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In the online marketing context, virtual reality (VR) has been used to display products and shopping environment, which effectively enhances the consumer experience. VR technology can not only recreate scenes similar to the real world (virtual authenticity, VA) but also create fictitious and desirable scenes that do not exist in the real world (virtual ideality, VI). The differences between VA and VI in influencing consumers' responses have not been fully understood. In addition, social signals have appeared in VR apps. However, the role of social signals in a VR context has rarely been studied. To fill the gaps in the literature, this study investigates the roles of VA and VI in shaping consumers' responses, as well as whether and how their effectiveness in shaping consumers' responses is influenced by social signals.

A VR real estate service platform was selected as the experimental platform, and two experiments were conducted to test the hypotheses. The ANOVAs and regressions were used for data analysis.

Results show that VA leads to a higher level of perceived diagnosticity than VI, whereas VI leads to a higher level of inspiration than VA; perceived diagnosticity and inspiration positively affect visit intention. Furthermore, the relationship between consumers' perceived diagnosticity, inspiration and visit intention is moderated by the presence of social signals.

The study revealed the differences between VA and VI in shaping consumers' responses, as well as the effect of social signals in VR environment, which provide a new perspective for future VR research in the context of interactive marketing.

This study focused on parents' health anxiety by proxy about their children when they started learning online during the COVID-19 pandemic, to explore the impact of academic stress by parent-proxy on parents' learning support services with the mediating role of health anxiety by parent-proxy and the moderating role of parental educational level.

In total, 8,940 primary school students' parents participated in the study. Bootstrapping was performed to test the constructed model.

(1) Academic stress by parent-proxy positively predicted health anxiety by parent-proxy. (2) Health anxiety by parent-proxy significantly positively predicted learning support services. (3) Academic stress by parent-proxy also significantly positively predicted learning support services. (4) Academic stress by parent-proxy positively predicted parents' learning support services through the mediating effect of health anxiety by parent-proxy. (5) Parental educational level moderated the relationship between academic stress by parent-proxy, health anxiety by parent-proxy, and learning support services. Academics and parents will benefit from the conclusions of this study in both theory and practice.

During the COVID-19 pandemic, offline learning has been replaced with online learning, which has brought with it many physical and mental health problems, including additional academic stress. Most studies on learning support services have focused on offline learning. However, this study explored the relationships between academic stress by parent-proxy, health anxiety by parent-proxy, learning support services, and parental educational level in the context of online learning. Results show that it is necessary to pay attention to academic stress and health to provide children with appropriate learning support services.

The purpose of this paper is to study the influence of alkyl chain length and kind of anions of ionic liquids on the tribological properties with different materials as friction pairs (steel-aluminum, steel-copper and steel-Si3N4 ceramic).

Tribological properties were evaluated by an optimol-SRV-IV reciprocation friction tester with a ball-on-block configuration at room temperature and high temperature, respectively. Friction-reducing and anti-wear properties of the ionic liquids for steel/aluminum, steel/copper and steel/ceramic contacts were evaluated on the ball-on-block reciprocating UMT-2MT tribometer. The morphologies of the worn surfaces were observed by a scanning electron microscope. The chemical states of several typical elements on the worn surfaces were examined by X-ray photoelectron spectroscopy.

Both the alkyl chain length and kind of anion influence the tribological properties of ionic liquids, especially for the length of alkyl chains. With the increase of alkyl chain length, the load carrying capacity of ionic liquids is improved at both room temperature and high temperature, and the friction reducing and antiwear behaviors are also significantly enhanced.

The paper presents potentially useful and highly efficient lubricants.

Owing to their good friction-reducing and wear resistance properties, these ionic liquids are promising candidates for versatile applications.

This work might provide a promising research direction for design and application of ionic liquids as lubricants.

Continuance usage of mobile applications (apps) has attracted much attention from scholars and enterprises, while the extant research mainly focuses on continuance intention. The inner effect mechanism of the characteristics of apps is still unclear. Under the tenet of continuance usage behaviour, through analysis of characteristics derived from online reviews, this paper aims to establish an effective model and discloses the commonalities and differences between two mainstream apps, which are entertainment and knowledge apps.

