Search Results (140)

This study investigates how positive and negative framing affect sustainable investment behaviour, emphasising the mediating role of investor confidence and the moderating role of intention. An experimental design with 301 participants was employed, comparing control, positive, and negative framing conditions. Participants allocated both simulated and real monetary endowments to a green investment (recycling) project, and the PROCESS macro for SPSS 29 was used to test mediation and moderation models. The results show that positive framing directly increases allocation to sustainable investment, while negative framing operates indirectly by enhancing investor confidence, which in turn drives greater investment. Moderation analysis further demonstrates that negative framing strengthens the link between intention and real monetary commitment, even though the direct effect of framing on actual financial behaviour remains weak. This paper contributes to behavioural finance by clarifying the differential mechanisms of positive and negative framing in investment decisions and highlighting confidence as a key psychological pathway in sustainable finance behaviour. It also differentiates short-term and long-term behaviour to capture the complexity of sustainable investment. Full article

The integration of Generative Artificial Intelligence (GenAI) into higher education represents a paradigm shift from static skill acquisition to dynamic, human–AI collaboration. However, the psychological mechanisms governing students’ adoption—specifically the interplay between pedagogical novelty, ethical awareness, and habit formation—remain underexplored. To address this, this study develops and implements a dynamic practical curriculum incorporating AI and ethical awareness, aiming to foster responsible behavioral patterns in computer programming education. Employing a quasi-experimental design, we implemented a 16-week dual-track instructional intervention (incorporating AI-integrated pedagogy and ethical scaffolding) for 148 computer science students. Structural Equation Modeling (SEM) was applied to test an extended UTAUT2 framework. The findings reveal three critical theoretical insights that redefine GenAI adoption: (1) The eclipse of utility: contrary to established models, traditional utilitarian drivers of performance expectancy (β = 0.076, p = 0.39) and effort expectancy (β = 0.125, p = 0.13) yielded non-significant effects on behavioral intention. This suggests that for digital natives, algorithmic efficiency has devolved into a baseline hygiene factor, losing its motivational power. (2) The dominance of pedagogical novelty: hedonic motivation emerged as the paramount predictor of both habit (β = 0.457, p < 0.001) and behavioral intention (β = 0.336, p = 0.001). This confirms that adoption is driven by the situational interest and interactional novelty inherent in the human–AI partnership. (3) The cognitive brake mechanism: ethical awareness exhibited a divergent regulatory role. While it significantly legitimized conscious behavioral intention (β = 0.166, p = 0.011), it showed a non-significant, negative association with habit (β = −0.032, p = 0.653). This demonstrates that ethical reasoning functions as a cognitive brake (system 2) and actively disrupts the formation of mindless, automated dependency (system 1). These results provide empirical evidence for a dual regulation model of AI adoption and suggest that sustainable education requires leveraging pedagogical novelty to drive engagement while utilizing ethical awareness to prevent blind habituation. Full article

The Sexual Intent Perceptions Questionnaire (SIP-Q) is a 25-item instrument designed to measure interpretations of women’s sexual willingness communicated via various behaviors. The instrument demonstrates high internal consistency using a 7-point Likert-type scale. Applications of the SIP-Q include assessing observers’ tendency to overperceive women’s sexual interest, testing the effects of drive states such as sexual arousal and feelings of power on ratings of women’s sexual interest, and exploring how variables such as physical attractiveness and actor–observer positionality may be associated with sexual perceptions. Studies employing the SIP-Q revealed that sexual arousal tends to increase ratings of sexual willingness, particularly among single men, and that women’s physical attractiveness can enhance these perceptions, especially when the man himself is the recipient of the woman’s behavior. The instrument is beneficial for examining sources of sexual miscommunication. Full article

