Human Behavior and Emerging Technologies最新文献

This study examines viewer stickiness in TikTok live streaming through a sociotechnical lens, asking how specific combinations of social and technical elements produce stronger versus weaker retention. Using fuzzy set qualitative comparative analysis on survey data from Indonesian viewers (N = 665) and complementing these configurational results with a linear regression analysis, we identify multiple, equifinal routes to high stickiness that pair conversational exchange with affective resonance and timely responses. Necessity and sufficiency tests show that interaction, identification, and vicarious expression are consistently present in high-stickiness cases, while synchronicity enhances engagement but is not required. In contrast, low stickiness is most strongly associated with the joint absence of interaction and vicarious expression, indicating that technical smoothness alone cannot compensate for weak social and emotional cues. The regression findings align with this pattern by showing interaction as the dominant linear predictor, with identification and vicarious expression adding smaller but reliable increments. Together, the asymmetric and symmetrical analyses provide convergent evidence that stickiness is a configuration problem: brands and creators should orchestrate microrituals, real-time acknowledgments, and identity-relevant segments—supported by responsive systems—to build durable audiences. The study advances the application of asymmetric methods in live streaming and translates sociotechnical insights into actionable design guidance for content, pacing, and on-screen interaction.

This study investigates the impact of gamification on student engagement moderated by public policy in higher education. The psychological perspective of student engagement refers to the deep involvement of students in learning and acquiring knowledge. There are three dimensions of student engagement: cognitive, emotional, and behavioral. This study selects computer science students who were already enrolled in gamification classes. The selected sample of the study is based on multiple cities of Pakistan, including Lahore, Islamabad, and Karachi. The selection of institutes from three cities is made based on a convenience sampling technique. A 5-point Likert scale questionnaire is used to assess the role of gamification and its impact on gaming platforms and student engagement with dummy variables as public policy management that controls and devises rules and regulations for gamification in higher education departments. We examine the impact of gamification content, challenges, rewards, and the Kahoot platform on student engagement. There are positive and weak results regarding the impact of gamification, as the Kahoot platform itself has no attraction for students, but it provides a user-friendly medium to play games. There are a few topics for future research, such as the role of gamification platforms and their significant impact on students’ motivation and the role of public policy regarding gamification platforms and engagement. Gamification challenges and rewards have been discussed in the study to observe the mediating impact. The analysis of the study is carried out in SmartPLS Version 4.0.

Recent decades have witnessed a rise in the prevalence of common mental health problems coupled with an increasing demand for talk-based psychological therapies. This has coincided with the rise of mental health chatbots (MHCs), a corollary of which is the use of MHCs, AI-driven, conversational agents, to provide interactive support, guidance, and therapeutic engagement for persons experiencing mental health challenges. There has been a growing research interest in MHCs, and this study provides a much-needed systematic review that examines this expanding research literature, identifying themes, trends, and areas worthy of further exploration. This review identified and systematically explored 97 published papers on MHCs. Most studies explored MHC design and evaluation, emphasizing empathy-based chatbots and their relative efficacy compared with conventional delivery modes (e.g., in-person human therapists). Text-based communication was the most frequently utilized modality over and above the use of audio, graphical, or mixed modes. The most commonly used therapeutic orientation among MHCs was cognitive behavioral therapy (CBT), with far less focus on third-wave evidence-based approaches such as dialectical behavior therapy and acceptance and commitment therapy. The most frequently targeted mental health condition was depression, although there were several other conditions also considered. Most MHC research has not considered cultural appropriateness or cultural adaptation of interventions. Further, limited attention to severe or high-risk symptomatology has been given. Meanwhile, we noted that most of the studies used quantitative and mixed evaluation methods. Evaluation shows persistent challenges around personalization, privacy, and technical reliability. Future research should focus on integrating human-in-the-loop mechanisms, advancing cultural adaptation, incorporating thought-challenging CBT techniques, embedding ethics into design, and exploring large language models (LLMs) for more adaptive and empathetic support.

The integration of artificial intelligence (AI), especially tools like generative pretrained transformer (GPT), in education has created new challenges, most notably a surge in academic misconduct such as plagiarism, exam cheating, and unethical collaboration. Guided by the fraud diamond theory, this study examines the factors that lead to academic cheating—pressure, opportunity, rationalization, and capability, with AI as a moderating factor. It involved 630 students selected through nonprobability sampling across general studies, natural sciences, and social sciences in Central Java, Indonesia. Using a quantitative approach, data were collected and analyzed using moderated regression analysis (MRA). Instrument testing confirmed strong validity and high reliability. Findings reveal that AI attenuates the effects of pressure, rationalization, and capability on academic fraud but exerts no moderating influence on opportunity. AI heightened the influence of capability, showing that technically skilled students with fraudulent intent are at greater risk of misconduct. This highlights the need for field-specific strategies, structural changes, and ethical education. It further advocates for integrating AI ethics into curricula, enhancing faculty capacity, and adopting alternative assessment methods. While AI demonstrates potential as a mitigating tool, it must be combined with strong rules, support systems, and educational logistics to uphold academic integrity.

