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The authors examine the volatility connections between the equity markets of China and its trading partners from developed and emerging markets during the various crises episodes (i.e. the Asian Crisis of 1997, the Global Financial Crisis, the Chinese Market Crash of 2015 and the COVID-19 outbreak).

The authors use the GARCH and Wavelet approaches to estimate causalities and connectedness.

According to the findings, China and developed equity markets are connected via risk transmission in the long term across various crisis episodes. In contrast, China and emerging equity markets are linked in short and long terms. The authors observe that China leads the stock markets of India, Indonesia and Malaysia at higher frequencies. Even China influences the French, Japanese and American equity markets despite the Chinese crisis. Finally, these causality findings reveal a bi-directional causality among China and its developed trading partners over short- and long-time scales. The connectedness varies across crisis episodes and frequency (short and long run). The study's findings provide helpful information for portfolio hedging, especially during various crises.

The authors examine the volatility connections between the equity markets of China and its trading partners from developed and emerging markets during the various crisis episodes (i.e. the Asian Crisis of 1997, the Global Financial Crisis, the Chinese Market Crash of 2015 and the COVID-19 outbreak). Previously, none of the studies have examined the connectedness between Chinese and its trading partners' equity markets during these all crises.

This paper gathers tourism digital footprint from online travel platforms, choosing social network analysis method to learn the structure of destination networks and to probe into the features of tourist flow network structure and flow characteristics in Guilin of China.

The digital footprint of tourists can be applied to study the behaviors and laws of digital footprint. This research contributes to improving the understanding of demand-driven network relationships among tourist attractions in a destination.

(1) Yulong River, Yangshuo West Street, Longji Terraced Fields, Silver Rock and Four Lakes are the divergent and agglomerative centers of tourist flow, which are the top tourist attractions for transiting tourists. (2) The core-periphery structure of the network is clearly stratified. More specifically, the core nodes in the network are prominent and the core area of the network has weak interaction with the peripheral area. (3) There are eight cohesive subgroups in the network structure, which contains certain differences in the radiation effects.

This research aims at exploring the spatial network structure characteristics of tourism flows in Guilin by analyzing the online footprints of tourists. It takes a good try to analyze the application of network footprint with the research of tourism flow characteristics, and also provides a theoretical reference for the design of tourist routes and the cooperative marketing among various attractions.

Due to the coronavirus disease 2019 (COVID-19) pandemic, the world faces different issues, and proper healthcare waste (HCW) treatment is one of them. If appropriate disposal of HCW is not performed, it will have hazardous effects on humanity. This paper has identified the significant barriers hindering the proper treatment of healthcare waste management (HCWM) with the strategies to overcome these barriers.

This paper has identified the significant barriers hindering the proper treatment of HCWM with the strategies to overcome these barriers, and different barriers are identified and categorized into organizational, waste handling, human resource and technical barriers. The analytical hierarchy process (AHP) process is used to rank the barriers and sub-barriers. Then, the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method evaluates the strategies for proper implementation of HCWM.

The results show that organizational barriers are the most significant barrier, with a lack of coordination of hospitals with other authorities and no priority given to waste management issues as highly ranked barriers. The results of the Fuzzy TOPSIS method indicate that “Increase govt support and policies” and “Enhance training and awareness of employees” are the most feasible strategies to overcome these barriers for the successful implementation of HCWM.

This study will be helpful in policy formulations for the proper treatment of HCW in an efficient manner. This paper helps to complete the research gap by providing the different characteristics of barriers.

This paper fills the research gap by expanding the limited knowledge in this field and providing further evidence on this phenomenon. The study also enables the distinctive characteristics of barriers to be understood within a particular context.

The purpose of this paper is to determine which criteria should be taken into account while choosing face masks for pandemic times and to what extent their effects are.

Nine face mask alternatives were evaluated based on the assessments of their performance with respect to twelve attributes. Seven experts were asked to evaluate the mask alternatives and the influences among attributes. In gathering expert judgments, spherical fuzzy number-based linguistic terms were utilized in the study to provide a more comprehensive representation domain to them.

