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Climate change and air pollution are among the key drivers of energy transition worldwide. The adoption of renewable resources can act as a peacemaker and give stability regarding the damaging effects of fossil fuels challenging public health as well as the tension made between countries in global prices of oil and gas. Understanding the potential and capabilities to produce renewable energy resources is a crucial pre-requisite for countries to utilize them and to scale up clean and stable sources of electricity generation. This paper presents a hybrid methodology that combines the data envelopment analysis (DEA) Window model, and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) in order to evaluate the capabilities of 42 countries in terms of renewable energy production potential. Based on three inputs (population, total energy consumption, and total renewable energy capacity) and two outputs (gross domestic product and total energy production), DEA window analysis chose the list of potential countries, including Norway, United Kingdom, Kuwait, Australia, Netherlands, United Arab Emirates, United States, Japan, Colombia, and Italy. Following that, the FTOPSIS model pointed out the top three countries (United States, Japan, and Australia) that have the greatest capabilities in producing renewable energies based on five main criteria, which are available resources, energy security, technological infrastructure, economic stability, and social acceptance. This paper aims to offer an evaluation method for countries to understand their potential of renewable energy production in designing stimulus packages for a cleaner energy future, thereby accelerating sustainable development.
Chia-Nan Wang; Thanh-Tuan Dang; Hector Tibo; Duy-Hung Duong. Assessing Renewable Energy Production Capabilities Using DEA Window and Fuzzy TOPSIS Model. Symmetry 2021, 13, 334 .
AMA StyleChia-Nan Wang, Thanh-Tuan Dang, Hector Tibo, Duy-Hung Duong. Assessing Renewable Energy Production Capabilities Using DEA Window and Fuzzy TOPSIS Model. Symmetry. 2021; 13 (2):334.
Chicago/Turabian StyleChia-Nan Wang; Thanh-Tuan Dang; Hector Tibo; Duy-Hung Duong. 2021. "Assessing Renewable Energy Production Capabilities Using DEA Window and Fuzzy TOPSIS Model." Symmetry 13, no. 2: 334.
Universities and academic institutions play a very crucial role in nation development through the production of highly competent manpower. The eight universities in New Zealand have been recognized as some of the top academic institutions in the world. However, the rankings from different international organizations are declining and are hardly likely to rise. Government policies in funding allocation are being blamed for the universities’ regress as they operate with an insufficient amount of funds. This study uses the Malmquist Productivity Index model to examine the technical efficiency, technological change, and productivity performance of the eight universities. This model uses a variety of inputs (number of academic and non-academic staff and total enrolment) and outputs (number of degree and postgraduate graduates, total graduates, and total operating revenue from the Equivalent Full-Time Student (EFTS) funding system and the Performance-Based Research Fund (PBRF), etc.) obtained for the period 2013–2018. The overall results show that the average catch-up and frontier-shift efficiencies of the universities are roughly in a “no-change” scenario, meaning that the universities did not make any progress over these years. The Malmquist Productivity Index (MPI) also shows a stable result, with average final values slightly higher than 1, wherein only five universities reached an actual productivity score of 1. It is recommended that the universities improve their internal factors, including personnel, equipment, facilities, and student services, while taking accounts of external aspects, such as rapid growth in technological environments and innovations, to achieve sustainable organizational progress and improved productivity. The re-assessment of government policies for funding allocation is also suggested. This research paper offers insights into the New Zealand universities’ productivity performances for the past few years. This could be used as a reference for other purposes.
Chia-Nan Wang; Hector Tibo; Van Nguyen; Duy Duong. Effects of the Performance-Based Research Fund and Other Factors on the Efficiency of New Zealand Universities: A Malmquist Productivity Approach. Sustainability 2020, 12, 5939 .
AMA StyleChia-Nan Wang, Hector Tibo, Van Nguyen, Duy Duong. Effects of the Performance-Based Research Fund and Other Factors on the Efficiency of New Zealand Universities: A Malmquist Productivity Approach. Sustainability. 2020; 12 (15):5939.
Chicago/Turabian StyleChia-Nan Wang; Hector Tibo; Van Nguyen; Duy Duong. 2020. "Effects of the Performance-Based Research Fund and Other Factors on the Efficiency of New Zealand Universities: A Malmquist Productivity Approach." Sustainability 12, no. 15: 5939.
The food and beverage industry plays a significant role in the economic development of developing and emerging countries in Asia through an immense contribution to the national income, employment, value-added inducement, and foreign exchange earnings. Among the developing countries in Asia, Thailand and Vietnam have recently experienced a significant growth in the industry due to their many advantages. However, the nascent stage of this industry was found to be lacking sustainable competitiveness in both countries. Therefore, this study aims to evaluate and forecast the performance efficiency of the food and beverage industry in Thailand and Vietnam to understand how efficient the food and beverage industry to these countries is and formulate suggestions to improve their productivity in accordance with the research findings. To achieve the research objectives, the resampling method in the data envelopment analysis is applied to measure and forecast the efficiency of 20 Vietnamese companies and 20 Thailand firms over the period of 2016 to 2023. The Malmquist productivity index is deployed to calculate the efficiency change over observed periods. The results reveal that Vietnam is found to have a higher efficiency than Thailand due to the outstanding performance of one company but have performed quite poorly due to low scores in technical and productivity change. The findings of this research can give useful information and practical suggestions to improve performance for inefficient companies as well as enhance competitiveness of the efficient companies trying to operate and reach global markets.
