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This study aims to explore the meanings of solo travel for Asian women, focussing on how Asian women construct and negotiate their identities in the heteronormalised, gendered and Western-centric tourism space.

In-depth interviews were conducted with 35 Asian solo female travellers from ten Asian countries/societies and analysed using constructivist grounded theory. The interpretation was guided by a critical stance and intersectionality lens.

The findings show that solo travel provides a means for self-discovery but the path was different for Asian women, for whom the self is constructed by challenging the social expectations of Asian women. Western-centric discourse was identified in the participants’ interactions with other (Western) travellers and tourism service providers, as well as in the ways these Asian women perceive themselves in relation to Western travellers. In addition to gendered constraints and risks, the findings also reveal the positive meaning of being Asian women in the gendered tourism space.

By labelling Asian women, the study risks adopting an essentialised view and overlooking the differences within the group. However, this strategic essentialism is necessary to draw attention to the inequalities that persist in contemporary tourism spaces and practices.

This study investigated Asian solo female travellers, an emerging but under-researched segment. It provides a critical examination of the intersectional effect of gender and race on identity construction for Asian solo female travellers. This study shows the need for a more inclusive tourism space.

Anchored in the role of a social arbiter, the purpose of this study is to examine whether and how media coverage has an impact on CEO overconfidence and further explore how media ownership and Confucianism affect the relationship in the Chinese context.

Using a sample of 1,492 Chinese listed companies from 2010 to 2015, the study adopts random effects models to empirically analyze the effect of media coverage on CEO overconfidence and the roles of media ownership and Confucianism.

The paper finds that media coverage is significantly and positively associated with CEO overconfidence, and the positive relationship between media coverage and CEO overconfidence becomes stronger for state-controlled media. What is more, the influence of media coverage on CEO overconfidence is attenuated for those firms located in stronger Confucianism atmosphere. A further analysis reveals that different tenors of media coverage yield asymmetric effects.

The paper provides a new and solid support for the argument that media praise stimulates CEO overconfidence and increases the knowledge about under what conditions CEO overconfidence varies, broadly speaking which fosters the development of upper echelons theory (UET). Meanwhile, the results extend the literature on media effect and information processing. The findings are also beneficial to improve corporate decisions and government regulation on Chinese media systems.

The evolution of crowd intelligence is a mainly concerns issue in the field of crowd science. It is a kind of group behavior that is superior to the individual’s ability to complete tasks through the cooperation of many agents. In this study, the evolution of crowd intelligence is studied through the clustering method and the particle swarm optimization (PSO) algorithm.

This study proposes a crowd evolution method based on intelligence level clustering. Based on clustering, this method uses the agents’ intelligence level as the metric to cluster agents. Then, the agents evolve within the cluster on the basis of the PSO algorithm.

Two main simulation experiments are designed for the proposed method. First, agents are classified based on their intelligence level. Then, when evolving the agents, two different evolution centers are set. Besides, this paper uses different numbers of clusters to conduct experiments.

The experimental results show that the proposed method can effectively improve the crowd intelligence level and the cooperation ability between agents.

This paper proposes a crowd evolution method based on intelligence level clustering, which is based on the clustering method and the PSO algorithm to analyze the evolution.

The purpose of this paper is to investigate the mediating effects of organization-based self-esteem (OBSE) for the relationship between workplace ostracism with helping behavior, voicing behavior, in-role behavior, and deviant behavior. The workplace has now become a social context where ostracism occurs and the study emphasizes how ostracism can affect workplace behaviors.

The study was designed using a three-wave self-reported survey. Confirmatory factor analysis, structural equation modeling, and bootstrapping for indirect effects were conducted to test the study’s hypotheses.

The study found OBSE to fully mediate the relationship between workplace ostracism and helping behavior, voicing behavior, and in-role behavior, while OBSE partially mediated workplace ostracism and deviant behavior as workplace ostracism was found to have a direct effect on deviant behavior.

The study explores and empirically tests the mediating effects of OBSE with helping behavior, voicing behavior, in-role behavior, and deviant behavior. Therefore, the study extends research on workplace ostracism by investigating beyond the direct effects of workplace ostracism on workplace behaviors.

The rapid development of 5G technology brings the expansion of the internet of things (IoT). A large number of devices in the IoT work independently, leading to difficulties in management. This study aims to optimize the member structure of the IoT so the members in it can work more efficiently.