This study examines how AI influences the efficiency of strategic planning, with attention to the AI dimensions: task automation, decision-making speed, resource use efficiency, the accuracy of automated predictions, the ability to handle complexity, scalability and flexibility, and integration into decision support. A quantitative research approach is adopted, using a structured questionnaire distributed to a sample of 218 senior managers from heterogeneous SMEs. The results suggest that artificial intelligence enhances the efficiency of strategic planning. considering the exploratory character of the investigation and the limited sample size. Further studies with larger and more diverse populations are needed for confirmation of these findings and to explore additional implications of artificial intelligence on strategic planning.

Aligned with the United Nations Sustainable Development Goals (SDGs) 5 (gender equality) and 9.c (technological access), this study investigates the endogenous nexus between access to mobile and smart telecommunication services (MSTSs) and women’s consumption of mobile financial services (MFS) in post-COVID-19 Burkina Faso, with a focus on the mediating role of formal financial inclusion. Utilizing data from the 2021 DHS-V survey of 17,659 women aged 15–49, we employ spatial semiparametric trivariate copula regression modeling to address the inherent endogeneity of MSTS access and its impact on MFS consumption. This study’s novelty lies in its pioneering use of advanced econometric modeling to disentangle the interplay between MSTS access, formal financial inclusion, and women’s MFS usage in a postcrisis, low-income African context, where gender gaps in financial access remain pronounced. Our findings reveal positive associations between women’s MSTS access and MFS consumption, with formal financial inclusion significantly enhancing women’s utility from MFS. Unexpectedly, standard mobile phone services yield higher MFS consumption premiums than smartphone access. Control factors, including internet access, household wealth, education, and rural–urban disparities, further shape MFS adoption. These insights offer critical guidance for policymakers and development agencies to advance women’s economic empowerment through targeted digital and financial inclusion strategies in Burkina Faso and similar contexts.

As artificial intelligence (AI) becomes increasingly integrated into decision-making processes, understanding how people trust and rely on AI versus human experts is essential. In particular, the complexities of medium-level task risk and advice reliability require further exploration. Using the judge–advisor system (JAS) model, this study investigates the effects of advice source (human vs. AI), advice reliability (low, medium, and high), and task risk (low, medium, and high) on subjective trust, advice reliance, and eye-tracking patterns. Results show that medium-risk tasks elicited the highest subjective trust but the lowest attention to advice, while reliance and final fixations were higher than in low-risk tasks. Importantly, trust in AI relative to human experts depended on both reliability and risk: AI was favored in medium-risk, medium-reliability conditions but was trusted less than humans in high-risk contexts. These findings highlight the often-overlooked role of medium levels of risk and reliability in human–AI collaboration, offering insights for optimizing AI-assisted decision-making.

Recently identified as a pet-friendly practice, teleworking allows people to perform their work while being near their pets. This study relied on the social exchange theory to develop a conceptual framework hypothesizing that work breaks including human–animal interactions would mediate the relationship between the work modality (onsite or telework) and affective (work engagement) and behavioral (performance) outcomes. Also, based on social exchange theory, this study tested the moderating role of attitudes toward teleworking in the previous indirect relationship. To test the model, 200 gig workers agreed to participate in this two-wave study. The results supported the hypotheses, revealing that work modality influenced both (a) work engagement and (b) performance through work breaks. The results also showed that this indirect relationship was moderated by the worker′s attitude toward teleworking, becoming stronger for those with more favorable attitudes compared to those with less favorable attitudes. Based on the results, strategies for adopting pet-friendly practices or work environments, including hybrid work models, are discussed.

Information and communication technologies have become an integral part of daily life. However, the increasing reliance on technology in both personal and professional contexts presents significant challenges. Individuals′ levels of digital literacy affect their ability to complete everyday and work-related tasks that depend on digital tools. The present systematic review is aimed at identifying the main predictors of digital literacy and understanding how these influence its three levels: digital competence, digital use, and digital transformation. This work (INPLASY Reference 202310053) followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. A literature search covering was conducted across Web of Science, Scopus, Elsevier, PsycInfo, and PubMed using a PICO framework-based search string, from 2017 to 2022. A total of 5342 records were identified, of which 103 underwent full-text screening. A total of 44 articles was included in the review. The analysis revealed that digital competence is primarily associated with higher education, higher socioeconomic status, and older age. Digital use is mainly predicted by access to digital devices and internet connectivity. Digital transformation is often associated with health-related contexts, where individuals are expected to self-manage their health through digital applications. Despite the growing interest in digital literacy, research on its determinants remains scarce and fragmented. Significant challenges and gaps persist, including inconsistent definitions and measurement approaches, limited investigation into digital transformation, a lack of intersectional analyses, and the overrepresentation of WEIRD (western, educated, industrialized, rich, and democratic) populations. There is a pressing need for more systematic, inclusive, and theory-driven research to inform policymakers and practitioners aiming to foster societal development. To address these gaps, we propose an ecological model of development that reflects how interconnected systems can shape digital literacy.