Business
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• 제9권6호
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• pp.1-9
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• 2022

The study aims to determine the factors and their influence on the income from using public agricultural land of households. Public agricultural land is agricultural land, including land for growing annual crops, perennial crops, and land for aquaculture, leased by commune-level People's Committees with a lease term of not more than 5 years. Secondary data were collected for the 2017-2021 period at state agencies. Primary data were collected from a survey of 150 households renting public agricultural land. The regression model assumed that there were 28 factors belonging to 7 groups. The test results show that 25 factors affect income, and 03 factors do not. The group of COVID-19 pandemic factors has the strongest impact, followed by the groups of agricultural product market factors, land factors, capital factors, production cost factors, labor factors, and climatic factors. The impact rate of COVID-19 pandemic factors is the largest (23.00%); The impact rate of climatic factors is the smallest (6.04%). Proposals to increase income include good implementation of disease prevention and control; increasing the land lease term; accurately forecasting the supply and demand of the agricultural market; raising the level of the household head; ensuring sufficient production capital, and adapting to the climate.

• International Journal of Internet, Broadcasting and Communication
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• 제14권3호
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• pp.91-100
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• 2022

Major developed countries are seriously considering smart factories to increase their manufacturing competitiveness. Smart factory is a customized factory that incorporates ICT in the entire process from product planning to design, distribution and sales. This can reduce production costs and respond flexibly to the consumer market. The smart factory converts physical signals into digital signals, connects machines, parts, factories, manufacturing processes, people, and supply chain partners in the factory to each other, and uses the collected data to enable the smart factory platform to operate intelligently. Enhancing personalized value is the key. Therefore, it can be said that the success or failure of a smart factory depends on whether big data is secured and utilized. Standardized communication and collaboration are required to smoothly acquire big data inside and outside the factory in the smart factory, and the use of big data can be maximized through big data analysis. This study examines big data analysis and standardization in smart factory. Manufacturing innovation by country, smart factory construction framework, smart factory implementation key elements, big data analysis and visualization, etc. will be reviewed first. Through this, we propose services such as big data infrastructure construction process, big data platform components, big data modeling, big data quality management components, big data standardization, and big data implementation consulting that can be suggested when building big data infrastructure in smart factories. It is expected that this proposal can be a guide for building big data infrastructure for companies that want to introduce a smart factory.

• 식품보건융합연구
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• 제8권3호
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• pp.1-9
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• 2022

Purpose-Meat plays an important role in the Chinese daily diet, however, due to the spread of COVID-19, food supply and safety have become a major concern. The safety and health features of chilled fresh meat have attracted the attention of consumers. To study consumers' purchasing behavior and willingness to pay for chilled meat under the influence of the epidemic. Research methodology- The data were obtained by questionnaire survey, major issues include consumers' meat consumption habits in the wake of the COVID-19 and their awareness of meat product quality labels. In addition, the gender, age, family income, and other basic personal information of the interviewees were also counted. Based on the binary Logit regression method, we study consumers' purchasing behavior and willingness to pay for chilled meat under different demographic characteristics. Results-The results showed that brand and quality certification are important factors influencing purchases. In addition, the presence of children under the age of 12 in the household and the level of income and education also influence consumers' purchase intention of the chilled fresh meat. However, mart promotions and city ratings can significantly lower consumers' propensity to buy the chilled fresh meat. Apart from this, such factors as gender, age, and living conditions have no significant influence on consumers' purchase of chilled fresh meat.

• Asia Marketing Journal
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• 제20권3호
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• pp.1-15
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• 2018

Dongwon Systems established in 1977 to exclusively supply Dongwon tuna cans, the parent company. Instead of its stable management and profits by relying on the parent company, the company was not complacent and started innovating and challenging new markets. Dongwon Systems decided to expand the business area and pioneer new markets so that it becomes the first domestic company to successfully expand into independent businesses other than parent company products. Such success of Dongwon Systems was driven by its differentiated B2B strategies. Unlike the characteristics of usual B2B companies, Dongwon Systems has been thinking both of its client companies and end-consumers. In this case-study, we will explore how Dongwon Systems became the No.1 packaging solution company in Korea through technology innovation in the aspects of unique B2B marketing strategy. The key success factor can be summarized in three ways; product and technology development with customer centric mind-set, systematically extending new markets through business diversification, and marking Southeast Asia as a bridgehead for its global strategy. It is expected that the current case study of Dongwon Systems will be able to provide implications for B2C companies as well as B2B companies that try to expand their business portfolio and global business areas through B2B marketing case analysis.

• 이베로아메리카
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• 제12권2호
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• pp.383-428
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• 2010

To make a critical revision on the inherited social problems throughout the time in Mexico, not always turns out to be easy task, especially when the subject is lent to approach it from diverse perspective, one of them, the educative one. To analyze the low quality of the educative supply is complex subject. One of the maximum profits of institutional revolutionary Mexico was the creation of the Public Education Ministry in 1921. In the post-revolutionary and modern period, the seventies were characterized to be applied to the growth the infrastructure and the fortification of the educative system following the policy of "modernization and development". From the eighties, to lift the quality of the education was considered like one of the specific rules in the strategy of the call "educative revolution". In the nineties, through political programs and agreements, structural changes within the educative system were carried out with the intention to lift the quality of the services. In synthesis, the perspective in the educative policy of Mexico during the last thirty years of century xx, or post-revolutionary period, can be understood, from at least five specific conditions: educative profits in cover, modifications in the educational programs and contents, profits in the political agreements between the agents who take part within the educative system, changes and modifications to the laws applicable to the education, and; the search of the fairness through the compensatory programs. This paper tries to give answer to questions such as: The educative system reflects the ideals of the revolution? The present educative system is the product of a truncated revolution or the fruit of an untimely democracy?

