Search Results (343)

Wellington, New Zealand, is highly vulnerable to disaster-induced food security crises due to its geography and geological characteristics, which can disrupt transportation and isolate the city following disasters. Urban agriculture (UA) has been proposed as a potential alternative food source for post-disaster scenarios. This study examined the potential of urban agriculture for enhancing post-disaster food security by calculating vegetable self-sufficiency rates. Specifically, it evaluated the capacity of current Wellington’s community gardens to meet post-disaster vegetable demand in terms of both weight and nutrient content. Data collection employed mixed methods with questionnaires, on-site observations and mapping, and collecting high-resolution aerial imagery. Garden yields were estimated using self-reported data supported by literature benchmarks, while cultivated areas were quantified through on-site mapping and aerial imagery analysis. Six post-disaster food demand scenarios were used based on different target populations to develop an understanding of the range of potential produce yields. Weight-based results show that community gardens currently supply only 0.42% of the vegetable demand for residents living within a five-minute walk. This rate increased to 2.07% when specifically targeting only vulnerable populations, and up to 10.41% when focusing on gardeners’ own households. However, at the city-wide level, the current capacity of community gardens to provide enough produce to feed people remained limited. Nutrient-based self-sufficiency was lower than weight-based results; however, nutrient intake is particularly critical for vulnerable populations after disasters, underscoring the greater challenge of ensuring adequate nutrition through current urban food production. Beyond self-sufficiency, this study also addressed the role of UA in promoting food diversity and acceptability, as well as its social and psychological benefits based on the questionnaires and on-site observations. The findings indicate that community gardens contribute meaningfully to post-disaster food security for gardeners and nearby residents, particularly for vulnerable groups with elevated nutritional needs. Despite the current limited capacity of community gardens to provide enough produce to feed residents, findings suggest that Wellington could enhance post-disaster food self-reliance by diversifying UA types and optimizing land-use to increase food production during and after a disaster. Realizing this potential will require strategic interventions, including supportive policies, a conducive social environment, and diversification—such as the including private yards—all aimed at improving food access, availability, and nutritional quality during crises. The primary limitation of this study is the lack of comprehensive data on urban agriculture in Wellington and the wider New Zealand context. Addressing this data gap should be a key focus for future research to enable more robust assessments and evidence-based planning. Full article

Background: Faced with the profound impact of major infectious diseases on public life and economic development, humans have long sought to understand disease transmission and intervention strategies. To better explore the impact of individuals’ different coping behaviors—triggered by changes in their psychological security due to public information and external environmental changes—on the spread to infectious diseases, the model will place greater emphasis on quantifying psychological factors to make it more aligned with real-world situations. Methods: To better understand the interplay between information dissemination and disease transmission, we propose a two-layer network model that incorporates psychological safety factors. Results: Our model reveals key insights into disease transmission dynamics: (1) active defense behaviors help reduce both disease spread and information diffusion; (2) passive resistance behaviors expand disease transmission and may trigger recurrence but enhance information spread; (3) high-timeliness, low-fuzziness information reduces the peak of the initial infection but does not significantly curb overall disease spread, and the rapid dissemination of disease-related information is most effective in limiting the early stages of transmission; and (4) community structures in information networks can effectively curb the spread of infectious diseases. Conclusions: These findings offer valuable theoretical support for public health strategies and disease prevention after government information release. Full article

Autonomous vehicles (AVs) have emerged as a promising sustainable urban mobility solution, expected to lead to enhanced road safety, smoother traffic flows, less traffic congestion, improved accessibility, better energy utilization and environmental performance, as well as more efficient passenger and freight transportation, in terms of time and cost, due to better fleet management and platooning. However, challenges also arise, mostly related to data privacy, security and cyber-security, high acquisition and infrastructure costs, accident liability, even possible increased traffic congestion and air pollution due to induced travel demand. This paper presents the results of a survey conducted among 654 residents who experienced an autonomous bus (AB) service in the city of Trikala, Greece, in order to assess their willingness to use (WTU) and willingness to pay (WTP) for ABs, through testing a range of factors based on a literature review. Results useful to policy-makers were extracted, such as that the intention to use ABs was mostly shaped by psychological factors (e.g., users’ perceptions of usefulness and safety, and trust in the service provider), while WTU seemed to be positively affected by previous experience in using ABs. In contrast, sociodemographic factors were found to have very little effect on the intention to use ABs, while apart from personal utility, users’ perceptions of how autonomous driving will improve the overall life standards in the study area also mattered. Full article