This study aims to explain what drives consumers to adopt e-tipping in restaurants and determine whether interface-based manipulation reduces perceived autonomy, lowers satisfaction, and weakens brand favorability. Prior research indicates that when autonomy is undermined through manipulative design, satisfaction declines. This study integrates UTAUT2 and Self-Determination Theories to examine the determinants of consumers’ e-tipping intention, satisfaction, and brand favorability in Saudi restaurants. Four UTAUT2 motivators (performance expectancy, facilitating conditions, social influence, hedonic motivation) and service quality were modeled as antecedents, cultural attitude as mediator, and inferred manipulation as moderator. An online survey of restaurant consumers in Saudi Arabia who had previously engaged in e-tipping generated 607 valid responses, providing adequate sample power for PLS-SEM testing. Results show that performance expectancy, social influence, hedonic motivation, and service quality significantly predict intention; cultural attitude mediates several effects; and manipulation weakens the intention–satisfaction relationship, negatively impacting brand favorability. This research offers a theoretical contribution by extending UTAUT2 to the e-tipping context through integrating service quality as an antecedent and positioning satisfaction and brand favorability as core outcomes. It advances theory by demonstrating how technology-driven manipulation within payment interfaces influences cultural attitudes, behavioral intentions, and post-experience evaluations in a high-context, non-tipping society. Managerial and policy implications for responsible e-tipping designs are discussed. Full article

The growth of e-commerce in emerging economies presents a critical opportunity to steer digital consumption toward sustainability, yet the mechanisms that drive online green purchases in these contexts remain underexplored. This study examines how green digital marketing signals, specifically eco-labeling and sustainability claims, influence the online purchase intention for sustainable coffee in urban Ethiopia, introducing digital literacy as a key moderating factor. Grounded in an integrated framework of Signaling Theory and the Theory of Planned Behavior, the research model was tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) on data from 451 urban e-commerce consumers. The results confirm that both eco-labeling and sustainability claims significantly enhance purchase intention, with green trust serving as a significant partial mediator. A pivotal finding is that digital literacy positively and significantly moderates the relationship between green trust and purchase intention, indicating that consumers with higher digital competence are more effective at translating trust into purchase decisions. These findings underscore that the success of online green marketing is contingent not only on signal credibility but also on user capability, offering crucial insights for platform design and policy in emerging digital markets. Full article

With the ubiquitous connectivity and exposure of social network service (SNS), the stressors it causes have received extensive attention in the academic community. Unlike previous studies, this research focuses on the cross-cultural dimension and explores the different effects of multiple SNS-generated stressors on user behavior outcomes. Based on the “Stressors-Strain-Outcome” (SSO) theoretical framework, we constructed a “technical stressors—exhaustion—reduced SNS usage intention” pathway to systematically investigate five types of technical stressors. These were perceived information overload, perceived social overload, perceived compulsive use, perceived privacy concern, and perceived role conflict. We introduce “fear of missing out” (FOMO) as a moderating variable to explore its moderating role in SNS exhaustion and reduced SNS usage intention. In this study, we took SNS users from China and the United States as the research subjects (338 samples from China and 346 samples from the United States), and conducted empirical tests using structural equation models and multiple comparative analyses. The results show that there are significant cultural differences between Chinese and American users in terms of the perceived intensity of technostress, the path of stress transmission, and the moderating effect of FOMO. Against the background of collectivist culture in China, perceived information overload, privacy concerns, and role conflicts have a significant positive impact on SNS exhaustion, and SNS exhaustion further positively drives the intention to reduce usage of SNS. However, the direct impacts of perceived social overload and perceived compulsive usage are not significant, and FOMO does not play a significant moderating role. In the context of the individualistic culture found in the United States, only perceived information overload and perceived social overload have a significant positive impact on SNS exhaustion, and FOMO significantly negatively moderates the relationship between exhaustion and reduced SNS usage intention, as high FOMO levels will strengthen the driving effect of exhaustion on reduced usage intention. The innovation this study exhibits lies in verifying the applicability of the SSO model in social media behavior research from a cross-cultural perspective, revealing the cultural boundaries of the FOMO moderating effect, and enriching the cross-cultural research system of reduced usage intention of SNS. The research results not only provide empirical support for a deep understanding of the psychological mechanisms of users’ SNS usage behaviors in different cultural backgrounds, but also offer important references that SNS enterprises can use to formulate differentiated operation strategies and optimize cross-cultural user experiences. Full article

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