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With the yearly increase of mileage and passenger volume in China's high-speed railway, the problems of traditional paper railway tickets have become increasingly prominent, including complexity of business handling process, low efficiency of ticket inspection and high cost of usage and management. This paper aims to make extensive references to successful experiences of electronic ticket applications both domestically and internationally. The research on key technologies and system implementation of railway electronic ticket with Chinese characteristics has been carried out.

Research in key technologies is conducted including synchronization technique in distributed heterogeneous database system, the grid-oriented passenger service record (PSR) data storage model, efficient access to massive PSR data under high concurrency condition, the linkage between face recognition service platforms and various terminals in large scenarios, and two-factor authentication of the e-ticket identification code based on the key and the user identity information. Focusing on the key technologies and architecture the of existing ticketing system, multiple service resources are expanded and developed such as electronic ticket clusters, PSR clusters, face recognition clusters and electronic ticket identification code clusters.

The proportion of paper ticket printed has dropped to 20%, saving more than 2 billion tickets annually since the launch of the application of E-ticketing nationwide. The average time for passengers to pass through the automatic ticket gates has decreased from 3 seconds to 1.3 seconds, significantly improving the efficiency of passenger transport organization. Meanwhile, problems of paper ticket counterfeiting, reselling and loss have been generally eliminated.

E-ticketing has laid a technical foundation for the further development of railway passenger transport services in the direction of digitalization and intelligence.

Resilience concepts in integrated urban transport refer to the performance of dealing with external shock and the ability to continue to provide transportation services of all modes. A robust transportation resilience is a goal in pursuing transportation sustainability. Under this specified context, while before the perturbations, robustness refers to the degree of the system’s capability of functioning according to its design specifications on integrated modes and routes, redundancy is the degree of duplication of traffic routes and alternative modes to maintain persistency of service in case of perturbations. While after the perturbations, resourcefulness refers to the capacity to identify operational problems in the system, prioritize interventions and mobilize necessary material/ human resources to recover all the routes and modes, rapidity is the speed of complete recovery of all modes and traffic routes in the urban area. These “4R” are the most critical components of urban integrated resilience.

The trends of transportation resilience's connotation, metrics and strategies are summarized from the literature. A framework is introduced on both qualitative characteristics and quantitative metrics of transportation resilience. Using both model-based and mode-free methodologies that measure resilience in attributes, topology and system performance provides a benchmark for evaluating the mechanism of resilience changes during the perturbation. Correspondingly, different pre-perturbation and post-perturbation strategies for enhancing resilience under multi-mode scenarios are reviewed and summarized.

Cyber-physic transportation system (CPS) is a more targeted solution to resilience issues in transportation. A well-designed CPS can be applied to improve transport resilience facing different perturbations. The CPS ensures the independence and integrity of every child element within each functional zone while reacting rapidly.

This paper provides a more comprehensive understanding of transportation resilience in terms of integrated urban transport. The fundamental characteristics and strategies for resilience are summarized and elaborated. As little research has shed light on the resilience concepts in integrated urban transport, the findings from this paper point out the development trend of a resilient transportation system for digital and data-driven management.

The major marine functional zoning plan (MMFZP) and marine functional zoning (MFZ) are two important kinds of marine spatial planning (MSP) in China. Their developing and implementation are integral to rational marine utilization and sustainable marine development. The purpose of this research is to study how these two kinds of MSP work in coordination in China.

This paper reviewed the present status of MSP research in China and abroad and presented a comparative study of the MMFZP and MFZ from different aspects, analyzing the relationship between the two.

The study found obvious differences between the MMFZP and MFZ, with respect to their concept and connotation, purpose and goal, as well as zoning methods and zoning functions. MFZ provides reference with respect to data, zoning methods and partial zoning results for the MMFZP, which in turn takes measures for addressing issues faced by MFZ and promotes the national MSP work.

In the process of developing and implementing the two zoning plans, this paper emphasizes the necessity to strengthen data sharing, reference of zoning techniques and coordination in zoning work, which will help to improve China's marine spatial management.

The purpose of this paper is to investigate the relationship between the characteristics of the incubation industry, government funding, and the intensity of funding for different services. Because the incubation industry has particular characteristics, government funding varies for different services, and its intensity varies with service.

Government funding is classified as incubation subsidy and incubation incentive. Besides, incubation services include property management, business mentoring as well as investment and financing. Based on this, this study examines the influence mechanism of different subsidy and incentive on incubation services by using the generalized propensity score matching method.

The empirical results show that subsidy and incentive have an inverse-U shape effect on property management service, but a linear effect on business guidance service. Furthermore, subsidy does not affect investment and financing service, but incentive that can have a significant impact.

The theme of government funding and incubator services plays an important role in helping entrepreneurs expand their businesses. Incubation subsidy and incentive can provide important support to help enterprises obtain more preferential loans, technical services and technical support in the incubator. Applying it to incubator services can provide better technology and entrepreneurship guidance. These services can help new entrepreneurs understand products and markets, and how to develop more successfully in the early stage. In short, incubators supported by government funds can provide important support to entrepreneurs to help them successfully realize their business plans.

