In this paper, we propose an integrated method, called quantile mediation analysis, which combines quantile regression and mediation analysis, to examine the impact of renewable energy on carbon dioxide emissions, whether connected to or separate from through economic growth, from 1990 to 2018 in Taiwan. The results of this novel approach indicate that Taiwan's renewable energy did not affect carbon dioxide emissions through the mediation effect of economic growth from the period of 1990 to 2018, and that there is only a direct effect from renewable energy to carbon dioxide emissions at any distribution. Moreover, this result is remarkably different from the result of the traditional ordinary least square approach, which shows that Taiwan‘s renewable energy affects carbon dioxide emissions through the partial mediation effect of economic growth. In conclusion, we suggest that the Taiwanese government should increase the use of renewable energy in reducing local and global carbon dioxide emissions.

Crude oil, Bitcoin, and carbon dioxide emissions are major issues that are significantly impacting the global economy and environment. These three issues are complexly interlinked, with profound economic and environmental implications. In this study, we explore the correlation among these three issues and attempt to understand the influence of crude oil and Bitcoin on carbon dioxide emissions. We created a novel approach, named quantile mediation analysis, which blends mediation regression with quantile regression, enabling us to explore the influence of Brent crude oil on carbon dioxide emissions by considering the mediating impact of Bitcoin. According to the findings from using our new approach, the impact of Brent crude oil on carbon dioxide emissions is partly mediated by Bitcoin, and the association between Brent crude oil and carbon dioxide emissions involves both direct and indirect effects. Since the carbon dioxide generated by the extraction of crude oil and Bitcoin has a great impact on the environment, accelerating the use of clean energy technologies to reduce our reliance on crude oil should be the direction that the cryptocurrency industry ought to pursue in the future.

In this study, we employ the novel method of quantile mediation analysis to explore dynamic relationships among hydropower energy consumption, economic growth, and carbon dioxide emissions in Taiwan during the period between 1990 and 2020. The empirical results show that hydropower energy consumption only has a direct effect on reducing carbon dioxide emissions at a 0.2 distribution of carbon dioxide emissions. Moreover, results indicate that economic growth does not have a mediating effect between hydropower energy consumption and carbon dioxide emissions at any distribution of carbon dioxide emissions. Lastly, evidence produced by this study supports the existence of an environmental Kuznets curve in the context of Taiwan.

This paper adopts an innovative method through combining an autoregressive distributed lag model and a quantile regression to examine the long-run equilibrium and short-run causal relationship between the stock price of Taiwan and the NTD/USD exchange rate from January 1980 to December 2014. The results indicate that there is long-run level equilibrium relationship between the stock price of Taiwan and the NTD/USD exchange rates at lower distribution of stock prices, and at higher and lower distribution of exchange rates. The causality results show that there is unidirectional causality running from Taiwan stock price to the NTD/USD exchange rate at higher distribution of exchange rates. The result shows that there is evidence in favor of the portfolio hypothesis.

To address the inherent limitations of qualitative hygiene inspections, this study establishes a structured MCDM framework to evaluate kitchen hygiene management in Taiwan’s catering industry by integrating the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The model integrates expert-weighted criteria to facilitate a structured risk-oriented assessment and support sustainable hygiene management through prioritized resource allocation and more systematic hygiene management. The AHP results determined hygiene behavior, cooking and processing, and storage operation management as the most influential criteria, underscoring the critical role of direct food handling practices. The framework was empirically applied to five large-scale catering enterprises and international tourist hotels with multinational operational backgrounds. TOPSIS analysis revealed significant performance variability, with establishment D achieving the highest relative closeness coefficient (0.6125) and establishment E the lowest (0.2358). These findings indicate that operational control measures play a more critical role in food safety and sustainable hygiene governance than supporting infrastructure alone. The proposed model serves as a quantitative decision-support tool for both industry self-assessment and regulatory inspections, facilitating prioritized resource allocation, continuous hygiene improvement, improved food safety governance, and more consistent long-term hygiene management practices. Sensitivity analysis further demonstrated that the overall comparative ranking structure remained generally consistent under alternative normalization conditions, although minor variation was observed between the two highest-performing alternatives.