Rapid urbanization has intensified global settlement density, significantly increasing the importance of urban street environmental quality, which profoundly affects residents’ physical and psychological well-being. Traditional methods for evaluating urban environmental quality have largely overlooked dynamic perceptual changes occurring throughout the day, resulting in incomplete assessments. To bridge this methodological gap, this study presents an innovative approach combining advanced deep learning techniques with time-series street view imagery (SVI) analysis to systematically quantify spatio-temporal variations in the perceived environmental quality of pedestrian-oriented streets. It further addresses two central questions: how perceived environmental quality varies spatially across sections of a pedestrian-oriented street and how these perceptions fluctuate temporally throughout the day. Utilizing Golden Street, a representative living street in Shanghai’s Changning District, as the empirical setting, street view images were manually collected at 96 sampling points across multiple time intervals within a single day. The collected images underwent semantic segmentation using the DeepLabv3+ model, and emotional scores were quantified through the validated MIT Place Pulse 2.0 dataset across six subjective indicators: “Safe,” “Lively,” “Wealthy,” “Beautiful,” “Depressing,” and “Boring.” Spatial and temporal patterns of these indicators were subsequently analyzed to elucidate their relationships with environmental attributes. This study demonstrates the effectiveness of integrating deep learning models with time-series SVI for assessing urban environmental perceptions, providing robust empirical insights for urban planners and policymakers. The results emphasize the necessity of context-sensitive, temporally adaptive urban design strategies to enhance urban livability and psychological well-being, ultimately contributing to more vibrant, secure, and sustainable pedestrian-oriented urban environments. Full article

Cybersecurity threats increasingly originate from human actions within organizations, emphasizing the need to understand behavioral factors behind non-compliance with information security policies (ISPs). Despite the presence of formal security policies, insider threats—whether accidental or intentional—remain a major vulnerability. This study addresses the gap in behavioral cybersecurity research by developing an integrated conceptual model that draws upon Operant Conditioning Theory (OCT), Protection Motivation Theory (PMT), and the Theory of Planned Behavior (TPB) to explore ISP compliance. The research aims to identify key cognitive, motivational, and behavioral factors that shape employees’ intentions and actual compliance with ISPs. The model examines seven independent variables of perceived severity: perceived vulnerability, rewards, punishment, attitude toward the behavior, subjective norms, and perceived behavioral control, with intention serving as a mediating variable and actual ISP compliance as the outcome. A quantitative approach was used, collecting data via an online survey from 302 employees across the public and private sectors. Structural Equation Modeling (SEM) with SmartPLS software (v.4.1.1.2) analyzed the complex relationships among variables, testing the proposed model. The findings reveal that perceived severity, punishment, attitude toward behavior, and perceived behavioral control, significantly and positively, influence employees’ intentions to comply with information security policies. Conversely, perceived vulnerability, rewards, and subjective norms do not show a significant effect on compliance intentions. Moreover, the intention to comply strongly predicts actual compliance behavior, thus confirming its key role as a mediator linking cognitive, motivational, and behavioral factors to real security practices. This study offers an original contribution by uniting three well-established theories into a single explanatory model and provides actionable insights for designing effective, psychologically informed interventions to enhance ISP adherence and reduce insider risks. Full article

Edible insects are emerging as a sustainable and eco-friendly alternative protein source, addressing global challenges in food security and environmental sustainability. This study investigates the willingness and acceptance of edible insects as sustainable alternative protein sources among Saudi participants, focusing on sociodemographic and attitudinal factors. A cross-sectional survey involving 2208 participants revealed that males and younger individuals (18–34 years) exhibited greater willingness to consume EIs, driven by environmental concerns, health benefits, and positive beliefs. Women and older participants showed higher levels of food neophobia, disgust, and uncertainty. Sociocultural barriers such as fear, a lack of familiarity, and perceptions of edible insects as unclean or forbidden were significant obstacles to acceptance and willingness. Interestingly, the education level did not significantly influence willingness, suggesting that cultural and religious norms may overshadow its impact. These findings underscore the need for targeted campaigns emphasizing the health, environmental, and sustainability benefits of edible insects, alongside culturally sensitive approaches to overcome psychological and social barriers. This research provides valuable insights to guide strategies for integrating EIs into Saudi diets as a step toward enhanced food security and environmental sustainability. Full article

Accepting a certain degree of investment loss risk is essential for long-term portfolio management. However, overconfidence bias within financial literacy can prompt excessively risky behavior and amplify susceptibility to other cognitive biases. These tendencies can undermine investment loss tolerance beyond the baseline level shaped by sociodemographic, economic, psychological, and cultural factors. This study empirically examines the association between overconfidence and investment loss tolerance, which is measured by the point at which respondents indicate they would sell their investments in a hypothetical loss scenario. Using a large-scale dataset of 161,765 active investors from one of Japan’s largest online securities firms, we conduct ordered probit and ordered logit regression analyses, controlling for a range of sociodemographic, economic, and psychological variables. Our findings reveal that overconfidence is statistically significantly and negatively associated with investment loss tolerance, indicating that overconfident investors are more prone to prematurely liquidating assets during market downturns. This behavior reflects an impulse to avoid even modest losses. The findings suggest several possible practical strategies to mitigate the detrimental effects of overconfidence on long-term investment behavior. Full article

