Search Results (972)

The growing need for sustainable energy practices necessitates technology-driven interventions that can effectively bridge the disparity between consumer intentions and actual behavior. This paper formulates and empirically substantiates an IoT-enabled digital nudge architecture designed to promote sustainable energy behavior. The architecture provides goal-setting, social comparison, feedback, and informational nudges across multiple digital channels, utilizing linked devices, data processing layers, and a rule-based nudge engine. An 815-responder survey was analyzed using structural equation modeling with partial least squares (SEM-PLS) to identify the drivers of sustainable energy behavior and explore technology readiness as a moderating factor. The results show that nudges utilizing the Internet of Things (IoT) significantly enhance the alignment between intention and behavior. Goal-setting and feedback mechanisms have the highest effects. The findings also demonstrate that being ready for new technology improves nudge response, highlighting the importance of user-centered system design. This paper presents a scalable infrastructure for integrating IoT into sustainability projects, as well as theoretical contributions to technology adoption and behavioral intervention research. The study enhances the dialogue on environmental technology by illustrating the implementation of digital nudges through IoT infrastructures to expedite progress toward the Sustainable Development Goals (SDGs). Full article

Small Modular Reactors (SMRs) are becoming one of the key trends in the development of nuclear technology, offering a flexible, safe and cost-effective alternative to large nuclear power plants. This review defines the “driving force” of SMRs as their ability to enhance safety, modular scalability, and fuel sustainability through innovative design and policy integration. It aims to provide a systematic assessment of technological trends, deployment strategies, and fuel innovations that underpin the future of nuclear energy. This article provides a comprehensive overview of the main classes of SMRs, categorised by fuel type and application, ranging from Low-Enriched Uranium (LEU) and High-Assay Low-Enriched Uranium (HALEU) reactors to thorium-232, metallic fuel and reprocessed nuclear materials. The key technical advantages of SMRs are discussed—passive safety systems, extended fuel cycles (longer operational periods before refuelling compared to conventional reactors), modular production and compactness—which make such reactors particularly suitable for use in hard-to-reach regions, military facilities, in space and as part of hybrid power systems. Special attention is paid to the prospects of advanced fuel cycles, including the conversion of thorium to uranium-233 and the reuse of actinides, which contributes to waste reduction and supports the realisation of a closed nuclear cycle. The current status of SMR projects around the world is also analysed, highlighting the most promising solutions and discussing regulatory, infrastructure readiness and geopolitical factors. Full article

The growing negative consequences of climate change support the need to deepen and investigate factors that may sustain the engagement of pro-environmental behaviors. In this scenario, eco-emotions represent a key factor that can potentially shape sustainable behaviors. In keeping with this, the present study aimed at observing the potential relationships between eco-emotions and readiness to change (RTC), namely a psychological construct closely related to pro-environmental behaviors. Specifically the RTC dimensions were the following: perceived importance of the problem, motivation, self-efficacy, effectiveness of the proposed solution, social support, action, and perceived readiness. In detail, Generalized Additive Models (GAMs) were performed in order to detect both linear and non-linear associations between eco-emotions and the dimensions of RTC by assuming a complex perspective. The final sample was composed of 252 participants (mean age = 32.99, SD = 14.640). The results pointed out several significant associations (both linear and non-linear) between eco-emotions and the RTC dimensions. In detail, the perceived importance of the problem was linearly associated with anger and anxiety, while sorrow and enthusiasm showed non-linear effects. Furthermore, motivation was linearly linked to anger and guilt and non-linearly to contempt, enthusiasm, and sorrow. In terms of self-efficacy, anger, enthusiasm, and sorrow showed linear relationships, whereas isolation showed a non-linear association. Perceived effectiveness of the proposed solution was linearly related to enthusiasm and sorrow and non-linearly to anger, powerlessness, isolation, and anxiety. Similarly, social support was linearly connected with enthusiasm, isolation, and sorrow, and non-linearly with powerlessness and anxiety. Moreover, action was primarily driven by anger in a linear relationship, while enthusiasm, powerlessness, guilt, and anxiety showed non-linear associations. Finally, perceived readiness was linearly related to anxiety and non-linearly to anger, contempt, enthusiasm, powerlessness, guilt, and sorrow. These findings should be interpreted in light of the study’s limitations, including its cross-sectional nature, reliance on self-reported measures, use of snowball sampling, and sample demographic characteristics, all of which may affect the generalizability of the results. Nevertheless, the results pointed out the presence of several significant linear (e.g., anxiety and the perceived importance of the problem) and non-linear (e.g., contempt and motivation) associations between various eco-emotions and RTC factors. The findings underscore the need for a complex approach to this field of research, suggesting that further studies, policies, and environmental awareness programs should consider the multifaceted nature of these phenomena in order to develop effective and valuable interventions. Full article

