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This paper identifies the effects of different dimensions of the cuteness (i.e. baby schema cuteness and whimsical cuteness) of artificial intelligence (AI) agents on attachment to them. In addition, the current paper examines the consequences of the attachment to AI agents.

A pretest to validate the measurement scale for the attachment to AI agents and a survey study were conducted with AI agent users. The authors used structural equation modeling to analyze the data for hypothesis testing.

The baby schema and whimsical cuteness of AI agents drive consumers to develop stronger attachments to their AI agents. This is because consumers perceive cute AI agents as being more trustworthy. As a result, consumers who feel attached to their AI agents are more inclined to report higher satisfaction and commitment levels. They are also more likely to purchase products or services recommended by their AI agents and use them more frequently.

Despite the growing popularity of AI agents, there is a lack of understanding regarding which characteristics of AI agents affect consumer behavior. Therefore, this research examines how the attribute of cuteness influences consumers' attachment to AI agents and subsequently affects their satisfaction and purchase intention toward products recommended by AI agents. Our study demonstrates that the element of cuteness in AI agents plays a crucial role in shaping perceptions of benevolence trustworthiness, as well as fostering users' attachment to AI agents. Furthermore, we observe positive consumer behaviors as a result of their attachment to AI agents. The findings from this study provide valuable insights for practitioners on how to effectively utilize cuteness in AI agents.

This study seeks to explore the impact of “fear of missing out” (FOMO) and “psychological enhancement” (PE) on addiction to social media applications, subsequently influencing users' life satisfaction and continuous usage intention.

This research involved the administration of two sets of questionnaires during distinct periods: December 15 to December 30, 2022 and August 26 to September 2, 2023. The participants were college students from three universities in China, and the data collection utilized the “Questionnaire Star” platform. Only responses deemed valid and consistent were included in the subsequent statistical analysis. A total of 1,108 valid samples were used for the final analysis. Analyses including reliability, validity, path analysis, structural equation modeling, mediation effects and moderation effects were conducted using SPSS and AMOS software.

The study revealed that both FOMO and PE exerted positive influences on users' addiction to social media applications. Furthermore, this addiction was found to have a negative effect on users' life satisfaction while simultaneously contributing positively to their intention to continue using these platforms. The mediating effect of social media application addiction and the moderating impact of self-regulation were also substantiated through the analysis.

Firstly, it is important to note that the research population of this study is limited to college students, which may limit its generalizability and representativeness. Although college students are a group known for their familiarity with and frequent use of smartphones and social media apps, the findings may not fully capture the behaviors of social media app users in other age groups. To enhance the understanding of social media app addiction across different age groups, future studies should consider expanding the research population and conducting multi-group difference analyses. Secondly, while focusing on specific users within a particular region can minimize unexplained variance in model estimation, it may also restrict the broader applicability of the study results. Therefore, future studies should consider testing the research model with diverse groups from different regions and cultural backgrounds. This approach will provide valuable insights into how social media app addiction may vary across various contexts, thereby enriching our understanding of this phenomenon.

Our findings reveal that in the “attention economy” environment shaped by addiction, social media app managers should leverage technology to swiftly and accurately target audiences, attract them to their platforms and cultivate long-term relationships. Encouraging users to develop new beneficial habits through app-specific functions and precise services will foster continuous usage and unlock revenue and marketing opportunities for app companies.

Despite the extensive scholarly discourse on social media application addiction, there is a lack of a well-defined framework delineating how addictive user behaviors can be leveraged in the marketing strategies of social media application platforms. The present study seeks to address these gaps, contributing to a better understanding of the formation mechanisms and knowledge systems related to social media application addiction. By investigating the causes and consequences of such addiction, this research offers valuable insights and recommendations for the innovative development of these apps, given their widespread popularity. Concurrently, the study establishes a theoretical basis for the concept that users can mitigate the negative effects of social media addiction by exercising their own self-regulation.

