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The purpose of this paper is to analyze the linear and nonlinear effects of market integration on carbon emissions and explore the direct and indirect paths of market integration on carbon emissions through path analysis.

The authors first conduct a measurement and contrastive study of the market integration and carbon emissions of China’s 28 provinces from year 1995 to 2015. Then, the linear effect of market integration on carbon emissions is analyzed by using the fixed-effect model. Next, based on the path analysis method, the direct and indirect paths of market integration’s impact on carbon emissions are explored. Finally, the panel threshold regression model is used to evaluate the effect of market integration on carbon emissions under different situations of geographic distance.

The results show that first, the improvement of market integration can increase carbon emissions in the form of a linear relationship. Second, market integration not only has a direct and positive impact on the carbon emissions, but also has an indirect and positive impact on carbon emissions through the level of economic development, and a negative impact on carbon emissions through technological level. Third, an increase in market integration can reduce its positive effect on carbon emissions, but the improvement of economic growth and technology level can both enhance the positive effect of market integration on carbon emissions.

This paper focuses on the impact of market integration on carbon emissions in 30 provinces in China, while, the authors do not conduct a comparative analysis of different regions, so there are certain limitations. In addition, policy interaction between regional governments is also a key factor affecting carbon emissions, but this paper does not consider the effect of policy interaction, future follow-up research will try to incorporate it into the analytical models.

An important practical implication of this research is that market integration should be regarded highly in China’s energy conservation and emission reduction efforts. The research results have important reference value for policy authorities to formulate relevant policies. That is, the government can play a more active role in the process of integration through breaking the regional blockade and interest barriers to comprehensively improve resource utilization efficiency and technical level, and ultimately achieve regional low-carbon development.

This paper explores the effects of market integration on China’s carbon emissions based on different methods and perspectives, and confirms that market integration plays a vital role in China’s carbon emissions through economic growth and technological progress. Notably, based on the studied results, some specific and practical suggestions are proposed in this paper so as to reduce carbon emission and realize the sustainable development of economy and society in China.

MicroRNAs (miRNAs) have been proved to be a significant type of non-coding RNAs related to various human diseases. This paper aims to identify the potential miRNA–disease interactions.

A computational framework, MDIRM is presented to predict miRNAs-disease interactions. Unlike traditional approaches, the miRNA function similarity is calculated by miRNA–disease interactions. The k-mean method is further used to cluster miRNA similarity network. For miRNAs in the same cluster, their similarities are enhanced, as the miRNAs from the same cluster may be reliable. Further, the potential miRNA–disease association is predicted by using recommend method.

To evaluate the performance of our model, the fivefold cross validation is implemented to compare with two state-of-the-art methods. The experimental results indicate that MDIRM achieves an AUC of 0.926, which outperforms other methods.

This paper proposes a novel computational method for miRNA–disease interaction prediction based on recommend method. Identifying the relationship between miRNAs and diseases not only helps us better understand the disease occurrence and mechanism through the perspective of miRNA but also promotes disease diagnosis and treatment.

Under the classical mean-variance framework, the purpose of this paper is to investigate the properties of the instability of minimal variance portfolio and then propose a novel penalized expected risk criterion (PERC) for optimal portfolio selection.

The proposed method considers not only a portfolio’s expected risk, but also its instability that is quantified by the variance of the estimated portfolio weights. This study tests the out-of-sample performance of various portfolio selection methods on both China and US stock markets.

It is very useful to control portfolio stability in real application of portfolio selection. The empirical results on both US and China stock markets show that PERC portfolio effectively controls turnover and consequently the transaction cost, and that is why it is so competing compared with other alternative methods.

The findings suggest that the rebalancing turnover and the associated transaction cost that is usually ignored in theoretical analysis play a very important role in real investment.

For investors, especially institutional investors, the rebalancing turnover and corresponding transaction cost must be carefully addressed. The variance of the estimated portfolio weights is a good candidate to quantify portfolio instability.

This study addresses the important role of portfolio instability and proposes a novel expected risk criterion for portfolio selection after the quantitative definition of portfolio instability.

The purpose of this paper is to examine the impact of free cash flow (FCF) on the agency costs and how these FCF and agency costs affect the performance of REITs in Asia. Unlike previous studies that focus on conventional public listed companies and non-regulated industry, the Asian REIT industry being a highly regulated industry provides a new context for further research.

The samples for this study comprise REIT data from four major Asian REIT countries, namely, Japan, Singapore, Hong Kong and Malaysia. These countries are the leaders in Asian REITs which account for 94 percent of the total market capitalization of REITs in Asia. The study period is from 2002 to 2012 using panel data. This study employs GMM method which is more robust compared to previous studies that used pooled ordinary least squares (OLS) and other panel data methods.

The results indicate that FCF and agency costs persist over time in Asian REITs even though REITs are in a highly regulated industry. The findings also imply that REIT managers face substantial costs when they wish to adjust to the equilibrium level of agency costs, whereby the optimum level is always dynamic and not constant over time and moves with the changes in the determinants of agency costs. These agency costs persist over time and have significant impacts on the performance of REITs in Asia.

