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This study investigates the competition–risk nexus for Taiwan’s banking industry from the stability–inefficiency perspective over the period 2002–2021.

This study investigates the effect of competition on bank risk from the perspective of stability inefficiency. Following Koetter et al. (2012), we measured bank competition levels by adjusting the Efficiency Lerner index.

This finding supports the competition–stability hypothesis for the banking sector, which states that intensified competition reduces banks’ insolvency and credit risk, making the banking sector sounder. However, banks enjoy a “quiet life” environment and face less competition but still obtain high profits despite inefficiency.

This study considers the moderating effects of multiple factors and finds that bank size, the revenue growth rate and new business income moderate the relationship between risk and competition. In addition, compared with the Z-score, this study investigates the competition–risk relationship through stability inefficiency, which was evaluated using the stochastic frontier approach, offering more robust results than previous studies.

This research aims to examine the link between distributed leadership and team ambidexterity and the sequential mediation of team climate innovation and knowledge management in this relationship.

This study draws on a sample of 546 knowledge workers involved within 157 service research and development (R&D) teams of knowledge-intensive firms (KIFs) and uses partial least squares-structural equation modelling (PLS-SEM) through SMART PLS 4 to analyse the data collected.

Findings reveal that distributed leadership has a significant direct impact on team ambidexterity. Besides, they indicate that team climate innovation and knowledge management in teams mediate this link. Results also highlight the sequential mediation of team climate innovation and knowledge management in teams, linking distributed leadership to team ambidexterity.

This study explores the relationship between distributed leadership and ambidexterity at the team level and proposes a sequential mediation model linking these variables through team climate innovation and knowledge management in teams. It offers practical insights for KIFs’ managers on the importance of using a distributed leadership approach and building a team climate innovation to motivate R&D teams, encourage dynamic participation in knowledge management practices and cultivate both exploitative and exploratory learning activities.

Digital platform work monitored by algorithms is increasingly supplementing or substituting standard employment. Though gig workers are faced with the vulnerable, fragile and precarious digital platform work environment, the reason why gig workers remain highly willing to show good task performance has been so far unexamined. Building upon the reciprocity of the social exchange theory, this study aims to explore the antecedents and boundary condition of facilitating gig workers’ task performance.

First, to minimize common method variance, decline spurious mood effects and ensure data robustness, we conducted a two-wave time-lagged survey and collected 269 survey responses from gig workers on different gig platforms in China (e.g. Meituan, Eleme, Didi, Credamo, Zaihang) at two time nodes. Second, abiding by two stage procedures of the PLS-SEM (partial least square structural equation model) approach, we analyzed a moderated mediation model in the digital platform work context.

Results present that both platform work remuneration and flexibility help gig platforms develop an affective trust relationship with gig workers, thus encouraging them to repay the platform by performing platform tasks well. Algorithmic monitoring shows a “double-edged sword” moderating role since it weakens the indirectly positive relationship between platform work remuneration and task performance via affective trust but enhances the indirectly positive relationship between platform work flexibility and task performance via affective trust.

Understanding the importance of remuneration and flexibility in developing affective trust can help platforms design effective human resource management (HRM) strategies that enhance worker motivation of maintaining high engagement and performance under precarious working conditions. Additionally, optimizing the “double-edged sword” moderating role of algorithmic monitoring makes it more humanized, enhancing the efficiency with these HRM strategies and making both workers and platforms beneficial.

These findings offer an affective trust-based explanation for the mechanism of maintaining high work performance motivation in the nonstandard and precarious employment from the social exchange perspective, while understanding the (de)humanized aspect of algorithmic monitoring by revealing its “double-edged sword” moderating role.

This study aims to investigate the corrosion behavior of Cu-containing 3Ni steel in simulated marine environments and to provide basic guidance for improving the corrosion resistance of marine high-strength steels.

The corrosion properties of Cu-containing 3Ni steel were evaluated in five different NaCl concentrations by alternating wet and dry cycling method. The corrosion behavior was investigated by electrochemical impedance spectroscopy, scanning electron microscopy, X-ray diffraction and X-ray photoelectron spectroscopy. The mechanism of the influence of Cl ion concentrations on the corrosion behavior of Cu-containing 3Ni steel in marine environments was analyzed.

The results showed that the corrosion resistance of Cu-containing 3Ni steel decreased with NaCl concentration increasing. With the increase of NaCl concentration, the number of FeOOH particles decreased and their size increased, resulting in an increase in the porosity and a decrease in the density of corrosion products. High NaCl concentration could inhibit the formation of NiFe₂O₄ and disrupt the electronegativity of the inner film of corrosion products, which further weakened the enrichment of Ni and Cu, and enhanced the permeability of Cl ions.

