Sustainable Transport Development Research Articles

Trans-Caspian International Transport Route: Kazakhstani Perspective on Challenges, Opportunities, and Prospects

The sustainable development of transport and logistics systems and projects is one factor for the successful development of states and an indicator of integration processes in certain regions, including Central Asia. This study is devoted to the analysis of some aspects of the diversification of the external transport and logistics infrastructure; namely, an assessment of the potential of the Trans-Caspian International Transport Route (TITR) from the perspective of the Republic of Kazakhstan. While the route is useful for trade in multiple sectors, this paper will focus on the shipment of petroleum products via the TITR. Despite the absence of restrictions on the transit of goods to Europe through Russia, there are serious challenges to increasing the delivery time. The development of transport and logistics infrastructure is also relevant for Kazakhstan in the context of its new foreign policy role in the international arena to strengthen interregional cooperation. This requires serious attention and research into potentially promising routes. One of these routes is the TITR. Its development can significantly strengthen the economic position of Kazakhstan and strengthen its diplomatic potential. Along with this, there are several challenges and difficulties that need to be analyzed and overcome.

Vehicle pricing considering EVs promotion and public transportation investment under governmental policies on sustainable transportation development: The case of Norway

The present research investigates the advancement of sustainable transportation by promoting electric vehicles, expanding public transit, and implementing tax increases on fossil fuels and automobiles, via crucial strategies. The present study has examined a market with a fossil fuel vehicle (FFV) manufacturer, an electric vehicle manufacturer, and the government. The manufacturers' pricing strategies are geared towards optimizing profits, whereas the government's objectives for transportation are centered on attaining sustainability across economic, environmental, and social dimensions. The government has considered two strategies, one taxation-based and the other non-taxation-based, to achieve its objectives. In the taxation-based strategy, fixed taxes on fossil-fuel vehicles and fossil fuels are considered, while in the non-taxation-based strategy, subsidies for purchasing electric vehicles and the number of buses purchased for public transportation are predefined. Based on this, eight scenarios with different values for the predefined factors of each strategy have been defined to attain their respective objectives. Game theory has been utilized to determine an optimal solution based on Norwegian data, owing to the interconnected decision-making among stakeholders. By analyzing the findings, managers can enhance their decision-making capabilities. The results suggest that appropriately adjusting subsidies, taxes, and bus numbers within specific thresholds is crucial for mitigating air pollution and achieving other objectives. The assertion that electric cars are a definitive solution may not be accurate, as it depends on the source of the generated electricity. While excessive subsidies in non-renewable energy countries can lead to increased pollution, even in Norway, where most electricity is renewable, rising demand for electric vehicles contributes to air pollution due to increased production. In countries where electricity generation is not primarily from renewable resources, the growth of electric vehicles further exacerbates pollution.Simultaneous increases in fuel taxes and tariffs on fossil fuel vehicles negatively impact the demand for fossil fuel vehicles and government revenues. Therefore, it is recommended that an increase in fuel taxes be implemented to optimize both government revenues and social welfare. This approach safeguards public revenues, promotes societal well-being, and mitigates air pollution.

Assessing the EU Climate and Energy Policy Priorities for Transport and Mobility through the Analysis of User-Generated Social Media Content Based on Text-Mining Techniques

For over three decades, the European Union’s (EU) transport policy has aimed at fostering environmental sustainability and energy efficiency. Since 2015, European policymakers have focused more on three key sustainable development goals: decarbonizing the transport system, promoting low-emission mobility solutions, and transitioning to renewable and alternative fuels. To effectively communicate priorities and engage stakeholders, EU policymakers regularly use social media platforms like Twitter (now known as X). This active discourse involves policymakers, industrial stakeholders, the media, and the public, offering insights into the role of transport policy in addressing climate change and energy transition challenges. The current research endeavors to track and analyze the evolution of user-generated content related to climate change, energy transition, and smart mobility on Twitter from 2011 to 2021. This research uses text-mining and social network analysis techniques to quantitatively and qualitatively assess the dynamics of relevant EU policies and their effects. The study’s findings can be used to establish a robust monitoring and evaluation framework at the EU and national levels. This framework will assess the effectiveness of communicating strategic priorities for sustainable transport development. It also holds potential for application in other sectors, broadening its impact.