There are limited data in selling, general and administrative expenses in Asian REITs which render only limited use of selling, general and administrative expenses ratio in this empirical study on Asian REITs. For future research, researchers can embark on research studies on issues that might determine the speed of adjustment toward the equilibrium level of agency costs in Asian REITs.

For REIT regulators in Asia, this empirical study helps to provide useful information for policy planning and formulation in REIT corporate governance; and to transform the inherent satellite structure of the externally managed REIT structure into internally managed REIT structure. For REIT managers and practitioners, this empirical study serves as a reflection for them which helps them to be more aware of the dynamism of FCF and agency costs in REITs; and alert them that these FCF and agency costs persist over time which can have significant impacts on the REIT performance, return on assets and return on equity, REIT value and REIT return, respectively in Asia. Thus, they could consider internalizing their REIT management structure for better and more efficient management in REITs in order to mitigate the agency costs that are persistent over time. As a whole, this empirical study contributes significant benefits to all level of the REIT industry in Asia.

This implies that the REITs in Asia should consider internally managed REIT structure since the agency costs persist over time and there are always dynamic and not constant over time and moves with the changes in the determinants of agency costs. The findings also imply that the regulators in Asian REITs should enforce absolute stringent corporate governance rules and regulations in order to govern the existing inherent satellite structure of the externally managed REITs in Asia.

This empirical study contributes significant benefits to all levels of the REIT industry in Asia and the current limited literature on Asian REITs by examining the impact of FCF and agency costs on the performance of REITs in Asia. This is the first research to embark on FCF and agency costs on REITs in Asia. Furthermore, this study employs GMM method which is more robust compared to previous studies that used pooled OLS and other panel data methods.

The purpose of this paper is to present initial findings from a vulnerability assessment based on the perceptions of practitioners working in four tourism and hospitality sectors in Wuhan and Hubei Province, namely, cruise lines, hotels, travel agencies and touristic attractions.

The research note focuses on the coronavirus (COVID-19) outbreak from January to March 2020. Using the destination sustainability framework and an “interpretation” mixed methods research design, the authors analyze phone interviews (n = 151) and subsequent online surveys (n = 370) to assess sector-specific perceptions of exposure, sensitivity and system adaptiveness.

Overall, findings paint a grim picture of each sector in the short-term. All respondents reported an immediate economic loss due to COVID-19, as well as recovery concerns and uncertainties. Immediate actions for addressing these issues centered on internal cost control and governmental subsidies, while anticipated next steps focused on product adjustment, a transformation of business structures and seeking governmental guidance and policies in restoring market confidence. Findings also allude to future strategies/directions.

This study is limited in its focus on practitioner views in the immediate COVID-19 outbreak. Implications highlight a crucial strategic dependence of each sector on effective government/managerial communication and support, with smaller, local businesses needing particular attention in crisis situations.

To the authors’ knowledge, this research note is the first comprehensive study presenting vital information pertaining to the impact of COVID-19 on tourism and hospitality businesses from a large group of business leaders in the site of the initial outbreak (i.e. Wuhan and Hubei Province). With the highly infectious COVID-19 representing an ongoing threat for populations worldwide, this paper hopes this research note provides valuable insights for practitioners in other vulnerable regions, as well as for researchers examining strategies for resilience against this and future disasters.

Project portfolio risk (PPR) management plays an important role in promoting the smooth implementation of a project portfolio (PP). Accurate PPR prediction helps managers cope with risks timely in complicated PP environments. However, studies on accurate PPR impact degree prediction, which consists of both risk occurrence probabilities and risk impact consequences considering project interactions, are limited. This study aims to model PPR prediction and expand PPR prediction tools.

In this study, the authors build a PPR prediction model based on a genetic algorithm and back-propagation neural network (GA-BPNN) integrated with entropy-trapezoidal fuzzy numbers. Then, the authors verify the proposed model with real data and obtain PPR impact degrees.

The test results indicate that the proposed method achieves an average absolute error of 0.002 and an average prediction accuracy rate of 97.8%. The former is reduced by 0.038, while the latter is improved by 32.1% when compared with the results of the original BPNN model. Finally, the authors conduct an index sensitivity analysis for identifying critical risks to effectively control them.

This study develops a hybrid PPR prediction model that integrates a GA-BPNN with entropy-trapezoidal fuzzy numbers. The authors use this model to predict PPR impact degrees, which consist of both risk occurrence probabilities and risk impact consequences considering project interactions. The results provide insights into PPR management.

The absence of government intervention and market supervision cannot effectively promote green process innovation in manufacturing industries. As a new government regulation approach, environmental taxes provide a platform to internalize the externality of environmental pollution. This paper empirically investigates the impact of environmental taxes on green process innovation and the moderating effects of industry pollution heterogeneity and green credit.

