Research in Transportation Business and Management最新文献_第10页

Analysis of the factors influencing university community satisfaction about public transport trips in small and medium-sized cities in Brazil 巴西中小城市大学生群体对公共交通出行满意度的影响因素分析

IF 4.1 2区工程技术 Q2 BUSINESS

Research in Transportation Business and Management

Pub Date : 2024-11-01 DOI: 10.1016/j.rtbm.2024.101233

Alejandro Ruiz-Padillo , Letícia Barcellos de Moraes , Paula Sandri Rhoden , Juan de Oña

Urban mobility in small and medium-sized cities presents unique aspects from the perspective of academic communities. Understanding the perceptions and expectations of this population is crucial for improving satisfaction with their journeys, especially when using public transport. The aim of this study was to analyze the constructs that influence the satisfaction and mobility behavior of public transport users on trips to university campuses in small and medium-sized cities in Brazil. A case study was performed, employing a SEM-MIMIC approach to the answers of a questionnaire applied to students, teachers, and support staff of a university in the interior of southern Brazil. Seven constructs affecting satisfaction were identified and the relationships between them were investigated. These were as follows: walking infrastructure, noise, safety, trip to the stop, infrastructure of stops, trip in the vehicle, and service operation. The results revealed that the greatest influence on overall satisfaction was related to the user's experience inside the vehicle and the characteristics of the service. It was also evident that there was a high direct effect of the users' overall satisfaction on their behavior. The study population presented homogeneity, although younger users were less loyal and less likely to recommend the bus to others, while owning a private vehicle improved satisfaction with the operation of the service.

从学术界的角度来看，中小城市的城市交通具有独特性。了解这些人群的看法和期望对于提高他们的出行满意度至关重要，尤其是在使用公共交通时。本研究旨在分析影响巴西中小城市大学校园公共交通用户满意度和出行行为的因素。研究采用了 SEM-MIMIC 方法，对巴西南部内陆地区一所大学的学生、教师和后勤人员的问卷答案进行了案例研究。研究确定了七个影响满意度的因素，并对它们之间的关系进行了调查。这七个因素是：步行基础设施、噪音、安全、到站行程、站点基础设施、乘车行程和服务运营。结果显示，对总体满意度影响最大的是用户在车内的体验和服务的特点。用户的总体满意度对其行为的直接影响也很明显。尽管年轻用户对公交车的忠诚度较低，也不太可能向他人推荐公交车，但研究对象呈现出同质性，而拥有私家车的用户则提高了对服务运营的满意度。

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引用次数: 0

Comprehensive evaluation in urban green transportation development: Evidence from 30 cities in China 城市绿色交通发展的综合评价：来自中国 30 个城市的证据

IF 4.1 2区工程技术 Q2 BUSINESS

Research in Transportation Business and Management

Pub Date : 2024-11-01 DOI: 10.1016/j.rtbm.2024.101231

Chunqin Zhang , Waner Li , Wenbin Huang , Hui Wu , Martin Skitmore , Bo Xia , Wangxiong Wang

This study develops a Comprehensive Index of Urban Green Transportation Development Levels in Chinese cities to address the absence of a comprehensive framework for evaluating China's urban transportation system. Using expert interviews and the eDPSIR framework, it creates a causal network diagram and employs DEMATEL to assess relationships among 13 key factors and 26 indicators. The system evaluates urban green transportation development comprehensively, covering effectiveness in systems, social, environmental, economic, and transportation aspects. The framework employs the difference coefficient method, subjective and objective entropy weighting, and fuzzy hierarchical analysis. Empirical research on 30 Chinese cities from 2011 to 2020, using improved set-pair analysis and a variable fuzzy set model, identifies challenges in achieving green development levels, with megacities surpassing large cities. Fishbone analysis reveals policy deficiencies, prompting proposed design ideas and enhancement paths. This study enriches green transportation assessment indicators, offering valuable insights for sustainable urban transportation development in China.

