Search Results (160)

The gap between consumers’ intent to buy electric cars and their actual purchasing behaviour of petrol cars has motivated researchers to conduct numerous investigations over the last decade. Nevertheless, with the explosive development of the field, bibliographic mapping remains a difficult task. This study combines bibliometric analysis and a PRISMA-oriented systematic review of consumer purchase intentions towards sustainable vehicles. A systematic literature search in Scopus retrieved 1447 records between 2015 and June 2026, of which 706 empirical studies met the inclusion criteria for qualitative synthesis. Based on performance analysis and science mapping using VOS viewer software, one can conclude that the topic area develops at around 23%, gathers 43,758 citations, and shifts geographically over time. China contributes 418 papers, and India goes from publishing one piece in 2015 to occupying the third position overall. Keywords co-occurrence identifies five research clusters, whereas co-citations show that there are three intellectual bases for the field: behavioural theory, choice modelling, and methodological approaches based on the PLS-SEM framework. The results also emphasize some recurring gaps, namely the lack of a moderating effect of demographic characteristics, personality traits, intention-to-behaviour relationship, and longitudinal surveys. This study proposes an eight-point research agenda driven by keyword analysis. Full article

Hydrogel-enabled adoptive cell therapy (ACT) offers a localized and controllable strategy for improving cellular immunotherapy in solid tumors. Hydrogels can enhance cell retention and persistence, support immune cell function within the tumor microenvironment, and reduce systemic toxicity associated with broadly delivered immune stimulants. However, delivery of living immune cells imposes practical constraints on hydrogel selection, including cytocompatible encapsulation, minimal handling and injection stress, adequate transport of oxygen and soluble cues, and an appropriate balance between local retention and timely cell egress. This review summarizes natural, synthetic, and hybrid hydrogel platforms and compares physical/supramolecular assembly, covalent and enzymatic crosslinking, and photo-crosslinking. Injectable in situ-forming depots and shear-thinning/self-healing gels are highlighted for locoregional administration. Key design and reporting dimensions of hydrogels are linked to immune cell outcomes relevant to ACT. These properties include mechanics and viscoelasticity, porosity and mass transport, degradability and remodeling, bioadhesion and extracellular matrix (ECM) mimicry, and immunogenicity versus immune shielding. Finally, a cell-type-tailored framework is presented for chimeric antigen receptor T (CAR-T), T cell receptor-engineered T (TCR-T), and tumor-infiltrating lymphocyte (TIL) products, natural killer (NK) cells, and dendritic cells (DCs) or macrophage/monocyte-derived effectors. Distinct biological requirements are used to motivate corresponding material architectures and cue presentation strategies. The review also provides quantitative reporting guidance, identifies evidence gaps for γδ T cells, and discusses in vivo validation, combination ACT strategies, and translational handling constraints. Full article

Economically motivated adulteration (EMA) of high-value geographical indication (GI) food ingredients poses serious risks to consumer trust and food safety. Rubus chingii Hu (RcH), a GI-designated edible-medicinal fruit originating from Dexing, is susceptible to adulteration with cheaper non-GI sources. This study developed a rapid, non-destructive near-infrared (NIR) spectroscopy approach combined with chemometric modeling for adulteration identification and ratio prediction of GI RcH. Two-dimensional correlation spectroscopy (2D-COS) using adulteration ratio as an external perturbation identified the 4200–6000 cm⁻¹ region as the most sensitive spectral window, mainly reflecting changes in proteins, lipids, and carbohydrates. Using this 2D-COS-guided interval, we systematically compared four discriminant models (PLS-DA, SVM-DA, RF-DA, BPNN-DA) under ten preprocessing strategies. SNV + Smo-BPNN-DA achieved 100% test accuracy, while 1st D-RF-DA also showed excellent generalization (A_tes = 99.67%). For adulteration ratio prediction, wavenumber selection (CARS, IWOA) significantly improved Raw-SVR performance (R² from 59.8% to 78.6%) but provided no benefit—and sometimes degraded accuracy—for PLS, RF, and BPNN models, revealing a model-dependent effect rarely reported in food adulteration studies. The optimal regression model was SNV-BPNN-R (R² = 96.96%); for computationally constrained scenarios, CARS + IWOA-2nd D-RF-R is recommended (R² ≈ 95.93% with only 20–40 variables). Our findings provide a practical, physically interpretable, and transferable strategy for rapid EMA screening of powder-based GI food products, supporting on-site or online food authenticity control. Full article