• 무역학회지
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• 제47권1호
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• pp.1-12
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• 2022

This study analyzes FCEV among measures to respond to climate change policies. In particular, it proposes alternatives to solve this problem in the trade industry, which relies on transportation sectors with high greenhouse gas emissions such as exports and imports of goods. Therefore, when FCEV is introduced in the transportation sector, changes in CO2 emissions, a greenhouse gas, and changes in logistics costs for changes in CO2 emissions are set through scenarios to evaluate the impact on product trade, such as imports and exports. As a result, the increase in logistics costs due to carbon dioxide emissions affected the import and export volume of goods, and when FCEV was introduced, the export volume would increase by up to 5.6%, and the import volume by up to 30%. In addition, CO2 emissions decreased to about 60% in 2050. Therefore, the introduction of FCEV in the transportation sector will greatly contribute to increasing sales in the trading industry and will be able to solve environmental problems such as greenhouse gas reduction.

• Steel and Composite Structures
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• 제49권6호
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• pp.645-666
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• 2023

Due to the steadily declining supply of natural coarse aggregates, the concrete industry has shifted to substituting coarse aggregates generated from byproducts and industrial waste. Oil palm shell is a substantial waste product created during the production of palm oil (OPS). When considering the usage of OPSC, building engineers must consider its uniaxial compressive strength (UCS). Obtaining UCS is expensive and time-consuming, machine learning may help. This research established five innovative hybrid AI algorithms to predict UCS. Aquila optimizer (AO) is used with methods to discover optimum model parameters. Considered models are artificial neural network (AO - ANN), adaptive neuro-fuzzy inference system (AO - ANFIS), support vector regression (AO - SVR), random forest (AO - RF), and extreme gradient boosting (AO - XGB). To achieve this goal, a dataset of OPS-produced concrete specimens was compiled. The outputs depict that all five developed models have justifiable accuracy in UCS estimation process, showing the remarkable correlation between measured and estimated UCS and models' usefulness. All in all, findings depict that the proposed AO - XGB model performed more suitable than others in predicting UCS of OPSC (with R², RMSE, MAE, VAF and A_15-index at 0.9678, 1.4595, 1.1527, 97.6469, and 0.9077). The proposed model could be utilized in construction engineering to ensure enough mechanical workability of lightweight concrete and permit its safe usage for construction aims.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권3호
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• pp.528-550
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• 2024

Warehousing demand prediction is an essential part of the supply chain, providing a fundamental basis for product manufacturing, replenishment, warehouse planning, etc. Existing forecasting methods cannot produce accurate forecasts since warehouse demand is affected by external factors such as holidays and seasons. Some aspects, such as consumer psychology and producer reputation, are challenging to quantify. The data can fluctuate widely or do not show obvious trend cycles. We introduce a new model for warehouse demand prediction called MAGRU, which stands for Multi-layer Attention with GRU. In the model, firstly, we perform the embedding operation on the input sequence to quantify the external influences; after that, we implement an encoder using GRU and the attention mechanism. The hidden state of GRU captures essential time series. In the decoder, we use attention again to select the key hidden states among all-time slices as the data to be fed into the GRU network. Experimental results show that this model has higher accuracy than RNN, LSTM, GRU, Prophet, XGboost, and DARNN. Using mean absolute error (MAE) and symmetric mean absolute percentage error(SMAPE) to evaluate the experimental results, MAGRU's MAE, RMSE, and SMAPE decreased by 7.65%, 10.03%, and 8.87% over GRU-LSTM, the current best model for solving this type of problem.

• 산학경영연구
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• 제20권2호
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• pp.61-85
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• 2007

기업의 경쟁력은 본질적으로 기업이 생산하는 제품이나 서비스의 가치에 의존한다. 왜냐하면 가치가 높은 제품이나 서비스는 고객으로 하여금 구매행동을 유발하기 때문이다. 서비스 믹스는 제품의 물리적 특성과 서비스의 최적결합을 통해서 고객을 위한 가치창출을 통해 경쟁력을 창출하는 프로세스이다. 본 연구에서는 기업에서 서비스 믹스가 기업경쟁력에 미치는 영향에 관한 연구를 통해서 우리나라 제조 기업의 경쟁력 향상에 기여하고자 한다. 경쟁우위를 위한 접근은 흔히 산업 구조 경쟁이론과 자원기반 관점 접근에 의존하고 있다. 그러나 산업 구조에 경쟁 이론은 어느 산업이 매력적인 산업 인가를 발견 하는 데에도 도움이 되지만 어느 기업은 특정의 산업에 진출하여 성공 할 수 있고 다른 기업은 실패하였는가에 대해서는 별다른 도움을 주지 못한다고 논의되고 있다. 자원기반 관점 절은 경쟁력 제고에 많은 공헌에도 불구하고 기업 전략 분석을 위한 이론이나 체계적인 틀은 제시하지 못하는 한계성이 있다. 본 연구에서는 이러한 한계성을 극복하고, 기업의 경쟁력 향상을 위하여 파워 프로세스 적 접근을 적용하였다. 파워프로세스는 권력요소, 가치, 욕구, 환경, 관계의 다섯 권력결정요소의 상호작용에 의해서 권력원천인 가치를 창출하는 프로세스이다. 즉 파워프로세스는 권력주체의 목적을 달성하기 위해서 권력객체를 만족시키는 가치를 창출하는 프로세스이다. 본 연구는 파워프로세스의 관점에서 서비스믹스 전략을 수립하여 우리나라 제조기업의 경쟁력 향상에 기여고자 한다.