本研究开发了中国城市绿色交通发展水平综合指数，以解决中国城市交通系统缺乏综合评价框架的问题。通过专家访谈和 eDPSIR 框架，建立了因果网络图，并运用 DEMATEL 评估了 13 个关键因素和 26 个指标之间的关系。该系统全面评估了城市绿色交通发展，涵盖了系统、社会、环境、经济和交通等方面的有效性。该框架采用了差分系数法、主客观熵权法和模糊层次分析法。利用改进的集对分析法和可变模糊集模型，对中国 30 个城市从 2011 年到 2020 年的绿色发展水平进行了实证研究，发现了实现绿色发展水平所面临的挑战，其中特大城市超过了大城市。鱼骨分析揭示了政策缺陷，提出了设计思路和改进路径。本研究丰富了绿色交通评价指标，为中国城市交通的可持续发展提供了有价值的启示。

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引用次数: 0

Perceived value, service quality and behavioral intentions towards bike-sharing services: Using an extended technology acceptance model 共享单车服务的感知价值、服务质量和行为意向：使用扩展的技术接受模型

IF 4.1 2区工程技术 Q2 BUSINESS

Research in Transportation Business and Management

Pub Date : 2024-11-01 DOI: 10.1016/j.rtbm.2024.101236

Jing Su, Sisi Luo, Kexin Ji, Boshi Tian

In recent years, the bike-sharing industry has experienced rapid development as a business model but still faces several challenges. Prior research has predominantly focused on bicycle service quality and traffic safety from the perspective of companies. This article takes a consumer-centered approach and incorporates security as a crucial perceptual factor into the technology acceptance model. Drawing on the consumer perceived value theory, we employ app perceived value and bicycle perceived value as mediating variables to construct a model of consumers' behavioral intentions to use bike-sharing. The study finds that app perceived value and bicycle perceived value are strong predictors of consumers' willingness to use bike-sharing. At the same time, app perceived value also indirectly affects their perceived behavioral control of using bike-sharing through the mediating role of bicycle perceived value. Furthermore, the perceived usefulness, ease of use, and security of the app are found to positively impact app perceived value, which in turn increases the preference for bike-sharing of consumers. In conclusion, these findings provide practical management recommendations for bike-sharing companies to balance and enhance app services and the quality of the bicycle, thus enabling the ride-hailing ecosystem to generate more sustainable urban transport solutions.

近年来，共享单车行业作为一种商业模式经历了快速发展，但仍面临着一些挑战。以往的研究主要从企业角度出发，关注自行车服务质量和交通安全。本文采用以消费者为中心的方法，将安全作为一个重要的感知因素纳入技术接受模型。借鉴消费者感知价值理论，我们将应用程序感知价值和自行车感知价值作为中介变量，构建了消费者使用共享单车的行为意向模型。研究发现，应用程序感知价值和自行车感知价值对消费者使用共享单车的意愿有很强的预测作用。同时，应用程序感知价值还通过自行车感知价值的中介作用间接影响消费者使用共享单车的感知行为控制。此外，研究还发现应用程序的有用性、易用性和安全性会对应用程序感知价值产生积极影响，进而增加消费者对共享单车的偏好。总之，这些研究结果为共享单车公司提供了切实可行的管理建议，以平衡并提升应用程序服务和单车质量，从而使共享单车生态系统产生更多可持续的城市交通解决方案。

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引用次数: 0

Integrating experience management and theoretical decision-making for optimizing train service network: A case study of China railway operation 经验管理与理论决策相结合，优化列车服务网络：中国铁路运营案例研究

IF 4.1 2区工程技术 Q2 BUSINESS

Research in Transportation Business and Management

Pub Date : 2024-10-31 DOI: 10.1016/j.rtbm.2024.101229

Boliang Lin , Zhenyu Wang , Yaming Tian , Ruixi Lin

Decision-makers in railway companies often face the challenge of balancing the differences between theoretical optimization decision-making and practical experience management when designing train service network. In response, this paper proposes a practical car-to-train strategy for train service network, which originates from the operational experience of yard (marshalling station) operators. It is noteworthy that existing studies usually focus on theoretical research, while neglecting practical operation strategies at yards. These real-world operation strategies always rely on experience management by highly-experienced railway operators. In this paper, we first design train service network optimization models based on the proposed practical car-to-train strategy and theoretical optimization strategy, respectively. Subsequently, a semi-experience car-to-train strategy is developed. The established mathematical models are bi-level programming. To solve the models, a simulated annealing algorithm is developed. Taking Beijing-Shanghai Railway as an example, three numerical experiments based on three car-to-train strategies are carried out.

