Search Results (4,235)

The logistics industry faces challenges from evolving consumer expectations, technological advances, sustainability demands, and market disruptions. Logistics collaboration is in theory perceived as one of the most promising solutions to solve these issues, but here are still a lot of challenges that needs to be better understood and addressed. While vertical collaboration among supply chain actors is well advanced, horizontal collaboration among competing service providers remains under-explored. This study developed a novel methodology based on the COM-B behaviour-change framework to better understand the main challenges, opportunities, capabilities and drivers that would motivate competing companies to exploit the potential of horizontal logistics collaboration. A survey was designed and conducted among 71 logistics service providers in Slovenia, chosen for its fragmented market and low willingness to collaborate. Statistical analysis reveals cost reduction (M = 4.21/5) and improved vehicle utilization (M = 4.29/5) as the primary motivators. On the other hand, maintaining company reputation (M = 4.64/5), fair resource sharing (M = 4.20/5), and transparency of logistics processes (M = 4.17/5) all persist as key enabling conditions. These findings underscore the pivotal role of behavioural drivers and suggest strategies that combine economic incentives with targeted trust-building measures. Future research should employ experimental designs in diverse national contexts and integrate vertical–horizontal approaches to validate causal pathways and advance theory. Full article

Understanding the carbon emissions of multimodal travel—comprising walking, metro, bus, cycling, and ride-hailing—is essential for promoting sustainable urban mobility. However, most existing studies focus on single-mode travel, while underlying spatiotemporal and behavioral determinants remain insufficiently explored due to the lack of fine-grained data and interpretable analytical frameworks. This study proposes a novel integration of high-frequency, real-world mobility trajectory data with interpretable machine learning to systematically identify the key drivers of carbon emissions at the individual trip level. Firstly, multimodal travel chains are reconstructed using continuous GPS trajectory data collected in Beijing. Secondly, a model based on Calculate Emissions from Road Transport (COPERT) is developed to quantify trip-level CO₂ emissions. Thirdly, four interpretable machine learning models based on gradient boosting—XGBoost, GBDT, LightGBM, and CatBoost—are trained using transportation and built environment features to model the relationship between CO₂ emissions and a set of explanatory variables; finally, Shapley Additive exPlanations (SHAP) and partial dependence plots (PDPs) are used to interpret the model outputs, revealing key determinants and their non-linear interaction effects. The results show that transportation-related features account for 75.1% of the explained variance in emissions, with bus usage being the most influential single factor (contributing 22.6%). Built environment features explain the remaining 24.9%. The PDP analysis reveals that substantial emission reductions occur only when the shares of bus, metro, and cycling surpass threshold levels of approximately 40%, 40%, and 30%, respectively. Additionally, travel carbon emissions are minimized when trip origins and destinations are located within a 10 to 11 km radius of the central business district (CBD). This study advances the field by establishing a scalable, interpretable, and behaviorally grounded framework to assess carbon emissions from multimodal travel, providing actionable insights for low-carbon transport planning and policy design. Full article

Public–private partnership (PPP) logistics infrastructure projects have become increasingly prevalent globally. Consequently, the effective management of these projects as their concession periods expire presents a crucial challenge for governments, vital for the sustainable management of PPP logistics infrastructure. This study addresses this challenge by focusing on the pivotal post-concession decision: whether the government should self-operate the mature logistics infrastructure or re-delegate its management to a private entity. Our theoretical model, built on a principal–agent framework, first establishes a social welfare baseline under government self-operation and then analyzes delegated operation under symmetric information, identifying efficiency frontiers. Under symmetric information, we find that government self-operation is more advantageous when its own operational efficiency is sufficiently high, irrespective of the private enterprise’s efficiency; conversely, delegating to an efficient private enterprise is optimal only when government operational efficiency is low. We also demonstrate that if the government can directly specify the demand quantity and service level and delegates operation via a fixed fee, the enterprise can be incentivized to align with the social optimum. However, under asymmetric information, potential welfare gains from delegation are inevitably offset by informational rent and output distortion. We further uncover non-monotonic impacts of parameters like the proportion of low-cost firms on social welfare loss and demonstrate how information asymmetry can indirectly compromise the long-term resilience of the infrastructure. Ultimately, our work asserts that delegation is only superior if its potential efficiency gains sufficiently offset the inherent losses stemming from information asymmetry. Full article