The authors collected reviews of TikTok and Zhihu, which are typical representatives of entertainment and knowledge apps, respectively, from 2018 to 2020. They then derive effect factors and establish the effect model using grounded theory. A deep comparison is then conducted. They analysed the similarities and differences in the general effect model, internal effect mechanism and detailed characteristics of the two types of apps.

Entertainment app and knowledge apps share the same general effect mechanism; that is, the effect chain of characteristics to perceived value then finally to continuance usage behaviour. However, obvious differences also exist in detailed and specific effects between the two apps.

The present research is among the first to have a deep analysis of the comparison of entertainment apps and knowledge apps under the context of continuance usage behaviour. The findings contribute to understanding continuance usage behaviours. Suggestions are proposed on how to promote apps, which may benefit app managers.

To reduce the wheel maintenance costs caused by wheel wear and to transition from traditional periodic maintenance to condition-based maintenance for railway freight wagons, it is necessary to investigate the prediction of wheel wear and understand the evolution rule of wheel profile wear.

This paper established a wheel wear prediction model for railway freight wagons based on Archard’s wear theory and proposed a prediction method that combines vehicle system dynamic, interpolation iteration and intelligent simulation. The wear coefficients in the model were obtained through wheel wear tests by using the roller rig. The model’s effectiveness was further verified through line testing and simulation models, and the corrected wear coefficient can be used for wear prediction of heavy-haul freight wagons in China.

The wheel wear prediction showed that the results of the wheel wear prediction model by adopting the wear coefficients obtained from the roller rig tests are close to the actual wheel wear, with the difference of the maximum in wear depth at the nominal rolling circle being within 7%.

This paper proposed a method that can establish a database of wheel wear coefficients for predicting wheel wear of railway freight wagons under similar operating conditions. The revised wear coefficient can be used for wear prediction of heavy-haul freight wagons in China.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2024-0329/

The purpose of this paper is to analyse the publication of big data in the library from Scopus database by looking at the writing time period of the papers, author's country, the most frequently occurring keywords, the article theme, the journal publisher and the group of keywords in the big data article. The methodology used in this study is a quantitative approach by extracting data from Scopus database publications with the keywords “big data” and “library” in May 2019. The collected data was analysed using Voxviewer software to show the keywords or terms. The results of the study stated that articles on big data have appeared since 2012 and are increasing in number every year. The big data authors are mostly from China and America. Keywords that often appear are based on the results of terminology visualization are including, “big data”, “libraries”, “library”, “data handling”, “data mining”, “university libraries”, “digital libraries”, “academic libraries”, “big data applications” and “data management”. It can be concluded that the number of publications related to big data in the library is still small; there are still many gaps that need to be researched on the topic. The results of the research can be used by libraries in using big data for the development of library innovation.

The Scopus database was accessed on 24 May 2019 by using the keyword “big data” and “library” in the search box. The authors only include papers, which title contain of big data in library. There were 74 papers, however, 1 article was dropped because of it not meeting the criteria (affiliation and abstract were not available). The papers consist of journal articles, conference papers, book chapters, editorial and review. Then the data were extracted into excel and analysed as follows (by the year, by the author/s’s country, by the theme and by the publisher). Following that the collected data were analysed using VOX viewer software to see the relationship between big data terminology and library, terminology clustering, keywords that often appear, countries that publish big data, number of big data authors, year of publication and name of journals that publish big data and library articles (Alagu and Thanuskodi, 2019).

It can be concluded that the implementation of big data in libraries is still in an early stage, it is shown from the limited number of practical implementation of big data analytics in library. Not many libraries that use big data to support innovation and services since there were lack of librarian skills of big data analytics. The library manager’s view of big data is still not necessary to do. It is suggested for academic libraries to start their adoption of big data analytics to support library services especially research data. To do so, librarians can enhance their skills and knowledge by following some training in big data analytics or research data management. The information technology infrastructure also needs to be upgraded since big data need big IT capacity. Finally, the big data management policy should be made to ensure the implementation goes well.

This paper discovers the adoption and implementation of big data in library, many papers talk big data in business and technology context. This is offering new idea for many libraries especially academic library about the adoption of big data to support their services. They can adopt the big data analytics technology and technique that suitable for their library.