Search Results (134)

Artificial intelligence (AI) is transforming accounting by automating cognitive tasks and redefining mechanisms of governance and risk control. This study examines how AI operates as an intelligent control system—one that substitutes manual accounting procedures while enhancing transparency, internal control, and fraud detection. Integrating the Technology Acceptance Model (TAM) with Organizational Information Processing Theory (OIPT), the research develops a behavioral–organizational framework linking perceived usefulness, ease of use, AI literacy, technology readiness, social influence, and facilitating conditions to AI adoption and perceived substitution benefits. A structured survey was administered to accounting students and practitioners in Northern Italy (n = 185) and analyzed through reliability tests and partial least squares structural equation modeling (PLS-SEM). The results show that AI literacy, facilitating conditions, and social influence significantly drive adoption intention, while perceived substitution benefits fully mediate the relationship between adoption and governance outcomes. The findings demonstrate that AI adoption enhances governance and risk management effectiveness by functioning as an intelligent control mechanism. The study introduces the AI-to-Control (A2C) Blueprint to guide responsible integration of AI into accounting systems, reframing AI adoption as a structural evolution in corporate governance rather than a mere technological upgrade. Full article

Background: nowadays, traditional delivery options are challenging to the urban last-mile logistics and sustainability goals. The purpose of this study is to investigate the practical factors that drive frequent e-shoppers to actively switch their intention from conventional delivery options to utilizing smart lockers. Methods: the hypothetical framework tested integrating constructs from the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), and supplementary constructs such as privacy and convenience. Data were collected via a structured online questionnaire from 513 respondents in major Egyptian cities, including Alexandria and Cairo. The framework was tested using Structural Equation Modeling (SEM) via SmartPLS 4.0 software to assess the relationship between constructs and switching intention. Results: the analysis confirms that switching intention to use smart lockers is positively driven by Perceived Usefulness, Perceived Ease of Use, Convenience, Privacy, and Perceived Behavioral Control. Notably, a positive attitude towards smart lockers was found to have a non-significant effect on the intention to switch in the Egyptian context. Conclusions: this research contributes to addressing the gap in the extant literature by focusing on analyzing the unique contextual determinants in the emerging last-mile logistics within a developing market context. Full article

Women’s entrepreneurship drives inclusive economic development and creates positive ripple effects throughout society. This study investigates the effects of entrepreneurship education in sustainability on female students, with particular emphasis on determining whether changes in entrepreneurial intentions were driven by the changes of the factors of the Theory of Planned Behavior. We employ a comparative framework with male students to contextualize our findings. The survey employed a pre-test/post-test group design (before and after a semester-long entrepreneurship course). The sample consisted of 271 business students from a Greek university (157 female students, 114 male students). After the course, women indicated positive changes in attitude, perceived behavioral control and entrepreneurial intention. The MEMORE macro revealed that both the positive changes in attitude and perceived behavioral control affected the positive change in entrepreneurial intention. Conversely, men indicated only a positive effect in perceived behavioral control. Notably, the levels of attitude, perceived behavioral control and entrepreneurial intention in women before the course were much lower than men. These findings underscore the importance of entrepreneurship education in sustainability, as a tool with a transformative force in the positive impacts on women’s entrepreneurship and gender equity that leads to sustainable growth. Full article

This study examines the adoption and implementation of the Zero Trust (ZT) cybersecurity paradigm using the Technology–Organization–Environment (TOE) framework. While ZT is gaining traction as a security model, many organizations struggle to align strategic intent with effective implementation. We adopted a sequential mixed-methods design combining 27 semi-structured interviews with cybersecurity professionals and a survey of 267 experts across industries. The qualitative phase used an inductive approach to identify organizational challenges, whereas the quantitative phase employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the hypothesized relationships. Results show that information security culture and investment significantly influence both strategic alignment and the technical implementation of ZT. Implementation acted as an intermediary mechanism through which these organizational factors affected governance and compliance outcomes. Strategic commitment alone was insufficient to drive effective implementation without strong cultural support. Qualitative insights underscored the importance of leadership engagement, cross-functional collaboration, and legacy infrastructure readiness in shaping outcomes. The findings emphasize the need for cultural alignment, targeted investments, and process maturity to ensure successful ZT adoption. Organizations can leverage these insights to prioritize resources, strengthen governance, and reduce implementation friction. This research is among the first to empirically investigate ZT implementation through the TOE lens. It contributes to cybersecurity management literature by integrating strategic, cultural, and operational dimensions of ZT adoption and offers practical guidance for decision-makers seeking to institutionalize Zero Trust principles. Full article