In the results of the experiments, the objective function of the semi-experience strategy increases by 4.82 % compared to the theoretical optimization strategy, and the proposed practical car-to-train strategy only increases by 2.02 %. For the operations of yards, the proposed practical car-to-train strategy is more in line with railway operation regulations.

铁路公司的决策者在设计列车服务网络时，经常面临如何平衡理论优化决策与实践经验管理之间差异的挑战。为此，本文从车场（调度站）运营商的运营经验出发，提出了一种实用的列车服务网络车对车策略。值得注意的是，现有研究通常侧重于理论研究，而忽视了车场的实际运营策略。这些实际运营策略始终依赖于经验丰富的铁路运营商的经验管理。在本文中，我们首先分别根据提出的实际车对车策略和理论优化策略设计列车服务网络优化模型。随后，建立了半经验车到列车策略。建立的数学模型为双层程序设计。为求解模型，开发了模拟退火算法。以京沪铁路为例，基于三种车到列车策略进行了三次数值实验。实验结果表明，与理论优化策略相比，半经验策略的目标函数增加了 4.82%，而所提出的实用车到列车策略仅增加了 2.02%。对于货场的运营而言，所提出的实用车对列车策略更符合铁路运营规定。

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引用次数: 0

Transit warehouse location selection by IF AHP- TOPSIS integrated methods for disaster logistics: A case study of Turkey 采用 IF AHP- TOPSIS 综合方法为灾害物流选择中转仓库位置：土耳其案例研究

IF 4.1 2区工程技术 Q2 BUSINESS

Research in Transportation Business and Management

Pub Date : 2024-10-30 DOI: 10.1016/j.rtbm.2024.101232

Nigar Yesilcayir , Gulsah Ayvazoglu , Sefa Celik , Iskender Peker

Disasters; like earthquakes, fires, floods, wars, etc., are totally undesired events because they can cause unforeseen enormous physical, economic and social losses. In this respect, disaster logistics is crucial in providing fast and effective humanitarian aid at the lowest cost and with no profit motive in case of these unpredictable events. There are many supporting elements to achieve this goal and one of them is building transit warehouses. The aim of this study is to select the most suitable transit warehouse location in the Province of Hatay, Turkey. The weights of the criteria are determined by Intuitionistic Fuzzy AHP and the alternatives are ranked by Intuitionistic Fuzzy TOPSIS. The results show that “Emergency Cases and Natural Disaster” is the most important criterion and Alternative 3 (Kırıkhan) is the best location for the transit warehouse.

灾害，如地震、火灾、洪水、战争等，是完全不希望发生的事件，因为它们可能造成不可预见的巨大物质、经济和社会损失。因此，在发生这些不可预知的事件时，灾害物流对于以最低成本、不受利益驱动地提供快速有效的人道主义援助至关重要。要实现这一目标，有许多辅助要素，其中之一就是建造中转仓库。本研究的目的是在土耳其哈塔伊省选择最合适的中转仓库地点。通过直觉模糊 AHP 确定标准的权重，并通过直觉模糊 TOPSIS 对备选方案进行排序。结果表明，"紧急情况和自然灾害 "是最重要的标准，而备选方案 3（克勒汗）是中转仓库的最佳地点。

引用次数: 0

Effects of COVID-19 on flex route transit utilization: An interrupted time series analysis COVID-19 对灵活路线公交利用率的影响：间断时间序列分析

IF 4.1 2区工程技术 Q2 BUSINESS

Research in Transportation Business and Management

Pub Date : 2024-10-24 DOI: 10.1016/j.rtbm.2024.101230

Jingcai Yu , Shunchao Wang , Bingtong Wang , Wenquan Li , Tao Feng

The COVID-19 outbreak has exerted serious effects on the transportation system, especially public transport. Flex route transit (FRT), one of public transport, has shown significant advantages in transporting passengers during COVID-19 due to its high flexibility and relatively large cabin spaces. This study aims to estimate the effects of the lockdown and first lockdown ease on FRT utilization through interrupted time series analysis. A survey was conducted in Beijing to collect data regarding the daily FRT utilization of individuals, spanning from December 2019 to May 2020. Results indicated that FRT utilization was immediately reduced during the lockdown, and a decreased trend was observed. After the first lockdown ease was rolled out, FRT utilization showed a rising level and trend. Private car owners showed a lower dependence on FRT than non-car owners. The level of income exerted varying effects in a wide range of periods. FRT utilization among the higher income group was more likely to take effect than the lower income group. The study yields various policy implications for FRT operations during COVID-19 or other pandemics.