Analysis of Intercity Transportation Network Efficiency Using Flow-Weighted Time Circuity: A Case Study of Seven Major City Clusters in China

Enhancing the efficiency of intercity transportation networks is crucial for sustainable regional transport development, significantly impacting travel behaviors and energy consumption. The transportation infrastructure within the city cluster is rapidly developing to accommodate the increasing traffic demand, necessitating substantial investments. It is imperative to investigate the effectiveness of intercity traffic within urban clusters, to evaluate the influence of transportation infrastructure enhancements on regional traffic efficiency. Circuity is a conventional metric used to assess the efficiency of transportation networks, primarily emphasizing distance, while overlooking factors such as travel time and traffic flow. In this study, the concept of circuity has been redefined in terms of travel time and has been referred to as the transportation network travel speed. Subsequently, the amalgamation of travel speed within the transportation network and traffic flow culminates in the proposition of Flow-Weighted Time Circuity (FWTC). Real-time intercity navigation data, offering accurate travel time estimations, are utilized to analyze the spatial distribution of intercity transport efficiency in the seven major city clusters of China, via both automobile and train modes of transportation. The results indicate that (1) as the travel distance extends, the speed of transportation within the network typically increases, albeit with increasing fluctuations, especially in the case of intercity train travel; (2) concerning the efficiency of intercity automobile travel, most city clusters demonstrate satisfactory performance, with the exception of the Guanzhong Plain. The Yangtze River Delta and Beijing–Tianjin–Heibei regions stand out for their superior performance. In terms of intercity train efficiency, the Yangtze River Delta, Beijing–Tianjin–Heibei, and Mid-Yangtze River regions exhibit higher levels of efficiency in intercity train transportation, while the Guanzhong Plain city cluster falls behind in this aspect. On the whole, the efficiency of intercity travel using automobiles surpasses that of train travel, indicating a pressing need for improvement in the latter.

Understanding the potential of taxi sharing: The case of Chengdu

The emergence of taxi sharing enhances urban transport efficiency and reduces carbon emissions. Using GPS tracking data from taxis in Chengdu, China, this study first outlines conditions for identifying shareable taxi orders based on their origins and destinations. We then develop a three-phase computational model to optimize matches among all potential shareable orders, calculating the shareable mileage and the proportion of original mileage that could be shared. Our comprehensive temporal and spatial analysis reveal a significant market for taxi sharing in Chengdu, with higher potential on workdays than non-workdays and four distinct demand peaks throughout the day. The morning peak on workdays and the night peak on non-workdays are particularly pronounced. Most shareable orders originate within major city districts. We find a positive correlation between the potential of taxi sharing and average traffic speed, and negative correlations with order volume, regional economic development, and population density. Functional zones related to Enterprises, Motorcycle Services, and Transportation Services exhibit significantly higher sharing potential. Compared to traditional taxi operations, taxi sharing significantly reduces total travel mileage. This quantitative analysis offers insights into the potential demand for taxi sharing among urban residents and may help government authorities optimize taxi resources for the sustainable development of urban transport.

Flight Technology Evaluation Based on Flight Parameters

Based on the flight safety, this paper develops a flight technology evaluation method based on the gradient boosting decision tree ( GBDT ) model by collecting and analyzing flight data. This method comprehensively considers flight parameters and provides a more accurate pilot flight technology assessment tool through the analysis of flight records. It is expected to improve the training plan and enhance the technical level of pilots to further improve the safety and sustainable development of air transportation. By introducing the deep learning network structure optimization evaluation method, the flight safety is further enhanced.

The operation mechanism of integrating urban and rural passenger transportation and logistics under the strategy of rural revitalization–Case study of Lianhua County, China

To alleviate the pressure of government financial subsidies for urban and rural public transport, this paper analyzes the intrinsic relationship between China's rural revitalization strategy and the integrated development of urban and rural public transport, and proposes an integrated development model of public transport and logistics based on urban and rural public transport. Taking Lianhua County, China, as an example, this paper investigates the operational mechanism and pilot effects of the bus-logistics integration model, and proposes strategies to promote the development of bus-logistics integration. The results of the case study show that the urban–rural bus integration model based on the integration of public transportation and logistics can reduce the deficit of urban–rural bus enterprises by 35.8% compared with the traditional urban–rural bus integration model, which can effectively alleviate the pressure of government financial subsidies. The research results have practical significance for promoting rural revitalization in Lianhua County and alleviating government financial pressure, and also have a certain reference role for the sustainable development of urban and rural public transportation in other small and medium-sized cities.

