The Chung-Hua Institution for Economic Research (CIER; Chinese: 中華經濟研究院; pinyin: Zhōnghuá Jīngjì Yánjiùyuàn) is a Taiwan-based international policy think tank for economic and industry-related research. It conducts both public research and fee-supported research..
Molybdenum-doped nickel-cobalt oxide (NCO-Mo) nanowires were directly grown on graphite felt to construct high-performance electrodes for vanadium redox flow batteries (VRFBs). Morphological and structural characterizations (XRD, HAADF-STEM, XPS, XANES, and EXAFS) confirm a well-integrated nanowire coating with uniform elemental distribution and Mo incorporation into the NiCo2O4 host without detectable crystalline impurity phases. Mo incorporation induces oxygen vacancies (+4.75 percentage points) and modulates near-surface electronic states, which are expected to benefit interfacial charge transfer and provide abundant active sites for vanadium redox reactions. Electrochemical tests demonstrate that the optimized NCO-Mo3 electrode delivers an energy efficiency of 86.96% at 80 mA cm(-2), 12.3 percentage points higher than pristine graphite felt (74.68%). Notably, it maintains strong performance over a wide current-density range (80-260 mA cm(-2)), achieving 63.46% efficiency at the maximum current density. The electrode also exhibits excellent durability over 250 charge-discharge cycles with coulombic efficiency above 97% and negligible performance decay (<0.2% per cycle). Mechanistically, oxygen-vacancy-mediated defect engineering reduces charge-transfer resistance, suppresses hydrogen evolution, and enhances intrinsic catalytic activity toward the VO2+/VO2+ redox reactions. These findings highlight oxygen-vacancy-regulated Mo doping as a general strategy for wide-current-density VRFB electrodes.
Despite growing scholarly interest in Big Data Analytics and Artificial Intelligence (BDA-AI) systems, empirical research lacks standardized measurement tools to assess their environmental impact. This research addresses the gap by developing an instrument that examines the influence of BDA-AI on eco-innovation (EIN) and ecological performance (EP). Building on the Technology-Organization-Environment (TOE) framework, this study introduces employee digital skills (EDS) and top management support (TMS) as key determinants of technology adoption. Following an extensive review of the literature from 2015 to 2025, a theoretical framework was constructed that encompasses six hypothesized relationships. The proposed measurement instrument comprises 37 items that measure BDA-AI, TOE framework, EP, EIN, TMS, and EDS. This research advances the environmental sustainability and technology management literature by offering researchers a robust tool for investigating how BDA-AI shapes organizational environmental practices.
Financial studies on the herding effect have been very popular for decades, as detecting herding behavior helps to explain price deviations and market inefficiencies. However, studying the herding effect as a single influencing factor is believed to be insufficient to explain the changes in investment behavior, as the herding effect itself may be caused by other influencing factors. In other words, the issue must be studied alongside other factors. In this study, we adopt the quantile regression model to comprehensively understand the herding effect’s influence on household investment in China, and the empirical results indicate that herding behavior leads to different investment outcomes for households in different scenarios. In this analysis, we consider a variety of household characteristics, such as income level and risk tolerance, to provide a nuanced understanding of investment behavior. Additionally, in this study, we explore the interaction between herding behavior and macroeconomic variables. Nevertheless, the results suggest that, if herding behavior can be reduced by the head of the household, profitability can be increased, or at the very least, losses can be reduced.
For the net-zero emission goal by 2050, the government of Taiwan has mandated large electricity consumers to utilize 10% green electricity to mitigate carbon emissions. Major enterprises face challenges in selecting appropriate green power options and integrating the benefits of carbon reduction into corporate governance decision-making. This study aims to optimize the combination of various green power options through a system dynamics approach, incorporating existing power purchase conditions and electricity consumption data from enterprises. In addition, by utilizing financial estimations with the monetization of environmental benefits, we constructed a more complete evaluation model for enterprises transitioning to green power. The results indicate low investment returns in various green energy portfolios. However, if power storage equipment is utilized to participate in auxiliary services, the investment return of green energy can be significantly enhanced. This evaluation model is also available online for business professionals across various sectors to explore and reference.