COVID-19 的爆发对交通系统，尤其是公共交通造成了严重影响。在 COVID-19 期间，作为公共交通之一的弹性路线交通（FRT）因其高度的灵活性和相对较大的客舱空间，在运送乘客方面表现出明显的优势。本研究旨在通过间断时间序列分析估算封锁和首次封锁的难易程度对 FRT 利用率的影响。在北京进行了一项调查，收集了从 2019 年 12 月到 2020 年 5 月期间个人每日 FRT 利用率的数据。结果表明，在封锁期间，FRT 利用率立即下降，并呈下降趋势。在首次实施封锁缓解措施后，FRT 利用率呈上升水平和趋势。私家车主对快速公交的依赖程度低于非私家车主。收入水平在不同时期产生了不同的影响。高收入群体比低收入群体更有可能使用快速公交。这项研究对 COVID-19 或其他流行病期间的快速公交运营产生了各种政策影响。

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引用次数: 0

Factors predicting green behavior and environmental sustainability in autonomous vehicles: A deep learning-based ANN and PLS-SEM approach 预测自动驾驶汽车绿色行为和环境可持续性的因素：基于深度学习的 ANN 和 PLS-SEM 方法

IF 4.1 2区工程技术 Q2 BUSINESS

Research in Transportation Business and Management

Pub Date : 2024-10-22 DOI: 10.1016/j.rtbm.2024.101228

Ibrahim Arpaci , Mohammed A. Al-Sharafi , Moamin A. Mahmoud

With their cost-effective performance, potential to encourage environmentally friendly behavior, and increased sustainability, autonomous vehicles (AVs) are expected to lead to significant changes in the economy, society, and the environment. This study investigates factors predicting green behavior and environmental sustainability in AVs. The study developed a research model based on the “Innovation Resistance Theory” (IRT). The proposed model was evaluated with data obtained from 1266 participants through a deep learning-based “artificial neural network” (ANN) and the “partial least squares structural equation modeling” (PLS-SEM) approach. The findings indicated a positive relationship between green behavior and environmental sustainability with AVs. A positive relationship is also found between green behavior and motivators, including environmental benefits, environmental concerns, economic benefits, and technophilia. In contrast, cost barriers, along with security and privacy concerns, negatively predict green behavior. The sensitivity analysis using the ANN approach revealed that economic benefits were the most crucial factor in predicting green behavior. These results offer important insights into understanding the key barriers and drivers predicting the acceptance of AVs. The findings contribute to stakeholders making informed decisions, developing effective strategies, and contributing to AVs' sustainable and successful integration into social life.

自动驾驶汽车（AVs）具有经济高效的性能、鼓励环保行为的潜力以及更高的可持续性，预计将给经济、社会和环境带来重大变化。本研究调查了预测自动驾驶汽车绿色行为和环境可持续性的因素。研究基于 "创新阻力理论"（IRT）建立了一个研究模型。通过基于深度学习的 "人工神经网络"（ANN）和 "偏最小二乘结构方程建模"（PLS-SEM）方法，利用从 1266 名参与者获得的数据对所提出的模型进行了评估。研究结果表明，使用自动驾驶汽车的绿色行为与环境可持续性之间存在正相关关系。绿色行为与动机之间也存在正相关关系，包括环境效益、环境问题、经济效益和技术爱好者。与此相反，成本障碍以及安全和隐私问题则对绿色行为产生负面影响。使用 ANN 方法进行的敏感性分析表明，经济效益是预测绿色行为的最关键因素。这些结果为了解预测自动驾驶汽车接受度的关键障碍和驱动因素提供了重要见解。研究结果有助于利益相关者做出明智的决策、制定有效的战略，并促进自动驾驶汽车可持续地成功融入社会生活。