Nanotechnology offers powerful new tools to enhance food quality monitoring and safety assurance. In the food industry, nanoscale materials (e.g., metal, metal oxide, carbon, and polymeric nanomaterials) are being integrated into sensory systems to detect spoilage, contamination, and intentional food tampering with unprecedented sensitivity. Nanosensors can rapidly identify foodborne pathogens, toxins, and chemical changes that signal spoilage, overcoming the limitations of conventional assays that are often slow, costly, or require expert operation. These advances translate into improved food safety and extended shelf-life by allowing early intervention (for example, via antimicrobial nano-coatings) to prevent spoilage. This review provides a comprehensive overview of the types of nanomaterials used in food sensory applications and their mechanisms of action. We examine current applications in detecting food spoilage indicators and adulterants, as well as recent innovations in smart packaging and continuous freshness monitoring. The advantages of nanomaterials—including heightened analytical sensitivity, specificity, and the ability to combine sensing with active preservative functions—are highlighted alongside important toxicological and regulatory considerations. Overall, nanomaterials are driving the development of smarter food packaging and sensor systems that promise safer foods, reduced waste, and empowered consumers. However, realizing this potential will require addressing safety concerns and establishing clear regulations to ensure responsible deployment of nano-enabled food sensing technologies. Representative figures of merit include Au/AgNP melamine tests with LOD 0.04–0.07 mg L⁻¹ and minute-scale readout, a smartphone Au@carbon-QD assay with LOD 3.6 nM, Fe₃O₄/DPV detection of Sudan I at 0.001 µM (linear 0.01–20 µM), and a reusable Au–Fe₃O₄ piezo-electrochemical immunosensor for aflatoxin B1 with LOD 0.07 ng mL⁻¹ (≈15 × reuse), alongside freshness labels that track TVB-N/amine in near-real time and e-nose arrays distinguishing spoilage stages. Full article

Robotaxi services represent a major step in the commercialization of autonomous driving, offering efficiency, consistency, and safety benefits. However, despite technological advances, their large-scale adoption is far from guaranteed. Most urban users already rely on mature ride-hailing platforms such as Didi and Uber, making the real behavioral question not whether to adopt Robotaxi, but whether to migrate from existing services. Prior studies based on TAM, UTAUT, or trust models have primarily examined users’ initial adoption decisions, overlooking the substitution behavior that better captures how people shift between competing mobility services in real contexts. This study addresses this gap by applying the Push–Pull–Mooring (PPM) framework to examine users’ migration from ride-hailing to Robotaxi services, based on survey data collected from 1206 respondents across four Chinese cities (Beijing, Shanghai, Guangzhou, and Wuhan). The model was tested using structural equation modeling and multi-group analysis (SEM–MGA). Push factors reflect negative experiences with ride-hailing, including social anxiety and insecurity caused by drivers’ behaviors; pull factors emphasize Robotaxi’ autonomy and service reliability; while mooring factors capture habitual ride-hailing use and perceived Robotaxi risk. Findings indicate that push and pull factors significantly promote migration intentions, whereas mooring factors hinder them. Among all factors, perceived risk exerted the strongest negative effect (β = −0.36), underscoring its critical role as a barrier to Robotaxi migration. Gender differences are also evident, with women more sensitive to risks and men more influenced by reliability. By situating adoption within a migration context, this study enriches high-risk innovation theory and offers practical guidance for designing gender-sensitive and user-specific promotion strategies. Full article