Background/Objectives: Against the backdrop of increasing global aging and the trans-formation of family structures, grandparental caregiving has become commonplace, and its impact on the mental health of older persons is of great concern. Methods: Based on data from the 2023 Xi’an Jiaotong University Urban and Rural Elderly Family Support and Psychological Condition Survey, this study analyzed the impact of grandparental care-giving behaviors on the mental health of the elderly through the Psychological Condition Measurement Scale (PCMS), and comprehensively assessed the presence, intensity, and heterogeneous impact of grandparental caregiving behaviors by gender by applying linear regression modeling, the Propensity Score Matching (PSM) method, and the Instrumental Variables Method (IVM). Results: Grandparental care has a significant positive effect on the mental health of older people, but this positive effect diminishes as the intensity of care increases. The results of the sub-sample estimation show that grandparental caregiving has a positive effect on men’s and low-intensity caregiving on women’s mental health, but high-intensity caregiving has a negative effect on women’s mental health. In addition, in-tergenerational financial support and intergenerational emotional comfort play an im-portant mediating role between grandparental caregiving and the mental health of older persons, in line with the explanatory framework of intergenerational exchange theory. Conclusions: It is recommended that the Government support grandparental care for the elderly at the financial, social security, and policy levels; that society build a diversified system of elderly care services and strengthen public childcare services; and that families establish a value identity of two-way support. Full article

The increasing frequency and sophistication of cyber attacks have posed significant challenges for digital financial organisations, particularly in quantifying their multidimensional impacts. These challenges are largely attributed to the lack of a standardised cyber impact taxonomy, limited data availability, and the evolving nature of technological threats. As a result, organisations often struggle with ineffective security investment prioritisation, reactive incident response planning, and the inability to implement robust, risk-based controls. Hence, an efficient and comprehensive approach is needed to quantify the diverse impacts of cyber attacks in digital financial services. This paper presents a systematic review and examination of the state of the art in cyber impact quantification, with a particular focus on digital financial organisations. Based on a structured search strategy, 44 articles (out of 637) were selected for in-depth analysis. The review investigates the terminologies used to describe cyber impacts, categorises current quantification techniques (pre-attack and post-attack), and identifies the most commonly utilised internal and external data sources. Furthermore, it explores the application of Machine Learning (ML) and Deep Learning (DL) techniques in cyber security risk quantification. Our findings reveal a significant lack of standardised taxonomy for describing and quantifying the multidimensional impact of cyberattacks across physical, digital, economic, psychological, reputational, and societal dimensions. Lastly, open issues and future research directions are discussed. This work provides insights for researchers and professionals by consolidating and identifying quantification technique gaps in cyber security risk quantification. Full article

Background/Objectives: The adoption of sustainable eating behaviors is not only crucial for environmental health but also has significant implications for individual health outcomes. A deeper understanding of the psychological determinants underlying such changes is needed. The Theory of Planned Behavior (TPB) has been widely used to understand the psychological factors influencing health behaviors, including dietary choices. Recent advances suggest integrating additional psychological constructs, such as personal values, to enhance TPB’s predictive power and the effectiveness of related behavioral interventions. Methods: A novel Food-Related Personal Values Questionnaire (FRPV-Q) was developed based on Schwartz’s circumplex model of basic values, and the role of these food-related personal values within an enhanced TPB framework was tested. Statistical analyses were conducted to explore the structure of the questionnaire. Results: Three components were identified within the FRPV-Q: Openness, Health and Security, and Autonomy (Kaiser–Meyer–Olkin test = 0.576). The regression analyses highlighted the potential role of personal values in predicting sustainable eating behaviors (adjusted R² = 0.318). Specifically, an orientation toward autonomy, hedonism, and self-directionality appeared to hinder the adoption of sustainable food choices, while an orientation toward health, security, and openness to novelty was found to promote more sustainable dietary choices. Conclusions: The results offer preliminary insights into the role of personal values in food-related behaviors. Future research aimed at understanding and promoting pro-environmental food-related behaviors should rigorously investigate the topic. Carefully tailored value-based psychological interventions may prove beneficial for the general population in the promotion of sustainable dietary lifestyles. Full article