Battery electric vehicle (BEV) adoption does not always result in long-term ownership, because some owners may return to internal combustion engine vehicles after purchase. This study examines how internal customer factors influence the formation of product attachment, an emotional bond between owners and their BEVs. This issue is important because such attachment may support long-term commitment, expressed through advocacy and loyalty after adoption. The study focuses on instrumental, affective, and symbolic car use motivation, customer innovativeness, and direct experience. Data were collected through face-to-face surveys with 392 Indonesian BEV owners who had driven their vehicles for more than 5000 km. ANOVA and PLS-SEM were used to examine segment differences and test the structural model. Affective motivation had the largest positive path coefficient for product attachment (β = 0.451), followed by symbolic motivation (β = 0.370), direct experience (β = 0.301), and instrumental motivation (β = 0.229). Customer innovativeness was not significant (β = −0.026, p = 0.324). Product attachment showed strong relationships with customer advocacy (β = 0.649) and loyalty (β = 0.686). This study extends the product attachment literature by explaining how internal customer factors are related to the development of product attachment and the extent to which owners become attached to their BEVs. Full article

Background: Pancreatic ductal adenocarcinoma (PDAC) exhibits high post-resection relapse and early systemic dissemination rates. The level of circulating tumor cells (CTCs) correlates with early metastatic failure, motivating CTC interception strategies. Methods: In this hypothesis-driven review, we synthesized the contemporary evidence on PDAC staging and therapy, CTC detection (including portal versus peripheral sampling), and circulating tumor DNA (ctDNA)-based minimal residual disease (MRD), and evaluated the translational rationale for CTC-targeted adoptive immunotherapy focusing on CEACAM6 and CAR-T cells. Results: Prospective studies report higher portal versus peripheral CTC yields and stronger associations with relapse; tumor-informed ctDNA positivity in peri-operative and surveillance windows predicts shorter disease-free survival. CEACAM6 is overexpressed in PDAC and linked to invasion and metastasis, supporting antigen selection. However, target overexpression alone does not establish clinical suitability for adoptive cell transfer. Consequently, its therapeutic implementation must contend with assay heterogeneity, on-target/off-tumor risks, and the lack of interventional outcome data in PDAC, all of which remain key hurdles. Conclusions: CTC-targeting is biologically plausible and operationally measurable in PDAC. Consequently, a CEACAM6-directed CAR-T approach is proposed as a potential strategy for the interception of minimal residual disease (MRD). Randomized and biomarker-selected trials with composite MRD-clearance endpoints (CTC < LOQ and ctDNA-negative) may be justified to validate this interventional hypothesis. Full article

Public transport is a critical instrument for mitigating traffic congestion, reducing environmental pollution, and promoting social inclusion in urban areas. This study presents the results of a quantitative survey conducted among 406 residents of Łódź, Poland, aimed at identifying the determinants of public transport use and the factors influencing modal choices. The findings indicate that 89% of respondents had used public transport within the past three years, with over half reporting the use of both buses and trams. However, public transport is predominantly chosen out of necessity rather than preference, driven by limited access to private vehicles, absence of a driver’s license, or the high costs of car ownership. Environmental considerations and service quality factors play a comparatively minor role. User satisfaction with public transport services in Łódź is moderate, and current users express limited intention to increase their usage or actively recommend the system, suggesting constrained potential for demand growth. In contrast, non-users declare a willingness to shift to public transport if travel costs are reduced and service quality is improved. Measures aimed at restricting private car use demonstrate limited motivational impact, whereas enhancing the reliability, accessibility, and affordability of public transport emerges as the most effective strategy. Methodologically, the study contributes by combining bibliometric mapping with quantitative survey analysis, providing a replicable framework for assessing urban mobility determinants in other cities with similar socio-economic and transport contexts. Full article

Chinese users possess unique service experiences and behavioural intentions for utilising car-sharing. Car-sharing services offer a variety of competitive car-sharing options and possess distinctive traits that merit exploration. This mixed methods study examines the factors influencing repurchase intention in China’s car-sharing market by combining qualitative insights with quantitative validation. Utilising the theory of planned behaviour and the technology acceptance model, we propose a framework wherein perceived ease of use, price consciousness, perceived security, perceived consumer effectiveness, and environmental concern directly affect repurchase intention, with service quality and perceived usefulness acting as essential mediators. Qualitative studies from 12 in-depth interviews indicate that user experiences are influenced by multifaceted convenience, pricing transparency, risk perception, and contextual usage patterns. A later quantitative analysis of 416 car-sharing service users was conducted utilising PLS-SEM. The findings indicate that perceived usefulness (β = 0.272, p < 0.001) is the most significant direct predictor of repurchase intention, followed by perceived security (β = 0.209) and environmental concern (β = 0.195). Service quality exerts a significant full mediating effect on the influence of perceived ease of use, and perceived security has a mediating effect on perceived usefulness (the direct effects of perceived ease of use and perceived security on perceived usefulness are not significant after including service quality as a mediator). The qualitative phase involved participants from eight major Chinese cities (Beijing, Shanghai, Guangzhou, Shenzhen, Dongguan, Wuhan, Changsha, and Zhengzhou), while the quantitative survey covered over 20 cities (including first-tier, new first-tier, and prefecture-level cities) via the Credamo platform, ensuring broad geographic representation. Significantly, price-quality beliefs do not substantially influence repurchase intention. This study contributes to the literature on the sharing economy by integrating technology, trust, and sustainability factors, providing practical recommendations for platform operators seeking to improve client retention in China’s competitive mobility sector. Full article

