Human Behavior and Emerging Technologies最新文献

{"title":"Enhancing Public Safety in Eswatini: A Machine Learning–Driven Predictive Policing Model","authors":"Lucky T. Tsabedze,&nbsp;Boluwaji A. Akinnuwesi,&nbsp;Banele Dlamini,&nbsp;Elliot Mbunge,&nbsp;Stephen G. Fashoto,&nbsp;Olusola Olabanjo,&nbsp;Petros Mashwama,&nbsp;Andile S. Metfula,&nbsp;Madoda Nxumalo,&nbsp;Bukola Badeji-Ajisafe,&nbsp;Grace Egenti","doi":"10.1155/hbe2/9939274","DOIUrl":"https://doi.org/10.1155/hbe2/9939274","url":null,"abstract":"<p>Public safety remains a critical concern in Eswatini, as it prevents crime, reduces delayed response mechanisms, and optimizes police resources. This study applied machine learning techniques in predictive policing within the Kingdom of Eswatini (formerly Swaziland) to improve proactive law enforcement strategies and public safety. Crime has been a challenge in many societies and continues to threaten public safety, social cohesion, and economic development. Law enforcement agents often use reactive approaches to handle criminal incidents, which are generally associated with various impediments, such as delayed responses to crime incidents, resource-intensive operations, victimization, and insufficient proactive crime prevention measures. Integrating machine learning techniques for predictive policing emerges as a new panacea for effective policing and crime prevention. However, there is a dearth of literature advocating proactive policing through predictive policing. Therefore, this study proposes a proactive approach to crime prediction and prevention by using machine learning models such as XGBoost, random forest, multilayer perceptron (MLP), and K-nearest neighbors (KNN) models. These models were trained and tested using data from the Royal Eswatini Police Services (REPS). Our findings indicate that XGBoost provides the highest predictive accuracy at approximately 71.4%, with precision ranging from 0.65 to 0.81 and recall from 0.34 to 0.81, making it the preferred model for balanced performance across the metrics. Random forest recorded an accuracy of 66.2%, while MLP and KNN have 62.2% and 55.5% accuracy, respectively. The study recommends the integration of intelligence-based models to enhance proactive crime prediction and identify potential crime hotspots. This can assist in optimizing resource allocation to prevent crime. Additionally, collaboration among stakeholders, including national security agents, policymakers, and the community, is essential to effectively adopt and utilize predictive policing technologies to enhance security operations.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2025 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/9939274","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145146651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Peer Influence, Impulse Buying, and Consumer Emotional Attachment: The Impact of Social Media Stalking and Psychological Nuances","authors":"Khoi Minh Nguyen,&nbsp;Ngan Thanh Nguyen,&nbsp;Linh Hoang Yen Vo,&nbsp;Thong Minh Kieu,&nbsp;Phi Vu Uyen Cao","doi":"10.1155/hbe2/3406183","DOIUrl":"https://doi.org/10.1155/hbe2/3406183","url":null,"abstract":"<p>Given the contemporary landscape of social media interactions and their profound influence on consumer behavior, this study is aimed at exploring the intricate connections between subjective norms, social media stalking, peer influence, and their impact on internal cognitive and emotional processes. Specifically, we explore how these factors, including envy, the need to belong, and self-congruence, lead to transformative interactions that manifest as impulse buying, customer satisfaction, and emotional attachment. We utilized an online survey to collect data from 659 participants and subsequently employed SmartPLS to analyze the data collected via structural equation modeling. The findings showed the significant positive impact of subjective norms and social media stalking on peer influence, which enhances the chain relationship from peer influence to envy and then impulse buying. The mediating role of obsessive passion between peer influence and emotional attachment is supported in contrast to self-congruence. Contrary to earlier research findings indicating a direct link between customer satisfaction and emotional attachment in the field of impulse buying, the satisfaction resulting from impulse buying does not influence emotional attachment in this paper. Both theoretical and practical implications were discussed.