Immersive technologies (IMTs) have significantly impacted the tourism sector by offering experiences that enhance engagement with destinations. Although previous research confirms that IMT affects travelers’ behavioral intentions, there is a lack of studies specifically focusing on the post-experience context of agritourism and the factors contributing to technological resistance. This study introduces a conceptual model that combines the Diffusion of Innovation framework, the technology acceptance model, and the psychological factors related to innovation resistance to examine the decision-making processes of IMT users in the post-experience context of agritourism. The research model is evaluated through partial least squares structural equation modeling (PLS-SEM) techniques involving 400 users who engaged with IMT for a duration not exceeding 3 months. The findings indicate that the amount of storytelling content, which enhances engagement in agritourism, significantly affects users’ perceptions of IMT and their intentions to revisit and continue using IMT. Additionally, factors related to compatibility, along with privacy and security risks, influence the reluctance or readiness to adopt IMT and the decision to revisit a destination. These findings contribute to the understanding necessary to develop content and apply IMT in the agritourism sector to promote long-term sustainability. Full article

Large Language Models offer transformative capabilities but also introduce growing cybersecurity risks, particularly through their use in generating realistic phishing emails. Detecting such content is critical; however, existing methods can be resource-intensive and slow to adapt. In this research, we present a dual-layered detection framework that combines supervised learning for accurate classification with unsupervised techniques to uncover emerging threats. In controlled testing environments, our approach demonstrates strong performance. Recognising that human users are often the weakest link in information security systems, we examine historical deception patterns and psychological principles commonly exploited in phishing attacks. We also explore watermarking as a complementary method for tracing AI-generated content. Together, these strategies offer a scalable, adaptive defence against increasingly sophisticated phishing attacks driven by Large Language Models. Full article

VR technology is increasingly being integrated into daily life, with virtual book communities emerging as novel platforms for immersive reading and interaction. This study investigates how internal and external factors jointly influence users’ usage intention from psychological and behavioral science perspectives. A multivariate structural equation model based on three-dimensional perception theory was developed and tested through a survey of individuals with prior VR reading experience. The model examines the roles of task–technology fit, privacy and security risks, emotional resonance, self-expression, and the sense of belonging. The results reveal that task–technology fit positively influences usage intention, while privacy and security risk has a negative effect. Internally, emotional resonance and a sense of belonging significantly enhance usage intention. Furthermore, emotional resonance mediates the relationship between self-expression and both sense of belonging and usage intention, while sense of belonging also mediates between emotional resonance and usage intention. These findings underscore the critical interplay between technical attributes and affective factors in shaping engagement with VR-based reading platforms. This study offers new insights into user acceptance mechanisms in virtual book communities, and provides a theoretical foundation and practical implications for enhancing user experience and adoption in digital library systems. Full article

By focussing on the emotional and affective dimensions of borders, this article suggests integrating the negative emotions that the European Union (EU) states’ border politics aim to instil—including fear, anxiety and trauma—with the positive emotions that the dream of a life in Europe encourages. Drawing upon the psychological and philosophical approaches to hope, this article highlights the centrality of hope in shaping agency, stimulating alternative visions, and overcoming difficulties. What is the impact of hope and daydreams in shaping migrants’ decision to engage with risky journeys? To what extent might the dream of Europe counterbalance the EU’s securitarian technologies? This article introduces and explores the processes of b/ordering and the role that emotions, as spatially grounded, play in it. This article will ultimately contend that, once confronted with the uncertainties of long and risky journeys and the prospect of a bright and dreamed future, the latter often prevails. Under this scenario, states’ deterrent systems might not be as effective as hoped, as the dream of Europe overrides the fear and anxiety that EU states’ border security aims to generate. Full article

The rapid growth of China’s aging population has made elderly care a pressing social issue. Due to an imperfect pension system, limited uptake of institutional care, and uneven regional economic development, most elderly people in China still rely on home-based care. Elderly people living at home are usually cared for by their family, partners, caregivers, or themselves. However, this often fails to meet their complex health, safety, and emotional needs. Artificial intelligence may provide promising solutions to improve home care experiences and address the multifaceted health and lifestyle challenges faced by homebound elderly people. This review explores the applications of artificial intelligence in home-based care from four main perspectives: home health care, home safety and security, smart life assistants, and psychological care and emotional support. We systematically searched PubMed, IEEE Xplore, CNKI, and Scopus databases, integrated the latest research published between 2015 and 2024, focused on peer-reviewed, practice-oriented research, and reviewed relevant technology development paths and the current status of the field. Unlike previous studies that focused on physiological monitoring, this study is the first to systematically and comprehensively evaluate the role of artificial intelligence in improving the convenience of daily life and mental health support for elderly people at home. By comprehensively reviewing and analyzing the basic principles and application background of artificial intelligence technology in this field, we summarize the current technical and ethical challenges and propose future research directions. This study aims to help readers gain a deeper understanding of the current status and emerging trends of artificial intelligence-enabled home-based elderly care, thereby providing valuable insights for continued innovation and application in this rapidly developing field. Full article