Electric Vehicles (EVs) are still facing prejudices about limited range, making them unattractive for many customers. However, their locally emission-free operation and the ability to recover kinetic energy during braking manoeuvres are significant advances against conventional drivetrains. Especially the function of one-pedal driving (OPD) can further reduce the energy consumption of EVs if properly realized and tuned. In this research, the optimisation and evaluation of an adaptive OPD strategy for a battery electric vehicle (BEV) with the aim of improving energy efficiency and driving comfort, which was previously introduced by the authors, is presented. Therefore, an adaptive pedal curve was designed first and extended through the integration of a fuzzy controller that considers the trade-off between efficient operation and driver intention based on vehicle speed and the drive pedal position signals. The strategy was extended by the incorporation of another input to represent the traffic area. The efficiency was evaluated in a proband study using virtual driving tests in a static simulator, in which different configurations were analysed and rated. It was found that the optimised strategy achieved the best overall result. Compared to pure regenerative braking as the benchmark, energy consumption as well as the amount of pedal changes were reduced by 8.45% as well as 62.27%, respectively, and the rate of energy recovery was increased by 67.8%. Full article

This study investigates how perceived value influences user satisfaction and usage intention toward AI Digital Human Advisors in digital finance, drawing on the Stimulus–Organism–Response (S–O–R) framework. Perceived value is conceptualized as comprising functional, cognitive, and emotional dimensions, reflecting users’ utilitarian, intellectual, and affective evaluations of AI advisors. To empirically test the proposed model, a structured questionnaire survey was conducted with 524 adult users of digital financial applications in mainland China, and the data were analyzed using structural equation modeling (SEM). The results reveal that cognitive and emotional value significantly enhance both satisfaction and usage intention, whereas functional value shows no significant effect. Satisfaction fully mediates the effect of cognitive value and partially mediates that of emotional value. Moreover, switching barriers negatively moderate the satisfaction–intention link, indicating that high friction weakens the behavioral impact of satisfaction. The findings extend perceived value theory to AI-mediated financial contexts by demonstrating that emotional and cognitive engagement—rather than functional efficiency—drives sustained behavioral intention. Practically, the study highlights the importance of designing emotionally intelligent and cognitively transparent AI advisors. As the data were collected from urban users in China, where digital finance is relatively advanced, future research should validate these findings in other cultural and institutional contexts. Full article

With the rapid advancement and widespread adoption of artificial intelligence (AI), AI-powered personalized product recommendation (AI-PPR) has become a core tool for enhancing user experience and driving monetization on short-form video platforms, fundamentally reshaping consumer behavior. While prior research has largely focused on impulse buying intention (I-BI)—purchases triggered by emotional and sensory stimuli—there remains a lack of systematic exploration of spontaneous buying intention (S-BI), which emphasizes rational and cognitively driven decisions formed in unplanned contexts. Addressing this gap, this study integrates the Technology Acceptance Model (TAM) with a perceived evaluation perspective to propose and validate a dual-mediation framework: “AI-PPR → Perceived Usefulness/Perceived Trust → S-BI”. Using a large-scale survey of Generation Z users in mainland China (N = 754), data were analyzed via SPSS 26.0, including reliability and validity tests, regression analysis, and Bootstrap-based mediation analysis. The results indicate that AI-PPR not only has a significant positive direct effect on S-BI but also exerts strong indirect effects through perceived usefulness and perceived trust. Specifically, perceived usefulness accounts for 35.17% and perceived trust for 31.18% of the mediation, jointly constituting 66.35% of the total effect. The findings contribute theoretically by extending the boundary of purchase intention research, differentiating rational S-BI from emotion-driven impulse buying, and enriching the application of TAM in consumption contexts. Practically, the study highlights the importance for short-form video platforms and brand managers to enhance recommendation transparency, interpretability, and trust-building while pursuing algorithmic precision, thereby fostering rational spontaneous buying and achieving a balance between short-term conversions and long-term user value. Full article

