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As the number of social media users continues to rise globally, a heated debate emerges on whether social media use improves or harms mental health, as well as the bidirectional relation between social media use and mental health. Motivated by this, the authors’ study adopts the stressor–strain–outcome model and social compensation hypothesis to disentangle the effect mechanism between social media use and psychological well-being. The purpose of this paper is to address this issue.

To empirically validate the proposed research model, a large-scale two-year longitudinal questionnaire survey on social media use was administered to a valid sample of 6,093 respondents recruited from a university in China. Structural equation modeling was employed for data analysis.

A longitudinal analysis reveals that social media use positively (negatively) impacts psychological well-being through the mediator of nomophobia (perceived social support) in a short period. However, social media use triggers more psychological unease, as well as more life satisfaction from a longitudinal perspective.

This study addresses the bidirectional relation between social media use and psychological unease. The current study also draws both theoretical and practical implications by unmasking the bright–dark duality of social media use on psychological well-being.

Online question-and-answer (Q&A) communities serve as important channels for knowledge diffusion. The purpose of this study is to investigate the dynamic development process of online knowledge systems and explore the final or progressive state of system development. By measuring the nonlinear characteristics of knowledge systems from the perspective of complexity science, the authors aim to enrich the perspective and method of the research on the dynamics of knowledge systems, and to deeply understand the behavior rules of knowledge systems.

The authors collected data from the programming-related Q&A site Stack Overflow for a ten-year period (2008–2017) and included 48,373 tags in the analyses. The number of tags is taken as the time series, the correlation dimension and the maximum Lyapunov index are used to examine the chaos of the system and the Volterra series multistep forecast method is used to predict the system state.

There are strange attractors in the system, the whole system is complex but bounded and its evolution is bound to approach a relatively stable range. Empirical analyses indicate that chaos exists in the process of knowledge sharing in this social labeling system, and the period of change over time is about one week.

This study contributes to revealing the evolutionary cycle of knowledge stock in online knowledge systems and further indicates how this dynamic evolution can help in the setting of platform mechanics and resource inputs.

Building information modelling (BIM), lean construction (LC) and prefabricated housing construction (PHC) have individually aroused great attention from academia and industry. However, the integration of LC and BIM in PHC projects has not been sufficiently explored. This study aims to assess the current status of the implementation of BIM and LC in China’s PHC sector given, firstly, that China is a developing country characterised by the world’s largest population and a huge housing market, and secondly, that although China’s PHC is strongly supported by the government, the adoption of BIM and LC in PHC varies.

A mixed approach (questionnaire survey and interviews) is adopted in this study. A total of 127 valid questionnaires were collected. This is followed by interviewing 12 interviewees who are key stakeholders in PHC and hold managerial positions.

The findings of the questionnaire survey show that BIM is more prevalent than LC in PHC projects in China. In addition, the adoption of LC exhibits more maturity in stages associated with production and manufacturing, and logistics and transportation, whereas BIM has seen wider adoption in design and construction. The interviews validated the factors that influence the implementation of BIM and LC in PHC projects in China.

The study uses a strengths, weaknesses, opportunities and threats analysis framework to clarify the opportunities, threats, strengths and weaknesses of BIM and LC in China’s PHC and proposes strategies.

This paper examines how soft skills training for owner-managers affects the financial performance of exporting small and medium-sized enterprises (SMEs). Furthermore, the authors examine the differential influence of specific owner-manager skills, such as “team working skills”, “technical skills” and “leadership skills”, on performance.

The paper utilises the Longitudinal Small Business Survey, which is a nationally representative employer dataset of UK SMEs with up to 249 employees, including those with no employees. The dataset contains information on firms' turnover, export status of goods or services and training provision for employees or owner-managers.

The results suggest that owner-manager's training has a positive effect on turnover in non-exporting firms. Moreover, a combination of soft and hard skills is associated with higher turnover in exporting firms. Amongst the specific skills of owner-managers, training on “team working” has the most significant impact on exporting SMEs' performance.

The authors' findings imply that managerial training to develop soft skills such as leadership, decision-making and communication is a worthwhile investment. The knowledge that owner-managers acquire through soft and hard skills training enables them to develop essential internationalisation competencies. Moreover, the authors demonstrate that teamwork is a significant predictor of performance.

The authors contribute to the literature by examining the role of owner-managers' training in shaping internal systems, structure, processes and internationalisation strategies, thus affecting SMEs performance. The authors' also provide a nuanced analysis of how various types of soft and hard skills underpin the successful implementation of internationalisation initiatives.

Building on social media and destination brand-related literature, this study aims to explore World Heritage Sites’ (WHSs) brand diffusion and formation process from long-term and short-term perspectives, which includes brand diffusion, user-generated content (UGC), opinion leaders and brand events’ impact.

This study uses a mixed-method including text mining, keyword analysis and social network analysis to explore the brand formation process of four popular WHSs in Beijing, namely, the Palace Museum, Great Wall, Summer Palace and Temple of Heaven and more than 10,000,000 users’ data on Sina Weibo has been implemented to uncover the underlying social media branding mechanism.

The results show that the number of postings keeps in a stable range in most months, but, in general, there are no common rules for changing trends among the four WHSs; long-term high-frequency keywords related to history and culture account for a higher percentage; different kinds of accounts have varying impacts on information diffusion, in which media accounts lead to a bigger influence. However, more followers do not necessarily mean more interactions and most of the interaction ratio is much lower than 0.01000; brand events facilitate brand dissemination and have an impact on the creation of UGC.

This study is valuable for destination marketers to deeper understand brand diffusion and formation and provides valuable insights for developing effective destination marketing strategies.

Unlike previous studies that only concern a few parts of destination brand formation via social media (e.g. brand diffusion, brand events or opinion leaders’ impact), this study takes a more comprehensive perspective by systematically analyzing the brand formation process of WHSs on social media. By considering both long-term diffusion and short-term representative events, this study provides a more holistic understanding of the branding mechanism.

Prefabricated buildings (PBs) have proven to effectively mitigate carbon emissions in the construction industry. Existing studies have analyzed the environmental performance of PBs considering the shift in construction methods, ignoring the emissions abatement effects of the low-carbon practices adopted by participants in the prefabricated building supply chain (PBSC). Thus, it is challenging to exploit the environmental advantages of PBs. To further reveal the carbon reduction potential of PBs and assist participants in making low-carbon practice strategy decisions, this paper constructs a system dynamics (SD) model to explore the performance of PBSC in low-carbon practices.

This study adopts the SD approach to integrate the complex dynamic relationship between variables and explicitly considers the environmental and economic impacts of PBSC to explore the carbon emission reduction effects of low-carbon practices by enterprises under environmental policies from the supply chain perspective.

Results show that with the advance of prefabrication level, the carbon emissions from production and transportation processes increase, and the total carbon emissions of PBSC show an upward trend. Low-carbon practices of rational transportation route planning and carbon-reduction energy investment can effectively reduce carbon emissions with negative economic impacts on transportation enterprises. The application of sustainable materials in low-carbon practices is both economically and environmentally friendly. In addition, carbon tax does not always promote the implementation of low-carbon practices, and the improvement of enterprises' environmental awareness can further strengthen the effect of low-carbon practices.

This study dynamically assesses the carbon reduction effects of low-carbon practices in PBSC, informing the low-carbon decision-making of participants in building construction projects and guiding the government to formulate environmental policies.