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The safety of high-speed rail operation environments is an important guarantee for the safe operation of high-speed rail. The operating environment of the high-speed rail is complex, and the main factors affecting the safety of high-speed rail operating environment include meteorological disasters, perimeter intrusion and external environmental hazards. The purpose of the paper is to elaborate on the current research status and team research progress on the perception of safety situation in high-speed rail operation environment and to propose directions for further research in the future.

In terms of the mechanism and spatio-temporal evolution law of the main influencing factors on the safety of high-speed rail operation environments, the research status is elaborated, and the latest research progress and achievements of the team are introduced. This paper elaborates on the research status and introduces the latest research progress and achievements of the team in terms of meteorological, perimeter and external environmental situation perception methods for high-speed rail operation.

Based on the technical route of “situational awareness evaluation warning active control,” a technical system for monitoring the safety of high-speed train operation environments has been formed. Relevant theoretical and technical research and application have been carried out around the impact of meteorological disasters, perimeter intrusion and the external environment on high-speed rail safety. These works strongly support the improvement of China’s railway environmental safety guarantee technology.

With the operation of CR450 high-speed trains with a speed of 400 km per hour and the application of high-speed train autonomous driving technology in the future, new and higher requirements have been put forward for the safety of high-speed rail operation environments. The following five aspects of work are urgently needed: (1) Research the single factor disaster mechanism of wind, rain, snow, lightning, etc. for high-speed railways with a speed of 400 kms per hour, and based on this, study the evolution characteristics of multiple safety factors and the correlation between the high-speed driving safety environment, revealing the coupling disaster mechanism of multiple influencing factors; (2) Research covers multi-source data fusion methods and associated features such as disaster monitoring data, meteorological information, route characteristics and terrain and landforms, studying the spatio-temporal evolution laws of meteorological disasters, perimeter intrusions and external environmental hazards; (3) In terms of meteorological disaster situation awareness, research high-precision prediction methods for meteorological information time series along high-speed rail lines and study the realization of small-scale real-time dynamic and accurate prediction of meteorological disasters along high-speed rail lines; (4) In terms of perimeter intrusion, research a multi-modal fusion perception method for typical scenarios of high-speed rail operation in all time, all weather and all coverage and combine artificial intelligence technology to achieve comprehensive and accurate perception of perimeter security risks along the high-speed rail line and (5) In terms of external environment, based on the existing general network framework for change detection, we will carry out research on change detection and algorithms in the surrounding environment of high-speed rail.

In this chapter, the authors provide a historical overview of the development of comparative and international education societies throughout the earth. In most cases, these societies have gradually grown and continue to thrive; in other cases, some comparative education societies have become dormant and a few no longer exist. A historical analysis that outlines the rise and fall of comparative education societies is provided. An overview of the World Council of Comparative Education Societies is also discussed, including its lead organizational role in serving as a historical hub to help comparative education societies preserve and disseminate their respective histories. The chapter concludes with suggestions on how anyone can get involved to help contribute to the history preservation of comparative education at the individual, national, regional, and global levels.

Drawing on experiential learning theory, this study seeks to understand how the perceived cultural difference in a foreign country and learning flexibility, which enables more integrated experiential learning from international experience, influence expatriates’ cultural intelligence (CQ) and consequently their adjustment and job performance.

Survey data were collected from 169 expatriates in China. Polynomial regression analyses were employed to test curvilinear relationships between cultural difference and CQ and between learning flexibility and CQ. Mediation hypotheses were tested either by the MEDCURVE procedure if a curvilinear relationship was confirmed or by the Haye’s Process procedure if a curvilinear relationship was not confirmed and instead a linear relationship was confirmed.

The results demonstrated a positive relationship between cultural difference and CQ and an inverted U-shape relationship between learning flexibility and CQ. CQ mediated the relationship between cultural difference and expatriate adjustment and partially mediated the relationship between learning flexibility and expatriate adjustment. CQ positively influenced expatriates’ job performance via expatriate adjustment.

Our findings suggest that companies should not hesitate to send expatriates on assignments to culturally very different countries and focus more attention on the selection of expatriates. The findings of this study suggest firms should choose candidates who are moderate or high in learning flexibility and could engage in integrated learning and specialized learning in a more balanced manner.

