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This paper aims to provide top-level design and basic platform for intelligent application in China high-speed railway.

Based on the analysis for the future development trends of world railway, combined with the actual development needs in China high-speed railway, The definition and scientific connotation of intelligent high-speed railway (IHSR) are given at first, and then the system architecture of IHSR are outlined, including 1 basic platform, 3 business sectors, 10 business fields, and 18 innovative applications. At last, a basic platform with cloud edge integration for IHSR is designed.

The rationality, feasibility and implementability of the system architecture of IHSR have been verified on and applied to the Beijing–Zhangjiakou high-speed railway, providing important support for the construction and operation of the world’s first IHSR.

This paper systematically gives the definition and connotation of the IHSR and put forward the system architecture of IHSR for first time. It will play the most important role in the design, construction and operation of IHSR.

The operating wagon records were produced from distinct railway information systems, which resulted in the wagon routing record with the same oriental destination (OD) was different. This phenomenon has brought considerable difficulties to the railway wagon flow forecast. Some were because of poor data quality, which misled the actual prediction, while others were because of the existence of another actual wagon routings. This paper aims at finding all the wagon routing locus patterns from the history records, and thus puts forward an intelligent recognition method for the actual routing locus pattern of railway wagon flow based on SST algorithm.

Based on the big data of railway wagon flow records, the routing metadata model is constructed, and the historical data and real-time data are fused to improve the reliability of the path forecast results in the work of railway wagon flow forecast. Based on the division of spatial characteristics and the reduction of dimension in the distributary station, the improved Simhash algorithm is used to calculate the routing fingerprint. Combined with Squared Error Adjacency Matrix Clustering algorithm and Tarjan algorithm, the fingerprint similarity is calculated, the spatial characteristics are clustering and identified, the routing locus mode is formed and then the intelligent recognition of the actual wagon flow routing locus is realized.

This paper puts forward a more realistic method of railway wagon routing pattern recognition algorithm. The problem of traditional railway wagon routing planning is converted into the routing locus pattern recognition problem, and the wagon routing pattern of all OD streams is excavated from the historical data results. The analysis is carried out from three aspects: routing metadata, routing locus fingerprint and routing locus pattern. Then, the intelligent recognition SST-based algorithm of railway wagon routing locus pattern is proposed, which combines the history data and instant data to improve the reliability of the wagon routing selection result. Finally, railway wagon routing locus could be found out accurately, and the case study tests the validity of the algorithm.

Before the forecasting work of railway wagon flow, it needs to know how many kinds of wagon routing locus exist in a certain OD. Mining all the OD routing locus patterns from the railway wagon operating records is helpful to forecast the future routing combined with the wagon characteristics. The work of this paper is the basis of the railway wagon routing forecast.

As the basis of the railway wagon routing forecast, this research not only improves the accuracy and efficiency for the railway wagon routing forecast but also provides the further support of decision-making for the railway freight transportation organization.

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.

Simulation is a well-known technique for using computers to imitate or simulate the operations of various kinds of real-world facilities or processes. The facility or process of interest is usually called a system, and to study it scientifically, we often have to make a set of assumptions about how it works. These assumptions, which usually take the form of mathematical or logical relationships, constitute a model that is used to gain some understanding of how the corresponding system behaves, and the quality of these understandings essentially depends on the credibility of given assumptions or models, known as VV&A (verification, validation and accreditation). The main purpose of this paper is to present an in-depth theoretical review and analysis for the application of VV&A in large-scale simulations.

After summarizing the VV&A of related research studies, the standards, frameworks, techniques, methods and tools have been discussed according to the characteristics of large-scale simulations (such as crowd network simulations).

The contributions of this paper will be useful for both academics and practitioners for formulating VV&A in large-scale simulations (such as crowd network simulations).

This paper will help researchers to provide support of a recommendation for formulating VV&A in large-scale simulations (such as crowd network simulations).

This study examines the relationship between trust, organizational climate and team learning among project team members (PTM). In recent years, many companies have come to recognize the important role team learning plays in achieving competitive advantage.