This study examines the impact of macroeconomic and energy factors on the sustainable development of the logistics sector in eight Baltic Sea Region (BSR) countries from 2008 to 2023. A synthetic logistics sustainability index (SD), ranging from 0.54 (Lithuania, 2009) to 0.93 (Germany, 2023), was constructed to capture economic, social, and environmental dimensions. The analysis employed country-level regressions, fixed-effects panel models, and a one-step dynamic GMM estimator. Results show that higher GDP per capita (β ≈ +0.35, p < 0.05) significantly supports sustainable logistics, while higher energy intensity (β ≈ −0.41, p < 0.01) constrains it. Across the region, GDP per capita increased by 45% on average, and energy intensity (EI) declined by 18%, contributing to a steady rise in SDI, particularly in Finland, Germany, and Denmark. Renewable energy (RES) has heterogeneous effects: it promotes sustainability in Germany, Finland, and Latvia, but negatively affects Sweden, where rapid energy transition and high electricity costs temporarily reduce logistics efficiency. Electrification rate (RE) also shows a short-term adverse effect in Sweden and Finland, where investment speed exceeds infrastructure adaptability. Labour productivity (LP) and unemployment (UR) exhibit inconsistent effects. Overall, the findings confirm GDP per capita and energy efficiency as dominant drivers of sustainable logistics, while structural and policy differences explain cross-country heterogeneity in sustainability outcomes. These insights provide practical guidance for policymakers by emphasising the need to balance energy transition speed with infrastructure readiness and to tailor sustainability strategies to national economic and energy profiles. Full article

The logistics sector contributes significantly to global warming, primarily through Scope 3 emissions. Green logistics practices (GLPs) can mitigate emissions and improve sustainability performance; however, their adoption remains limited due to high upfront costs and organizational barriers. This study aims to identify the driving factors of green logistics (GL) by conducting a systematic literature review following the PRISMA protocol. A total of 95 peer-reviewed articles published between 2016 and 2024 are analyzed. The review combines bibliometric and content analysis and develops a conceptual framework to guide future research. Findings reveal two main categories of drivers: (i) internal drivers, most notably top management commitment, which influences strategic direction, resource allocation, and organizational change; and (ii) external drivers, particularly institutional pressures. The study also identifies methodological patterns and theoretical gaps and proposes a theory–methodology–context agenda for future research. Practically, it shows how organizational readiness and supportive public policies can help overcome barriers, facilitate adoption, and promote more sustainable logistics systems. Full article

Sustainable consumption has become a global priority, yet the factors that encourage people to adopt environmentally friendly purchasing behavior differ across cultures and technologies. This study explores how environmental knowledge, environmental attitude, and the perception of AI-driven personalization influence green purchasing intention and actual purchasing behavior among young consumers in Java, Indonesia. A survey of 517 university students was conducted, and the relationships among these factors were analyzed using structural equation modeling. The findings reveal that environmental knowledge strongly shapes environmental attitudes, which in turn enhance the intention and behavior to purchase green products. Perception of AI-driven personalization also strengthens green purchasing intention, although its direct effect on behavior is limited. These results suggest that digital platforms and marketers can promote sustainable consumption by combining environmental education with transparent and value-based AI personalization. The study contributes to understanding how psychological readiness and technological engagement together encourage greener consumption among youth in emerging economies. Full article

