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Technology addiction is an increasingly severe problem. TikTok has become increasingly popular recently, and its addiction is also a major concern. This study aims to examine the antecedents and outcomes of TikTok addiction.

The authors collect 579 data from Chinese users using an online survey. The authors use structural equation modeling with partial least squares (PLS-SEM) to analyze data and test hypotheses.

The results illustrate that perceived enjoyment, social relationship, utilitarian need and social influence positively affect TikTok addiction. Both social anxiety and loneliness have positive effects on TikTok addiction. Moreover, parasocial relationships positively moderate the association between the antecedents of self-determination theory (SDT) (perceived enjoyment, social relationship, utilitarian needs, social influence, social anxiety and loneliness) and TikTok addiction. Meanwhile, TikTok addiction intensifies conflicts, including technology-family conflict, technology-person conflict and technology-work conflict. These conflicts reduce life satisfaction.

It offers practical implications for preventing and avoiding TikTok addiction to create a healthy environment.

This study is one of the few to provide a complete process of TikTok addiction. It systematically investigates the antecedents and outcomes of TikTok addiction.

While the rise of chain restaurants has attracted increasing research interest, few studies have taken servicescape into consideration to examine its effects on transformative service outcomes. This study aims to assess how social service elements can provide customers with restorative qualities, though social components are considered vital in constituting a dining locale's servicescape (AKA Social Servicescape).

The study fills the void above by undertaking a survey-based quantitative research method. Using online surveys with a sample of 306 diners, the study employed structural equation modeling to explore a proposed moderated mediation model. A post-hoc interview followed to provide qualitative data to complement the findings developed from surveys.

Results first point to a positive relationship between social servicescape and attention restoration. Moreover, the authors unveil that substantive servicescape has a moderating effect on the relationship of interest, suggesting the interplay of social and built servicescape in promoting restorative experiences.

Social and built stimuli can be intertwined to offer restorative qualities for customers. Through such an intertwined network of relationships, one may derive better mental health resources from hospitality settings.

This research presents new nuances to the existing field of inquiry by linking social servicescape and restoration through an intertwined network of attentional recovery.

In recent years, instant messaging platforms like WhatsApp have gained substantial popularity in both academic and practical domains. However, despite this growth, there is a lack of a comprehensive overview of the literature in this field. The primary purpose of this study is to bridge this gap by analyzing a substantial dataset of 12,947 articles retrieved from the Dimensions.ai, database spanning from 2011 to March 2023.

To achieve the authors' objective, the authors employ bibliometric analysis techniques. The authors delve into various bibliometric networks, including citation networks, co-citation networks, collaboration networks, keywords and bibliographic couplings. These methods allow for the uncovering of the social and conceptual structures within the academic discourse surrounding WhatsApp.

The authors' analysis reveals several significant findings. Firstly, the authors observe a remarkable and continuous growth in the number of academic studies dedicated to WhatsApp over time. Notably, two prevalent themes emerge: the impact of coronavirus disease 2019 (COVID-19) and the role of WhatsApp in the realm of social media. Furthermore, the authors' study highlights diverse applications of WhatsApp, including its utilization in education and learning, as a communication tool, in medical education, cyberpsychology, security, psychology and behavioral learning.

This paper contributes to the field by offering a comprehensive overview of the scholarly research landscape related to WhatsApp. The findings not only illuminate the burgeoning interest in WhatsApp among researchers but also provide insights into the diverse domains where WhatsApp is making an impact. The analysis of bibliometric networks offers a unique perspective on the social and conceptual structures within this field, shedding light on emerging trends and influential research. This study thus serves as a valuable resource for scholars, practitioners and policymakers seeking to navigate the evolving landscape of WhatsApp research. The study will also be useful for researchers interested in conducting bibliometric analysis using Dimensions.ai, a free database.

Previous studies have shown how the nature of businesses and the strategies pursued by their owners are affected by the personality traits of their owners. These personality traits can be formed in the early stages of life due to experiences and the surrounding context, where religion is a particularly important aspect of this context. This study aims to explore how religion affects entrepreneurial activities through the personality traits created.

This study uses interviews with 43 Muslim entrepreneurs in Scotland to examine the role played by religion. This ensures that the national institutional context is kept consistent but also allows an in-depth examination of relationships, which are likely to be interlinked and recursive.

The traits created influence the nature of the entrepreneurial activities undertaken with the potential to harm and support the entrepreneurial endeavours. It is the combination of personality traits that are formed which have the greatest effect. As such, it is found that Muslim entrepreneurs display less openness and creativity associated with new ideas, but this does not reflect risk aversion rather hard work in itself is valued, and patience combined with an external locus of control mean entrepreneurial behaviours are not altered to boost poorly performing business activities.

For Muslim entrepreneurs in Scotland, their traits explain why growth may not be a foremost consideration of these entrepreneurs rather they may value hard work and meeting the ideals of formal and informal institutions associated with religion. For those seeking to support minority groups through the promotion of entrepreneurship, either they must seek to overcome these ingrained traits or alter support to complement the different objectives held by Muslim entrepreneurs.

This paper aims to give an oversight of what is being done by researchers in GIS and remote sensing (field) to explore minerals. The main objective of this review is to explore how GIS and remote sensing have been beneficial in identifying mineral deposits for easier and cost-effective mining.

The approach of this research used Web of Science to generate a database of published articles on the application of GIS and remote sensing techniques for mineral exploration. The literature was further digested, noting the main findings, adopted method, illustration and research scales.

When applied alone, each technique seems effective, but it is important to know that combining different methods is more effective in identifying ore deposits.

This paper also examined and provided possible solutions to both current and future perspective issues relating to the application of GIS and remote sensing to mineral exploration. The authors believe that the conclusions and recommendations drawn from case studies and literature review will be of great importance to geoscientists and policymakers.

Retail investors are prone to be affected by information dissemination in social media with the rapid development of Web 2.0. The purpose of this study is to recognize the factors that may impact users' retweet behavior, namely information dissemination in the online financial community, through machine learning techniques.

This paper crawled data from the Chinese online financial community (Xueqiu.com) and extracted author-related, content-related, situation-related, stock-related and stock market-related features from the dataset. The best information dissemination prediction model based on these features was determined by evaluating five classifiers with various performance metrics, and the predictability of different feature groups was tested.

Five prevalent classifiers were evaluated with various performance metrics and the random forest classifier was proven to be the best retweet prediction model in the authors’ experiments. Moreover, the predictability of author-related, content-related and market-related features was illustrated to be relatively better than that of the other two feature groups. Several particularly important features, such as the author's followers and the rise and fall of the stock index, were recognized in this paper at last.

This study contributes to in-depth research on information dissemination in the financial domain. The findings of this study have important practical implications for government regulators to supervise public opinion in the financial market.