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This study aims to explore the connection between travel content consumption in social networks and social comparison, envy as well as travel intention. It analyzes whether tourists’ travel intention is affected by travel content consumption in social networks, and more importantly, whether social comparison and envy play a mediating role in this process.

Data was collected through intercept in four popular tourist spots in Guangzhou and Zhuhai in South China. A self-administered questionnaire was used. A total of 400 participants were recruited, and 291 valid questionnaires were obtained. Bias-corrected nonparametric percentile bootstrap mediation variable test method was used to test hypotheses.

The study yielded three results. First, travel content consumption in the social networks positively influences travel intention. Second, travel content consumption in social networks indirectly affects travel intention through social comparison and envy. Third, the control variables, such as gender, age, education and income, mainly affect envy.

This study constructs a theoretical framework of stimulus–cognitive appraisal–emotion–behavioral responses. To the best of the authors’ knowledge, it is the first study to reveal that the internal psychological mechanism of travel content consumption affects travel intention. It also discloses that envy of seemingly negative emotions can encourage positive behaviors in certain situations.

As cross-cultural mergers and acquisitions (M&A) have learning effects on organisations, assessing their impacts on corporate performance is crucial. This study aims to explore the impact of inter-firm cultural differences on long-term post-M&A stock market performance.

The authors select domestic M&A transactions of Chinese listed companies during 2010–2021 as the sample. Then, the authors use the partial least squares structural equation model (PLS-SEM) to construct the latent variable of cultural differences in four dimensions to explore long-term stock market performance.

Cultural differences first positively and then negatively impact post-M&A performance. Three transmissions mechanisms are identified: investor sentiment, takeover premiums and information disclosure quality. Further analysis reveals that acquirer stock performance improves with higher analyst coverage and non-local shareholders but worsens if there are business affiliations between the acquirer and target firms.

This study can help optimise information disclosure systems in M&A transactions for regulatory authorities and aid investors’ understanding of post-M&A performance changes. Furthermore, it can improve acquirers’ understanding of the risks and opportunities in cross-cultural M&A, thereby facilitating the adaptation of management practices to the im-pacts of cultural differences.

By integrating the theories of resource dependence and transaction costs, this study examines the reversal effect of cultural differences between merging companies on post-M&A performance. The authors use a PLS-SEM to empirically analyse the main effects and reveal three transmission mechanisms.

The impact of rolling on the performance of micro arc oxidation (MAO) coatings on ZM5 alloy has been underreported. The purpose of this study is to explore the correlation between rolling and the failure mechanism of MAO coatings in greater depth.

The influence of rolling on the corrosion and wear properties of MAO coating was investigated by phase structure, bond strength test (initial bond strength and wet adhesion), electrochemical impedance spectroscopy and wear test. The change of the surface electrochemical properties was studied by first principles analysis.

The results showed that the MAO coating on rolled alloy had better corrosion and wear resistance compared to cast alloy, although the structure and component content of two kinds of MAO coating are nearly identical. The difference in interface bonding between MAO coating and Mg substrate is the primary factor contributing to the disparity in performance between the two types of samples. Finally, the impact of the rolling process on MAO coating properties is explained through first-principle calculation.

A comprehensive explanation of the impact of the rolling process on MAO coating properties will provide substantial support for enhancing the application of Mg alloy anticorrosion.

To understand the mechanisms underlying social media discontinuance behavior, this study explores factors affecting social media discontinuance behavior from the perspective of social cognitive theory (SCT).

Based on SCT, this study puts forward a theoretical model incorporating habit, excessive use and negative emotions to predict social media discontinuance behavior. The proposed research model was empirically tested with 465 responses collected from WeChat users in China via an online survey. WeChat is one of the most popular social media in China. However, WeChat also faces the challenges of reduced or terminated usage among its users. Partial least squares structural equation modeling (PLS-SEM) technique was used to analyze the data.

The research results in this study show that habit exerts a negative effect on social media discontinuance behavior, while exhaustion and regret have positive influences. In addition, habit positively affects excessive use, which further leads to negative emotions of social media exhaustion and regret. Moreover, gender moderates the relationship between habit and social media discontinuance behavior.

This study adds to the literature of information system (IS) use lifecycle by investigating user behavioral changes regarding a transition from habituated to excessive use and further to discontinuance behavior. This study also helps elucidate the complex role of habit by explaining social media discontinuance from the social cognitive view. Furthermore, this study advances the current understanding of gender difference in social media discontinuance in the Chinese context. The study also offers insights to practitioners on how to prevent individuals from discontinuing their use of social media.