The influence of NaCl concentrations on the corrosion behavior of Cu-containing 3Ni steel was systematically studied and the influence laws of corrosion behavior were obtained in this paper, providing basic data for the optimal design of Cu-containing 3Ni steels.

With an increasing array of new technologies and devices emerging as novel approaches to museum narratives, scholars are intrigued by the narrative effect they produce. Within this context, this study aims to conduct a quantitative case study on the influencing mechanisms among technology embodiment, technology attachment, museum narrative effect and perceived museum image based on embodied cognitive theory (ECT).

By introducing the Opium War Museum, Dongguan City, Guangdong Province, China, as an empirical case study, the authors collected data, through questionnaires, from 425 visitors who had experienced virtual reality (VR) technology in the museum. The data was then analyzed by using the maximum likelihood estimate for structural equation modeling.

Technology embodiment and technology attachment have significant positive correlations with the museum narrative effect. Technology attachment provides a partial mediating effect between technology embodiment and the museum narrative effect. The perceived museum image moderates such mediating effects of technology attachment.

This study brings the emerging idea of developing visitor experiences with VR through expanding the applications of ECT in the museum scenario. First, the authors identified the underlying interaction patterns between various factors that influence the museum narrative effect. Second, the authors verified that technology can optimize the museum narrative effect and help the creative transformation of cultural relics and culture. This study also provides practical recommendations to improve the technological service experience and strengthen the “audience-centric” management concept of museums

随着越来越多的新技术和设备作为博物馆新颖的叙事方法出现, 学者们对它们产生的叙事效果感到兴趣。在这一背景下, 我们基于具身认知理论对技术具身感、技术依恋、博物馆叙事效果和感知博物馆形象之间的影响机制进行了定量案例研究。

通过引入中国广东省东莞市鸦片战争博物馆作为实证案例研究, 我们从体验了博物馆VR技术的425名参观者中收集了问卷数据。然后, 我们使用极大似然法估计结构方程模型对数据进行了分析。

(1) 技术具身感和技术依恋与博物馆叙事效果存在显著正相关关系。 (2) 技术依恋在技术具身感与博物馆叙事效果之间起到了部分中介作用。 (3) 感知博物馆形象调节了技术依恋的上述中介效应。

本研究通过扩展具身认知理论在博物馆场景中的应用, 提出了利用VR优化访客体验的新兴理念。首先, 我们识别了影响博物馆叙事效果的各种因素之间的潜在互动模式。其次, 我们验证了技术可以优化博物馆叙事效果, 并有利于文物和文化的创造性转化。本研究还提出了实际建议, 以改善技术服务体验, 并加强博物馆“以观众为中心”的管理理念。

Flooding is China’s most frequent and catastrophic natural hazard, causing extensive damage. The aim of this study is to develop a comprehensive assessment of urban flood risk in the Hubei Province of China, focusing on the following three issues: (1) What are the factors that cause floods? (2) To what extent do these factors affect flood risk management? (3) How to build an effective comprehensive assessment system that can be used to reduce flood risk?

This study combines expert opinion and evidence from the extent literature to identify flood risk indicators across four dimensions: disaster risk, susceptibility, exposure and prevention and mitigation. The Criteria Importance Through Intercriteria Correlation (CRITIC) and the Grey Relational Analysis (RA)-based Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) decision-making approach were applied to calculate the weighting of factors and develop a model of urban flood risk. Then, ArcGIS software visualizes risk levels and spatial distribution in the cities of Hubei Province; uncertainty analysis verified method accuracy.

The results show that there are significant differences in the level of urban flood risk in Hubei Province, with cities such as Tianmen, Qianjiang, Xiantao and Ezhou being at high risk, while cities such as Shiyan, Xiangyang, Shennongjia, Yichang, Wuhan and Huanggang are at lower flood risk.

The innovative method of combining CRITIC-GRA-TOPSIS reduces the presence of subjective bias found in many other flood risk assessment frameworks. Regional data extraction and uncertainty analysis enhance result reliability, supporting long-term decision-making and urban planning. Overall, the methodological approach developed provides an advanced, highly effective and efficient analysis and visualization of flood risk. This study deepens the understanding of flood risk assessment mechanisms and more broadly supports the development of resilient cities.

This study aims to develop cause-and-effect relationships among the critical success factors (CSFs) of fintech adoption and rank these CSFs based on their importance in the model.

To achieve the objectives of the study, the Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL) approach was used. The data was collected from 16 experts using a questionnaire.

The findings demonstrated the interrelationships among the CSFs. In total, 16 critical factors were recognized as causal factors, and the remaining eight were considered effect factors. The CSFs were ranked based on their importance in fintech adoption.

This study is novel as it investigates CSFs of fintech adoption using FDEMATEL, and it contributes to understanding the nature of these factors and how they affect fintech adoption. The findings propose a significant basis to deepen fintech adoption and deliver a clue to design a practical framework for fintech adoption.