To ensure stability and transparency in the European logistics sector, in May 2017, the European Commission presented several proposals to change the regulation of the market—in particular, market access, driving and rest periods, and business trips. In the development of this package, several unfavourable decisions were made that go against Lithuanian transport companies, which will have a significant impact on the companies’ finances, as the frequent return of trucks will lead to additional fuel costs and is also in contradiction with the concept of green logistics. Thus, it is essential to study the Mobility Package’s pros and cons and compare researchers’ views. Accordingly, the subject of this article is the impact of the Mobility Package on Lithuanian logistics companies. This article employs various methods, including an analysis of the scientific literature and legislation, statistical data analysis, PEST analysis, and qualitative research based on expert interviews. The results allow us to identify that the content of the Mobility Package is driven by the goal of ensuring equivalent working conditions throughout the EU, which in this case is the most important object of the legal changes. Also, based on the results obtained, it can be stated that Lithuanian logistics companies that want to remain in the market have several solutions they can employ to achieve that goal, and to support their efforts, a competitiveness improvement model for Lithuanian logistics companies has been developed. Full article

This research examines the traffic disruptions resulting from the collapse of the Francis Scott Key Bridge in Baltimore, utilizing advanced econometric methods and real-time ClearGuide data. Employing Fixed Effects (FEs), Mixed Effects (MEs), Difference-in-Differences (DiDs), and stratified regression models, the study uniquely examines the impacts of congestion across Immediate, Fall, and Winter periods, distinctly separating AM and PM peak patterns. Significant findings include severe PM peak congestion, up to four times greater than AM peak congestion, particularly on critical corridors such as the Harbor Tunnel Thruway northbound and MD-295 northbound. Initial route-level impacts were heterogeneous, gradually becoming uniform as the network adapted. The causal DiD analysis provides strong evidence that increased congestion is causally linked to proximity to the collapse. It is anticipated that incorporating the suggested framework will yield insightful information for stakeholders and decision-makers, such as targeted freight restriction, peak-hour dynamic pricing, corridor-specific signal adjustments, and investments in real-time traffic monitoring systems to strengthen transportation network resilience. Full article

This study examines the safety and cost-effectiveness of implementing shoulder rumble strips (SRS) and road lighting on Saudi Arabian freeways, providing insights into their roles in fostering sustainable transport systems. By leveraging the Highway Safety Manual (HSM) framework, this research develops localized Crash Modification Factors (CMFs) for these interventions, ensuring evidence-based and context-specific evaluations. Data were collected for two periods—pre-pandemic (2017–2019) and post-pandemic (2021–2022). For each period, we obtained traffic crash records from the Saudi Highway Patrol database, traffic volume data from the Ministry of Transport and Logistic Services’ automated count stations, and roadway characteristics and pavement-condition metrics from the National Road Safety Center. The findings reveal that SRS reduces fatal and injury run-off-road crashes by 52.7% (CMF = 0.473) with a benefit–cost ratio of 14.12, highlighting their high cost-effectiveness. Road lighting, focused on nighttime crash reduction, decreases such crashes by 24% (CMF = 0.760), with a benefit–cost ratio of 1.25, although the adoption of solar-powered lighting systems offers potential for greater sustainability gains and a higher benefit–cost ratio. These interventions align with global sustainability goals by enhancing road safety, reducing the socio-economic burden of crashes, and promoting the integration of green technologies. This study not only provides actionable insights for achieving KSA Vision 2030’s target of improved road safety but also demonstrates how engineering solutions can be harmonized with sustainability objectives to advance equitable, efficient, and environmentally responsible transportation systems. Full article

The COVID-19 pandemic has highlighted critical vulnerabilities in urban logistics systems, particularly in last-mile delivery. To enhance logistics resilience and efficiency, the Korean government has initiated an innovative project that repurposes idle spaces in subway vehicle bases within the Seoul Metropolitan Area into logistics centers. This study proposes a comprehensive multi-criteria evaluation framework combining the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to assess the suitability of ten candidate sites. The evaluation criteria span four dimensions, facility, geographical, environmental, and social factors, derived from the literature and expert consultations. AHP results indicate that geographical factors, especially proximity to urban centers and major logistics facilities, hold the highest weight. Based on the integrated analysis using TOPSIS, the most suitable locations identified are Sinnae, Godeok, and Cheonwang. The findings suggest the strategic importance of aligning infrastructure development with spatial accessibility and stakeholder cooperation. Policy implications include the need for targeted investment, public–private collaboration, and sustainable logistics planning. Future research is encouraged to incorporate dynamic data and consider social equity and environmental impact for long-term urban logistics planning. Full article

