Search Results (814)

Driven by the “dual carbon” goal and the strategy for cultivating new productive forces, China’s economy is undergoing a crucial transformation from high-speed growth to high-quality development. As a typical high-energy consumption and high-emission sector, the green and low-carbon transformation of the building materials industry directly affects the optimization of the national energy structure and the realization of ecological goals. However, traditional building material enterprises generally face practical challenges such as low resource utilization efficiency, insufficient digitalization and greening integration of the industrial chain, and weak green innovation momentum. The transformation actions of a single entity are difficult to break through systemic bottlenecks, and it is urgently necessary to establish a dynamic evolution mechanism involving multiple entities in collaboration. This paper aims to explore the evolutionary rules and stability of digital green (DG) transformation strategies of building materials enterprises (BMEs) under multi-agent interactions involving government, universities, and consumers. Centering on BMEs, a four-party evolutionary game model among the government, enterprises, universities, and consumers is constructed, and the evolutionary processes of strategic behaviors are characterized through replicator dynamic equations. Using MATLAB R2022 (Version number: 9.13.0.2049777) bnumerical simulations, this study investigates how key parameters, such as government subsidies, penalty intensity, and consumers’ green preferences, affect the transformation pathways of enterprises. The results reveal that the DG transformation behavior of BMEs is significantly influenced by governmental policy incentives and universities’ knowledge innovation. Stronger subsidies and penalties enhance enterprises’ willingness to adopt proactive DG strategies, while consumers’ green preferences further accelerate transformation through market mechanisms. Among multiple strategic combinations, active DG transformation emerges as the main evolutionarily stable strategy. This study provides a systematic multi-agent collaborative analysis framework for the transformation of BME DG, revealing the mechanisms by which policies, knowledge, and market demands influence enterprise decisions. Thus, it offers theoretical and decision-making references for the green and low-carbon transformation of the building materials industry. Full article

Fish screens are a sustainable agricultural innovation that offers economic and environmental benefits by protecting aquatic life and enhancing the efficiency of irrigation. In freshwater irrigation ecosystems, fish screens help protect aquatic organisms by reducing fish entrainment, facilitating ecological connectivity, and lowering mortality at early life stages. Therefore, they contribute significantly to aquatic biodiversity conservation. However, the role of trust in media in influencing Australian irrigators’ intentions to use fish screens remains underexplored. The study, guided by the Elaboration Likelihood Model (ELM) and incorporating the Theory of Consumption Values, examines trust in media as a persuasive factor impacting the functional, environmental, and Interpersonal Trust Cue of fish screens. The irrigators’ willingness to test, adopt, or implement fish screens can also predict the irrigators’ readiness to act for biodiversity-relevant outcomes. Data were collected between December 2021 and May 2023 from 192 Australian irrigators (sampling frame = 3736; response rate = 5.1%). The PLS-SEM results reveal that trust in media significantly predicts adoption intention (β = 0.134, 95% CI [0.021, 0.246]) and resource (time) efficacy (β = 0.170, 95% CI [0.054, 0.289]), with resource efficacy partially mediating this relationship. The study offers a theoretical contribution by integrating the ELM, the Theory of Consumption Value, and resource efficacy to explain how trust in media influences adoption through different persuasive routes. The model explains 22.5% of the variance in adoption intention. The findings indicate that resource efficacy is a critical enabling factor in translating conservation-oriented communication into an effective measure to protect freshwater biodiversity. Full article

Sustainable packaging has become a major area of academic and practical interest, reflecting growing environmental awareness, regulatory pressure, and changing consumer expectations. This study aims to synthesize existing knowledge on consumers’ behavior toward sustainable packaging and their willingness to pay (WTP) for environmentally friendly solutions. Following PRISMA guidelines, a systematic literature review was conducted, encompassing 78 peer-reviewed publications from 2019 to 2025. Bibliometric mapping using VOSviewer (version 1.6.20) identified three main research streams: consumer attitudes and determinants of behavior, willingness to pay for sustainable packaging, and perception of packaging materials and systems. The reviewed studies, conducted across Europe, Asia, Australia, and North America, employed diverse methods, including surveys, discrete choice experiments, structural equation modeling, and mixed designs. Results indicate that consumer behavior is shaped by environmental awareness, self-identity, perceived usefulness, and trust in labeling, while packaging material and functionality remain decisive for acceptance. Most studies show that consumers are willing to pay a premium of about 10–20% for sustainable packaging, though price sensitivity and hygiene concerns limit actual adoption. The findings highlight the conditional nature of consumer acceptance and emphasize the need for transparent communication, credible certification, and functional design. This study provides guidance for policymakers and businesses seeking to promote sustainable packaging solutions. Full article