As the functionalities and features of social media apps converge, their individual uniqueness starts to diminish, intensifying the competition among social media companies. This escalating rivalry places higher demands on these companies. This study aims to aid social media app companies in comprehending and analyzing the diverse psychological needs of users. By enriching their platform features and services, leading users towards addiction and gaining an edge in the “Attention Economy” competition. Understanding and catering to users' needs will be instrumental in thriving within this dynamic and evolving attention economy landscape.

The lockdown of schools to control the spread of Coronavirus Disease 2019 (COVID-19) has adversely affected elementary and secondary school students in China. However, little evidence is available that documents their perceptions toward the use of e-learning under the pandemic context. This study aims to explore (1) the underlying determinants influencing the students' intentions to continue e-learning and (2) the role that the COVID-19 pandemic plays in this decision. This study extends the expectation–confirmation model (ECM) through a mixed-methods study.

This study uses a mixed-methods approach. Phase 1 draws conclusions and extracts significant elements related to e-learning during the pandemic by analyzing students' user reviews from platforms. Based on the findings, the authors identify the relevant variables and develop an extended ECM by integrating attitudes and the perceived threat of COVID-19. In Phase 2, the research model is empirically validated using data collected from 36,920 elementary and secondary school students in China. This study uses a mixed-methods approach. Phase 1 draws conclusions and extracts significant elements related to e-learning during the pandemic by analyzing students' user reviews from platforms. Based on the findings, the authors identify the relevant variables and develop an extended ECM by integrating attitudes and the perceived threat of COVID-19. In Phase 2, the research model is empirically validated using data collected from 36,920 elementary and secondary school students in China.

In Phase 1, the results reveal that students' most concern elements in the COVID-19 pandemic are user perceptions toward e-learning and threat perceptions of COVID-19. In Phase 2, the results reveal that perceived usefulness and attitude are the most significant factors in students' intention to continue. The perceived threat of COVID-19 indirectly influences their intention to continue.

The study extends the ECM with a mixed-methods study to understand students' perceptions toward e-learning during the COVID-19 pandemic. This study can be helpful in related studies in the context of COVID-19-related diseases or other novel scenarios.

This study aims to investigate barriers and enablers of social media usage by zooming on one specific type of domain: disaster management. First, by systematically reviewing previous studies using a typology to social media usage, this study identifies the challenges often faced. Second, the results are visualized by qualitatively analyzing the focus group discussion data.

This paper opted for an inductive thematic approach of grounded theory, including focus group discussion with ten participants from diverse backgrounds working in the disaster domain. The data is transcribed verbatim and coded using Atlas.ti software.

The findings suggest that the vogue of social media significantly ascends its usage in disaster management. Regulatory, software, physical, authenticity, cultural and demographic rose as challenges for social media usage in disaster management. Findings further indicate enablers as the rise in mobile penetration, democratic participation, increase in living standards, two-way real-time communication, global reach, expeditious decision-making, no space-time constraint and cheaper source of information. Social media, compared to traditional media, is explored. This study has practical implications in helping authorities understand the barriers and enablers for social media usage in disaster management.

Qualitative data analysis of social media usage for disaster management has received scant attention. The main takeaway of this research is to offer clear findings of the purview of social media usage for disaster management. It demonstrates the challenges and enablers of disaster management using social media in the Indian context. Results indicate that leveraging social media for disaster management can extend decision-making for effective disaster management.

Esthetic trend changes with the development of society and cultural differences. A minimizer bra designed to make breasts appear smaller is now popular with large-breasted women in China. To conform to the requirements of modern aesthetics in China, this paper aims to investigate vital features of breast appearance that influence people’s subjective evaluation of breast size and analyze how bra design parameters affect breast shape and make breasts appear smaller.

This study used 3D scanning technology and reverse engineering software to obtain objective breast measurements in detail. A subjective evaluation experiment was conducted to evaluate the overall performance of seven minimizer bras compared to a basic comparison bra. Around 20 design parameters of 8 sample bras were identified to make a further study about the correlation between bra design features and breast shaping effect. To gain a deeper understanding of how bras interact with breast tissue, this study presented heat maps of the breast surface to visualize the deformation of breast shape.