Despite extensive research on the detrimental work-related impact of customer mistreatment, there has been limited investigation into the outcomes that encompass both positive and negative connotations (i.e. unethical pro-organizational behavior [UPB]). This study aims to test whether, how and when daily customer mistreatment leads to hospitality employees’ daily UPB.

This study conducted a two-phase daily diary study. In the first phase, participants completed measures of their sense of power and provided demographic information. During the subsequent two-week period, participants completed questionnaires twice daily. The analysis included data from 87 hospitality employees, with 781 surveys remaining. This study performed multilevel analyses using Monte–Carlo simulations.

This study revealed that hospitality employees experiencing daily customer mistreatment exhibited heightened perceptions of status threats, resulting in increased daily UPB. The moderating effects of employees’ sense of power were found to be significant in both direct and indirect relationships.

Hospitality managers should recognize that customer mistreatment can threaten employees’ social status and result in daily UPB. To protect employees, implementing daily training programs is essential. Moreover, hotels and managers should provide HR management/recognition programs and empowerment initiatives to boost employees’ sense of power and counteract the harmful effects of customer mistreatment on their status.

This study makes contributions to the existing literature on customer mistreatment by establishing a positive relationship between daily customer mistreatment and daily UPB through the mechanism of status threat. Furthermore, thise study highlights the importance of enhancing hospitality employees’ sense of power as a protective factor against the negative consequences of customer mistreatment.

The climate change and related impacts are experienced around the world. There arise different triggering factors to climate change and impact. The purpose of this study is to figure out how changes in vegetation cover may or may not have an impact to climate change. The research will produce ideas for vegetation preservation and replant.

The investigation was probed for 34 years’ time period starting from the year 1981 to 2015. After testing and checking for serial autocorrelation in the vegetation data series, Mann–Kendal nonparametric statistical evaluation was carried out to investigate vegetation cover trends. Sen’s method was deployed to investigate the magnitude of vegetation cover change in natural differential vegetation index (NDVI) unit per year. Furthermore, the ArcGIS spatial analysis tools were used for the calculation of mean NDVI distribution and also for carrying out the spatial investigation of trends at each specific location within the study region.

The yearly mean NDVI during the study period was observed to have a decreasing trend. The mean NDVI value ranges between 0.32 and 0.98 NDVI unit, and hence, this means from less or poor vegetated zones to higher or healthier vegetated zones. The mean NDVI value was seen decreasing toward the highlands regions. The NDVI-rainfall correlation was observed to be stronger than the NDVI-temperature correlation. The % area coverage of NDVI-rainfall positive correlation was higher than the negative correlation. The % area coverage of NDVI-temperature negative correlation was higher than the positive correlation within the study region. Rainfall is seen as a highly influencing climatic factor for vegetation growth than the temperature within the study region.

This study in this country is a new approach for climate change monitoring and planning for the survival of the people of Papua New Guinea, especially for the farmer and those who is living in the coastal area.

At present, the scale of China's floating population has reached 376 million people. Compared with the local inhabitants, the poverty problem of the floating population is more complex, and this problem should also attract the attention of all sectors of society. This paper aims to measure and analyze the multidimensional poverty of the floating population in China.

The data used in this paper are the data of the China Migrants Dynamic Survey (CMDS) in China. This survey is a large-scale national migratory population sampling survey organized by the China National Health Commission, covering 31 provinces (autonomous regions and cities) and other autonomous regions. This paper uses the dynamic monitoring and Alkire and Foster (A-F) method to study the multidimensional poverty problem of the floating population.

This study finds that income poverty is no longer the main type of poverty faced by the floating population. The multidimensional poverty of the floating population mainly occurs in the social security and education dimensions, of which social security has become the most severe poverty dimension of the floating population. From the perspective of group differences, compared with the floating population in urban areas, the multidimensional poverty of migrant workers is more serious. However, the poverty of migrant workers is mainly concentrated in one-dimensional poverty and two-dimensional poverty.

In the future, the authors should focus on the social security of the floating population in the place of influx and the education of the floating population.

Through the review of the existing literature, the authors find that the current research on the multidimensional poverty of the floating population is mainly concentrated on the migrant worker groups that move from rural areas to urban areas. However, insufficient attention is paid to the urban floating population groups moving between cities.