This research collects manufacturing industry data ranging from 2008 to 2020, resulting in a total of 351 observations. Time-individual, two-way fixed effect models are constructed to examine the hypotheses.

The results indicate environmental taxes have an inverted-U effect on green process innovation in manufacturing industries. Implementation intensity of the current environmental taxes on China's manufacturing industries does not reach an inflection point. Further analysis suggests that environmental taxes exert influence on the inverted-U relationship with low-pollution industries displaying a steeper curvilinear pattern than high-pollution industries. Moreover, the analysis shows that green credit plays a moderating role in the inverted-U relationship, as low green credit provides more limited stimulus than high green credit in terms of the effect of environmental taxes on green process innovation.

This study offers empirical evidence to accommodate negative externalities of corporate production and provides new perspectives in nudging corporate green-process innovation.

This paper verifies the effect of environmental taxes on green process innovation amid industry pollution heterogeneity by introducing an industrial-level analysis unit. This study improves the means by which environmental taxes are measured. Existing literature has narrowly used pollution discharge fees as a proxy for environmental taxes. The authors have summed up the taxes on vehicle and vessels, urban land use, urban maintenance and construction, vehicle purchases, waste gas, wastewater and solid waste to measure the effect of environmental taxes in this study.

This study aims to explore the dissemination and evolutionary path of online public opinion from a crisis management perspective. By clarifying the influencing factors and dynamic mechanisms of online public opinion dissemination, this study provides insights into attenuating the negative impact of online public opinion and creating a favorable ecological space for online public opinion.

This research employs bibliometric analysis and CiteSpace software to analyze 302 Chinese articles published from 2006 to 2023 in the China National Knowledge Infrastructure (CNKI) database and 276 English articles published from 1994 to 2023 in the Web of Science core set database. Through literature keyword clustering, co-citation analysis and burst terms analysis, this paper summarizes the core scientific research institutions, scholars, hot topics and evolutionary paths of online public opinion crisis management research from both Chinese and international academic communities.

The results show that the study of online public opinion crisis management in China and internationally is centered on the life cycle theory, which integrates knowledge from information, computer and system sciences. Although there are differences in political interaction and stage evolution, the overall evolutionary path is similar, and it develops dynamically in the “benign conflict” between the expansion of the research perspective and the gradual refinement of research granularity.

This study summarizes the research results of online public opinion crisis management from China and the international academic community and identifies current research hotspots and theoretical evolution paths. Future research can focus on deepening the basic theories of public opinion crisis management under the influence of frontier technologies, exploring the subjectivity and emotionality of web users using fine algorithms and promoting the international development of network public opinion crisis management theory through transnational comparison and international cooperation.

This chapter sets out to analyze the impact of the Covid-19 virus on the holidays provided by UK group tour operators (GTOs) and the implications for overtourism. With tourism arrivals expected to fall by up to 30% in 2020 and a slow return to pre-Covid-19 levels for 2021 and beyond, the industry is possibly suffering the loss of up to 100 million travel-related jobs (World Travel and Tourism Council, 2020). GTOs will need to assess and possibly change the way they do business to initially survive and subsequently build up tourism numbers in the coming years.

This chapter identifies how GTOs could alter their holiday proposition to reassure travellers including the challenges of operating international tours when airlines have reduced capacity, the need to consider alternative age demographics who are more likely to travel and assessing existing itineraries to visit rural or small town locations rather than cities where numerous itineraries travel to now.

Finally, this chapter discusses and describes the significance of the findings with insights about possible opportunities based upon the approaches taken by various countries to target potential holidaymakers and the need to create a ‘crisis management plan’ for current and future countries. This may result in operational adjustments to meet these new requirements including the changing outlook of potential customers and the possibility of offering domestic tours to meet the current demand.

The purpose of this study was to evaluate the grey relational analysis method as a way of determining quickly the important factors affecting the atmospheric corrosion of Q235 carbon steel in one year.

Atmospheric corrosion exposure tests on Q235 steel were carried out at seven typical test sites in China. The test period lasted one year. The corrosion rate of the Q235 test panels was determined using the weight-loss method and environmental factors were monitored and recorded by standard methods. The importance of the various environmental factors was evaluated using the grey relational analysis method.

The results obtained by the grey relational analysis method showed that the ranking order of factors affecting the corrosion of Q235 carbon steel from “slightly” to “severely” was as follows: relative humidity > dew days > SO₃ > pH value of rain > rain precipitation > temperature > rainy days > Cl− > H₂S > NO₂. Furthermore, the initial atmospheric corrosion of Q235 carbon steel was recognized as being the corrosion of the smooth surface by water medium, or acidic aqueous solution.

Materials corrosion can be defined as a grey system because corrosion has a clear outcome and complex but uncertain characteristics. The grey relational analysis method, a part of grey system theory, is an effective and quick data processing method that can be used to sort out the degree of correlation of environmental factors affecting atmospheric corrosion in terms of it being a grey system with a lot uncertain information.