Background: In recent decades, the emigration of Bulgarian health professionals has become a persistent challenge driven by multiple interplaying factors. A comprehensive understanding of these key determinants is essential for the development of targeted retention strategies. This study examines the primary factors influencing the migration and retention of physicians and nurses in Bulgaria. Methods: A cross-sectional study was conducted in 2022 involving 338 health professionals without professional experience abroad. Data were collected using an online questionnaire administered by a polling agency. To identify the underlying structure of the driving and retention factors, we conducted Exploratory Factor Analysis (EFA). Subsequently, the Mann–Whitney U test was employed to examine the differences in retention and motivational factors between physicians and nurses. Results: EFA of the migration drivers identified a three-factor structure, explaining 70.34% of the total variance: professional advancement and work environment; financial incentives; and family benefits. The analysis of retention determinants revealed three distinct constructs, explaining 54.46% of the variance: socioeconomic and healthcare framework; employment and career development; and personal considerations and social environment. The Mann–Whitney U test indicated that the impact of financial incentives on migration decisions exerted a weaker influence on physicians’ intentions (r = −0.23). Personal considerations and the social environment emerged as more significant retention determinants for nursing professionals (r = −0.15). Conclusions: This study extends current understanding by identifying the underlying constructs of driving and retention factors in health professional migration. The findings underscore the need for evidence-based interventions to mitigate brain drain and retain skilled professionals. Full article

Blockchain technology has become a game changer in sectors like accounting and auditing. Its usage is still restricted due to a lack of insight into what drives people to adopt it for financial services like accounting and auditing. This research delves into the factors that influence the adoption of blockchain systems in accounting and auditing services by utilizing an enhanced edition of the Theory of Planned Behavior. In this study, alongside the previously established elements like Attitude, subjective norm, and Perceived Behavioral Control, self-perception and personal moral values are included to reflect how identity and ethics impact decision-making processes. Data were gathered via an online survey (N = 751) conducted on the Prolific platform, and the hypotheses were tested using Structural Equation Modeling. The hypotheses were examined through the Structural Equation Modeling method. The findings indicate that each of the five predictors plays a significant role in influencing Behavioral Intention, with personal moral values being the influential factor followed by subjective norm and Perceived Behavioral Control. Attitude plays an important role in shaping adoption choices and showcases the complexity involved in such decisions. As such, it is crucial to take into account ethical factors when encouraging the use of blockchain technology. This study adds to the existing knowledge of the Theory of Planned Behavior framework, offering insights for companies aiming to boost the implementation of blockchain systems in professional settings. Future research avenues and real-world implications are explored with an emphasis placed on developing targeted strategies that align technological adoption with personal values and organizational objectives. Full article

As a key domain within smart buildings, Smart Sports Venues represent a strategic direction for the future development of the construction industry and hold immense potential to drive the transformation and upgrading of the sports industry. To explore the underlying mechanisms influencing consumer willingness to use Smart Sports Venues, this study constructs a theoretical model based on cognitive evaluation theory and collects data from 632 spectators in core cities of Western China (a region undergoing rapid urbanization where the sports industry is accelerating its development). As an emerging consumption scenario, Smart Sports Venues demonstrate significant development potential and representativeness in these cities. Empirical testing using structural equation modeling (SEM) combined with mediation and moderation analysis revealed the following results: (1) Perceptions of technology and convenience positively influence consumption intention; (2) Risk perceptions negatively influence consumption intention; (3) Critical experiences mediate the effects of technology perceptions, convenience perceptions, and risk perceptions on consumption intention; (4) Subjective Experience exerts a moderating effect. This study offered a novel theoretical explanation for how smart sports venues enhanced sports consumption willingness by revealing the “cognition-experience-behavior” transmission pathway—the complete journey consumers traversed from forming perceptions and experiencing on-site activities to ultimately making purchase decisions. Compared to existing research, this model innovatively integrated psychological cognition with behavioral response mechanisms, breaking away from traditional studies’ isolated analysis of technical parameters or consumption motivations. From an interdisciplinary perspective of sports consumption psychology and behavioral science, this study not only highlighted the value of smart sports venues as a pivotal link in technological innovation and industrial upgrading but also filled a gap in existing literature regarding how smart technologies influenced consumer behavior through psychological mechanisms. The findings provided theoretical foundations for optimizing smart sports architecture through user behavior data analysis and offered practical insights for the widespread adoption and development of smart building technologies. Full article

