The following research utilizes Multi-Criteria Decision Making (MCDM) in order to build a business strategy to reduce product costs, improve competitiveness, focus on production planning based on actual operating capacity and flexible adjustment according to the market, maximize the labor productivity of technology workshops, reduce costs and inventory, and focus on producing many petrochemical products and products of high economic value. Selecting the right materials supplier is of paramount importance to the success of the organization as a whole. Supplier evaluation and the selection of a suitable supplier is a complex problem in which the decision maker must consider both qualitative and quantitative factors. Multi-Criteria Decision Making Models are an effective tool used to solve complex selection issues including multiple criteria and options, especially for qualitative variables. Thus, the author proposes an MCDM model including the Supply Chain Operation Reference (SCOR) model, analytic hierarchy process (AHP) and the Data Envelopment Analysis (DEA) method to evaluate and select the optimal supplier in the oil industry. The criteria used to evaluate potential suppliers are determined through the SCOR model, the weight of all criteria are defined by the AHP model through an expert’s opinion, and DEA is used to rank providers at the final stage. After the model implementation and the results, decision-making unit DMU_01, DMU_04 and DMU_10 are shown to be the best suppliers. This research provides a Multi-Criteria Decision Making model for supplier evaluation and selection in oil production projects. This research also presents useful guidelines for supplier selection processes in other industries.

In recent years, the market of textile and garment materials has been volatile, and the ongoing US-China trade war is creating good opportunities for other markets such as Vietnam, Bangladesh and Mexico to continue to expand their market share in the United States. Vietnam is expected to have great advantages thanks to cheap labor cost and strong production capacity. Raw material supplier selection in a volatile competitive environment is crucial for a company to succeed, and supplier selection is a complicate process in which decision-makers must consider multiple quantitative and qualitative features, along with their symmetrical impact, in order to achieve an optimal result. The purpose of selecting the right supplier is to improve competitiveness and product quality, while satisfying customer demand at a minimum production cost. The aim of this paper is to propose a multicriteria decision making model (MCDM) for garment and textile supplier selection. In the first stage, all criteria affecting this process are defined by using the supply chain operations reference model (SCOR) and experts’ opinion. Incorporating hybrid fuzzy set theory into the analytical network process (ANP) model is the most effective tool for addressing complex problems of decision-making, which has a connection with various qualitative criteria; thus, the Fuzzy Analytical Hierarchy Process (FAHP) was applied for determining the weight of all potential suppliers, and the preference ranking organization method for enrichment of evaluations (PROMETHEE II) was used for ranking the supplier. The results of this research will assist researchers and decision makers in identifying, adapting and applying appropriate methods to identify the optimal material suppliers in the textile and garment industry. This research can also be used to support supplier selection decisions in other industries.

Following the recent development trend in the struggle for cleaning the earth’s environment, solar is the one of most promising area that can partially be used as a replaceable energy from non-renewable fuel sources. As such, it plays a significant role in protecting the environment from global warming. As solar power does not emit harmful gases into the atmosphere, its production, distribution, setup, and operation are vital should the production remain constant. Even solar energy waste emissions are small; when compared to current energy sources, the amount of harmful gases is negligible. This paper presented an integrated approach for site of solar plants by using data envelopment analysis (DEA) and Fuzzy Analytical Network Process (FANP). Furthermore, these integrated methodologies, incorporated with the most relevant parameters of requirements for solar plants, are introduced. First, the paper considers an integrated hierarchical DEA and FANP model for the optimal geographical location of solar plants in Mekong Delta Region, Vietnam. Using the proposed model for implementation would allow the renewable energy policy makers to select and control the optimal location for allocating and constructing a solar energy power plant in Vietnam. This is the preferred strategy for location optimization problems associated with solar plant units in Vietnam and around the world.

This study aims to measure the impact of factors on the loyalty of employees at small and medium enterprises (SMEs) in Ho Chi Minh City through interviews with 640 surveys with a non-probability sampling method, a convenient approach. Quantitative analysis techniques used in the study include reliability analysis of the scale through Cronbah's Alpha index, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and Structural Equation Modeling (SEM).From the results of SEM analysis of the whole model, it is shown that the fit of the tested model is relatively high, satisfying the conditions that are CMIN = 1.975 < 3; RMSEA = 0.043 < 0.05; CFI = 0.924 > 0.9; GFI = 0.823 > 0.8, Pclose = 1.00 > 0.05; and Pvalue = 0.000 < 0.05. Besides, the SEM analysis results also show that independent factors(1) Opportunities for training and resource development; (2) Direct employee involvement; (3) Support from superiors and colleagues; (4) Environment and working conditions; (5) Salary, allowances, and benefits; (6) Fair rewards; (7) Alignment with organizational goals; (8) Level of empowerment; have a positive impact on employee job satisfaction at 1% significance level. At the same time, the job satisfaction factor in the employee's work positively impacts employees' loyalty to the organization at the 1% significance level. Accordingly, independent factors explain 72.10% of the change in job satisfaction in the employee's work; the remaining 37.90% of the change is explained by other factors. In addition, job satisfaction in employees' work explained 63.1% of the shift in employee loyalty to the organization, and 36.9% of the change was explained by factors other than the model. From the research results, the author proposes managerial implications to increase the loyalty of employees in SMEs.The study has some limitations: The study only surveyed 640 employees representing SMEs in HCMC, and the sample representativeness is not high. The governance implications are still qualitative, and obstacles to implementing the above impacts have not been assessed. The research sample uses a non-probability sampling method, so the representativeness of the study population is not high.

Trong thời đại công nghệ số, Chat GPT (Generative Pre-trained Transformer) là một trong những công nghệ tiên tiến nhất trong lĩnh vực xử lý ngôn ngữ tự nhiên. Chat GPT là một mô hình học sâu được huấn luyện trước trên dữ liệu lớn, có khả năng tự sinh ra các văn bản có ý nghĩa. Sử dụng Chat GPT làm công cụ hỗ trợ trong việc dạy và học truyền thông có thể giúp nâng cao hiệu quả giảng dạy và học tập. Mục tiêu của nghiên cứu này là làm rõ những vấn đề nảy sinh, sự thay đổi trong quy trình dạy và học khi Chat GPT được sử dụng làm công cụ hỗ trợ. Đối tượng chính là sự thay đổi của hoạt động dạy và học truyền thông khi dùng Chat GPT. Phương pháp nghiên cứu chủ yếu là phân tích tư liệu thứ cấp, điều tra xã hội học, phỏng vấn định tính. Kết quả nghiên cứu là làm sáng tỏ thay đổi trong dạy và học truyền thông khi có Chat GPT, đồng thời đưa ra dự báo về triển vọng dùng Chat GPT như công cụ hỗ trợ. Kết luận: Đưa ra được kết luận mang tính cốt lõi về sự tác động của Chat GPT đến việc dạy và học ngành truyền thông. Kiến nghị: Đưa ra được những kiến nghị về công tác đào tạo ngành truyền thông ở đại học trong điều kiện mới.