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2025 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/3406183","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145181561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Role of Artificial Intelligence in Improving Organizational Behavior: A Systematic Study","authors":"Reza Rostamzadeh,&nbsp;Fereshteh Khajeh Alizadeh,&nbsp;Shirvan Keivani,&nbsp;Hero Isavi","doi":"10.1155/hbe2/8094428","DOIUrl":"https://doi.org/10.1155/hbe2/8094428","url":null,"abstract":"<p>Artificial intelligence (AI) represents a transformative technology with the potential to profoundly influence organizational behavior (OB). It can enhance organizational performance and efficiency through mechanisms such as automation, resource optimization, and advanced data analysis. Nevertheless, the integration of AI within organizations presents various social and ethical dilemmas that could adversely impact fairness, privacy, and employee satisfaction. This research aims to develop a comprehensive framework that elucidates the role of AI in enhancing OB while also identifying the associated challenges and opportunities through a meta-synthesis approach. A systematic review of the literature was conducted, focusing on studies that explore the intersection of AI and OB, employing a qualitative meta-synthesis methodology. The data were sourced from scholarly articles published in esteemed scientific databases from 1995 to 2024. Ultimately, 18 articles specifically relevant to this subject were selected, and the data underwent analysis through open coding. This process yielded 231 distinct codes, which were subsequently organized and integrated based on their conceptual similarities into various dimensions and components. The findings showed that the impact of AI on OB includes five main dimensions: (1) automation, (2) innovation and organizational learning, (3) intelligent decision-making, (4) organizational culture and human interactions, and (5) ethics and leadership. These dimensions include components such as data analysis, improved decision-making, personalization, trust and information security, and adaptation to new technologies. Finally, a research model was presented focusing on these dimensions. In addition to the benefits related to productivity and improved decision-making, the implementation of AI in organizations requires ethical and cultural considerations to maintain satisfaction and human interactions. Paying attention to algorithmic fairness and transparency in decision-making can strengthen employee trust and facilitate the adoption of this technology. Therefore, organizations should manage the implementation of AI in a way that serves the development of OB and improved performance through training, developing ethical frameworks, and providing appropriate support.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2025 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/8094428","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145102124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing Beliefs About Cryptocurrencies: Development and Validation of the Scale of Beliefs About Cryptocurrencies (SBaC)","authors":"Mirko Duradoni,&nbsp;Elena Serritella,&nbsp;Martina Bellotti,&nbsp;Alessio Luciano Licata,&nbsp;Andrea Guazzini","doi":"10.1155/hbe2/6251242","DOIUrl":"https://doi.org/10.1155/hbe2/6251242","url":null,"abstract":"<p>The technological revolution of the last decades has revolutionized economic interactions, introducing new paradigms like e-banking and cryptocurrencies. Although the literature has questioned the antecedents associated with the use of cryptocurrencies and, in particular, the attitudes and beliefs underlying them, there is still a lack of a robust, multidimensional tool to measure beliefs about cryptocurrencies. Therefore, the aim of the study is to preliminarily validate a brand-new scale for a comprehensive assessment of beliefs related to cryptocurrencies: the scale of beliefs about cryptocurrencies (SBaC). The first version of the scale was tested on 395 Italian-speaking participants (53.1% were women, mean age 27.44 years, SD = 11.03). Thirteen percent of the sample also held cryptocurrencies at the time of completing the questionnaire. The results of the exploratory factor analysis (EFA) showed that the SBaC, with a total of 12 items, has four factors: (i) self-fulfillment, related to achieving independence and goals through cryptocurrencies; (ii) investment, indicating potential profitability; (iii) cryptocurrencies as a medium of exchange, as an alternative for transactions; and (iv) locus of control, related to individual attribution of success or failure in the crypto market. The results of the confirmatory factor analysis (CFA) on an independent sample (<i>N</i> = 133, mean age = 34.47, SD = 11.79) confirm the four-factor structure of the scale. The correlation analysis showed that positive beliefs toward cryptocurrencies as a