This paper analyzes the application of digital twin technology in the field of intelligent operation and maintenance of high-speed railway infrastructure from the perspective of top-level design.

This paper provides a comprehensive overview of the definition, connotations, characteristics and key technologies of digital twin technology. It also conducts a thorough analysis of the current state of digital twin applications, with a particular focus on the overall requirements for intelligent operation and maintenance of high-speed railway infrastructure. Using the Jinan Yellow River Bridge on the Beijing–Shanghai high-speed railway as a case study, the paper details the construction process of the twin system from the perspectives of system architecture, theoretical definition, model construction and platform design.

Digital twin technology can play an important role in the whole life cycle management, fault prediction and condition monitoring in the field of high-speed rail operation and maintenance. Digital twin technology is of great significance to improve the intelligent level of high-speed railway operation and management.

This paper systematically summarizes the main components of digital twin railway. The general framework of the digital twin bridge is given, and its application in the field of intelligent operation and maintenance is prospected.

We examine whether the social capital of the area where a firm’s headquarters is located affects that firm’s credit rating. Given that credit rating agencies only infrequently visit a firm’s headquarters, it is pertinent to investigate whether this soft information is considered.

In order to test whether social capital affects firms’ credit ratings, we estimate the following model using an ordinary least squares regression: Rating_it = β₀ + β₁ Social Capital_it + ∑ Controls_it + Industry fixed Effects_i + State−year fixed effects_it + ε_it. We follow recent accounting and finance research and measure societal-level social capital at the county level (Jha & Chen, 2015; Cheng et al., 2017; Hasan et al., 2017a, b; Jha, 2017; Hossain et al., 2023). We use four inputs to calculate social capital: (1) voter turnout in presidential elections, (2) the census response rate, (3) the number of social and civic associations and (4) the number of nongovernmental organizations in each county.

W provide evidence that social capital has a causal effect on credit ratings. Interesting is that this effect is not merely localized to firms near credit rating agencies. We also find that the effect of social capital on credit ratings is concentrated among firms with moderate levels of default risk. For firms with extremely low or extremely high default risk, social capital appears irrelevant to credit ratings, suggesting that social capital plays a larger role in more ambiguous contexts or when greater judgment is required. We demonstrate that the effect of social capital on credit ratings disappears when the rating agency has extensive experience in a particular region. This result is consistent with rating agencies stereotyping certain regions of the USA and using that information to inform their ratings when they have less experience in the region. Finally, we find that while social capital is associated with credit ratings, it has no association with future defaults.

Though we cautiously followed prior studies and were confident in our data construction process, it is possible that we are measuring social capital with error.

Our findings suggest that credit rating agencies could benefit from reevaluating how they incorporate non-financial information, such as social capital, into their assessment processes, potentially leading to more nuanced and equitable credit ratings. Additionally, firms could use these insights to bolster their engagement with local communities and stakeholders, thereby enhancing their creditworthiness and attractiveness to investors as part of a broader corporate strategy. The findings also underline the need for regulatory frameworks that foster transparency and the inclusion of social factors in credit evaluations, which could lead to more comprehensive and fair financial reporting and rating systems.

Recognizing that social capital can influence economic outcomes like credit ratings may encourage both communities and firms to invest more in building and maintaining social networks, trust and civic engagement. By demonstrating how social capital impacts credit ratings, our research highlights the potential to address inequalities faced by regions with lower social capital, guiding targeted social and economic development initiatives. Moreover, understanding that regional social capital can influence credit ratings might affect public perception and trust in the impartiality and accuracy of these ratings, which is essential for maintaining market stability and integrity.

Our research provides fresh insights into how social capital, an intangible asset, influences credit ratings – a topic not extensively explored in existing literature. This sheds light on the dynamics between social structures and financial outcomes. Methodologically, our use of the 9/11 attacks as an exogenous shock to measure changes in social capital introduces a novel approach to study similar phenomena. Additionally, our findings contrast with prior studies such as Jha and Chen (2015) and Hossain et al. (2023), by delving deeper into how proximity and familiarity impact financial assessments differently, enriching academic discourse and refining existing theories on the role of local knowledge in financial decisions.

Engaged employees assure organizational competitiveness and sustainability. The purpose of this study is to explore the relationship between job resources and employee turnover intentions, with employee engagement as a mediating variable.

Data were collected from 934 employees of eight wholly-owned pharmaceutical industries. The proposed model and hypotheses were evaluated using structural equation modeling. Construct reliability and validity was established through confirmatory factor analysis.

Data supported the hypothesized relationship. The results show that job autonomy and employee engagement were significantly associated. Supervisory support and employee engagement were significantly associated. However, performance feedback and employee engagement were nonsignificantly associated. Employee engagement had a significant influence on employee turnover intentions. The results further show that employee engagement mediates the association between job resources and employee turnover intentions.

The generalizability of the findings will be constrained due to the research’s pharmaceutical industry focus and cross-sectional data.

The study’s findings will serve as valuable pointers for stakeholders and decision-makers in the pharmacuetical industry to develop a proactive and well-articulated employee engagement intervention to ensure organizational effectiveness, innovativeness and competitiveness.

