In Vietnam, fishing is a crucial source of nutrition and employment, which not only affects the development of the domestic economy but is also closely related to exports, heavily influencing the economy and foreign exchange. However, the Vietnamese fishery sector has been facing many challenges in innovating production technology, improving product quality, and expanding markets. Hence, the fishery enterprises need to find solutions to increase labor productivity and enhance competitiveness while minimizing difficulties. This study implemented a performance evaluation from 2015 to 2018 of 17 fishery businesses, in decision making units (DMUs), in Vietnam by applying data envelopment analysis, namely the Malmquist model. The objective of the paper is to provide a general overview of the fishery sector in Vietnam through technical efficiency, technological progress, and the total factor productivity in the four-year period. The variables used in the model include total assets, equity, total liabilities, cost of sales, revenue, and profit. The results of the paper show that Investment Commerce Fisheries Corporation (DMU10) and Hoang Long Group (DMU8) exhibited the best performances. This paper offers a valuable reference to improve the business efficiency of Vietnamese fishery enterprises and could be a useful reference for related industries.
Supply chain sustainability, which takes environmental, economic, and social factors into account, was recently recognized as a critical component of the supply chain (SC) management evaluation process and known as a multi-criteria decision-making problem (MCDM) that is heavily influenced by the decision-makers. While some criteria can be analyzed numerically, a large number of qualitative criteria require expert review in linguistic terms. This study proposes an integration of Data Envelopment Analysis (DEA), spherical fuzzy analytic hierarchy process (SF-AHP), and spherical fuzzy weighted aggregated sum product assessment (SF-WASPAS) to identify a sustainable supplier for the steel manufacturing industry in Vietnam. In this study, both quantitative and qualitative factors are considered through a comprehensive literature review and expert interviews. The first step employs DEA to validate high-efficiency suppliers based on a variety of quantifiable criteria. The second step evaluates these suppliers further on qualitative criteria, such as economic, environmental, and social factors. The SF-AHP was applied to obtain the criteria’s significance, whereas the SF-WASPAS was adopted to identify sustainable suppliers. The sensitivity analysis and comparative results demonstrate that the decision framework is feasible and robust. The findings of this study can assist steel industry executives in resolving the macrolevel supplier selection problem. Moreover, the proposed method can assist managers in selecting and evaluating suppliers more successfully in other industries.
Real estate management and its operation play a crucial role in supporting company operation. Going hand-in-hand with the rapid growth of companies, the real estate portfolio has expanded dramatically, attracting large numbers of domestic and foreign investors. This paper studied the top 12 real estate companies listed on Vietnam’s stock market to develop a method that combines the Grey methodology and the Data Envelopment Analysis (DEA) Malmquist model, intending to predict and evaluate their performances in two periods: 2015–2018 and 2019–2022. The proposed model considered three input factors, namely total assets, cost of sales, and cost of goods sold, and two output factors, namely total revenue and gross profit. Findings revealed that drastic efficiency changes in some companies should be observed at the beginning of the process, even if the technological efficiency in the period is stable. In the future period, most companies achieved relatively stable productivity. This study serves as a reference for policymakers and strategy makers by analyzing insights for the operational status of real estate businesses and providing an overview in the future toward sustainable development.
Steel is one of the most powerful industries globally, and the associated products have a tremendous impact on nurturing a sustainable society. Considering environmental concerns within this industry's supply chain is highly successful in saving both energy and natural resources and lowering greenhouse gas emissions. In light of this, sustainable suppliers are considered input partners who play a specific role in the chain of business operations of every enterprise, maintaining them to achieve higher levels of customer satisfaction and thus gain more market share. Supplier selection can be characterized as a multi-criteria decision-making (MCDM) problem under a vague and uncertain environment. In this paper, a hybrid model of fuzzy analytic hierarchy process (FAHP) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) is suggested to determine the most potent green supplier of steel manufacturing in Vietnam based on a complete set of five main criteria (price, quality, delivery, service, environment) through literature review and experts' responses. The significance of each criterion is measured by experts' judgments in linguistic terms, which can be expressed in triangular fuzzy numbers using the FAHP model. Then, the FTOPIS model is deployed to rank alternatives. A case study of Vietnam's top 10 steel manufacturers is implemented to exhibit the model's effectiveness. From FAHP findings, "lead time", "warranty", "defect rate", "supply capacity", and "product price" were recognized as the most impactful criteria. As for the ranking of sustainable suppliers, "Hoa Phat Group Joint-stock company", "Hoa Sen Group", and "Pomina Steel Corporation" are the top three optimal suppliers. In dealing with qualitative data and input uncertainties in the supplier evaluation and selection problem, this paper can suggest more possible solutions and provide significant materials in similar outsourcing selection problems and applications of relevant industries.
Maritime transport, which includes shipping and port operations, is the fundamental basis of international trade and globalization. In transportation management, efficiency is critical for verifying performance and proposing the best countermeasure to meet predetermined goals. Various efforts in this field have been made to solve this problem satisfactorily. However, the significant proportion of conventional approaches are based on long-term observations and professional expertise, with only a few exceptions based on practice-based historical data. Data Envelopment Analysis (DEA) is a non-parametric technique for analyzing various output and input variables parallelly. The efficiency of maritime transport in European countries is explored using a two-stage DEA approach based on Malmquist and Epsilon-Based Measure (EBM). First, the Malmquist model analyses countries’ total productivity growth rates and their breakdown into technical efficiency (catch-up) and technology change (frontier-shift). Second, the EBM model is used to determine the efficiency and inefficiency of the maritime transportation systems in each European country. Apart from identifying the best-performing countries in specific areas over the study period (2016–2019), the results highlight that the gap in applying the EBM method to maritime transport has been successfully closed and that the emerging paradigm, when combined with the Malmquist model, can be a sustainable and appropriate evaluation model for other research areas.
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