In the face of escalating environmental crises, sustainable development is becoming one of the key global challenges. A growing body of research indicates that transitioning to plant-based diets, including a vegan diet, can significantly improve environmental sustainability. Young people from Generation Z play a crucial role in shaping future consumption patterns, and their beliefs and attitudes toward sustainable food may serve as an important indicator of social changes in the area of nutrition and the potential for implementing pro-ecological practices. The aim of the study is to assess students’ perceptual attitudes toward plant-based products, which constitute an integral part of vegan diets, addressing a significant gap in the literature on sustainable consumption among Generation Z in emerging economies. The study allows for the identification of the main sources of information, psychosocial barriers, and motivational factors underlying the adoption of a vegan diet, situating them within sustainable development paradigms. The research group consisted of 263 university students in Warsaw (Poland). A CAWI survey method was used, with a proprietary questionnaire. The study shows that more than 60% of respondents were not interested in this dietary option, and a similar proportion did not expect to adopt veganism in the future. Students’ attitudes toward the vegan diet are shaped primarily by their self-assessment of nutritional knowledge, previous experiences with plant-based diets, and socio-cultural factors. Although many respondents recognize the health and environmental benefits of a plant-based diet, the lack of reliable knowledge, concerns about deficiencies, higher product costs, and social pressure remain key barriers limiting their willingness to change eating habits. From a practical perspective, the findings highlight the need to develop nutrition education focused on the competencies required to properly balance plant-based diets, to increase the economic and sensory accessibility of vegan food, and to counteract persistent stereotypes and misconceptions about veganism, especially on social media, which is the main source of information for this age group. Full article

AI Recommender Systems (RecSys) function as personalised forecasting engines, predicting user preferences to reduce information overload. However, the efficacy of these systems is often bottlenecked by the “Last Mile” of forecasting: the end-user’s willingness to adopt and rely on the prediction. While the existing literature often assumes that algorithmic accuracy (e.g., low RMSE) automatically drives utilisation, empirical evidence suggests that users frequently reject accurate forecasts due to a lack of trust or cognitive friction. This study challenges the utilitarian view that users adopt systems simply because they are useful, instead proposing that sustainable adoption requires a state of Cognitive Absorption—a psychological flow state enabled by the Cognitive Economy of trust. Grounded in the Motivation–Opportunity–Ability (MOA) framework, we developed the Trust–Absorption–Intention (TAI) model. We analysed data from 366 users of a major predictive platform using Partial Least Squares Structural Equation Modelling (PLS-SEM). The Disjoint Two-Stage Approach was employed to model the reflective–formative Higher-Order Constructs. The results demonstrate that Cognitive Trust (specifically the relational dimensions of Benevolence and Integrity) operates via a dual pathway. It drives adoption directly, serving as a mechanism of Cognitive Economy where users suspend vigilance to rely on the AI as a heuristic, while simultaneously freeing mental resources to enter a state of Cognitive Absorption. Affective Trust further drives this immersion by fostering curiosity. Crucially, Cognitive Absorption partially mediates the relationship between Cognitive Trust and adoption intention, whereas it fully mediates the impact of Affective Trust. This indicates that while Cognitive Trust can drive reliance directly as a rational shortcut, Affective Trust translates to adoption only when it successfully triggers a flow state. This study bridges the gap between algorithmic forecasting and behavioural adoption. It introduces the Cognitive Economy perspective: Trust reduces the cognitive cost of verifying predictions, allowing users to outsource decision-making to the AI and enter a state of effortless immersion. For designers of AI forecasting agents, the findings suggest that maximising accuracy may be less effective than minimising cognitive friction for sustaining long-term adoption. To solve the cold start problem, platforms should be designed for flow by building emotional rapport and explainability, thereby converting sporadic users into continuous data contributors. Full article

