The period of industrialization and modernization has increased energy demands around the world. As with other countries, the Taiwanese government is trying to increase the proportion of renewable energy, especially solar energy resources. Thus, there are many solar power plants built in Taiwan. One of the most important components of a solar power plant is the solar panel. The solar panel supplier selection process is a complex and multi-faceted decision that can reduce the cost of purchasing equipment and supply this equipment on time. In this research, we propose fuzzy MCDM approach that includes fuzzy analytical hierarchy process model (FAHP) and data envelopment analysis (DEA) for evaluation and selection of solar panel supplier for a photovoltaic system design in Taiwan. The main objective of this work is to design a fuzzy MCDM approach for solar panel supplier selection based on qualitative and quantitative factors. In the first step of this research, FAHP is applied to define the priority of suppliers. The AHP combined with fuzzy logic (FAHP) can be used to rank suppliers; however, the disadvantages of the FAHP model is that input data, expressed in linguistic terms, depends on experience of experts and the number of suppliers is practically limited, because of the number of pairwise comparison matrices. Thus, we applied several DEA models for ranking potential suppliers in the final stages. As the result, decision making unit 1 (DMU 1) is the optimal solar panel supplier for photovoltaic system design in Taiwan. The contribution of this research is a new fuzzy MCDM for supplier selection under fuzzy environment conditions. This paper also lies in the evolution of a new approach that is flexible and practical to the decision maker. It provides a useful guideline for solar panel supplier selection in many countries as well as a guideline for supplier selection in other industries.

In the early 2000s, Vietnam’s government concentrated on the promotion of supporting industries which can be seen as a “key” solution to sustaining economic growth, thereby improving the national welfare. However, Vietnam’s supporting industries still exhibit lower development and competitive weakness. The main reason for this condition is due to a lack of capital, technological innovation, and necessary management skills for development. Therefore, attracting foreign direct investment (FDI) for developing supporting industries offers the best strategy to realize this solution. However, attracting FDI to develop supporting industries represents a weakness which lies in both the quantity (total capital and projects) and quality of investment. So which factors are effective to attract FDI for developing supporting industries in Vietnam? This investigation establishes an analytical hierarchy framework available to the Vietnamese government and to policymakers in order to evaluate the influence of criteria needed to attract FDI for developing supporting industries based on eight main criteria. They include legal and institutional criteria, the market size of supporting industries, human resources, infrastructure facilities, technological development and innovation, domestic supply capacity, international cooperation and competition, and other criteria. This paper uses fuzzy preference relations (FPR) to evaluate the influence of criteria necessary to attract FDI for developing supporting industries, and these analytical results demonstrate that legal and institutional criteria, domestic supply capacity, human resources, technology development and innovation are all major considerations for attracting FDI.

These days’ technologies offer new channels to reach public and market, the convergence between the various communications fields increases which is in marketing public relations strategies used to for developing a brand awareness the product such as coffee products. This paper likewise provides a solution to develop a brand awareness via media store sellers who might help the company to promote their products in light of consumer behavior. In this study, one hundred and fifteen questionnaires, on facilities available in the society, and technology distributed online, and it focuses on generations millennial in Taiwan. The purpose of the survey will focus on coffee products from Indonesia which is called Coffindo Nusantara from Coffindo Company.

Indonesia is the one of the world’s top coffee producing and exporting countries. Meanwhile, in this study, only focus on forecasting the total of domestic coffee consumption in Indonesia applied the Grey differential model which is called GM (1,1) model of Grey theory to predict the amount of domestic coffee consumption in Indonesia from 1990 to 2017. According to the estimated result, the average residual error of the Grey forecast model is over 5 percent. The model predicts that the total of consumption will increase in each year. Based on the experimental results, this proposed method apparently not only improve the forecasting accuracy of the original Grey models but also provide a valuable reference for Indonesia coffee farmer and industries to make the action plan for the future.

In this paper we analyze the relationships between certain knowledge management, organizational culture, and the results of petrochemical industries. Facing high competitive market, the enterprises should be encouraged to reform and develop knowledge management performance. The objective of this research is to identify petrochemical firms by using Decision Making Trial and Evaluation Laboratory (DEMATEL) approaches to solve this KM adoption problem, and ranks the gaps of the KM aspects in control items to achieve the aspired level of performance. This paper is matrix method-oriented, and the depth of investigation into any individual case is limited. Therefore, the methods proposed in same fields of study should preferably be used to associate deeper and more practical implications.

This paper recommends that Vietnam Airlines use a pro-offered model to both evaluate and improve its current service network being operated at international airports. The model includes cluster analysis, ANOVA, and Scheffé post hoc to provide service performance insights and to serve as a complementary corporate benchmark for evaluating service potential and for identifying deficient service areas. By means of this model, the managerial board can designate a potent strategy for ground handling service. Additionally, the given model provides expatriate station managers with a clearer viewpoint of the localized productivity level as performed in relation to other airports concomitant within their own clusters.