This study aims to examine the ability of Generative Pre-trained Transformer 4 (GPT-4), one of the most powerful large language models, to generate a literature review for peer-reviewed journal publications. The objective is to determine whether business scholars can rely on GPT-4’s assistance with literature reviews and how the nature of human–artificial intelligence (AI) interaction may affect the quality of the reviews generated by GPT-4.

A survey of 30 experienced researchers was conducted to assess the quality of the literature reviews generated by GPT-4 in comparison with a human-authored literature review published in a Social Science Citation Index (SSCI) journal. The data collected were then analyzed with analysis of variance to ascertain whether we may trust GPT-4’s assistance in writing literature reviews.

The statistical analysis reveals that when a highly structured approach being used, GPT-4 can generate a high-quality review comparable to that found in an SSCI journal publication. However, when a less structured approach is used, the generated review lacks comprehensive understating and critical analysis, and is unable to identify literature gaps for future research, although it performed well in adequate synthesis and quality writing. The findings suggest that we may trust GPT-4 to generate literature reviews that align with the publication standards of a peer-reviewed journal when using a structured approach to human–AI interaction.

The findings suggest that we may trust GPT-4 to generate literature reviews that align with the publication standards of a peer-reviewed journal when using a structured approach to human–AI interaction. Nonetheless, cautions should be taken due to the limitations of this study discussed in the text.

By breaking down the specific tasks of a literature review and using a quantitative rather than qualitative assessment method, this study provides robust and more objective findings about the ability of GPT-4 to assist us with a very important research task. The findings of this study should enhance our understanding of how GPT-4 may change our research endeavor and how we may take a full advantage of the advancement in AI technology in the future research.

This study aims to investigate a possible transmission mechanism by which the coming of financial technology (FinTech) lending can contribute to enhance the competitiveness of commercial banks and considered to affect banks’ efficiency. In addition, this study also identifies the different responses among bank groups (based on their size, type and ownership) and the joint impact of COVID-19 on the FinTech lending-competition-efficiency nexus.

Using an unbalanced panel data set of 118 commercial banks in Indonesia over the period 2018–2022, static panel (fixed and random effect model) and 2SLS/IV data analysis were used to accommodate possibility of endogeneity problem.

The results, using the stochastic frontier analysis for cost efficiency, show that higher competition leads to cost efficiency, providing evidence to support the quiet life hypothesis. However, the emergence of FinTech lending enhanced bank competitiveness, reducing the cost efficiency of Indonesian commercial banks. The negative relationship between the FinTech lending expansion and the level of cost efficiency supports this finding. Furthermore, different responses were found to the impact of FinTech lending on bank efficiency among different bank groupings. The banks were found to be less efficient in the COVID-19 period due to the coming of FinTech lending. This study signals stakeholders, especially Indonesian commercial banks, to anticipate the impact of higher competition created by FinTech lenders, which leads to bank inefficiencies. Other variables, such as asset growth, profitability and liquidity, positively impact cost efficiency, while the nonperforming loan negatively affects cost efficiency. Finally, a higher bank credit growth and lower inflation rate boost cost efficiency.

This study highlights some policy recommendations for commercial banks to be aware of the coming of FinTech lenders since they moderate the competition-efficiency nexus by reducing the efficiency level. Hence, the government should create a more collaborative ecosystem between banks and Fintech lending and provide legal authority for the FinTech industry to support the acceleration of digital transformation in the Indonesian banking industry.

This study will contribute to the literature by carrying out the transmission from the emergence of FinTech lending to bank efficiency, which includes the moderating role of FinTech lending development on the competition-efficiency nexus in banking.

This study aims to explore the perceptions of follower identities among Chinese youth and the formation of these identities within the context of use and gratification theory and mediated relationships.

Interviews were conducted with 22 individuals who followed digital influencers on various social media platforms, and a general inductive approach was followed to analyze the collected data.

The research uncovered that influencers’ followers view themselves as learners, advisees, surveillants, friends and sponsors, aligning these identities with their reasons for following influencers. These reasons are classified as either emotionally or functionally driven. The study further highlights the critical role these motivations and identities play in influencing the followers’ intentions to buy products and brands endorsed by influencers. Followers motivated by utilitarian reasons focus more on the product’s functionality and practical value, whereas those attracted to influencers for their unique personalities and perceived personal connections place greater importance on the products’ symbolic value.

Despite the widespread attention the influencer market has garnered, scant literature has deeply explored the psychological mechanisms behind individuals’ behavior in following influencers and their subsequent purchasing intentions. This study introduces new insights into influencer marketing by focusing on followers’ psychological motivations, offering a refined understanding of their impact on the dynamics of digital marketing.