medium of exchange and as investments are significantly correlated with willingness to engage and hold cryptocurrencies. Internal locus of control negatively correlates with willingness to engage with cryptocurrencies but does not significantly affect the amount held or investment willingness. Social influence plays a role in shaping perceptions of cryptocurrencies as a medium of exchange and investment but does not significantly impact locus of control or self-fulfillment. Self-fulfillment is positively correlated with willingness to engage with cryptocurrencies and investment willingness, albeit with weaker correlations. This study showed that the SBaC is a valuable tool for assessing cryptocurrencies’ beliefs, predicting behavioral intentions, and understanding cognitive processes driving engagement with digital currencies.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2025 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/6251242","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145102264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Future Potential of Intelligent Systems in Fiscal Oversight: A Systematic Review","authors":"Pablo A. Quijano-Cabezas,&nbsp;Carlos A. Escobar-Marulanda,&nbsp;Jaime A. Restrepo-Carmona,&nbsp;Jovani A. Jiménez-Builes","doi":"10.1155/hbe2/5770257","DOIUrl":"https://doi.org/10.1155/hbe2/5770257","url":null,"abstract":"<p>The way challenges are addressed across multiple areas of knowledge is currently being revolutionized by intelligent systems. These systems offer novel opportunities and viewpoints that deserve examination, particularly in the context of fiscal surveillance and control. However, although recent studies underscore a paradigm shift toward technology-driven audit research, the evidence on intelligent systems in fiscal oversight remains fragmented and has not been systematically organized. This article provides a systematic literature review that examines the potential of intelligent systems for efficiently managing public resources. To conduct the review, a search of documents from 2018 was conducted in databases such as Scopus, ScienceDirect, IEEE Xplore, DOAJ, and Google Scholar, following the PRISMA statement and the Kitchenham and Charters method. The objective was to select 48 documents for analysis, adhering to the inclusion and exclusion criteria, and to address the four research questions posed. Guided by these questions, the review (i) assesses the potential benefits of intelligent systems for fiscal surveillance and control, covering fraud detection, auditing, risk management, financial analysis, and automation; (ii) contrasts those advantages (greater transparency, efficiency, and efficacy) with the associated technical, organizational, legal, and social challenges; (iii) evaluates the current treatment of four core oversight areas; and (iv) identifies the prevailing technological trends, most notably blockchain, data mining, and artificial intelligence. Despite the limitations of the review, including its temporal scope, individual interpretations, and specific focus, these findings can provide valuable information for government agencies, enabling them to prioritize investments and enhance the management of public resources, thereby contributing to fairer and more equitable societies.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2025 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/5770257","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Traditional or Digital? Inspiring Teachers’ Preferences in Arabic Language Primary Education in Malaysia","authors":"Siti Sharah Rajab,&nbsp;Nurahimah Mohd Yusoff,&nbsp;Muhammad Noor Abdul Aziz","doi":"10.1155/hbe2/1788597","DOIUrl":"https://doi.org/10.1155/hbe2/1788597","url":null,"abstract":"<p>Digital transformation in education has become increasingly crucial in the 21^st century, particularly in multilingual contexts like Malaysia where Arabic language education faces persistent resource gaps and uneven technology implementation despite supportive policy frameworks. This mixed-methods study investigates primary Arabic language teachers’ anticipated acceptance of a proposed Arabic interactive module (AIM) in Malaysia using an extended technology acceptance model (TAM) framework. With 290 teachers participating in cross-sectional surveys and five teachers in semistructured interviews after AIM usage, the research examined expected usefulness (EU), expected ease of use (EEU), and perceived awareness (PA) through PLS-SEM analysis and thematic analysis. Results revealed that PA serves as a critical predictor of technology acceptance, showing exceptionally strong relationships with EU (<i>β</i> = 0.800, <i>p</i> &lt; 0.001) and moderate influence on EEU (<i>β</i> = 0.288, <i>p</i> = 0.002), while demographic factors showed unexpected patterns, with male teachers perceiving lower ease of use (<i>β</i> = −0.225, <i>p</i> = 0.025) and experienced teachers showing reduced perceived usefulness (<i>β</i> = −0.072, <i>p</i> = 0.023). Qualitative findings identified three key themes: perceived effectiveness in achieving learning outcomes, enhanced student motivation and interest, and significant support for teaching processes, particularly in addressing Arabic language resource scarcity through multimedia integration and interactive elements. The study extends TAM theory by demonstrating awareness as a foundational antecedent to technology acceptance in educational contexts and suggests that successful digital transformation in Arabic education requires comprehensive awareness-building initiatives, differentiated training approaches, and pedagogically grounded interactive tools that thoughtfully integrate traditional and digital methods to inspire teachers and enhance learning outcomes.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2025 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/1788597","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Photo-Editing Scale: Development and Validation of a New Self-Report Scale of Photo-Editing Behaviors Among Chinese Females","authors":"Jinghao Feng,&nbsp;Simin Xu,&nbsp;Zeguang Wang,&nbsp;Yin Xu","doi":"10.1155/hbe2/3064810","DOIUrl":"https://doi.org/10.1155/hbe2/3064810","url":null,"abstract":"<p>A comprehensive measurement encompassing all photo-editing techniques to assess photo-editing behaviors remains absent. Based on 621 Chinese females, we developed and validated a self-report scale to measure photo-editing behaviors among Chinese females. In Study 1, experts classified photo-editing techniques from mainstream apps into categories based on their functionalities. Initial items for the Photo-Editing Scale (PES), comprising two subscales designed to measure the frequency and extent of participants’ photo-editing behaviors, were developed. The final items of PES were determined via factor analyses. In Study 2, the validity and reliability of both subscales were examined. Findings revealed that each subscale, containing eight items associated with one factor, exhibited satisfactory internal consistency (McDonald^’s omega = 0.91 for Photo-Editing Extent subscale; McDonald^’s omega = 0.85 for Photo-Editing Frequency subscale), test–retest reliability, as well as discriminant, predictive, and convergent validity. The newly developed PES may help us better understand the photo-editing behaviors and their impact on various mental health issues.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2025 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/3064810","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cognitive Benefits of Employing Multiple AI Voices as Specialist Virtual Tutors in a Multimedia Learning Environment","authors":"Tze Wei Liew,&nbsp;Su-Mae Tan,&nbsp;Tak Jie Chan,&nbsp;Yang Tian,&nbsp;Faizan Ahmad","doi":"10.1155/hbe2/8813532","DOIUrl":"https://doi.org/10.1155/hbe2/8813532","url":null,"abstract":"<p>Limited prior research provides some evidence of the cognitive and learning benefits of employing multiple pedagogical agents, each assigned to distinct knowledge bases, in a multimedia learning environment. However, follow-up studies and extensions of these findings remain scarce. To address this gap, we draw on multimedia learning and cognitive models to investigate the effects of using multiple AI voices as specialist virtual tutors for distinct programming algorithm subtopics on cognitive load and learning outcomes. A between-subjects experimental design was employed with first-year business undergraduates who had minimal programming knowledge. Participants engaged with a multimedia learning video, narrated either by a single AI voice or by three distinct AI voices, each assigned to a different subtopic. Cognitive load was measured via a survey, while learning outcomes were assessed using immediate and 2-week delayed posttests covering retention, near-transfer, and far-transfer tasks. Results indicated that participants in the multiple AI voice condition reported significantly lower intrinsic and extraneous cognitive load compared to those in the single AI voice condition. Furthermore, the multiple AI voice group outperformed the single AI voice group in both immediate and delayed retention, as well as in immediate far-transfer tasks and delayed near-transfer. This study empirically extends prior research on the cognitive effects of using multiple AI voices as virtual tutors in multimedia learning environments. It offers preliminary evidence that using unique voices to distinguish subtopics can benefit cognitive load and learning outcomes, with theoretical and instructional design implications for leveraging AI text-to-speech engines to simulate multiple virtual tutors for distinct instructional topics.