In this paper, the authors consider from the perspective of crowd science, combining genetic algorithms and crowd intelligence together to optimize the total intelligence of the IoT. Computing, caching and communication capacity are used as the basis of the intelligence according to the related work, and the device correlation and distance factors are used to measure the improvement level of the intelligence. Finally, they use genetic algorithm to select a collaborative state for the IoT devices.

Experimental results demonstrate that the intelligence optimization method in this paper can improve the IoT intelligence level up to ten times than original level.

This paper is the first study that solves the problem of device collaboration in the IoT scenario based on the scientific background of crowd intelligence. The intelligence optimization method works well in the IoT scenario, and it also has potential in other scenarios of crowd network.

Explains why, following China‘s implementation of a market economy, public accounting firms were required to affiliate (hook‐up) with existing government or educational institutions until 1993 when partnerships and limited liability firms were also allowed. Describes the rules relating to independent accounting firms and changes which should foster their development but reports that, in fact, most firms are still affiliated. Discusses the reasons for this and the resulting problems, e.g. lack of competition and independence, low quality of service and increases in fraud, misrepresentation and under‐disclosure. Reveals that despite the 1995 exposure draft on eliminating the hooking‐up structure few de‐affiliations have taken place and identifies four problems which need solving if full de‐affiliation is to be achieved.

There is a link between stress experienced during adversity and negative outcomes, which demands the identification of mechanisms to minimize the harm. However, to date, these mechanisms remain unclear. This study will help us understand how to reduce the negative impact of COVID-19 stress (CS) on COVID-19 burnout (CB). The purpose of this study is to investigate the mediating role of meaning in life (MIL) in the relationship between CS and CB in the general population.

During the second wave of COVID-19 in India, 514 adults aged 18–75 years (M = 33.11 ± SD =10.42) completed the survey online. Testing of the model was conducted using the structural equation modeling technique.

Results indicated that CS had a positive impact on CB. CS explained 49% of the variance in CB. A mediation model was used to examine the relationship between CS and CB through MIL, which was also supported.

These findings explain the efficacy of MIL in reducing harm. It is imperative to promote MIL to prevent negative outcomes. Instead of treating symptoms of disorders, psychologists, mental health professionals and health-care workers should focus on prevention.

The model explains the underlying mechanisms between CS and CB. This is among the very few studies attempting to explore these variables among the general population. Therefore, it adds to the literature on ways to reduce the negative impact of stressors.

Propaganda is a prevalent technique used in social media to intentionally express opinions or actions with the aim of manipulating or deceiving users. Existing methods for propaganda detection primarily focus on capturing language features within its content. However, these methods tend to overlook the information presented within the external news environment from which propaganda news originated and spread. This news environment reflects recent mainstream media opinions and public attention and contains language characteristics of non-propaganda news. Therefore, the authors have proposed a graph-based multi-information integration network with an external news environment (abbreviated as G-MINE) for propaganda detection.

G-MINE is proposed to comprise four parts: textual information extraction module, external news environment perception module, multi-information integration module and classifier. Specifically, the external news environment perception module and multi-information integration module extract and integrate the popularity and novelty into the textual information and capture the high-order complementary information between them.

G-MINE achieves state-of-the-art performance on both the TSHP-17, Qprop and the PTC data sets, with an accuracy of 98.24%, 90.59% and 97.44%, respectively.

An external news environment perception module is proposed to capture the popularity and novelty information, and a multi-information integration module is proposed to effectively fuse them with the textual information.

The purpose of this paper is to examine meaning in life as an important resource during the COVID-19 pandemic.

This paper summarized key research establishing links between meaning in life and mental health and well-being variables, reviewed the literature on meaning as a protective factor and meaning-making as a coping mechanism amidst the COVID-19 pandemic, as well as provided focal points in cultivating meaning in life.

Studies strongly support the notion that meaning in life is essential for health and well-being. Research also suggests that meaning protects against worsening mental health, and that engaging in meaning-making is a coping process that ultimately leads to improved adjustment despite the stressors of the COVID-19 pandemic. Eight themes are also identified in cultivating skills to build meaning during adverse times.

Integrating what research has found about meaning, resilience and coping can help individuals develop practical strategies to cultivate meaning in their lives to support themselves and their communities during stressful times.

Understanding the ways in which meaning can support individuals’ health and well-being is critical during a global upheaval such as that of the COVID-19 pandemic.