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Beijing rail transit can actively control the density of rail transit passenger flow, ensure travel facilities and provide a safe and comfortable riding atmosphere for rail transit passengers during the epidemic. The purpose of this paper is to efficiently monitor the flow of rail passengers, the first method is to regulate the flow of passengers by means of a coordinated connection between the stations of the railway line; the second method is to objectively distribute the inbound traffic quotas between stations to achieve the aim of accurate and reasonable control according to the actual number of people entering the station.

This paper analyzes the rules of rail transit passenger flow and updates the passenger flow prediction model in time according to the characteristics of passenger flow during the epidemic to solve the above-mentioned problems. Big data system analysis restores and refines the time and space distribution of the finely expected passenger flow and the train service plan of each route. Get information on the passenger travel chain from arriving, boarding, transferring, getting off and leaving, as well as the full load rate of each train.

A series of digital flow control models, based on the time and space composition of passengers on trains with congested sections, has been designed and developed to scientifically calculate the number of passengers entering the station and provide an operational basis for operating companies to accurately control flow.

This study can analyze the section where the highest full load occurs, the composition of passengers in this section and when and where passengers board the train, based on the measured train full load rate data. Then, this paper combines the full load rate control index to perform reverse deduction to calculate the inbound volume time-sharing indicators of each station and redistribute the time-sharing indicators for each station according to the actual situation of the inbound volume of each line during the epidemic. Finally, form the specified full load rate index digital time-sharing passenger flow control scheme.

This study aimed to facilitate a rapid evaluation of track service status and vehicle ride comfort based on car body acceleration. Consequently, a low-cost, data-driven approach was proposed for analyzing speed-related acceleration limits in metro systems.

A portable sensing terminal was developed to realize easy and efficient detection of car body acceleration. Further, field measurements were performed on a 51.95-km metro line. Data from 272 metro sections were tested as a case study, and a quantile regression method was proposed to fit the control limits of the car body acceleration at different speeds using the measured data.

First, the frequency statistics of the measured data in the speed-acceleration dimension indicated that the car body acceleration was primarily concentrated within the constant speed stage, particularly at speeds of 15.4, 18.3, and 20.9 m/s. Second, resampling was performed according to the probability density distribution of car body acceleration for different speed domains to achieve data balance. Finally, combined with the traditional linear relationship between speed and acceleration, the statistical relationships between the speed and car body acceleration under different quantiles were determined. We concluded the lateral/vertical quantiles of 0.8989/0.9895, 0.9942/0.997, and 0.9998/0.993 as being excellent, good, and qualified control limits, respectively, for the lateral and vertical acceleration of the car body. In addition, regression lines for the speed-related acceleration limits at other quantiles (0.5, 0.75, 2s, and 3s) were obtained.

The proposed method is expected to serve as a reference for further studies on speed-related acceleration limits in rail transit systems.

The purpose of the current study is to illustrate the importance of strategic agility (SA), the capacity to respond agilely to a rapidly changing environment, for digitally transforming firms during the COVID-19 crisis. A secondary purpose of the study is to conceptually frame SA as a function of the creative to realized intangible capital (IC) ratio.

To inferentially corroborate the hypothesis, this study exploits the results of a recent firm-level survey, conducted under the H2020 project GlobalInto (2021). Via OLS and ordered logistic regressions, the relationship among SA, economic performance and IC was tested.

The exploratory findings implied that the more strategically agile companies were those that responded more effectively to the pandemic crisis, but only if they were ahead in terms of digital transformation. Moreover, the results implied that firms that were able to efficiently convert their creative IC into realized IC were the most strategically agile.

This study developed a new conceptual framework for digitally transforming firms that included the role of SA and the IC conversion ratio in the context of extreme threats to the survival of firms. Some preliminary practical recommendations were offered to management about how to measure the IC conversion ratio as well as how to stimulate and reward greater creativity among employees, filling a notable gap in the SA literature that provides less than precise guidance about how this concept can be measured.

This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

Global climate change characterized by an increase in temperature has become the focus of attention all over the world. China is a sensitive and significant area of global climate change. This paper specifically aims to examine the association between agricultural productivity and the climate change by using China’s provincial agricultural input–output data from 2000 to 2019 and the climatic data of the ground meteorological stations.

The authors used the three-stage spatial Durbin model (SDM) model and entropy method for analysis of collected data; further, the authors also empirically tested the climate change marginal effect on agricultural productivity by using ordinary least square and SDM approaches.

The results revealed that climate change has a significant negative effect on agricultural productivity, which showed significance in robustness tests, including index replacement, quantile regression and tail reduction. The results of this study also indicated that by subdividing the climatic factors, annual precipitation had no significant impact on the growth of agricultural productivity; further, other climatic variables, including wind speed and temperature, had a substantial adverse effect on agricultural productivity. The heterogeneity test showed that climatic changes ominously hinder agricultural productivity growth only in the western region of China, and in the eastern and central regions, climate change had no effect.

The findings of this study highlight the importance of various social connections of farm households in designing policies to improve their responses to climate change and expand land productivity in different regions. The study also provides a hypothetical approach to prioritize developing regions that need proper attention to improve crop productivity.

The paper explores the impact of climate change on agricultural productivity by using the climatic data of China. Empirical evidence previously missing in the body of knowledge will support governments and researchers to establish a mechanism to improve climate change mitigation tools in China.

This paper aims to investigate materiality judgement providing insights, critiques and future research paths in light of the open debate on the role of materiality in corporate financial disclosure, highlighting potential connections and implications with sustainability and intellectual capital (IC) reporting.