Nine breasts' characteristics, such as the distance between bust points, breast depth, outer breast curvature and slope, etc. have been determined to be highly correlated with the visual reduction effect of breasts. In addition, for the bras in this experiment, the high-performance bra for women with large breasts tends to have a wider side panel, a wider under band, higher gore and a stronger transverse rigidity of the bra cup. According to the observation of heat maps of the breast surface, soft full-figure bras provide a wider range of compression to the breasts and effectively flatten the breasts.

This paper first aimed at the need to shape the ideal breast appearance for large-breasted women and make a further study of several hot-selling minimizer bras in China. The suggestions given in this paper help lingerie manufacturers better understand how design features of bras can affect their shaping effect and improve the wearing effect of minimizer bras for large-breasted women.

The purpose of this paper is to conceptualise a research study to examine leadership as a relational concept between leaders and followers. The context is within surgical practice examining how motivated consultant surgeons are to lead junior doctors and which type of leadership style they use. From a follower perspective, the motivation of junior doctors will be explored, and their leadership preferences will be correlated with those of the actual style of consultant surgeons.

In this paper, the authors provide a detailed description of the methods for an international quantitative research study, exploring sequentially how motivated consultant surgeons are to lead and how leadership styles impact on the motivation of junior doctors. The objectives, method and data collection of this study are explained, and the justification for each method is described.

The findings for this outline study illustrate how critical it is to redefine leadership as a relational concept of leader and follower to ensure adequate support is provided to the next generation of consultant surgeons. Without consideration of the relational model of leadership, attrition will continue to be a critical issue in the medical workforce.

The research limitations are that this is a proposed quantitative study due to the need to collect a large sample of data from surgeons across the UK, Egypt and Germany. This research will have immense implications in developing new knowledge of leadership as a relational concept in medicine and healthcare. This study additionally will impact on how leadership is conceptualised in the curriculum for specialist surgical practice.

The practical implications are that relational leadership is supportive of generating a supportive leadership culture in the workplace and generating more effective teamwork.

To the best of the authors’ knowledge, this is the first study of its kind to look at a relational model of leadership in surgical practice between consultant surgeons and surgical trainees. This study will also identify any specific country differences between the UK, Germany and Egypt.

The purpose of this study is to identify the main perspectives and trends in educational data mining (EDM) in the e-learning environment from a managerial perspective.

This paper proposes a systematic literature review to identify the main perspectives and trends in EDM in the e-learning environment from a managerial perspective. The study domain of this review is restricted by the educational concepts of e-learning and management. The search for bibliographic material considered articles published in journals and papers published in conferences from 1994 to 2023, totaling 30 years of research in EDM.

From this review, it was observed that managers have been concerned about the effectiveness of the platform used by students as it contains the entire learning process and all the interactions performed, which enable the generation of information. From the data collected on these platforms, there are improvements and inferences that can be made about the actions of educators and human tutors (or automatic tutoring systems), curricular optimization or changes related to course content, proposal of evaluation criteria and also increase the understanding of different learning styles.

This review was conducted from the perspective of the manager, who is responsible for the direction of an institution of higher education, to assist the administration in creating strategies for the use of data mining to improve the learning process. To the best of the authors’ knowledge, this review is original because other contributions do not focus on the manager.

This paper uses the complex proportionality assessment (COPRAS) method to examine the driving factors of Industry 4.0 (I4) technologies for lean implementation in small and medium-sized enterprises (SMEs).

Adopting I4 technology is imperative for SMEs seeking to maintain competitiveness within the manufacturing sector. A thorough understanding of the driving factors involved is required to support the implementation of I4. For this objective, the multi-criteria decision-making (MCDM) tool COPRAS was used to efficiently analyze and rank these driving elements based on their importance. These factors can help small and medium-sized firms (SMEs) prioritize their efforts and investments in I4 technologies for lean implementation.

This study evaluates and prioritizes the nine I4 factors according to the perceptions of SMEs. The ranking offers significant insights into the factors SMEs consider more accessible and effective when adopting I4 technologies.

The author's original contribution is to examine I4 driving factors for lean implementation in SMEs using COPRAS.