Sustainable development has become a global catchphrase in the recent development age. This leads to the growth of various methodologies in evaluating environmental efficiency, such as the Data Envelopment Analysis (DEA) method. The purpose of this study is to propose an extended DEA model, i.e., the undesirable output model, in measuring the relative eco-efficiency scores across nations. The study collected the data of inputs, namely bad outputs and good outputs of the top 20 Asian economies in the period of 2005–2019, and then estimated the environmental efficiency of each country and classified them. The results have shown that there are four nations having higher average environmental efficiency than others. Japan is a good example of sustainable development that simultaneously balances economic development and environmental protection. The study has also discussed possible solutions for improvement to the group of nations with low environmental efficiency. Contributing to applying a novelty extended DEA model, this work recommends a more precise model, taking the weight of outputs into account for further studies.

The emergence of non-fungible tokens (NFTs) has elicited both excitement and apprehension among consumers, who find themselves influenced by the perceived scarcity and the perceived risks surrounding these novel digital assets. This study investigates the factors influencing consumer adoption of NFTs by integrating the concepts of perceived scarcity and perceived risks within the theoretical framework of the Theory of Planned Behavior (TPB). Employing structural equation modeling, the research evaluates the impact of perceived scarcity, perceived ease of use, attitudes, subjective norms, perceived behavioral control, and perceived risk on NFT purchase intentions. The findings reveal that perceived scarcity and perceived ease of use significantly positively affect consumers' intentions to purchase NFTs. Conversely, perceived risk exerts a negative effect on purchase intentions. Additionally, the study demonstrates that attitudes, subjective norms, and perceived behavioral control positively affect NFT purchase intentions. This study provides a behavioral roadmap for navigating the complex love-hate relationship consumers have with NFTs, shedding light on the factors that motivate individuals to embrace or avoid these digital collectibles.

The outbreak of COVID-19 in 2020 resulted in notable disruptions to global shipping and the global economy. As a key indicator influenced by supply and demand conditions in the shipping industry, the Baltic Dry Index (BDI) serves as an early economic indicator for global economic production. Contrary to expectations of decline, the BDI has exhibited a substantial increase. This research paper aims to investigate the impact of the COVID-19 pandemic on global shipping through a comprehensive analysis of the BDI. The study incorporates data spanning from 2019 to 2021, encompassing the pre- and post-pandemic periods. It examines 13 independent variables, including raw material prices (such as iron ore prices), international scrap steel prices, energy prices, stock market indexes, international commodity price volatility (as represented by the Commodity Research Bureau Index), global port calls, and confirmed COVID-19 cases. The primary objective is to explore the factors influencing the BDI and how they were affected by the pandemic. The study employs stepwise regression to select variables and build models before and after the pandemic. The findings of this study elucidate the prominent factors that influence the BDI in different temporal contexts. Before the outbreak, the BDI was notably impacted by variables, including the US Dollar Index (positive relationship), Brent, Port Calls, and CRB Index. However, a discernible shift in the relative significance of these factors has been observed in the post-pandemic period. Specifically, the US Dollar Index now exhibits a negative relationship with the BDI, whereas variables such as Port Calls, Iron Price, Steel Scrap Price, and confirmed COVID-19 cases had attained heightened prominence in shaping the dynamics of the freight index. These findings underscored the dynamic nature of the factors influencing the BDI, particularly in light of the unique circumstances brought about by the COVID-19 pandemic.

Countries are paying increasing attention to environmental issues and are moving towards the goal of energy saving and carbon reduction. This research presents a method to analyse the effects of the use of non-thermal plasma (NTP) and water injection (WI) devices on the efficiency of internal combustion engines. The devices were installed on the intake manifold to investigate the effects of additional substances produced by electrolysis on the engine performance and exhaust emissions. According to the results, the addition of the NTP and WI devices affected the power efficiency and the rate of change of the brake-specific fuel consumption (BSFC) of the internal combustion engines. In addition, the change rate of hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NOx) in the exhaust gases was affected. In conclusion, the study found that the additional substances generated by the NTP-electrolysed water mist or air influenced the fuel combustion efficiency and exhaust emissions.

The outbreak of COVID-19 in 2020 caused significant disruptions to global shipping and the world economy. This paper aims to investigate the impact of the pandemic on global shipping by analyzing the Baltic Dry Index (BDI). The BDI is a metric that reflects the worldwide shipping costs and directs related to supply and demand conditions, making it an indicator of economic production. The study utilizes data from 2019 to 2021, before and after the outbreak of COVID-19, and considers 13 independent variables, including raw materials, energy, stock market indexes, global port calls, and confirmed COVID-19 cases to investigate how to influent the BDI. The study employs stepwise regression to select variables and build models before and after the pandemic. The findings reveal that the key factors affecting the freight index BDI before the outbreak are: international scrap steel prices, iron ore prices, and the Commodity Research Bureau Index. However, after the COVID-19 outbreak, the factors affecting the BDI changed to the Shanghai Index, global port calls, and the number of confirmed COVID-19 cases.

Currently, people spend many more hours on smartphones, and the potential impact of phone radiation is receiving more attention. Reducing the impact of a phone’s magnetic field on human health is vital. Although many studies advise changing phone use habits, such as reducing call times to impede phone radiation, there are no specific products found in the literature to prevent or reduce phone radiation. Therefore, this study used TRIZ theory as a research method to design prototypes in order to reduce the potential impacts of magnetic fields generated by smartphones on the human body. The results show that the distance between the human body and the phone is negatively related to phone radiation; the longer the distance is, the less phone radiation there is. Three prototypes have been designed through this research in order to reduce a phone’s radiation. The first testing condition simulates a phone conversation in which the prototypes are installed on the phone while having a WhatsApp conversation. The second testing condition simulates phone standby mode in which the prototypes are installed on a phone while the phone’s Wi-Fi, Bluetooth, data, GPS, and hotpot are on. A magnetic field tester was used to measure the magnetic fields every 5 s, and each measurement set lasted for 3 min. Five sets of measurements were completed at the end, and the average result shows that the use of prototypes under these two conditions can reduce 100% and 90% of the magnetic field generated by a smartphone during a phone conversation and the phone’s standby mode, respectively.