The research presents an overview of the analysis of financial materiality, including new stimuli from recent studies and regulatory requirements for financial and non-financial reporting. Accordingly, this study used a systematic literature review (SLR) based on a combination of content, text and bibliometric analysis of materiality in accounting research studies, collecting data from the Scopus database as one of the most relevant repositories.

The SLR identified four relevant research trends, concerning: (1) the relevance of materiality principles in corporate disclosure; (2) financial reporting practices and materiality; (3) theories and approaches in defining financial materiality and (4) the existence of quantitative and qualitative thresholds in the materiality judgement.

The results provide theoretical and practical implications when comprehending the development of the concept of financial materiality in financial statements and whether they can be appropriate in reporting IC as well. We identified future research paths.

From a practical perspective, this study is useful for companies implementing financial materiality based on stakeholder engagement and improving their transparency in financial and non-financial reporting practices.

The research investigates if the process for assessing materiality is in line with the expectations of all stakeholders involved in financial and non-financial reporting.

This research is the first to investigate the scientific basis and applicability of the concept of financial materiality to sustainability and IC reporting.

The study explores the perspectives of college students on the pedagogical shift as well as frequent transitions between online and offline learning modes during the COVID-19 pandemic in Kerala, the most literate state in India.

A descriptive cross-sectional study was conducted among 1,366 college students in Kerala during December 2021. A pre-tested questionnaire was sent using Google Forms to students of arts and science colleges. The authors analyzed quantitative data using descriptive statistics and qualitative data using thematic content analysis.

The reported advantages of online learning were increased technical skill, flexibility in study time, effectiveness in bridging the gap of the missed academic period and provision of attending more educational webinars. Students expressed concerns of increased workload, difficulty in concentration due to family circumstances, academic incompetency, uncleared doubts and addiction to mobile phones and social media during the online classes. The main advantages reported for switching to an offline learning mode were enhanced social interaction, effective learning, better concentration and reduced stress. The reported challenges of offline classes were fear of getting the disease, concern of maintaining social distancing and difficulty in wearing masks during the classes. The shift in offline to online learning and vice versa was perceived as a difficult process for the students as it took a considerable time for them to adjust to the switching process of learning.

Students' concerns regarding transition between different learning modes provide important information to educators to better understand and support the needs of students during the pandemic situations.

An integrative model that predicts users' stickiness to WeChat is built. In the proposed model, perceived value plays a dual mediating role in the causal pathway from users' immersive experiences of presence and flow to their engagement and stickiness. Furthermore, presence is treated as a bi-dimensional construct made up of spatial feelings and the sense of being in company, and users' engagement is conceived as cognitive, affective and behavioural contributions to WeChat's marketing functions.

The authors develop a measurement instrument and analyse data from a survey of 917 WeChat users. They use a hybrid partial least squares-structural equation modelling (PLS-SEM) and neural network approach to confirm the reliability and validity of the measurement items and all the relationships between the constructs.

The paper provides robust evidence about the mediating influences of both utilitarian and hedonic value on users' engagement with the immersive experiences of presence and flow. An additional finding highlights the role of social norms in engagement and stickiness.

Rather than studying the effects of the immersive experiences of presence and flow from either a hedonic or a utilitarian perspective, the authors consider how immersive experiences shape both utilitarian and hedonic value, as well as their joint impact (along with that of social norms) on users' engagement and stickiness.

This study aims to determine the current state of research on sustainability in the context of human resource management (HRM) practices adopted by small and medium-sized enterprises (SMEs), identify the most important gaps and propose an agenda for future studies.

Through a systematic literature review (SLR), this study comprehensively examines the relevant literature on sustainability-related aspects of HRM in SMEs. It includes descriptive and thematic analyses of 29 research articles published in high-ranked academic journals selected from 506 records retrieved from four major databases (Scopus, Web of Science, ScienceDirect and EBSCOhost).

The findings suggest a growing interest in sustainability-related HRM in SMEs after 2020. Notably, most studies focused on green and social sustainability concerns, with limited attention to the triple bottom line (TBL) perspective. A detailed examination revealed variations among the three streams of research in terms of methodology, location of studies, nature of sustainability-HRM linkage and placement of HRM practices in research models. Despite these differences, positive effects of HRM practices on sustainability integration seem evident, including impacts on employee competences, behaviors and company-level outcomes.

This article is the first to systematically review the literature on the sustainability-HRM nexus specifically for SMEs. It contributes by identifying thematic clusters, methodological trends, contextual aspects and outcomes of sustainability-HRM integration, thereby laying the groundwork for future research.

Inscrutable machine learning (ML) models are part of increasingly many information systems. Understanding how these models behave, and what their output is based on, is a challenge for developers let alone non-technical end users.

The authors investigate how AI systems and their decisions ought to be explained for end users through a systematic literature review.

The authors’ synthesis of the literature suggests that AI system communication for end users has five high-level goals: (1) understandability, (2) trustworthiness, (3) transparency, (4) controllability and (5) fairness. The authors identified several design recommendations, such as offering personalized and on-demand explanations and focusing on the explainability of key functionalities instead of aiming to explain the whole system. There exists multiple trade-offs in AI system explanations, and there is no single best solution that fits all cases.

Based on the synthesis, the authors provide a design framework for explaining AI systems to end users. The study contributes to the work on AI governance by suggesting guidelines on how to make AI systems more understandable, fair, trustworthy, controllable and transparent.

This literature review brings together the literature on AI system communication and explainable AI (XAI) for end users. Building on previous academic literature on the topic, it provides synthesized insights, design recommendations and future research agenda.