Introduction: In today’s world of increasing competition, diminishing product differentiation, higher customer expectations, easy product replacements and lowering brand loyalty, organisations are evolving new marketing strategies for economic, societal and sustainability. Cause-related marketing (hereafter referred to as CRM), a strategic sustainable philanthropic practice, is the upcoming form of CSR. CRM plays an instrumental role in achieving self-brand connection and brand loyalty.

Purpose: To explore, integrate and interconnect concepts of CRM and self-brand connection to get more insights into the imperative role of CRM strategy in developing self-brand connections that can lead to brand loyalty in the most sustainable way. For this, CRM and self-brand connection, as proposed by societal marketing and branding literature, were explored. This chapter is a propositional inventory where the researcher has explored the antecedents of CRM strategy and its role in developing brand loyalty through self-brand connection.

Methodology: This chapter is centred upon the existing literature on sustainability, CRM and branding to understand better the relationships between dimensions and consequences of CRM and its interlinkage with brand loyalty.

Findings: The literature recommends that selected dimensions: Cause-brand fit, product type, altruistic motivation and brand credibility determine the effectiveness of CRM strategy. It also establishes the profound impact of attitude towards brand, brand perception and brand distinctiveness on self-brand connection. A theoretical framework based on the existing literature represents an amalgamated groundwork for developing effective, sustainable CRM strategies in conjunction with the self-brand connection. The proposed framework is distinct as no study conjoins the abovementioned concepts and aims to comprehend whether this integration is brand loyalty.

This study establishes the principles and process steps of a new basic trousers pattern using measurements obtained according to the rules of the anthropometric measurement system. The newly developed pattern-making system in this study will be called the “Anthropometric Measurements Based Pattern Making System” (AnMePa). It is aimed at producing trousers that are more fitting to the body, thanks to this pattern-making system.

In this research, four pattern-making systems used in many parts of the world were compared with the “Anthropometric Measurements Based Pattern Making System” (AnMePa) with regard to the overall appearance and body fit of trousers prepared according to these systems. 10 virtual mannequins (VM) with different adult female body measurements were created, and trousers patterns were prepared for these mannequins. The trousers’ patterns were made and dressed on the mannequins in a 3D virtual dressing system. The body fit of the virtual garments was evaluated by five experts. The scores given by the experts were evaluated using the fuzzy logic method.

According to the results, it is seen that the new basic trousers pattern developed by utilizing the anthropometric measurement system, AnMePa, provides the best body fit among the basic trousers patterns created according to the other examined pattern-making systems. The combination of 3D virtual dressing and fuzzy logic in the evaluation of garment body fit is considered an innovative method for the future of fashion design and production.

In the developed AnMePa, unlike the existing pattern-making systems, values that can be associated with the body measurements of individuals in a way that could be suitable for each community were used instead of constant values in the pattern-making process. Furthermore, the integration of 3D virtual fitting and fuzzy logic in assessing garment fit is considered a pioneering approach with significant implications for the future landscape of fashion design and production.

Given the increasing importance of engineering insurance, it is still unclear which specific factors can enhance the role of engineering insurance as a risk transfer tool. This study aims to propose a hybrid approach to identify and analyze the key determinants influencing the consumption of engineering insurance in mainland China.

The empirical analysis utilizes provincial data from mainland China from 2008 to 2019. The research framework is a novel amalgamation of the generalized method of moments (GMM) model, the quantile regression (QR) technique and the random forest (RF) algorithm. This innovative hybrid approach provides a comprehensive exploration of the driving factors while also allowing for an examination across different quantiles of insurance consumption.

The study identifies several driving factors that significantly impact engineering insurance consumption. Income, financial development, inflation, price, risk aversion, market structure and the social security system have a positive and significant influence on engineering insurance consumption. However, urbanization exhibits a negative and significant effect on the consumption of engineering insurance. QR techniques reveal variations in the effects of these driving factors across different levels of engineering insurance consumption.

This study extends the research on insurance consumption to the domain of the engineering business, making theoretical and practical contributions. The findings enrich the knowledge of insurance consumption by identifying the driving factors specific to engineering insurance for the first time. The research framework provides a novel and useful tool for examining the determinants of insurance consumption. Furthermore, the study offers insights into the engineering insurance market and its implications for policymakers and market participants.