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The aviation sector is transforming as electrification emerges as a promising technology. Adopting battery-electric aircraft (BEA) - aircraft that solely rely on rechargeable onboard batteries - is a sustainable alternative to conventional aviation that could change short-haul regional travel habits for business and leisure travellers. This study examines the factors influencing individuals’ public acceptance in China's Greater Bay Area (GBA) context. Given the limited research, a qualitative methodology grounded in the Theory of Planned Behaviour (TPB) examines the underlying factors influencing behavioural intentions (attitudes, subjective norms, perceived behavioural control, and perceived risks). The findings indicate that participants recognise the technology's environmental benefits and potential to enhance regional connectivity; however, they still have concerns about safety, infrastructure, and operations. The respondents’ perceived ease of access, information available, and endorsements from reputable sources also have essential roles in influencing broader acceptance. Addressing these factors with appropriate communication efforts is vital for promoting trust and accelerating technology acceptance and use. Although exploratory, this study offers insights to develop strategies for infrastructure readiness, build public confidence, and endorse sustainable aviation. The research is conducted within the GBA context. Still, the findings also apply to regions with fragmented geographies or developing transportation networks, thus contributing to global environmental sustainability and advancing regional integration goals.
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While the initial adoption of technology is widely studied, the factors driving its long-term retention remain a critical gap. This research shifts the focus from adoption to sustained use by applying the Model for Sustained Technology Use (MSTU) to investigate generative AI engagement among Vietnamese university students. A cross-sectional survey of 100 students measured the key constructs of Habit, Satisfaction, and Perceived Usefulness, as well as their impact on Sustained Technology Use. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that Habit is the strongest direct predictor of sustained use, surpassing the influence of Perceived Usefulness (PU). While PU drives initial adoption, its effect diminishes over time, whereas Satisfaction (ST) plays a crucial mediating role in long-term engagement. These results challenge the prevailing assumption that perceived usefulness alone is sufficient to ensure long-term success. The study offers key implications for researchers and practitioners, emphasizing the importance of designing AI educational tools that seamlessly integrate into and adapt to user workflows to promote habitual use. For educators and developers, this means prioritizing features that create engaging, positive, automatic user experiences to ensure generative AI remains a retained educational resource, not a momentary novelty.
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All-electric aircraft (AEA) have garnered significant attention due to their potential to achieve zero carbon emissions and reduce noise pollution, contributing to global environmental sustainability. This study examines consumer behavioural intentions toward AEA in Guangdong, China, using the Theory of Planned Behavior (TPB) as the theoretical framework. Data were collected through structured questionnaires distributed to 100 potential adopters, assessing their awareness, influencing factors, and willingness to adopt the technology. Structural Equation Modeling (SEM) was employed to analyse the responses. The findings indicate that consumers’ attitudes, subjective norms, and environmental concerns positively influence their adoption of AEAs. Interestingly, perceived behavioural control and perceived risk were found to have no significant effect. These insights offer practical implications for accelerating AEA adoption in Guangdong's aviation sector. For airlines, the results highlight the importance of emphasising environmental benefits and social endorsements in marketing campaigns. Manufacturers can strengthen safety perceptions to align with consumer expectations, while policymakers may consider infrastructure investments to mitigate adoption barriers. Collectively, these measures could foster broader acceptance of AEAs, supporting regional decarbonisation goals in the regional air transport sector.
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Purpose Research on battery electric vehicles (BEVs) has typically considered environmental concern a key determinant of behavioral intention that leads individuals to prefer electric vehicles. This paper challenges this assumption and argues that technology frameworks may require new variables to capture consumers' preferences. A UTAUT2-based study has been developed to assess the role of environmental concern in the BEVs context and put forward the technology show-off (TS) concept to explain the technology's acceptance. Design/methodology/approach A quantitative and cross-sectional look at behavioral intention is adopted. The study uses structural equation modeling to analyze a sample of 236 Macau residents to determine the relevance of the factors behind the choice to adopt BEVs. Findings The findings indicate that environmental concern and price may be relevant to explain behavioral intention to adopt the BEVs technology. Furthermore, the UTAUT2 framework seems to benefit from adding new variables, with TS playing a pertinent role in explaining technology acceptance. Social implications The findings show that environmental concern fails to build an argument for the shift to full electric mobility and promote the desired behavioral change toward adopting BEVs. Herein lies the necessity to consider new variables that can better describe the characteristics of modern society. Originality/value This paper proposes the TS construct, combining visibility and trialability as significant determinants of behavioral intention to use technology. The study also stresses the need to reconsider the role of environmental concerns' impact on consumer decision-making.