Road transport is a significant contributor to greenhouse gas emissions within the European Union, with Poland showing one of the most pronounced increases since 1990. Motivated by gaps in national inventories (absence of vehicle-level mileage, limited fuel/age/spatial breakdowns, and scarce real-world hybrid performance data), we develop a novel vehicle-level integration method that links administrative vehicle records with scraped online car-sale listings via deterministic and probabilistic record linkage, imputes missing mileage, and applies age- and fuel type-adjusted emission multipliers to estimate per-vehicle emissions. The approach produces high-resolution breakdowns by fuel type, vehicle age and spatial units while explicitly accounting for hybrid vehicle behavior. This study introduces a novel methodology and analytical product that can be used to estimate emissions from the entire Polish passenger car fleet and monitor decarbonization progress. Applying this method to the Polish passenger-car fleet yields total 2024 passenger-car CO₂ emissions of ≈41.4 million tonnes (our estimate aligns closely with independent national figures), with diesel, gasoline and LPG/CNG accounting for roughly 38%, 47% and 12% of CO₂, respectively. We find that hybrids and EVs currently cut fleet emissions by ~2.6% (CO₂), but their higher utilization magnifies their effect, while vehicle ageing increases total emissions by ~1.2% per year. These results demonstrate that integrating microdata substantially improves the monitoring of decarbonization progress. Full article

Fully integrated airport access requires managing many aspects from both the passengers’ and the operational point of view. It is noted that air passenger preferences, influenced by distance, time, and other travel-related factors, are one of the fundamentals for understanding airport choice within multi-region airport systems. Therefore, an online survey was conducted in Europe, collecting more than two thousand responses, from which passengers’ attitudes and motives for selecting airport access travel modes were obtained. On the basis of the mobility profile of respondents, Fuzzy C-means (FCM) clustering analysis was performed to identify segments with similar travel attributes. The outcomes of clustering were validated through the comparison between the FCM and K-means clustering algorithms. The results of the study showed that (i) the car was the most preferred mode of transport across different age groups, and (ii) waiting time, travel costs, and travel time were rated as important, with reliability identified as the most important factor when making travel mode choices. These findings may serve as a reference for improving multimodal airport access services and encouraging a shift from private to public transportation modes. Full article

With the acceleration of urbanization and the continuous rise in private car ownership, urban traffic congestion has become a critical issue constraining sustainable development. As an important extension of carbon reduction policies, the personal carbon trading mechanism provides a new approach to regulate travel behavior through economic incentives. This study constructs a game model incorporating stakeholders from both government and private car owners, explores their decision-making behaviors under the personal carbon trading mechanism, and conducts simulation analysis of evolutionary paths using MATLAB 2019a. The findings reveal that choosing public transportation results from interactive strategic interactions between government and private car owners. Proactive implementation of personal carbon trading policies by the government can accelerate private car owners’ adoption of public transportation strategies. Reducing government implementation costs of personal carbon trading (PCT), increasing carbon trading costs for private cars (through higher carbon prices or lower allowances), and improving public transit comfort are key factors in achieving equilibrium between government and private car owners’ strategies. Carbon trading costs exhibit differentiated impacts on the convergence speed of both parties’ states. This research aims to provide decision-making references for governments in formulating and implementing personal carbon trading systems, as well as motivating private car owners to adopt green and environmentally friendly travel behaviors. Full article

With the advancement of sensing, communication, and cooperative capabilities of connected automated vehicles (CAVs), the capacity and operational state of signalized intersections have become increasingly observable and suitable for prospective assessment. However, existing capacity models based on homogeneous traffic assumptions are insufficient to describe the capacity evolution of mixed traffic under varying CAV penetration levels. Motivated by this limitation, this study proposes a quantitative capacity estimation method for signalized intersections considering CAV penetration, serving as an evaluation and prediction baseline for intersection operations. The proposed method improves the CAV gain parameter and accounts for multiple typical car-following states in mixed traffic to derive equivalent headways and spacing coefficients, enabling a continuous estimation of intersection capacity with respect to CAV penetration. Using data from an actual signalized intersection, capacity and saturation trends are analyzed across different movement directions and traffic demand conditions. The results indicate a nonlinear increasing pattern of intersection capacity as CAV penetration rises, with distinct growth rates between straight-through and left-turn movements. The proposed approach provides an engineering-oriented reference for capacity estimation and traffic state prediction under mixed traffic conditions. Full article