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2025 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/8813532","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145062723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring Everyday Media Use: Viewing Motives, Multitasking, and Viewing Duration as Potential Drivers of Parasocial Interactions and Relationships","authors":"Michelle Möri,&nbsp;Dominique S. Wirz,&nbsp;Andreas Fahr","doi":"10.1155/hbe2/5276510","DOIUrl":"https://doi.org/10.1155/hbe2/5276510","url":null,"abstract":"<p>Parasocial interactions (PSIs) and relationships (PSRs) are prevalent in media use. They are influenced by media characters, viewers, the viewing situation, and combinations thereof. While characteristics of media characters and viewers have been studied extensively, little is known about the impact of situational factors tied to viewing sessions in viewers’ everyday media use. Situational factors potentially vary in each viewing situation. Especially for PSIs, a reception phenomenon bound to a specific viewing situation, these factors should be highly relevant. This preregistered study analyzed situational viewing motives, content-related and unrelated multitasking, and different forms of viewing session extensiveness (duration, number of episodes watched, and watching intensity) as potential situational drivers for PSIs and PSRs. The study applies an innovative multimethod design combining usage tracking of 95 participants and experience sampling surveys (<i>N</i> = 693) triggered before and after each viewing session. Through this new approach to analyzing PSIs/PSRs within everyday viewing sessions, influences on PSIs and PSRs were covered close to viewers’ everyday media use, resulting in high external validity. The results show that PSIs depend on viewers’ motives for social interaction and escapism, engagement in nonmedia multitasking, and self-assessed viewing intensity. None of the analyzed situational factors influenced viewers’ PSRs.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2025 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/5276510","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145062724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding Cryptocurrency Adoption: The Role of Technology, Users, and Trust in Unregulated Markets","authors":"Tran Le Nguyen,&nbsp;Van Kien Pham,&nbsp;Thi Thuy Dung Pham","doi":"10.1155/hbe2/7750468","DOIUrl":"https://doi.org/10.1155/hbe2/7750468","url":null,"abstract":"<p>The rise of cryptocurrencies, powered by blockchain technology, shifts trust from centralized institutions to technology itself. However, the drivers of trust in cryptocurrency adoption (CA) remain unclear, with existing models like commitment-trust theory, trust in technology, and digital trust insufficiently addressing decentralized systems. To bridge this gap, this study integrates the task-technology fit (TTF) framework and five-factor theory (FFT) into a comprehensive cryptocurrency trust model. TTF explains how blockchain features—security, transparency, traceability, price value, and transaction speed—impact technology characteristics (TCs), while FFT captures user characteristics (UCs), including psychological and behavioral dimensions, essential for trust development. Analyzing survey data from 200 participants using structural equation modeling (SEM), the findings highlight the mediating role of crypto trust (CT) between TC, UC, and external environmental factors (EX) in driving CA. CT mitigates concerns about fraud, security breaches, and reliability, transforming technological and individual readiness into adoption, particularly in unregulated markets like Vietnam. This study updates trust frameworks by integrating TTF and FFT, emphasizing the need for trust-building strategies, technological transparency, and regulatory clarity. In particular, the findings underscore that clear, supportive, and consistent regulatory policies are essential for legitimizing cryptocurrency use, reducing uncertainty, and indirectly fostering user trust. These insights provide concrete policy directions for governments seeking to enhance adoption in decentralized financial systems while ensuring public protection and market stability.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2025 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/7750468","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145062726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}