Vietnam is currently among the top-five textile and apparel exporters, and the industry is considered quite attractive to foreign investors. Nevertheless, the global textile and garment industry is experiencing important changes. The three main producing regions in the world are China, Southwest Asia (India, Pakistan, Bangladesh, and Turkey), and ASEAN. In order to maintain its positioning and to establish stable and sustainable Vietnam textile and apparel development, there must be radical changes. Due to this necessity, the authors conducted this study by using grey forecasting to predict and reflect the condition of businesses in the period of 2017-2020, together with combining a DEA model to help businesses select the most appropriate strategic partner in the supply chain in order to achieve economic goals and promote the strength of the businesses partaking in the association. Besides, this helps businesses exploit market opportunities and take advantage of the capabilities of the textile and apparel industry.

Economic development and the overpopulation in Vietnam have led to rapid urbanization, which has posed countless difficulties and challenges to its government. In particular, creating adequate accommodation, life activities, and entertainment are extremely urgent issues. The planning and investment in industry zones, urban areas, residential districts, and amusement parks at the right time and right place contribute to social stability and economic development, and are important issues for every government-especially in Vietnam which remains a developing country with regard to rapid industrialization and modernization speed. The population density in many localities is too dense, while in others it is too thin, resulting in a state where inhabitants have no shelter, whereas many of the buildings have been abandoned. To deal with these matters, the authors used this study to assess the investment effectiveness of leading corporations in the field of investment in urban development and infrastructure investment in Vietnam. The study focused on addressing the following issues: assessing the effectiveness of corporations in urban development and infrastructure investment in Vietnam and predicting the business state of the groups. Through business data of corporations from 2013-2016, the authors used a Grey system theory to forecast business situations for the period from 2017-2020. The authors also used data envelopment analysis (DEA) to evaluate the effectiveness of investments of the group from 2013-2020. The results will help corporations in creating suitable investment and business strategies with the changes of the domestic and world economy, and can be considered as a foundation for management units, for local government to create planning projects with feasible content, for long-term vision, and practical efficiency to quickly meet the needs of urban development plans.

Thailand’s economy is developing rapidly, with energy being a significant factor in this development. This study uses a variety of models to assess the performance of Thailand’s energy industry in two different phases, the first being from 2013 to 2017 and the second from 2018 to 2020. The Malmquist model-one of data envelopment required input and output data that showed Thailand’s productivity index and the rate-of-change ratio, which is used to assess technical changes, change efficiency, and productivity changes of the 12 listed companies in energetic generation and distribution in Thailand. To calculate future indicators, the forecast data are generated by applying the Grey model (1,1) GM(1,1). Accuracy prediction is determined by the mean absolute percentage error (MAPE). The results show that the magnitude of the change in efficiency during the first period is stable, and some major changes in the technical level of some companies may be observed. In the future, the performance of most companies has increased steadily, but performance has been outstanding. This research provides insights into Thailand’s energy over the past few years, and predictions of future performance may be used as a reference for more purposes.

The competition between enterprises in the construction market is fierce. If enterprises are unable to afford financial and technological capabilities, they could go bankrupt. Therefore, the implementation of alliances between businesses can help increase their competitiveness. In this study, the authors simultaneously used data envelopment analysis (DEA), the Grey model (GM (1,1)), and autoregressive integrated moving average (ARIMA) to choose a suitable strategic partner to boost the strength of each business and cut the cost of transportation and personnel in an attempt to help managers come up with suitable solutions, offer sustainability, and develop creative management. The results show that the chosen solution improves the business efficiency of construction businesses and offers cost savings on materials, production, and transportation. Management agencies can use the results of this study to propose suitable orientations, strengthen decision-making, and ensure strategic planning to develop the construction sector in Vietnam.

During the months of the COVID-19 epidemic, the number of processing and manufacturing agricultural products enterprises in Vietnam faced many difficulties in the consumption of agricultural products, even when they were unable to sell. Therefore, the enterprises are more and more difficult. Many enterprises are not strong enough to restore production, so it is necessary to find solutions to overcome this difficult period. In this research, the author used the application of modern statistical techniques, along with the Grey method, to predict enterprises’ business results in the future, combined with the model of Super-slacks-based-measure efficiency (Super-SBM) to help businesses select the right partners in a supply chain to achieve their business goals. By our proposed approach, the selected solution (AG6 combined with AG10) should be implemented in the future to upgrade efficiency to help stabilize output and raise productivity; thus, both parties are able not only to improve their product quality but also achieve business goals and sustainable development. In fact, it is necessary to further this study, in combination with these factors and other quantitative models, to give investors a more comprehensive view, helping them to make the right decisions and appropriately develop their businesses and social and economic development.