Public Transport Accessibility Policy for Disabled Batam City in the Concept of Sustainable Transportation

This study evaluates sustainable transportation development in Batam City, focusing on the accessibility of public transportation for persons with disabilities as a sustainability indicator. Utilizing qualitative research methods, primary data were collected through interviews, complemented by secondary data from various sources such as Department of Transportation reports, Batam City Government documents, and online media. Data analysis employed triangulation, supported by Vosviewer Tools for processing secondary data. Findings reveal inadequate transportation accessibility services for people with disabilities in Batam City. Effectiveness, efficiency, adequacy, and equality for this demographic remain suboptimal, indicating a lack of sustainable and inclusive approaches. Regional regulations concerning disabilities are not fully implemented, and there's a lack of management strategies for transportation or Transport Demand Management tailored to assist people with disabilities. The Bus Rapid Transit (BRT) system's ineffectiveness hampers transportation connectivity, exacerbating access challenges. Essential disability facilities like ramps and bell signals are unevenly provided, while the limited number of special seats creates difficulties in prioritizing pregnant women and the elderly. Consequently, the current serviceability access falls short of meeting the standard needs of people with disabilities, as envisioned in Sustainable Transportation frameworks.

Exploring the gap in people’s travel behavior between urban villages and commercial housing: The role of built environment

As urban expansion accelerates, travel distance and vehicle miles traveled continue to grow. Simultaneously, agricultural land is gradually giving way to urban construction, and ancient communities are transforming into urban villages as a result of being surrounded by urban land. Given the widespread distribution of urban villages in Chinese cities, which accommodate a large number of low-income groups, paying attention to the travel behavior of these groups is beneficial for promoting the fair development ofsociety. Therefore, this study utilized resident survey data from urban villages and commercial housing communities of Zhuhai in 2018 and built a structural equation modeling analysis framework to investigate the differences in the influence of the built environment (BE) on the travel behavior of these two types of housing. The results showed that the BE of urban villages had a significantly different impact on travel behavior compared to commercial housing. This discovery can help authorities better understand the impact of the BE of urban villages on travel distance, transit choices, and walking/cycling decisions. Moreover, this research is conducive to proposing targeted measures for sustainable transportation development in urban villages.

Research Progress and Prospects of Transit Priority Signal Intersection Control Considering Carbon Emissions in a Connected Vehicle Environment

Transit priority control is not only an important means for improving the operating speed and reliability of public transport systems, but it is also a key measure for promoting green and sustainable urban transportation development. A review of signal intersection transit priority control strategy in a connected vehicle environment is conducive to discovering important research results on transit priority control at home and abroad and will promote further developments in urban public transport. This study analyzed and reviewed signal intersection transit priority control at four levels: traffic control sub-area divisions, transit signal priority (TSP) strategy, speed guidance strategy, and the impacts of intersection signal control on carbon emissions. In summary, the findings were the following: (1) In traffic control sub-area divisions, the existing methods were mainly based on the similarity of traffic characteristics and used clustering or search methods to divide the intersections with high similarity into the same control sub-areas. (2) The existing studies on the TSP control strategy have mainly focused on transit priority control based on fixed phase sequences or phase combinations under the condition of exclusive bus lanes. (3) Studies on speed guidance strategy were mainly based on using constant bus speeds to predict bus arrival times at intersection stop lines, and it was common to guide only based on bus speed. (4) The carbon emissions model for vehicles within the intersection mainly considered two types of vehicles, namely, fuel vehicles and pure electric vehicles. Finally, by analyzing deficiencies in the existing studies, future development directions for transit priority control are proposed.

The nonlinear impact of cycling environment on bicycle distance: A perspective combining objective and perceptual dimensions

Extending cycling distances is crucial for sustainable urban transport development and plays a role in encouraging the shift from motorized vehicles to public transport. However, there is a lack of research examining the combined impacts of both objective and perceived aspects of the cycling environment on cycling distance, and the existence of threshold effects remains unclear. This study uses 2019 cycling data from Shenzhen, China, employing the XGBoost algorithm to uncover the relative importance and thresholds of objective and perceived factors in the cycling environment. The results indicate that population density (24.8%), road network density (15.2%), the proportion of recreational facilities (9.1%), perceived accessibility (8.0%), and comfort (8.6%) hold high relative importance in predicting cycling distance. Also, maintaining road network density between 3 to 6 km/km2 and increasing the population density to exceed 22,000 people/km2 proves effective in extending cycling distances. Land use demonstrates a threshold effect, with cycling distances increasing when the recreational facilities share exceeds 8%, transport facilities share remains below 25%, and commercial facilities share stays below 30%. Perceived metrics exhibit a clear threshold effect. The study identifies that perceived safety indicates a psychological bottleneck in increasing cycling distance. Perceived accessibility is positively correlated with cycling distance when accessibility is at a low level, while comfort shows a positive correlation with cycling distance when comfort is at a high level. These findings can contribute to refining land planning and prioritizing resource allocation for organizations aiming to promote non-motorized travel and design bicycle-friendly environments.

