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Education, Industry 4.0 and Earnings: Evidence from Provincial-Level Data of Vietnam
TU, Anh Thuy,CHU, Phuong Thi Mai,PHAM, Truong Xuan,DO, Ngoc Minh Korea Distribution Science Association 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.2
This paper aims to analyze factors influencing earnings of workers in Vietnam using provincial-level data from 2016 to 2018. We show the important determinants of earnings of workers of more than 15 years old including working hour, labor force, life expectancy, education, regulation measured by Provincial Competitiveness Index (PCI) and especially Industry 4.0, our major depart from literature proxies by government expenditure on science and technology, number of phone lines, and number of internet users. Working hours are a typical measurement of quantity of labor supplied. Labor force represents market size from the supply side. Life expectancy measures the health of laborers, a physical quality measure of workers. PCI stands for institutional status of the locality. Two most important factors of our interest are education, representing qualification of workers, and Industry 4.0, reflecting the new working environment of workers. By estimating a robust standard error fixed-effect model, we have evidence that all factors are significant in explaining earnings of Vietnamese workers. Education and IR4.0 play an important role in earnings of workers of Vietnam. Results also provide an estimation of Vietnam's labor supply in the context of Industry 4.0. In addition, findings contribute to explain the income discrepancy among Vietnamese provinces.
MAI, Thi Cam Tu,NGUYEN, Hong Son,PHAN, Nguyen Ngoc Diem,LE, Minh Hang,LUU, Phuong Khanh,NGUYEN, Thi Thu Thao,NGUYEN, Thi Thu Trang Korea Distribution Science Association 2022 The Journal of Asian Finance, Economics and Busine Vol.9 No.6
This study examines the impact of CSR and its authenticity on customer loyalty through the brand image in the chain coffee shop industry. Using qualitative and quantitative methods, 601 survey questionnaires were distributed, of which 491 were analyzed. The results show that CSR has a positive impact on brand image and customer loyalty. In addition, authenticity does not moderate the impact of CSR on brand image and loyalty, as it is difficult for customers to verify the authenticity of CSR action programs. This study emphasizes the importance of CSR action programs and authenticity for businesses to sustainably enhance their distinctive brand image and customer loyalty. Therefore, for sustainable development in the future, managers of coffee shop chains need to focus on the following issues. First, the most important thing is the right awareness of businesses regarding CSR and CSR authenticity. Third, businesses should strengthen the transparency of CSR action programs in various media so that consumers can easily verify authenticity, to increase brand image and improve customer loyalty.
Dieu Linh Tran,Anh Phuong Nguyen Hong,Ngoc Hoi Nguyen,Ngoc Trinh Huynh,Bao Ha Le Tran,Cam Tu Tran,Minh Dung Truong,Quan Dang Nguyen,박기동,Dai Hai Nguyen 한국공업화학회 2023 Journal of Industrial and Engineering Chemistry Vol.120 No.-
α-calcium sulfate hemihydrate (α-HH) was synthesized by salt solution methods to prepare a promising biomaterial for bone tissue repair and regeneration. The successful synthesis of α-HH was evaluated by field emission scanning electron microscopy (FE-SEM), thermogravimetric analysis (TGA), X-ray diffraction (XRD), and Fourier transform infrared (FTIR) scanning. The sterility of α-HH before and after irradiation with gamma ray was firstly confirmed by Colonies Forming Units (CFU) counting assay, to target the surgical grade application. In vitro tetrazolium bromide (MTT) assay, crystal violet (CV) and acridine orange (AO) staining was performed to assess the initial cytotoxicity and cell attachment ability of α-HH. Further in vivo implantation into rabbit distal femoral condyles defect exhibited the ability of salt solution-synthesized α-HH to promote the localization of osteocytes and osteoblasts, which improve the bone tissue repair and regeneration. The findings suggested that α-calcium sulfate hemihydrate synthesized by salt solution method is a potential material that can be used as bone substitutes.
Innovation Capacity of Student: A Case Study in Vietnam
Anh Duc DO,Nguyen Nguyen Thao PHAM,Thi Minh Phuong NGUYEN,Van Son TU,Cam Nhung NGUYEN,Hai Duong NGUYEN 한국유통과학회 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.5
This study aimed to explore the factors affecting the innovation capacity of students at the National Economics University, Vietnam. Researchers used the innovation capacity model based on six factors, including personality traits, future orientation, creative skills, social interaction, content knowledge, and management skills. The empirical analysis used data from the survey of 303 students at National Economics University, Vietnam, with reliable tools (SPSS 26.0 software). The data were analyzed by testing the reliability of the scales, correlation analysis, and Pearson’ Linear Correlation Coefficient, exploratory factor analysis, as well as regression model based on the survey data. The research results identified the following factors affecting innovation capacity of students: management skills, social interaction, and personality traits have the strongest impact on innovation capacity of students; content knowledge has the following strongest effects on innovation capacity of students; and finally the creative skills that affects on innovation capacity of students. There is also a positive relationship between all the factors and innovation capacity of students. The result can serve as useful reference sources for scholars who are interested in the innovation field. It also helps university’s managers and policymakers build the appropriate environment to improve innovation capacity of students.
FGW-FER: Lightweight Facial Expression Recognition with Attention
Huy-Hoang Dinh,Hong-Quan Do,Trung-Tung Doan,Cuong Le,Ngo Xuan Bach,Tu Minh Phuong,Viet-Vu Vu 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.9
The field of facial expression recognition (FER) has been actively researched to improve human-computer interaction. In recent years, deep learning techniques have gained popularity for addressing FER, with numerous studies proposing end-to-end frameworks that stack or widen significant convolutional neural network layers. While this has led to improved performance, it has also resulted in larger model sizes and longer inference times. To overcome this challenge, our work introduces a novel lightweight model architecture. The architecture incorporates three key factors: Depth-wise Separable Convolution, Residual Block, and Attention Modules. By doing so, we aim to strike a balance between model size, inference speed, and accuracy in FER tasks. Through extensive experimentation on popular benchmark FER datasets, our proposed method has demonstrated promising results. Notably, it stands out due to its substantial reduction in parameter count and faster inference time, while maintaining accuracy levels comparable to other lightweight models discussed in the existing literature.