Quality requirements for mineral aggregate for concrete used to construct pavement for busy highways are high because of the fatigue traffic loads and environmental exposure. The use of local aggregate for infrastructure projects could result in important sustainability improvements, provided that the concrete’s durability is assured. The objective of this study was to identify the potential alkaline reactivity of local greywacke aggregate and select appropriate mitigation measures against the alkali–silica reaction. Experimental tests on concrete specimens were performed using the miniature concrete prism test at 60 °C. Mixtures of coarse greywacke aggregate up to 12.5 mm with natural fine aggregate of different potential reactivity were evaluated in respect to the expansion, compressive strength, and elastic modulus of the concrete. Two preventive measures were studied—the use of metakaolin and slag-blended cement. A moderate reactivity potential of the greywacke aggregate was found, and the influence of reactive quartz sand on the expansion and instability of the mechanical properties of concrete was evaluated. Both crystalline and amorphous alkali–silica reaction products were detected in the cracks of the greywacke aggregate. Efficient expansion mitigation was obtained for the replacement of 15% of Portland cement by metakaolin or the use of CEM III/A cement with the slag content of 52%, even if greywacke aggregate was blended with moderately reactive quartz sand. It resulted in a relative reduction in expansion by 85–96%. The elastic modulus deterioration was less than 10%, confirming an increased stability of the elastic properties of concrete. Full article

Ports in the Baltic Sea region play an integral role in advancing sustainable maritime practices in the area, due to their geographic interconnectedness, economic importance, and sensitivity to environmental challenges. While numerous port sustainability assessment methods exist, most of which are grounded in the Triple Bottom Line (TBL) metric, many tend to emphasise whether specific targets have been met, rather than evaluating port sustainability on a scalar basis. This study explores the sustainability strategies of seven selected ports in five Baltic Sea countries using an innovative qualitative evaluation framework developed by the Swedish Maritime Competence Centre (SMCC). The SMCC model integrates the three core pillars of sustainability-environmental, social, and economic dimensions, while incorporating energy efficiency and digitalisation as critical enablers of modern port operations. The findings reveal significant variation in sustainability performance among the selected ports, shaped by regional contexts, operational profiles, and prior engagement with sustainability initiatives. Also, the results bring into light the most common sustainable practices used in the ports, e.g., LED lightning, onshore power supply, and port information systems. Full article

(1) Background: The number of casualties due to car accidents in Europe is decreasing. However, there are still very large differences in the levels of road safety between countries, even within the European Union. Therefore, it is vital to conduct reliable international analyses to compare the effectiveness of actions taken to prevent road accidents. Information on the number of accidents, injuries, and fatalities can be found in various databases (e.g., Eurostat or OECD). In this paper, it is clearly shown that data on car accidents and the resulting injuries are not comparable between different countries, and any conclusions drawn using these data as their basis will be erroneous. (2) Methods: The indicators of the number of car accidents, injured people, and fatalities in relation to the number of inhabitants were determined, then their distribution and mutual correlations were examined for a group of selected European countries. (3) Results: There is no correlation between the indicators of the number of car accidents and injuries and the indicator of fatalities. An assessment of road safety based on these indicators would result in inconsistent and ambiguous conclusions. (4) Conclusions: It has been empirically shown that data on the number of car accidents and injured people from different countries are not comparable. These conclusions were verified by providing examples of the definitions of an injured person used in different countries. This paper clearly indicates that any international comparisons can only be made based on data regarding the number of road accident fatalities. Full article

This study investigates public perceptions of sustainable mobility within university environments, which are important trip generation hubs with the potential to influence and disseminate sustainable mobility behaviors. Using sentiment analysis on 120,236 tweets from São Paulo, Rio de Janeiro, Lisbon, and Porto, tweets were classified into positive, neutral, and negative sentiments to assess perceptions across transport modes. It was hypothesized that universities would exhibit more positive sentiment toward active and public transport modes compared to perceptions of these modes within the broader city environment. Results show that active modes and public transport consistently receive higher positive sentiment rates than individual motorized modes, and, considering the analyzed contexts, universities demonstrate either similar (São Paulo) or more positive perceptions compared to the overall sentiment observed in the city (Rio de Janeiro, Lisbon, and Porto). Chi-square tests confirmed significant associations between transport mode and sentiment distribution. An exploratory analysis using topic modeling revealed that perceptions around bicycle use are linked to themes of safety, cycling infrastructure, and bike sharing. The findings highlight opportunities to promote sustainable mobility in universities by leveraging user sentiment while acknowledging limitations such as demographic bias in social media data and potential misclassification. This study advances data-driven methods to support targeted strategies for increasing active and public transport in university settings. Full article