Smallholder farmers in semi-arid regions worldwide face persistent water scarcity, declining soil fertility, and increasing climate variability, which constrain food production. This study investigated soil and water management practices and their effects on soil health, crop productivity, and adoption among smallholder vegetable farmers in a semi-arid area in Kenya. A mixed-methods approach was employed, combining survey data from 397 farmers with a randomized field experiment. Results showed that hand watering (88.7%) and manure application (95.5%) were prevalent, while only 5.7% of farmers used drip irrigation. Compost and mulch treatments significantly improved soil organic carbon (p = 0.03), available water capacity (p = 0.01), and gravimetric moisture content (p = 0.02), with soil moisture conservation practices strongly correlated with higher yields in leafy green vegetables (R = 0.62). Despite these benefits, adoption was hindered by high water costs (42.6%) and unreliable sources (25.7%). Encouragingly, 96.2% of respondents expressed willingness to pay for improved water systems if affordable and dependable. The findings stress the need for integrated water–soil strategies supported by inclusive policy, infrastructure investment, and gender-responsive training to enhance resilience and productivity in smallholder farming under water-scarce conditions across sub-Saharan Africa and other regions globally, contributing to global sustainability targets such as SDG 6, 12 and 15. Full article

Payments for Ecosystem Services (PESs) have become a central instrument in global biodiversity finance, yet endangered species-specific PESs remain rare and poorly understood in implementation terms. Taiwan provides a revealing case: a three-year program paying farmers to conserve four threatened species—Prionailurus bengalensis, Lutra lutra, Tyto longimembris, and Hydrophasianus chirurgus—in working farmland across Taiwan and Kinmen island. Through semi-structured interviews with farmers, residents, and local conservation actors, we examine how payments are interpreted, rationalized, enacted, and emotionally experienced at the ground level. This study adopts Colaizzi’s data analysis method, the primary advantage of which lies in its ability to systematically transform fragmented and emotive interview narratives into a logically structured essential description. This is achieved through the rigorous extraction of significant statements and the subsequent synthesis of thematic clusters. Participants reported willingness to continue not only because subsidies offset losses, but because rarity, community pride, and the visible arc of “we helped this creature survive” became internalized rewards. NGOs amplified this shift by translating science into farm practice and “normalizing” coexistence. In practice, conservation work became a social project—identifying threats, altering routines, and defending habitat as a shared civic act. This study does not estimate treatment-effect size; instead, it delivers mechanistic insight at a live policy moment, as Taiwan expands PESs and the OECD pushes incentive reform. The finding is simple and strategically important: endangered-species PESs work best where payments trigger meaning—not where payments replace it. Full article

Although green housing is widely regarded as an effective solution to energy and environmental challenges, its actual rate of adoption remains lower than expected. In the context of increasingly prominent sustainable development goals, promoting residents’ adoption of green housing has become a key issue in advancing sustainable transformation within the housing sector. Consequently, enhancing residents’ willingness to adopt green housing is critical to its broader diffusion. Drawing on diffusion of innovation theory, attitude theory, and perceived value theory, this study develops a multidimensional integrated model to identify factors influencing the adoption of green housing. The model examines how the innovation attributes of green housing and residents’ psychological evaluations jointly shape adoption intention. A questionnaire survey was conducted among 387 residents in Nanjing, China, and the data were analysed using partial least squares modelling. The results indicate that the five attributes derived from diffusion of innovation theory are significant antecedents of residents’ attitudes. Relative advantage, compatibility, trialability, and observability exert significant positive effects on residents’ attitudes toward adopting green housing, with relative advantage emerging as the most influential factor. Complexity has a negative, though comparatively weaker, effect on residents’ attitudes toward green housing adoption. Residents’ attitudes and perceived value are identified as significant predictors of green housing adoption intention. These findings contribute to a clearer understanding of residents’ green housing adoption intentions for both researchers and practitioners. More importantly, the study offers general policy and managerial implications for governments and developers seeking to enhance the uptake of green housing. Full article