By empirically demonstrating that employee engagement mediates the nexus of job resources and employee turnover intentions, the study adds to the corpus of literature.

This study explores the characteristics of high-speed rail (HSR) and air transportation networks in China based on the weighted complex network approach. Previous related studies have largely implemented unweighted (binary) network analysis, or have constructed a weighted network, limited by unweighted centrality measures. This study applies weighted centrality measures (mean association [MA], triangle betweenness centrality [TBC], and weighted harmonic centrality [WHC]) to represent traffic dynamics in HSR and air transportation weighted networks, where nodes represent cities and links represent passenger traffic. The spatial distribution of centrality results is visualized by using ArcGIS 10.2. Moreover, we analyze the network robustness of HSR, air transportation, and multimodal networks by measuring weighted efficiency (WE) subjected to the highest weighted centrality node attacks. In the HSR network, centrality results show that cities with a higher MA are concentrated in the Yangtze River Delta and the Pearl River Delta; cities with a higher TBC are mostly provincial capitals or regional centers; and cities with a higher WHC are grouped in eastern and central regions. Furthermore, spatial differentiation of centrality results is found between HSR and air transportation networks. There is a little bit of difference in eastern cities; cities in the central region have complementary roles in HSR and air transportation networks, but air transport is still dominant in western cities. The robustness analysis results show that the multimodal network, which includes both airports and high-speed rail stations, has the best connectivity and shows robustness.

In recent years, railway systems worldwide have faced challenges such as the modernization of engineering projects, efficient management of intelligent digital railway equipment, rapid growth in passenger and freight transport demands, customized transport services and ubiquitous transport safety. The transformation toward intelligent digital transformation in railways has emerged as an effective response to the formidable challenges confronting the railway industry, thereby becoming an inevitable global trend in railway development.

This paper, therefore, conducts a comprehensive analysis of the current state of global railway intelligent digital transformation, focusing on the characteristics and applications of intelligent digital transformation technology. It summarizes and analyzes relevant technologies and applicable scenarios in the realm of railway intelligent digital transformation, theoretically elucidating the development process of global railway intelligent digital transformation and, in practice, providing guidance and empirical examples for railway intelligence and digital transformation.

Digital and intelligent technologies follow a wave-like pattern of continuous iterative evolution, progressing from the early stages, to a period of increasing attention and popularity, then to a phase of declining interest, followed by a resurgence and ultimately reaching a mature stage.

The results offer reference and guidance to fully leverage the opportunities presented by the latest wave of the digitalization revolution, accelerate the overall upgrade of the railway industry and promote global collaborative development in railway intelligent digital transformation.

User acceptance is a necessary precondition to implementing self-driving buses as a solution to public transport challenges. Focusing on potential users in a real-life setting, this paper aims to analyze the factors that affect their willingness to use public autonomous shuttles (PASs) as well as their word-of-mouth (WOM) intentions.

Grounded on Unified Theory of Acceptance and Use of Technology (UTAUT2), the study was carried out on a sample of 318 potential users in a real-life setting. The hypothesized relationships were tested using partial least squares structural equation modeling (PLS-SEM).

The study reveals that performance expectancy, facilitating conditions, hedonic motivation and trust are significant predictors of PAS usage intention, which is, in turn, related to WOM communication. Additionally, the factors that impact the intention to use a PAS are found to exert an indirect effect on WOM, mediated by usage intention.

This study includes practical insights for transport decision-makers on PAS service design, marketing campaigns and WOM monitoring.

While extant research focuses on passengers who have tried autonomous shuttles in experimental settings, this article adopts the perspective of potential users who have no previous experience with these vehicles and identifies the link between usage intention and WOM communication in a real-life traffic environment.

若要引入自動駕駛巴士來解決公共交通的問題和挑戰,一個必不可少的先決條件是得到用戶的認可。本研究透過重點分析活在真實生活環境中的潛在用戶,來探討影響他們使用公共自動交通工具的意願和口碑動機的各個因素。

本研究以延伸整合型科技接受模式為基礎,對一個涵蓋處身於真實生活環境中318名潛在用戶的樣本進行分析和探討。研究人員以偏最小平方法的結構方程模型 (PLS-SEM), 去測試各個被假設的關聯。

研究結果顯示,績效期望、有利條件、享樂動機和信任均明顯能夠預測人們使用公共自動交通工具的意願,而人們使用公共自動交通工具的意願又反過來與口碑溝通有所相關。另外,研究人員發現,影響人們使用公共自動交通工具意願的各個因素,對口碑會產生間接的影響,而使用意願是會起著調節作用的。

現存的學術研究均聚焦分析那些曾於實驗設置下坐過自動交通工具的人士,而本研究卻採用從未坐過自動交通工具人士的角度來進行分析與探討,並且找出了於實際的交通環境裡、使用意願與口碑溝通之間的關聯。

本研究提供的啟示,對有關公共自動交通工具服務設計、市場營銷活動和口碑監督工作的運輸決策者來說頗具實務意義。