Compressive Strength and Elastic Modulus of a 3D Woven Glass/Polyester Fire-Retardant Sandwich Composite

A 3D woven sandwich composite structure has been widely used in various fields due to its advantages in terms of its strength-to-weight ratio. The adoption of lightweight materials in the railway industry for train carriages is aligned with United Nations Sustainable Development Goal 11, as this fosters the development of sustainable transportation by reducing carriage weight, enhancing fuel efficiency, minimizing component wear, and mitigating air pollution. This study explores the effect of the addition of aluminum trioxide (ATH) filler on the core structure, density, compressive strength, elastic modulus, and the number of added layers of 3D woven core fabric with 2D woven face sheets. Sandwich composites were produced with varying ATH loads of 30%, 40%, and 50%. We also varied the number of 3D woven core fabric layers in the composite sandwich (one, two, three, and four layers) and the 2D preform (one on the upper side, two on the upper side, and one on the upper + two on the lower sides) used as a face sheet thickener. The results showed that the addition of ATH filler increased the composite density. The addition of up to 40% ATH improved the strength and elastic modulus of the composite, while excessive loading led to a decrease in both properties. Variation of the 3D and 2D preform layers also improved the compressive strength and elastic modulus. We conclude that 3D woven sandwich composites incorporating 40% ATH, multilayered 3D woven core fabric, and 2D woven fabric face sheet thickener represent promising materials for use in the railway industry.

Comparing Mini and full-size electric vehicles in China: Evidence from user heterogeneity and satisfaction asymmetry

Improving user satisfaction with electric vehicles (EVs) is crucial for their widespread diffusion and the development of sustainable transportation. Although numerous studies have investigated the impact of EV service factors on satisfaction, the nonlinear and asymmetric effects have been largely neglected. This study aims to fill this gap by comparing the factor differences in user perceptions, satisfaction asymmetries, and improvement priorities among heterogeneous adopters within two EV segments: Mini EVs and full-size EVs. Two common methods, the regression with dummy variables (RDV) and the Importance Grid (IG), are utilized to examine satisfaction asymmetry and determine which one is more appropriate for describing the relationship between service factors and overall satisfaction. Empirical evidence from EV segments in China indicates that the RDV method is more suitable than the IG method for characterizing factor attribute and asymmetry. Female, multi-vehicle, and daily users report higher levels of satisfaction and importance for service factors compared to male, single-vehicle, and weekly users. Based on the RDV method, the results emphasize the importance of improving charging satisfaction to enhance the overall satisfaction of Mini EV adopters, particularly for those who have multiple vehicles and frequent travel demands. For males and daily users of full-size EVs, it is critical to enhance vehicle performance and technology. This study not only expands the limited application of satisfaction asymmetry to the transportation field but also provides policy implications for Mini EV diffusion.

Unveiling The Nexus: Exploring the Impact of Behavioral Finance on Green Finance Initiatives

This research paper delves into the dynamic landscape of global climate finance during the fiscal years of 2021/2022, examining the collaborative efforts of public and private actors in addressing the multifaceted challenges posed by climate change. The equitable distribution of financial resources reflects a shared commitment to transformative action, with a focus on critical sectors such as energy, transport, and buildings and infrastructure. Both sectors emphasize the transition to renewable energy, sustainable transportation, and climate-resilient urban development. Public finance plays a pivotal role by directing support to relatively underserved sectors, including Agriculture, Forestry, and Other Land Use (AFOLU), water and wastewater management, and industry. This targeted intervention ensures inclusivity in climate action and contributes to broader sustainable development goals. The financial commitments not only reduce carbon footprints but also foster innovation, job creation, and economic resilience. The collaborative model of climate finance observed during this period sets a precedent for future endeavors, emphasizing a holistic and inclusive approach. The research suggests potential avenues for future studies, such as assessing the long-term impact of climate finance, evaluating evolving patterns in public-private collaboration, and exploring the integration of climate finance within global policy frameworks. Ultimately, this research contributes to the ongoing discourse on climate resilience, offering insights into the interconnectedness of financial commitments, sustainable development, and the global fight against climate change.