This study examines European citizens’ attitudes and willingness to pay for biobased materials in construction and renovation. A survey conducted across nine countries with over 4500 participants revealed a generally positive attitude toward using recycled materials, such as glass and wood, while skepticism persisted toward biobased options. Many respondents expressed willingness to pay more for biobased and innovative materials, though a notable proportion would pay less for recycled and reused components. The findings highlighted significant national differences in attitudes and preferences, underscoring the influence of socioeconomic and cultural factors on the adoption of circular economy practices in the construction sector. Full article

Objectives. To integrate clinical and economic evidence on the main non-pharmacological interventions aimed to reduce the burden of caregivers of people with dementia, with specific attention to stated preference measures (SPM), Willingness-to-Pay (WTP) and Willingness-to-Accept (WTA), alongside other cost-effectiveness indicators (ICER, QALY). Methods. A systematic review was conducted on randomized and quasi-experimental evaluations, economic models, and preference studies concerning psychoeducational/coping interventions, activity-centered/occupational programs (TAP), technological solutions and tele-support, and goal-oriented cognitive rehabilitation (CR). For each study, the following indexes were extracted: design, sample size, psychological outcomes (anxiety/depression, burden, engagement), utility per QALY, costs per perspective (the health–social and the broader societal perspectives), ICER, WTP/WTA, and sensitivity results. Results. Psychoeducational programs and CR show consistent benefits on distress, anxiety/depression, and caregiver quality of life; TAP reduces caregiver burden and patient behavioral problems, with favorable signs of cost–effectiveness; results on the effects of technologies are heterogeneous, but online modules with telephone support improve psychological morbidity. QALY improvement is generally modest, but the probability of cost-effectiveness remains high when costs do not differ significantly from treatment as usual, or when, from a societal perspective, the unpaid caregiving time of the caregiver is valued. Preference studies indicate positive WTP for additional hours of home care, health–social integration, and facilitated groups; evidence on WTA is scarcer and methodologically variable. Conclusions. Short, structured interventions with a human support component offer good value-for-money; the adoption of societal perspectives and the systematic use of WTP/WTA can better capture the value perceived by caregivers. Heterogeneity issues persist. Full article

The acceptance of, perceived advantages to, and skepticism toward the integration of artificial intelligence (AI) in undergraduate education is investigated in this paper. In this study, a total of 675 students from six Romanian universities answered a self-administered online questionnaire evaluating three main aspects: AI acceptance, AI benefits, and AI skepticism. While AI skepticism has a modest but substantial negative influence (β = −0.113, p = 0.001), results show that AI benefits favorably predict AI acceptance (β = 0.541, p = 0.001). Whereas AI skepticism negatively correlates with AI acceptance (r = −0.124, p = 0.001), correlational analysis reveals a high positive association between AI acceptance and AI benefits (r = 0.544, p = 0.001). Despite concerns about its limitations, the regression model suggests that students’ willingness to embrace AI in education is mostly driven by its perceived advantages. This explains 30.8% of the variance in AI acceptance (R² = 0.308, F(2, 641) = 142.909, p < 0.001). These results highlight the importance of techniques that improve perceived benefits while addressing uncertainty since they offer insightful analysis of student attitudes regarding artificial intelligence integration in higher education. By guiding policy decisions and educational activities meant to maximize AI-driven learning environments, this study adds to the current conversation on artificial intelligence adoption in education. Full article

The accelerating integration of artificial intelligence (AI) into cybersecurity operations has introduced new challenges and opportunities for modernizing incident response (IR) practices. This study explores how cybersecurity practitioners perceive the adoption of intelligent automation and the readiness of legacy frameworks to address AI-driven threats. A structured, two-part quantitative survey was conducted among 194 U.S.-based professionals, capturing perceptions on operational effectiveness, trust in autonomous systems, and the adequacy of frameworks such as NIST and SANS. Using binary response formats and psychometric validation items, the study quantified views on AI’s role in reducing mean time to detect and respond, willingness to delegate actions to autonomous agents, and the perceived obsolescence of static playbooks. Findings indicate broad support for the modernization of incident response frameworks to better align with emerging AI capabilities and evolving operational demands. The results reveal a clear demand for modular, adaptive frameworks that integrate AI-specific risk models and decision auditability. These insights provide empirical grounding for the design of next-generation IR models and contribute to the strategic discourse on aligning automation capabilities with ethical, scalable, and operationally effective cybersecurity response. Full article