According to the results, the most important attributes are found as material type, cost and bacteria–virus protection level. The best face mask is N95, which is followed by respirators and surgical masks.

The implication of the research is to evaluate face masks in terms of criteria such as physical, performance, protection and cost to decide on what basis they were selected as a personal protective equipment (PPE) based on expert assessments. This is useful in selection of the right face mask with optimum performance and provides guidance to the general public and profession specific groups for this purpose. The face mask companies might be also benefitted from the implications of the present study in their design and research and development (R&D) operations.

The preference ranking of the face mask alternatives has not been studied in detail yet in the literature. Focusing on this issue, the present study provides a comprehensive assessment of the selection criteria of face masks in the pandemic era.

In this paper, we aim to provide an extensive analysis to understand how various factors influence electricity prices in competitive markets, focusing on the day-ahead electricity market in Romania.

Our study period began in January 2019, before the COVID-19 pandemic, and continued for several months after the onset of the war in Ukraine. During this time, we also consider other challenges like reduced market competitiveness, droughts and water scarcity. Our initial dataset comprises diverse variables: prices of essential energy sources (like gas and oil), Danube River water levels (indicating hydrological conditions), economic indicators (such as inflation and interest rates), total energy consumption and production in Romania and a breakdown of energy generation by source (coal, gas, hydro, oil, nuclear and renewable energy sources) from various data sources. Additionally, we included carbon certificate prices and data on electricity import, export and other related variables. This dataset was collected via application programming interface (API) and web scraping, and then synchronized by date and hour.

We discover that the competitiveness significantly affected electricity prices in Romania. Furthermore, our study of electricity price trends and their determinants revealed indicators of economic health in 2019 and 2020. However, from 2021 onwards, signs of a potential economic crisis began to emerge, characterized by changes in the normal relationships between prices and quantities, among other factors. Thus, our analysis suggests that electricity prices could serve as a predictive index for economic crises. Overall, the Granger causality findings from 2019 to 2022 offer valuable insights into the factors driving energy market dynamics in Romania, highlighting the importance of economic policies, fuel costs and environmental regulations in shaping these dynamics.

We combine principal component analysis (PCA) to reduce the dataset’s dimensionality. Following this, we use continuous wavelet transform (CWT) to explore frequency-domain relationships between electricity price and quantity in the day-ahead market (DAM) and the components derived from PCA. Our research also delves into the competitiveness level in the DAM from January 2019 to August 2022, analyzing the Herfindahl-Hirschman index (HHI).

The aim is to analyze the European eco-management because the global warming has become a topical issue impacting the whole world. Individual countries are trying to minimize all the catalysts of global warming, such as carbon emissions. This paper addresses this issue and analyzes the performance of European eco-management for the purpose of future energy investments being environmentally.

This paper develops a fuzzy decision-making model to study the performance indicators of selected countries based on EMAS III standard. It employs interval type-2 fuzzy DEMATEL to evaluate the performance factors and TOPSIS methodology to assess five selected European countries' performance in relation to eco-friendly, emission and renewable energy.

Eco-friendly energy plays the most critical role in this respect followed by emissions and renewable energy which constitute significant factors. The novelty of this study is identifying significant criteria regarding environmental and energy efficiency of investments and making performance assessments of European countries with a new fuzzy decision-making model. Both expert opinions and datasets are used for the analysis. This paper supports previous research about energy efficiency investments in Europe.

The innovative feature of this study is identifying significant criteria regarding environmental and energy efficiency of investments and assessing the performance of European countries with a new fuzzy decision-making model. The fact that the analysis only concerns the European region is an important limitation. In future analyses, other groups of countries can be examined. Innovations can be made regarding the method applied. In this context, analyses can be done utilizing different fuzzy numbers. Finally, the importance of the criteria can be calculated with other methods such as SWARA.

The paper fills the gap in performance analysis of European eco-management for environmentally friendly and efficient energy investments is done in this manuscript.

Analysis of European eco-management performance was done for environmentally friendly and efficient energy investments. A fuzzy decision-making model is constructed. The paper fills the gap in performance analysis of European eco-management for environmentally friendly and efficient energy investments.