Convolutional Neural Network-Based Bidirectional Gated Recurrent Unit–Additive Attention Mechanism Hybrid Deep Neural Networks for Short-Term Traffic Flow Prediction

To more accurately predict short-term traffic flow, this study posits a sophisticated integrated prediction model, CNN-BiGRU-AAM, based on the additive attention mechanism of a convolutional bidirectional gated recurrent unit neural network. This model seeks to enhance the precision of traffic flow prediction by integrating both historical and prospective data. Specifically, the model achieves prediction through two steps: encoding and decoding. In the encoding phase, convolutional neural networks are used to extract spatial correlations between weather and traffic flow in the input sequence, while the BiGRU model captures temporal correlations in the time series. In the decoding phase, an additive attention mechanism is introduced to weigh and fuse the encoded features. The experimental results demonstrate that the CNN-BiGRU model, coupled with the additive attention mechanism, is capable of dynamically capturing the temporal patterns of traffic flow, and the introduction of isolation forests can effectively handle data anomalies and missing values, improving prediction accuracy. Compared to benchmark models such as GRU, the CNN-BiGRU-AAM model shows significant improvement on the test set, with a 47.49 reduction in the Root Mean Square Error (RMSE), a 30.72 decrease in the Mean Absolute Error (MAE), and a 5.27% reduction in the Mean Absolute Percentage Error (MAPE). The coefficient of determination (R2) reaches 0.97, indicating the high accuracy of the CNN-BiGRU-AAM model in traffic flow prediction. It provides a good solution for short-term traffic flow with spatio-temporal features, thereby enhancing the efficiency of traffic management and planning and promoting the sustainable development of transportation.

Vehicle Driving Behavior Analysis and Unified Modeling in Urban Road Scenarios

To improve the simulation accuracy and efficiency of microscopic urban traffic, a unified modeling method considering the behavioral characteristics of vehicle drivers is proposed by considering the lane-changing vehicles on the inlet lanes of signalized intersections and their approach following vehicles on the target lanes as research objects. Based on the driver’s multidirectional, multi-vehicle anticipation ability and introducing lateral vehicle influence coefficients, the full velocity difference car-following model was extended to microscopic traffic models that consider the driver’s capacity for multi-directional, multi-vehicle anticipation. The extended model can describe longitudinal movements of lane changing and car followers using lateral vehicle influential parameters. The influences of traffic control signals and the type of lane change on drivers’ decisions were integrated into the model by reformulating the optimal velocity function of the basic car following the model. Similar modeling methods and components were applied to formulate four groups of experimental models and one group of test models. Vehicle trajectory data and manual observations were collected on urban arteries to calibrate and evaluate the research models, experimental models, and test models. The results show that the car-following behavior is more sensitive to the variation in the status of the lateral moving vehicle and change of lane-changing type compared to lane-changing behavior during the lane-changing process. In addition, when lane changing gradually encroaches on the target lane, the vehicle observes the driving conditions and adjusts its driving behaviors differently. This research helps to analyze travel characteristics and influence mechanisms of vehicles on urban roads, which is a guide for the future development of sustainable transportation and self-driving vehicles and promoting the efficient operation of urban transportation systems.

Current social impact assessment practices for transport projects and plans in Chinese cities

ABSTRACT The importance of sustainable transport development is being increasingly realised in China. However, the understanding of social sustainability in the transport sector remains inadequate. Transport social impact assessment (SIA) at the local level, especially for small- to medium-sized cities, lacks systematic guidance. As a starting point for improving social sustainability in the transport sector, this research explores transport SIA practices in different-sized Chinese cities. Following a critical review of transport planning and appraisal documents collected from 83 sample cities in mainland China, 5 categories were identified based on the characteristics of their transport SIA practices. It was found that except for a few megacities, transport SIA in Chinese cities is generally weak, compared to developed countries. SIA has received little attention and had limited influence on decision-making in transport planning in China. Current guidance on transport SIA in China is relatively general and ambiguous compared to many developed countries, an established transport SIA framework and indicator set for local governments to refer to are lacking. The disparities in transport SIA among different-sized Chinese cities and different project types are significant. Interviews with Chinese transport practitioners were conducted to further explore the gaps in transport SIA practices and the potential for improvement. Based on the interview analysis, key aspects for improving transport SIA practices in China have been provided.