Background/Objectives: The identification of health risk factors in children should rely not only on body mass index but also on modifiable lifestyle behaviors. Early screening for physical inactivity, poor nutrition, inadequate sleep, and chronic stress is crucial for effective preventive healthcare. The aim of this project was to develop the OWL screening tool, a protocol for the holistic assessment of key lifestyle risk factors in children aged 6–12. Methods/Rationale: The OWL tool was developed by integrating evidence-based recommendations from major health societies (WHO, EFSA, the National Sleep Foundation, and the Pediatric Endocrine Society), incorporating psychological principles, and adapting validated components from existing pediatric screening instruments. Its design prioritizes flexibility for use across various age groups and settings. The development process resulted in the 20-item OWL questionnaire, structured into four lifestyle domains: nutrition, physical activity, sleep, and stress management. Each item is a closed-ended question requiring a dichotomous (yes/no) response. One point is awarded for each health-promoting behavior endorsed, yielding a total possible score of 20. The tool is suitable for self-report by older children, parent-report for younger children, or clinician-administered review. Conclusions: By integrating sleep and stress management with traditional lifestyle factors, the OWL screening tool offers a highly relevant approach to pediatric preventive care. The findings presented here should be interpreted as a proof-of-concept, and the tool is not yet ready for clinical implementation without further rigorous evaluation. Full article

Building maintenance is crucial, yet predicting financial resources for it remains challenging, particularly during the design and construction phases. This research aims to analyze and synthesize existing studies on maintenance cost estimation, with a focus on identifying key trends, methodologies, and sustainability considerations. The review finds that most studies emphasize educational and office buildings, while limited attention has been given to infrastructure such as bridges and roads. Moreover, growing attention is being directed toward early-stage maintenance cost estimation and integrating sustainability principles into cost prediction models. The findings underscore that incorporating sustainability factors in maintenance planning enhances long-term performance, reduces lifecycle costs, and supports future-ready building management. The study concludes by highlighting the need for more comprehensive, sustainability-oriented frameworks to improve the accuracy and applicability of maintenance cost estimation in the built environment. Full article

Background and objectives: Numerous studies and meta-analyses have established the efficacy of telemonitoring for blood pressure and other components of metabolic syndrome in improving disease management. Nevertheless, the adoption of telemonitoring technologies is often hindered by personal, technological, and systemic barriers. In Slovakia, where patient–physician contact rates are high, there is limited research on patients’ perspectives regarding telemedicine adoption for cardiovascular risk management. The objective of this study was to examine patients’ perspectives on and perceived obstacles to the use of telemonitoring for arterial hypertension and dyslipidemia in Slovakia. Methods: This cross-sectional, questionnaire-based survey targeted a cohort of 18,053 patients. The survey instrument was designed to gather data on several key areas: patient demographic characteristics, blood pressure measurement habits, the utilization of smart technologies, perceived benefits and barriers to telemonitoring, and patients’ knowledge of their lipid profiles and cardiovascular risk factors. Statistical analysis included chi-square tests, ANOVA, and effect size calculations with 95% confidence intervals (CI). Results: A total of 1787 patient responses (9.9%) were collected. Among the respondents, 67.4% (n = 1204) had arterial hypertension, while 7.9% (n = 95) were on non-pharmacological therapy. Only 21.2% (n = 255) of hypertensive patients measured their blood pressure daily, with a significantly higher proportion of men than women (28.6% vs. 12.7%, p = 0.011, Cohen’s d = 0.42). The most frequent users of blood pressure monitoring were in the 31–45 age group (p = 0.001, η² = 0.08). A total of 19.4% (n = 347) of respondents used wearable devices, and 6.3% (n = 113) used blood pressure monitors connected to an application. Smart technology use was significantly more common in the 31–45 age group (p = 0.01, Cramer’s V = 0.15). Moderate interest in telemedicine was expressed by 69.8% (n = 1247) of respondents, though only 27.4% (n = 490) showed strong interest. The majority of patients (73.8%, n = 1319) did not know their LDL-C levels, and 45.7% (n = 817) of those who did had elevated levels. Conclusions: The findings suggest that while interest in telemedicine methods for the management of arterial hypertension and dyslipidemia exists among Slovak patients, it is more moderate than initially assumed. Importantly, expressed willingness to participate in a study should not be directly equated with readiness to adopt new technologies in daily practice. Successful integration of telemonitoring into the Slovak healthcare system will therefore require not only patient engagement but also active support from healthcare providers to overcome practical and motivational barriers. These findings highlight the need for targeted implementation strategies that address the specific barriers identified in the Central and Eastern European healthcare context. Full article