This research is the first study that examines the influence of learning flexibility on CQ and expatriate effectiveness. It examines cultural difference through the lens of experiential learning theory and argues that cultural difference constitutes “stimuli” in the experiential learning environment for individual learning in an international context. The results advance our knowledge of the role of experiential learning in developing capable global managers.

The purpose of this research was to examine the influence of entrepreneurial orientation on social performance and the influence of social performance on financial performance of microfinance institutions (MFIs) in Indonesia. These tests use environmental dynamism as antecedents.

The research was conducted on a sample of 235 CEOs/top leaders of MFIs spread across all provinces in Indonesia. Data collection used survey questionnaires. Data testing used SPSS version 25, and structural modeling used Amos version 25.

The findings show that entrepreneurial orientation significantly influences the social performance of MFIs in Indonesia. Entrepreneurial orientation does not influence financial performance but must go through social performance mediation. Social performance has a significant effect on financial performance. The importance of MFIs improves social performance (depth and breadth of reach) to improve financial performance.

MFIs need to increase social contribution and responsibility to improve social performance which will impact financial performance.

Entrepreneurial orientation influence on financial performance goes through social performance. Social performance includes the depth of the reach to contribute to improving the quality of life of people experiencing poverty around the MFI's operations and the social responsibility of MFIs to the community through scholarships, free medical assistance, basic food assistance and building/renovating houses of worship and others.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2023-0478

Considering that when endorsing the same product, virtual influencers with different identity types (self-created, collaborative) can have different impacts on consumers' purchasing behaviors, this paper aims to explore how to maximize the impact effects of the VIs' respective identities. It provides companies with new perspectives on endorsement strategies.

The interaction between VI identity type and post type (informational, storytelling) on purchase intention was analyzed in four experiments (N = 1,007), considering informational and normative social influence as intermediate mechanisms and consumer self-construal as moderators.

The findings show that self-created VI is suited to informational posts and collaborative VI to storytelling posts. This identity-content match effectively triggers the social influence mechanism: informational posts of self-created VI significantly enhance informational social influence. In contrast, storytelling posts of collaborative VI primarily stimulate normative social influence. Consumer self-construal also moderates the process of influencing mechanisms.

Based on social influence theory and matching theory, this paper confirms the existence of an interaction between VI identity types, which influences consumers' purchase intention through informational and normative social influence. This finding fills the research gap in the field of VI endorsement strategy. It also emphasizes the importance of consumer self-construal and contributes new insights into the related field.

Recent years have witnessed the rapid development of massive open online courses (MOOCs). With more and more courses being produced by instructors and being participated by learners all over the world, unprecedented massive educational resources are aggregated. The educational resources include videos, subtitles, lecture notes, quizzes, etc., on the teaching side, and forum contents, Wiki, log of learning behavior, log of homework, etc., on the learning side. However, the data are both unstructured and diverse. To facilitate knowledge management and mining on MOOCs, extracting keywords from the resources is important. This paper aims to adapt the state-of-the-art techniques to MOOC settings and evaluate the effectiveness on real data. In terms of practice, this paper also tries to answer the questions for the first time that to what extend can the MOOC resources support keyword extraction models, and how many human efforts are required to make the models work well.

Based on which side generates the data, i.e instructors or learners, the data are classified to teaching resources and learning resources, respectively. The approach used on teaching resources is based on machine learning models with labels, while the approach used on learning resources is based on graph model without labels.

From the teaching resources, the methods used by the authors can accurately extract keywords with only 10 per cent labeled data. The authors find a characteristic of the data that the resources of various forms, e.g. subtitles and PPTs, should be separately considered because they have the different model ability. From the learning resources, the keywords extracted from MOOC forums are not as domain-specific as those extracted from teaching resources, but they can reflect the topics which are lively discussed in forums. Then instructors can get feedback from the indication. The authors implement two applications with the extracted keywords: generating concept map and generating learning path. The visual demos show they have the potential to improve learning efficiency when they are integrated into a real MOOC platform.

Conducting keyword extraction on MOOC resources is quite difficult because teaching resources are hard to be obtained due to copyrights. Also, getting labeled data is tough because usually expertise of the corresponding domain is required.