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引用次数: 0

The future of personal electric mobility in emerging economies: A survey of e-moto users in Vietnam 新兴经济体个人电动交通的未来：越南电动摩托车用户调查

IF 4.1 2区工程技术 Q2 BUSINESS

Research in Transportation Business and Management

Pub Date : 2024-10-20 DOI: 10.1016/j.rtbm.2024.101227

Minh Hieu Nguyen , Dorina Pojani , Duy Quy Nguyen-Phuoc

Decarbonizing private transport is crucial in the highly polluted cities of low- and middle-income countries, such as Vietnam. In motorcycle-dominated megacities, this means gradually converting the conventional motorcycle fleet into e-motos. In this study set in Hanoi, we examined the factors that explain existing e-moto riders' attachment to this mode. For this purpose, we built a novel theoretical framework called VEMM (Values and Expectations in Mobility Model), which combines the constructs of the Expectation Confirmation Model (ECM) and the Value-Based Adoption Model (VBAM). Survey data collected from 481 e-moto users in Hanoi were analysed by applying a Partial Least Squares Structural Equation Model (PLS-SEM). We found that the enduring intention to use e-motos is positively related to perceived value, user satisfaction, and perceived usefulness. We controlled for riders' gender, age, education, and living area but only education was statistically significant. Overall, we found that the perceived value of e-motos owed more to the perceived benefits (usefulness, enjoyment, and eco-friendliness) than the perceived costs (risk, price, technicality, habit, and stigma) of this mode. Based on these findings, we recommend that manufacturers consider the critical role of values when designing and promoting e-motos.

在越南等中低收入国家的高污染城市，私人交通工具的去碳化至关重要。在以摩托车为主的特大城市，这意味着要逐步将传统摩托车队转变为电动摩托车队。在这项以河内为背景的研究中，我们考察了现有电动摩托车骑手对这种出行方式的依恋程度。为此，我们建立了一个名为 VEMM（移动中的价值观和期望模型）的新理论框架，该框架结合了期望确认模型（ECM）和基于价值的采用模型（VBAM）。我们采用偏最小二乘法结构方程模型（PLS-SEM）分析了从河内 481 名电子摩托用户收集到的调查数据。我们发现，使用电动摩托车的持久意愿与感知价值、用户满意度和感知有用性呈正相关。我们对骑行者的性别、年龄、教育程度和居住地区进行了控制，但只有教育程度具有统计学意义。总体而言，我们发现电子汽车的感知价值更多地与感知到的益处（有用性、乐趣和环保性）有关，而非感知到的成本（风险、价格、技术性、习惯和耻辱感）。基于这些发现，我们建议制造商在设计和推广电子汽车时考虑价值观的关键作用。

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引用次数: 0

Who owns Electric Vehicles (EVs)? The relationship between EV adoption and socio-demographic characteristics across different price segments and brands in the Texas triangle 谁拥有电动汽车（EV）？德克萨斯三角区不同价格段和品牌的电动汽车采用率与社会人口特征之间的关系

IF 4.1 2区工程技术 Q2 BUSINESS

Research in Transportation Business and Management

Pub Date : 2024-10-16 DOI: 10.1016/j.rtbm.2024.101225

Seung Jun Choi, Junfeng Jiao, Tigris Mendez

This study investigates disparities in Electric Vehicle (EV) adoption among different socio-economic groups and geographic areas within Texas. We focused on the Texas Triangle, which includes Austin, Houston, San Antonio, and the Dallas-Fort Worth metropolitan area. Using EV registration data, our study applied unsupervised machine learning techniques, specifically hierarchical clustering analysis, to identify distinct patterns of EV adoption. We conducted a longitudinal analysis to investigate changes in carmakers' market share and to understand EV adoption patterns over time. We used Anselin Local Moran's I analysis to profile the characteristics of Tesla owners. Our analysis results revealed significant market segmentation in the EV market, particularly between different sale price ranges and brands. Notably, Tesla emerged as a market leader with strong brand appeal in the mid to high price tiers. EV adoption has been spreading from the Texas Triangle. Clusters with overall high EV registration, as identified in Anselin Local Moran's I analysis, were more associated with high-income, highly educated communities, where residents own multiple vehicles and are predominantly White. This trend was also observed among Tesla owners in relative to low-tier EV adopters. The mismatch exists between the density of registered EVs and the availability of both public and Tesla charging stations, with a notable disparity between urban centers and outskirts. More importantly, we highlight the reluctance of disadvantaged groups to purchase EVs, regardless of price or brand, underscoring the need for policy interventions that address distributive fairness. Current federal incentives and local rebate programs should better serve disadvantaged communities to promote equitable EV adoption.