Worldwide the adoption of electric vehicles (EVs) is recognized as a key strategy for reducing transport-related greenhouse gas (GHG) emissions, a major contributor to global warming and climate change. The objective of this pilot study is to examine the key variables that might have influenced electric vehicle (EV) purchase decisions among current EV owners and how they are aligned or different for the prospective EV owners in North Carolina (NC). By adopting a web-based survey for data collection, the study specifically aims to identify economic, demographic, environmental, and commuting behaviors, along with existing government policies and incentives that might motivate consumer choices regarding EV adoption. Most existing EV owners who participated in the survey identified themselves as college-educated White men with USD 100 K or higher income, have more than two cars, commute more than 30 min, and live in single-family homes with EV charging. In contrast, among non-EV owners who plan to adopt an EV within the next three years, a significant proportion are non-White, women, and earn USD 50,000 or less annually. While home charging is important to both current EV owners and non-EV owners, EV incentive policies and proximity to public changing stations are found to be more important to non-EV owners’ decision to adopt EVs. A reasonable conclusion from this research is that expanding EV-friendly policies, incentives, and infrastructure will encourage first-time EV ownership in NC while providing deeper insights into the dynamics of sociodemographic among both EV owners and non-EV owners. Full article

Objectives: Traffic accidents cause severe social and economic impacts, demanding fast and reliable detection to minimize secondary collisions and improve emergency response. However, existing cloud-dependent detection systems often suffer from high latency and limited scalability, motivating the need for an edge-centric and consensus-free accident detection framework in IoV environments. Methods: This study presents a real-time accident detection framework tailored for Internet of Vehicles (IoV) environments. The proposed system forms an integrated IoV architecture combining on-vehicle inference, RSU-based validation, and asynchronous cloud reporting. The system integrates a lightweight ensemble of Vision Transformer (ViT) and EfficientNet models deployed on vehicle nodes to classify video frames. Accident alerts are generated only when both models agree (vehicle-level ensemble consensus), ensuring high precision. These alerts are transmitted to nearby Road Side Units (RSUs), which validate the events and broadcast safety messages without requiring inter-vehicle or inter-RSU consensus. Structured reports are also forwarded asynchronously to the cloud for long-term model retraining and risk analysis. Results: Evaluated on the CarCrash and CADP datasets, the framework achieves an F1-score of 0.96 with average decision latency below 60 ms, corresponding to an overall accuracy of 98.65% and demonstrating measurable improvement over single-model baselines. Conclusions: By combining on-vehicle inference, edge-based validation, and optional cloud integration, the proposed architecture offers both immediate responsiveness and adaptability, contrasting with traditional cloud-dependent approaches. Full article

The production and sales figures for electric vehicles are showing a steady upward trend, clearly indicating the growing importance of sustainability goals. A unique historical situation has developed in the US: the owner of the leading electric car manufacturer (Tesla), Elon Musk, has taken an active role in political life. Amid a rising trend in electric vehicle (EV) adoption aligned with global sustainability goals, the political activism of Musk has provoked public backlash, including acts of vandalism and aggression toward Tesla vehicles. Using a multidisciplinary approach, the study explores (1) the psychological underpinnings of object-directed violence, (2) the legal classification of politically motivated vandalism, and (3) the broader market implications of corporate politicization. Our findings confirm that object-directed aggression stems from displaced frustration, especially when individuals feel politically powerless or morally outraged. Our analysis revealed that most Tesla-related vandalism will likely be prosecuted as property crimes. Although U.S. officials have labeled some acts as domestic terrorism or hate crimes, legal thresholds are generally not met. Our interdisciplinary model suggests that the politicization of Tesla has broader implications. Tesla’s symbolic status in the electric vehicle market means that attacks on it risk triggering a decline in public trust toward electric mobility. Full article

The study analyzes pro-environmental attitudes and behaviors of residents in the mountainous regions of Małopolska regarding energy saving and transportation. The main objective was to determine the extent to which environmental awareness, vehicle technical condition, and driving style translate into actual energy-efficient behaviors. The research was conducted using a quantitative method among 423 respondents from six mountain districts of Małopolska, based on a proprietary questionnaire and statistical analysis employing non-parametric tests, correlation coefficients, and principal component analysis. The results indicate that respondents most frequently declare simple pro-environmental actions such as waste segregation and energy saving, while less often engaging in activities requiring higher effort or investment, such as eco-driving or limiting car use. Women exhibit higher environmental sensitivity and greater support for ecological regulations, whereas men tend to focus on the technical aspects of vehicle maintenance. The most pro-environmental attitudes and motivations to switch to low-emission vehicles are observed among individuals aged 25–44. The findings confirm that demographic factors significantly differentiate eco–energy-saving orientations, and that environmentally friendly transport behaviors are closely linked to everyday energy-saving practices. Full article