Public trust in artificial intelligence (AI) is often assumed to promote acceptance by reducing perceived risks. Using a nationally representative survey of 10,294 Chinese adults, this study challenges that assumption and introduces the concept of vigilant trust. We argue that trust in AI does not necessarily diminish risk awareness but can coexist with, and even intensify, attention to potential harms. By examining four dimensions of trust—trusting stance, competence, benevolence, and integrity—we find that all of them consistently enhance perceived benefits, which emerge as the strongest predictor of AI acceptance. However, trust shows differentiated relationships with perceived risks: benevolence reduces risk perception, whereas trusting stance is associated with higher perceptions of both benefits and risks. Perceived risks do not uniformly deter acceptance and, in some contexts, are positively associated with willingness to adopt AI. By moving beyond the conventional view of trust as a risk-reduction mechanism, this study conceptualizes vigilant trust as a mode of engagement in which openness to AI is accompanied by sustained awareness of uncertainty. The findings offer a more nuanced understanding of public acceptance of AI and its implications for governance and communication. Full article

Agrivoltaic systems (AVs) combine agricultural production with photovoltaic energy generation, enabling the dual use of land resources. This approach has gained increasing attention as a promising strategy to address pressing social, environmental, and energy challenges. Although the global expansion of AVs is accelerating, empirical research remains limited—particularly regarding farmers’ perspectives on adopting such systems. This study investigates Greek farmers’ perceptions and attitudes toward the adoption of photovoltaic technologies in agricultural practices. For this purpose, a questionnaire-based survey was conducted on a sample of 287 participants selected using purposive convenience sampling, based on predefined inclusion criteria relevant to the objectives of the study. The data were analyzed using a binary logistic regression model to identify factors positively associated with farmers’ willingness to adopt AVs. The findings reveal that 46.3% of farmers expressed willingness to adopt AVs, indicating a moderate level of acceptance. The logistic regression results indicated that higher education levels (OR = 3.53, p = 0.007), membership in farmers’ organizations (OR = 2.00, p = 0.001), and familiarity with agro-energy concepts (OR = 3.49, p = 0.016) significantly increased farmers’ motivation to engage as renewable energy producers. The model demonstrates a moderate level of explanatory power (Nagelkerke R² = 0.37). The study’s findings provide valuable insights into the key factors influencing farmers’ willingness to adopt AVs, contributing to a deeper understanding of the decision-making processes involved. Based on these findings, it is recommended that agricultural policies and community-based renewable energy initiatives focus on targeted education and extension services, the strengthening of farmers’ organizations to facilitate collective decision-making, and the implementation of focused agro-energy information campaigns. Full article

The rapid integration of artificial intelligence (AI) and smart technologies is transforming hospitality operations, yet guest acceptance remains uneven, shaped by utilitarian, experiential, ethical, and cultural evaluations. This study develops and empirically tests a multicomponent framework to explain how these factors jointly influence two behavioral outcomes: whether AI-enabled features affect hotel choice and whether guests are willing to pay a premium. A cross-sectional survey of 689 hotel guests in Tirana, Albania, an emerging hospitality market and rapidly growing tourist destination in the Western Balkans, was analyzed using cumulative link models, partial proportional-odds models, nonlinear and interaction extensions, and binary robustness checks. Results show that prior experience with smart or AI-enabled hotels, higher awareness, and trust in AI, especially trust in responsible data handling, consistently increase both acceptance and willingness to pay. Perceived value, operationalized through the breadth of identified benefits and desired features, also exhibits robust positive effects. In contrast, privacy concerns selectively suppress strong acceptance, particularly financial willingness, while cultural–linguistic fit and support for human–AI collaboration contribute positively but modestly. Interaction analyses indicate that trust can mitigate concerns about reduced personal touch. Open-ended responses reinforce these patterns, highlighting the importance of privacy, human interaction, and staff–AI coexistence. Overall, findings underscore that successful AI adoption in hospitality requires aligning technological innovation with ethical transparency, experiential familiarity, and cultural adaptation. Full article