Chia-Nan Wang; Minh Nguyen; Anh Le; Hector Tibo. A DEA Resampling Past-Present-Future Comparative Analysis of the Food and Beverage Industry: The Case Study on Thailand vs. Vietnam. Mathematics 2020, 8, 1140 .
AMA StyleChia-Nan Wang, Minh Nguyen, Anh Le, Hector Tibo. A DEA Resampling Past-Present-Future Comparative Analysis of the Food and Beverage Industry: The Case Study on Thailand vs. Vietnam. Mathematics. 2020; 8 (7):1140.
Chicago/Turabian StyleChia-Nan Wang; Minh Nguyen; Anh Le; Hector Tibo. 2020. "A DEA Resampling Past-Present-Future Comparative Analysis of the Food and Beverage Industry: The Case Study on Thailand vs. Vietnam." Mathematics 8, no. 7: 1140.
In the fight against climate change, the utilization of renewable energy resources is being encouraged in every country all over the world to lessen the emissions of greenhouse gases. However, not all countries are able to efficiently utilize these resources, and instead of providing solutions, the inefficient use of renewable energy may lead to even more damage to the environment. Data from eight countries belonging to the highly industrialized countries (HIC) group and nine from newly industrialized countries (NIC) group were used to evaluate the energy utilization of these groups. Factors such as total renewable energy capacity, the labor force, and total energy consumption were considered to be the input factors, while, CO2 emission and gross domestic product are the output factors. These factors were used to calculate efficiency scores of every country from 2013 to 2018 using the undesirable output model of Data envelopment analysis (DEA). The grey prediction model was also used to measure the forecasted values of the input and output factors for the year 2019 to 2022, and measure again the future efficiency scores of the HICs and NICs. The combination of grey prediction and DEA undesirable output model made this paper unusual and the most appropriate method in dealing with data that contains both desired and undesired outputs. The results show that the United Kingdom, Germany, France, and the United States continuously top the efficiency ranking among the HIC group, with a perfect 1.0 efficiency score from 2013 to 2022. Russia demonstrates the lowest score of 0.1801 and is expected to perform the same low-efficiency score in the future. Within the NIC group, Indonesia can be highlighted for performing with perfect efficiency starting from the year 2015 and even through 2022. Other NICs are performing at a very low-efficiency, with scores ranging from 0.2278 to 0.2734 on average, with Turkey displaying the lowest rank. This study recommends some useful strategies to improve the utilization of renewable energy resources such as improvements in the political and legal structure surrounding their use and regulation, tax incentives or exemptions to private power producers to encourage shifting away from conventional energy production, partnerships with non-governmental and international organizations that can provide assistance in managing renewable energies, strengthening of the energy sector’s research and development activities and long-term strategic plans for the development in renewable energy with considerations to the social, environmental, and economic impact on each country.
Chia-Nan Wang; Hector Tibo; Duy Hung Duong. Renewable Energy Utilization Analysis of Highly and Newly Industrialized Countries Using an Undesirable Output Model. Energies 2020, 13, 2629 .
AMA StyleChia-Nan Wang, Hector Tibo, Duy Hung Duong. Renewable Energy Utilization Analysis of Highly and Newly Industrialized Countries Using an Undesirable Output Model. Energies. 2020; 13 (10):2629.
Chicago/Turabian StyleChia-Nan Wang; Hector Tibo; Duy Hung Duong. 2020. "Renewable Energy Utilization Analysis of Highly and Newly Industrialized Countries Using an Undesirable Output Model." Energies 13, no. 10: 2629.
The automobile industry is one of the largest economies in the world, by revenue. Being one of the industries with higher employment output, this has become a major determinant of economic growth. In view of the declining automobile production after a period of continuous growth in the 2008 global auto crisis, the re-evaluation of automobile manufacturing is necessary. This study applies the Malmquist productivity index (MPI), one of the many models in the Data Envelopment Analysis (DEA), to analyze the performance of the world’s top 20 automakers over the period of 2015–2018. The researchers assessed the technical efficiency, technological progress, and the total factor productivity of global automobile manufacturers, using a variety of input and output variables which are considered to be essential financial indicators, such as total assets, shareholder’s equity, cost of revenue, operating expenses, revenue, and net income. The results show that the most productive automaker on average is Volkswagen, followed by Honda, BAIC, General Motors, and Suzuki. On the contrary, Mitsubishi and Tata Motors were the worst-performing automakers during the studied period. This study provides a general overview of the global automobile industry. This paper can be a valuable reference for car managers, policymakers, and investors, to aid their decision-making on automobile management, investment, and development. This research is also a contribution to organizational performance measurement, using the DEA Malmquist model.
Chia-Nan Wang; Hector Tibo; Hong Anh Nguyen. Malmquist Productivity Analysis of Top Global Automobile Manufacturers. Mathematics 2020, 8, 580 .
AMA StyleChia-Nan Wang, Hector Tibo, Hong Anh Nguyen. Malmquist Productivity Analysis of Top Global Automobile Manufacturers. Mathematics. 2020; 8 (4):580.
Chicago/Turabian StyleChia-Nan Wang; Hector Tibo; Hong Anh Nguyen. 2020. "Malmquist Productivity Analysis of Top Global Automobile Manufacturers." Mathematics 8, no. 4: 580.