Data were collected through a survey questionnaire, and responses from 86 PTM provide support for the research model and demonstrate that how organizational climate mediates the relationship between trust and team learning.

The structural equation analysis of the data collected from 86 project team members indicate that both vertical and horizontal trust influences organizational climate, which, in turn, is a determinant of team learning. In addition, although both types of trust contributed to organizational climate, the results indicated that horizontal trust had a greater influence on organizational climate and team learning.

The study employed the survey method and is not without limitations. The first limitation concerns our sample size, which was selected from one global company. Second, the survey data were all collected at a single point in time. Therefore, the authors cannot unambiguously infer causality. To attempt to do so, it would be useful to investigate the model in the context of organizational and development change. Despite these limitations, the results of the study have implications for theory and practice.

The implication for theory is that the results provide empirical support for the view that organization climates mediate the relationship between trust and team learning. On the practical side, the organizations should also pay more attention to increasing trust at the work place, especially among PTM that may contribute to favorable organizational climate, which is vital for team learning.

This paper addresses the simultaneous role of vertical and horizontal trust on organizational climate and how it contributes to team learning. The results indicate that organizations emphasis on horizontal trust can plays a vital role in team learning, which is a contribution to enhancing teamwork and performance in organizations.

Drawing from tripartite theory of attitude, this study examined whether interaction effect of psychological ownership (cognitive component) changes the nature of the relationship between job satisfaction (affect component) and job performance (behavioral component) toward a higher or weaker relationship. Furthermore, the study draws from psychological ownership theory to find support whether job satisfaction is nurtured by the feeling of psychological ownership.

Longitudinal data from 211 academic and non-academic employees was randomly collected and partial least square-structural equation model (PLS-SEM) was used for data analysis through SmartPLS version 3.3.2.

The study found a positive interaction effect of psychological ownership on the relationship between job satisfaction and job performance. Furthermore, the study found that feeling of psychological ownership nurtures employees' satisfaction with their job.

The findings of the study explicate to human resource managers and practitioners the mechanism through which job satisfaction affects job performance and how feelings of psychological ownership nurtures employees' satisfaction with their job.

The study provides new insight into the relationship between job satisfaction and job performance by drawing on the tripartite theory of attitude perspective, and concluded that job performance as overall employee attitude toward the organization is predicted by the interaction and interplay of job satisfaction, psychological ownership and job performance as components of attitude. To the authors’ best knowledge, none of the previous literatures on job satisfaction–job performance relationship draws its conclusions from the perspective of tripartite theory of attitude. Furthermore, the study found empirical evidences that psychological ownership nurtures employees' job satisfaction.

Drawing upon the conservation of resources theory, the authors expected that daily micro-events, daily hassles and uplifts at work influenced well-being via work engagement at the daily level.

The authors conducted two diary studies. In study 1, 181 workers answered a daily questionnaire for four working days (N = 181 × 4 = 724). In study 2, 51 workers filled in a questionnaire for ten consecutive working days (N = 51 × 10 = 510).

In study 1, the results demonstrated that work engagement fully mediated the effects of daily uplifts on well-being and partially mediated the effects of daily hassles on well-being. The results of study 2 revealed a full mediation for both kinds of daily micro-events. Hence, daily uplifts stimulated work engagement, which, in turn, enhanced well-being, and daily hassles minimized work engagement and, consequently, well-being.

The relationships explored provide new theoretical elements for models that explain well-being.

This paper aims to investigate the impact of total rewards on retention. The finding relies on need satisfaction approach as a mechanism. This is done by investigating the role of need satisfaction of “autonomy, competence and relatedness” as possible mediators between elements of total rewards and retention.

This paper focussed on exploring the literature published in various popular databases .Based on the conceptual analysis, a set of possible frameworks linking the three constructs has been stated for future research.

The research has evolved with few possible frameworks to model the assertions by investigating and corroborating it with quantitative studies to be empirically tested.

The originality lies in applying self-determination theory framework of need satisfaction mechanism in explaining the relationships between total rewards and retention, thereby adding new insights to the employee retention literature.