The experiment results support that MOOC resources are good enough for building models of keyword extraction, and an acceptable balance between human efforts and model accuracy can be achieved.

This paper presents a pioneer study on keyword extraction on MOOC resources and obtains some new findings.

The present research attempts to address what kinds of attitude variables influence individuals' debt behavior. Although credit card debt has been extensively documented recently, the main focus is on the pure amount of debt. Little research is concerned with the source of credit card debt. This research tries to investigate how different attitude variables affect revolving credit card use and petty installment use which are two main sources of credit card debt. It is generally accepted that attitude variables are one of the causes of credit card misuse. But there is no research to compare the differential effect of each factor in one model. The present research tries to use statistical method to find out the distinctive effect of each attitude factor.

The study was conducted by using mail‐in questionnaires, which were sent to credit card holders who were using or had used either revolving credit or petty installment plans. After reliability and validity tests, stepwise regression model has been used to test the differential effect of each attitude variable.

According to regression functions, it was found that attitude variables had a wonderful explanatory power in accounting for revolving credit use and petty installment use. Specifically, it was found that revolving credit use and petty installment use were closely related to attitudes about credit card, money, and debt. Risk attitude efficiently predicted petty installment use; however, it did not correlate with revolving credit use. Meanwhile, it was found that all of the attitude factors account for 82.1 percent of variance for revolving credit use. In contrast, they account for 41.6 percent of variance for petty installment use. The findings shed light on the role of attitude variables in debt behavior. Moreover, the paper identifies the specific role of different attitude variables, which has great implications for practice.

Existing research has significantly clarified credit card debt issues, but there are still some gaps to fill in. For one, although the previous literature tests both separate effects and joint effects, it ignores some important variables, such as attitude variables. Meanwhile, previous research focuses on single variables most of the time, such as credit card attitude and debt attitude, and little research has simultaneously considered a bunch of attitude factors simultaneously. In summary, further exploration of the attitude factors is necessary. Additionally, previous researchers have focused only on the final consequences of credit usage – the outstanding balance or credit card debt rather than the behavior which triggers credit card debt. The present research aims to address these two questions.

The purpose of this paper is to improve the customer satisfaction by offering online personalized recommendation system.

By employing an innovative associative classification method, this paper is able to predict a customer’s pleasure during the online while-recommending process. Consumers can make an active decision to recommended products. Based on customer’s characteristics, a product will be recommended to the potential buyer if the model predicts that he/she will click to view the product. That is, he/she is satisfied with the recommended product. Finally, the feasibility of the proposed recommendation system is validated through a Taobao shop.

The results of the experimental study clearly show that the online personalized recommendation system maximizes the customer’s satisfaction during the online while-recommending process based on an innovative associative classification method on the basis of consumer initiative decision.

Conventionally, customers are considered as passive recipients of the recommendation system. However, customers are tired of the recommendation system, and they can do nothing sometimes. This paper designs a new recommendation system on the basis of consumer initiative decision. The proposed recommendation system maximizes the customer’s satisfaction during the online while-recommending process.

This paper aims to investigate the role that institutional shareholders play in acquisition decisions using micro data in the Chinese stock market during 2003‐2008.

Acquisition decision is the selection and coordination process of shareholders as strategic alliances, which is determined by corporate acquisition ability, composition of institutional shareholders and concentration of tradable share (TS) in China. The paper uses the Heckman selection model to surmount the selection biases in acquisition decision.

The paper finds that institutional shareholders, including qualified foreign institutional investors (QFII), social security funds (SSF), security firms (SF) and security investment funds (SIF), as well as TS concentration, affect acquisition probability rather than annual acquisition scale. SSF, SIF and TS concentration can increase acquisition probability while QFII decreases it.

This paper suggests a strategic alliance model in which institutional shareholders choose whether to collaborate with controlling shareholders and management. However, detailed information of the selection and coordination process is unavailable in the authors' data. Future research need provide more evidence of this postulate.

The paper contributes to the published literature in three ways. First, it offers a model to understand the selection and coordination process of acquisition decision. Second, it investigates whether institutional shareholders could effectively monitor annual acquisition scale. Third, it identifies the Heckman selection problem that institutional shareholders could affect PLCs' acquisition decision on whether to acquire rather than how much to acquire.