Listeria monocytogenes is a significant foodborne pathogen associated with high rates of hospitalization and death, especially among vulnerable populations. Despite established regulatory standards and available antimicrobial intervention strategies, L. monocytogenes remains as a pathogen of concern in ready-to-eat (RTE) foods. This ultimately can lead to food recalls or listeriosis outbreak, highlighting its ongoing risks to food safety and public health. This review consolidates publicly accessible surveillance case counts and recall data of L. monocytogenes contamination from Australia, Europe, Canada, and the United States to assess the contamination trends in the RTE food supply chain. It also evaluates the effectiveness of antimicrobial intervention strategies, including both those currently implemented in industry and those that have been studied as potential interventions but are not yet widely adopted. Key factors affecting the efficiency of those strategies are identified, including food matrix composition, water activity (a_w), fat content, and strain variability. Emerging multi-hurdle technology that integrates physical, chemical, and biological antimicrobial interventions are highlighted as promising approaches for maintaining both food safety and product quality. It also outlines the role of quantitative microbial risk assessment (QMRA) as a decision-support tool to select appropriate control strategies, predict recall risk and guide evidence-based risk management. Future research directions are proposed to expand the application of QMRA in managing recall risks throughout the RTE food supply chain due to L. monocytogenes. Full article

In recent years, Positive Energy Districts (PEDs) have been interpreted in many—and often conflicting—ways. We recast PEDs as a vehicle for verifiable climate neutrality and present a declaration-ready assessment that integrates (i) a cumulative, science-based GHG budget per m² gross floor area (GFA), (ii) full life-cycle accounting, and (iii) time-resolved conversion factors that include everyday motorized individual mobility and quantify flexibility. Two KPIs anchor the framework: the cumulative GHG LCA balance (2025–2075) against a maximum compliant budget of 320 kg_CO2e·m⁻²_GFA and the annual primary energy balance used to declare PED status with or without mobility. We follow EN 15978 and apply time-resolved emission factors that decline to zero by 2050. Its applicability is demonstrated on six Austrian districts spanning new builds and renovations, diverse energy systems, densities, and mobility contexts. The baseline scenarios show heterogeneous outcomes—only two out of six meet both the cumulative GHG budget and the positive primary energy balance—but design iterations indicate that all six districts can reach the targets with realistic, ambitious packages (e.g., high energy efficiency and flexibility, local renewables, ecological building materials, BESS/V2G, and mobility electrification). Hourly emission factors and flexibility signals can lower import-weighted emission intensity versus monthly or annual factors by up to 15% and reveal seasonal import–export asymmetries. Built on transparent, auditable rules and open tooling, this framework both diagnoses performance gaps and maps credible pathways to compliance—steering PED design away from project-specific targets toward verifiable climate neutrality. It now serves as the basis for the national labeling/declaration scheme klimaaktiv “Climate-Neutral Positive Energy Districts”. Full article

As part of urban sustainable food strategies, reducing land and emission footprints motivates interest in edible insects (EI) as a sustainable protein source. However, research on the determinants of young consumers’ acceptance and willingness to pay for insect-based foods in Central and Eastern Europe remains limited. This study assessed whether Polish students are willing to pay more for foods containing EI when production is environmentally friendly. The analysis focused on identifying socio-demographic and product-related factors influencing willingness to pay a higher price. Data were collected in November 2023 through a nationwide Computer-Assisted Web Interview (CAWI) conducted via Google Forms among 947 Polish university students. A logistic regression model was applied to determine socio-demographic predictors, while exploratory factor analysis was used to identify latent dimensions of product attributes and food categories. Results revealed that gender and place of residence significantly affected willingness to pay, with women and urban residents showing higher readiness. Attributes related to convenience, availability, sensory appeal, health and nutrition claims, and CO₂ reduction benefits were the strongest positive correlates. The findings suggest pragmatic pathways for introducing insect-based foods into sustainable urban food systems and highlight the role of education in fostering environmentally responsible consumer behavior. Full article