Improving students’ course satisfaction is conducive to the development of sustainable education. Based on the stimulus–organism–response (SOR) theory and the perceived value theory, this paper constructs an analytical framework of “teacher teaching–students’ psychological transformation–students’ course satisfaction”; puts forward hypotheses; builds models; collects 270 valid questionnaires from current students in universities majoring in economics and management in mainland China; and uses correlation analysis, regression analysis, and mediation test methods to study the influence of the economics and management major teachers’ teaching on students’ course satisfaction. This research shows that (1) teachers’ teaching has a differentiated driving effect on students’ psychology, with the usefulness of teaching content being the key path to enhancing students’ perceived value, teachers’ teaching attitudes and methods being the core means to building trust in a course, and the moderate difficulty of examination driving students’ examination preparation intention, and (2) students’ psychology is the core means for the transformation of course satisfaction, with perceived value directly driving course satisfaction; course trust being the cornerstone of course satisfaction and playing a significant mediating role between teachers’ teaching attitudes and methods and students’ course satisfaction, and students’ examination preparation intention positively promoting course satisfaction and playing a significant mediating role between moderate difficulty of examination and course satisfaction. This study provides some scientific basis for improving course satisfaction and teaching efficiency, enhancing the teaching quality of higher education, and promoting the development of sustainable education. Full article

The progression of generative artificial intelligence (GenAI) has lowered the technical barriers for consumers to independently customize clothing. Its profit potential has driven fashion brands to adopt GenAI-based interactive customization services. However, the factors influencing consumers’ behavioral intention toward GenAI-supported clothing customization services (GAICCS) remain underexplored. In this study, an extended framework is constructed based on the Technology Acceptance Model (TAM), incorporating trust, perceived enjoyment, service quality, and social influence to examine their effects on behavioral intention across cognitive, affective, service, and social dimensions. A total of 692 valid responses were collected from Chinese consumers via convenience sampling. A multi-stage SEM-ANN analysis was conducted to test the model. The results show that perceived usefulness (β = 0.237, p < 0.001), perceived ease of use (β = 0.332, p < 0.001), social influence (β = 0.181, p < 0.001), and service quality (β = 0.093, p < 0.05) significantly enhance behavioral intention, with perceived ease of use being the most influential. Perceived ease of use and perceived usefulness also act as key mediators. Unlike previous studies, satisfaction showed no significant effect. This study underscores the importance of functional performance, social influence, and service quality in driving GAICCS adoption, providing theoretical insights and multi-level practical guidance for promoting GenAI in fashion contexts. Full article

Augmented reality (AR) technologies—such as Instagram filters—bridge the digital and physical worlds by allowing users to virtually try on clothing, thereby reducing the risk of virus transmission. In the T-shirt retail industry, AR enables product personalization, decreases the need for physical production, minimizes textile waste, and lowers carbon emissions. It also benefits individuals with limited mobility or those who prefer shopping online. This study tested several hypotheses on 105 active Instagram filter users using filters from the ’Apprecio’ account on mobile devices. Data analyzed using the partial least squares method revealed that interactivity significantly influences both purchase intention and continued use of digital platforms. While hedonic and vivid features enhance the user experience, they have a limited impact on driving purchases or long-term engagement. Customers’ engagement and buying intent are more strongly shaped by practical and interactive elements. The study recommends that companies invest in developing interactive AR features to boost customer satisfaction and foster trust. Future research should involve larger participant samples and investigate specific interactive elements—such as virtual try-on tools—to better understand their impact on consumer behavior. This study highlights the critical role of interactivity in AR for delivering meaningful and engaging shopping experiences. Full article