Under the impetus of digital rural development and the rapid advancement of smart logistics, intelligent terminal delivery technologies are gradually expanding into rural areas. This study employs a three-phase mixed research approach to systematically investigate the factors influencing and mechanisms underlying rural residents’ willingness to adopt smart logistics in Hebei Province. In the first phase, grounded theory is employed to identify seven key perceived factors: perceived usefulness, perceived ease of use, sensitivity to collective evaluation, cultural conservatism, infrastructure quality, facilitating conditions, and technological trust. In the second phase, integrating the TAM and the UTAUT, this study incorporates context-specific variables and conducts empirical analysis using SEM and the bootstrap method on 451 valid questionnaire responses. The results indicate that all factors except infrastructure quality significantly influence adoption willingness, with cultural conservatism exerting a negative effect. In the third phase, fsQCA is applied to identify eight configurations that lead to high adoption willingness, further supplementing and enriching the explanatory power of the SEM results. This research expands the theoretical understanding of smart logistics technology adoption mechanisms in rural areas and offers practical guidance for the promotion and application of related technologies. Full article

The relationship between economic progress and environmental quality remains a central focus in global sustainability discourse. This study examines the link between per capita economic growth and CO₂ emissions across 128 countries from 1996 to 2022, controlling for energy consumption, trade volume, and foreign direct investment (FDI) inflows. It also evaluates the role of governance quality—measured by regulatory quality and its volatility—while considering the globalization index as a confounding factor influencing CO₂ emissions. We test the Environmental Kuznets Curve (EKC) hypothesis, which suggests that emissions initially rise with income but decline after reaching a certain economic threshold. Our findings confirm the global presence of the EKC. The analysis further shows that trade openness, governance, and globalization significantly influence FDI inflows, with FDI, in turn, reinforcing institutional quality through improved governance and globalization indicators. However, in countries with weaker governance and regulatory frameworks, FDI tends to promote pollution-intensive industrial growth, lending support to aspects of the Pollution Haven Hypothesis (PHH). We find a significant departure in EKC explained by post-COVID governance and globalization compromises, which induced the environment towards the PHH phenomenon. These results highlight the need for context-specific policy measures that align economic development with environmental constraints. Full article

Promoting behavioral change in mobility is essential for sustainable urban development. This study evaluates the effectiveness of gamified challenges in fostering sustainable travel behaviors among high school students and teachers within the High School Challenge (HSC) 2024 campaign in Lecco, Italy. Over a 13-week period, participants tracked their commuting habits via gamified mobile application, Play&Go, that awarded points for sustainable mobility choices and introduced weekly challenges. Using behavioral (GPS-based tracking) and self-report data, we assessed the influence of challenge types, player characteristics (HEXAD Player Types, Big Five traits), and user experience evaluations on participation, retention, and behavior change. The results show that challenges, particularly those based on walking distances and framed as intra-team goals, significantly enhanced user engagement and contributed to improved mobility behaviors during participants’ free time. Compared to the 2023 edition without challenges, the 2024 campaign achieved better retention. HEXAD Player Types were more predictive of user appreciation than Personality Traits, though these effects were more evident in subjective evaluations than actual behavior. Overall, findings highlight the importance of tailoring gamified interventions to users’ motivational profiles and structuring challenges around SMART principles. This study contributes to the design of behaviorally informed, scalable solutions for sustainable mobility transitions. Full article

Introduction. Road safety issues occupy scientists around the world. This study is aimed at creating a comprehensive digital model that will become a tool for developing recommendations for improving road safety in the regions of the Russian Federation. Methods. The assessment of the current state of road safety in the regions of Russia was carried out by means of rating. The object of the study was studied using econometric models, machine learning models, and system dynamics; sensitivity analysis and a balanced scorecard were used. Results. The regions of Russia were divided into three groups according to the level of safety. The econometric model and machine learning model made it possible to assess the influence of independent variables on dependent variables. The identified interrelations formed the basis of a system dynamics model. It was concluded that it is possible to extrapolate the results to groups of regions. For each group of regions, recommendations are given on the formation of a strategy for improving road safety. Conclusions. The practical significance of the study lies in the creation of a tool for the formation of recommendations for the creation of a strategy for improving road safety in the regions of the Russian Federation. Full article