The readiness of tourists to accept innovative food is investigated in this research through the prism of the Protection Motivation Theory and the Theory of Planned Behavior, combining two previously developed yet seldom researched psychological dimensions, namely, food neophobia as a restraining force and food involvement as a motivating force. The quantitative approach and the generation-by-generation analysis using partial least squares (PLS-SEM) and multiple group analysis were used to conduct the study on a sample of 985 domestic tourists in Serbia. The results suggest that food involvement eases openness toward gastronomic innovations and mitigates the negative impact of neophobia, whereas the generational differences reveal that younger tourists are more willing to be experimental, and older generations tend to be conservative in their food consumption. The study is relevant to the academic literature because it puts motivational and barrier factors into context within the PMT and TPB paradigms and provides operational implications for the design of tourism propositions that can be used to promote innovative and sustainable gastronomic experiences. The novelty of the present study is that it uses the hybrid model of food neophobia and food involvement in the generational context of a post-transition society, i.e., Serbia. Full article

Pedestrian crashes remain a leading cause of road traffic fatalities in developing countries (DCs); yet reliable crash data are scarce, constraining the ability to model pedestrian safety risks and evaluate countermeasure effectiveness. This study developed a methodological process for estimating the influence of contextual factors on pedestrian crashes using artificial data. The process integrated literature-derived trend analysis, artificial data generation, external face validity checks, correlation analysis, stepwise negative binomial regression, sensitivity testing, and mapping of results against the International Road Assessment Programme (iRAP) framework. Of the 26 contextual factors considered, 20 were retained in the negative binomial (NB) models, while six were excluded due to weak or inconsistent trend data. Results showed that behavioural and institutional factors, including ad hoc countermeasure implementation, gender composition of pedestrian flows, and vehicle age or technology, exerted stronger influence on crash outcomes than several geometric variables typically emphasised in global models. External validity testing confirmed broad alignment of the artificial dataset with published values, while sensitivity analysis demonstrated the robustness of factor influence values (Fi) across bootstrap resampling and scenario perturbations. The Fi values derived are illustrative rather than decision-ready, reflecting the artificial-data basis of this study. Nonetheless, the findings highlight methodological proof of concept that artificial-data modelling can provide credible and context-sensitive insights in data-scarce environments. Mapping results to the iRAP framework revealed complementarity, with opportunities to extend global models by incorporating behavioural and institutional variables more systematically. The approach provides a replicable pathway for improving pedestrian safety assessment in DCs and informs the development of an enhanced iRAP effectiveness model in subsequent research. Future applications should prioritise empirical calibration with real-world crash datasets and support policymakers in integrating behavioural and institutional factors into countermeasure prioritisation and safety planning. Full article

With the growth of digital economies, data quality forms a key factor in enabling use and delivering value. Existing research defines quality through technical benchmarks or provider-led frameworks. Our study shifts the focus to actual users. Thirty-seven distinct data quality dimensions identified through a comprehensive review of the literature provide limited applicability for practitioners seeking actionable guidance. To address the gap, in-depth interviews of senior professionals from 25 organizations were conducted, representing sectors like computer science and technology, finance, environmental, social, and governance, and urban infrastructure. Data are analysed using content analysis methodology, with 2 level coding, supported by NVivo R1 software. Several newer perspectives emerged. Firstly, data quality is not simply about accuracy or completeness, rather it depends on suitability for real-world tasks. Secondly, trust grows with data transparency. Knowing where the data comes from and the nature of data processing matters as much as the data per se. Thirdly, users are open to paying for data, provided the data is clean, reliable, and ready to use. These and other results suggest data users focus on a narrower, more practical set of priorities, considered essential in actual workflows. Rethinking quality from a consumer’s perspective offers a practical path to building credible and accessible data ecosystems. This study is particularly useful for data platform designers, policymakers, and organisations aiming to strengthen data quality and trust in data exchange ecosystems. Full article