Alternative prioritization for mitigating urban transportation challenges using a Fermatean fuzzy-based intelligent decision support model

Practitioners and decision-makers often face difficulties in selecting and prioritizing effective strategies to address challenges to sustainable urban transportation development. Although there has been considerable research conducted on the subject, the Tanzanian context, which is greatly affected by social and environmental problems, has received inadequate attention. Therefore, this study intends to bridge this gap by pinpointing the obstacles to sustainable urban transportation and proposing the most appropriate strategies to tackle them. The study proposes seven strategies and determines five criteria to prioritize them. To accomplish this, the study proposes a novel Fermatean fuzzy-based intelligent decision support model to assess the criteria weights and prioritizes strategies based on the weighted criteria. The study validates the proposed methodology by conducting a sensitivity analysis, which indicates that restricting car use (A5), improving sector coordination (A1), and conducting extensive research on transportation issues (A7) are the top three strategies for promoting sustainable urban transportation. The study’s findings hold significant value in providing urban transportation planners with helpful guidance to develop optimization techniques that can improve transportation systems.

Transportation Infrastructure and Common Prosperity from the Perspective of Chinese-Style Modernization: Enabling Effects and Advancement Paths

“Common prosperity depends on development, and development comes first in transportation.” Achieving common prosperity is the essential requirement for Chinese-style modernization under the construction of a sustainable transportation power country. Based on China’s 30 provincial panel data from 2001 to 2021, this paper calculates the common prosperity index under modernization construction and uses the fixed-effect model and bootstrap mediation effect analysis method to examine the impact and promotion path of transportation infrastructure empowering common prosperity (mediating effect). The study found that transportation infrastructure has a significant enabling effect on common prosperity, and the higher the level of common prosperity, the stronger this effect. After a variety of robustness tests, the conclusion is still reliable. The specific path is that transportation infrastructure further strengthens its role in empowering common prosperity through the four intermediaries of economic growth, factor flow, industrial upgrading, and market expansion. Except for the complete intermediary effect of factor flow, the other intensity ratios are all at 65% or above. In addition, there is heterogeneity in the impact of transportation infrastructure on common prosperity, which is reflected in the significant effect in areas with large urban populations, eastern regions, and first-tier or former new first-tier cities. To this end, a quadrilateral orientation focusing on “economy, factors, industries, and markets” is proposed, with dense transportation networks and regional differentiation as the focus of sustainable transportation development, providing empirical support for promoting common prosperity.

A Quantitative Study on Factors Influencing User Satisfaction of Micro-Mobility in China in the Post-Sharing Era

In the post-sharing era, the evolution of the shared micro-mobility industry has transitioned from expanding market share to providing precise services. The focus on user satisfaction has shifted from a singular emphasis on functional utility to diversified product values. Product perceived value has emerged as a comprehensive factor for enhancing user satisfaction, aiding companies in formulating precise services, mitigating urban resource wastage, and promoting sustainable urban development. From the perspective of product perceived value, this study combined the analysis of factors affecting user satisfaction of shared micro-mobility and the interaction between these aspects and carried out the following two studies. Research No. 1: By mining the user review data on app platforms related to shared micro-mobility and adopting the latent dirichlet allocation (LDA) algorithm, we have initially identified 17 major factors affecting the satisfaction of users and summarized these factors into four research topics constituting product perceived value. Research No. 2: On the basis of Research No. 1, the content of the American Customer Satisfaction Index (ACSI) was expanded, and a user satisfaction research model focusing on the perceived value of shared micro-mobility products was constructed. Afterwards, by using the data collected in questionnaire surveys, structural equation modeling (SEM) was used to model the user satisfaction of shared micro-mobility through SEM, which was deployed to establish an empirical analysis. It is found that (1) both user expectation and product quality can positively affect the perceived value of products through interactive experience; (2) factors such as user expectation, product quality, interactive experience, and subjective consciousness can positively affect user satisfaction through the perceived value of products, with user expectation delivering the greatest influence; and (3) subjective consciousness has a direct positive effect on users’ willingness to continuously use a product but no significant effect on user satisfaction. These findings expand the user satisfaction theoretical model in the field of shared micro-mobility, constitute suggestions for product development and service promotion in the shared micro-mobility industry, and can provide new ideas and methods for the sustainable development of urban transportation.