本研究调查了德克萨斯州内不同社会经济群体和地理区域在电动汽车 (EV) 应用方面的差异。我们将重点放在德克萨斯三角区，包括奥斯汀、休斯顿、圣安东尼奥和达拉斯-沃斯堡大都会区。利用电动汽车注册数据，我们的研究采用了无监督机器学习技术，特别是分层聚类分析，来识别电动汽车采用的独特模式。我们进行了纵向分析，以调查汽车制造商市场份额的变化，并了解电动汽车随时间推移的采用模式。我们使用安塞林地方莫兰 I 分析法来概括特斯拉车主的特征。我们的分析结果表明，电动汽车市场存在明显的市场细分，尤其是在不同销售价格范围和品牌之间。值得注意的是，特斯拉在中高价位层成为市场领导者，具有强大的品牌号召力。电动汽车的采用已从德克萨斯三角洲蔓延开来。根据 Anselin Local Moran's I 的分析，电动汽车注册率较高的集群更多地与高收入、高学历社区相关，这些社区的居民拥有多辆汽车，且以白人为主。相对于低层次的电动汽车采用者，特斯拉车主也呈现出这种趋势。注册电动汽车的密度与公共充电站和特斯拉充电站的可用性之间存在不匹配，城市中心与郊区之间存在明显差异。更重要的是，我们强调弱势群体不愿购买电动汽车，无论价格或品牌如何，这突出表明需要采取政策干预措施来解决分配公平问题。当前的联邦激励措施和地方返利计划应更好地服务于弱势群体，以促进电动汽车的公平采用。

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引用次数: 0

Revolutionizing commutes: Unraveling the factors shaping Chinese consumers' acceptance of shared autonomous vehicles (SAVs) with an integrated UTAUT2 model 通勤方式的变革：利用UTAUT2综合模型揭示影响中国消费者接受共享自动驾驶汽车（SAVs）的因素

IF 4.1 2区工程技术 Q2 BUSINESS

Research in Transportation Business and Management

Pub Date : 2024-10-15 DOI: 10.1016/j.rtbm.2024.101224

Wenchao Cao , Yanyan Chen , Ke Wang

This study aims to systematically investigate the key factors influencing the acceptance and usage intentions of potential users towards Shared autonomous vehicles (SAVs). To achieve this, we employ an integrated and extended Unified Theory of Acceptance and Use of Technology (UTAUT2) framework to comprehensively elucidate the factors influencing the intention to use SAVs. We collected 435 survey responses from people residing in China, and structural equation modeling was utilized to confirm the theoretical model. According to the results, factors such as effort expectancy, social influence, hedonic motivation, and facilitating conditions have significant positive effects on the behavioral intention of SAVs, while perceived risk exhibits a significant negative impact. Furthermore, demographic variables (such as age, education level, and occupation) exert significant moderating effects on the model. This study expands the understanding of users' intentions in the context of SAVs, providing valuable insights for a more comprehensive understanding of the public's willingness to accept SAVs.

本研究旨在系统研究影响潜在用户对共享自动驾驶汽车（SAV）的接受和使用意愿的关键因素。为此，我们采用了一个整合和扩展的技术接受和使用统一理论（UTAUT2）框架，以全面阐明影响共享自动驾驶汽车使用意向的因素。我们收集了 435 份来自中国居民的调查问卷，并利用结构方程模型确认了理论模型。结果显示，努力期望、社会影响、享乐动机和便利条件等因素对SAV的行为意向有显著的正向影响，而感知风险则表现出显著的负向影响。此外，人口统计学变量（如年龄、教育水平和职业）对模型有显著的调节作用。本研究拓展了对SAV背景下用户意图的理解，为更全面地了解公众接受SAV的意愿提供了有价值的见解。

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引用次数: 0