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In the paradox of personalized services and privacy risks, what factors influence users’ decisions is considered an interesting issue worth exploring. The current study aims to empirically explore privacy behavior of social media users by developing a theoretical model based on privacy calculus theory.

Privacy risks, conceptualized as natural risks and integrated risks, were proposed to affect the intention of privacy disclosure and protection. The model was validated through a hybrid approach of structural equation modeling (SEM)-artificial neural network (ANN) to analyze the data collected from 527 effective responses.

The results from the SEM analysis indicated that social interaction and perceived enjoyment were strong determinants of perceived benefits, which in turn played a dominant role in the intention to disclose the privacy in social media. Similarly, trust and privacy invasion experience were significantly related to perceived risks that had the most considerable effect on users’ privacy protection intention. And the following ANN models revealed consistent relationships and rankings with the SEM results.

This study broadened the application perspective of privacy calculus theory to identify both linear and non-linear effects of privacy risks and privacy benefits on users’ intention to disclose or protect their privacy by using a state-of-the-art methodological approach combining SEM and ANN.

The purpose of this paper is to explain how sociability and usability enhanced members’ satisfaction, and how such satisfaction in turn, influenced their continuance intention of knowledge sharing in academic virtual communities (AVCs).

Drawing on social capital theory and technology acceptance model, this study proposed a theoretical socio-technical model, and the partial least squares method is used to examine the proposed model, based on data collected from 431 subjects in a well-known academic community in China (i.e. ScienceNet).

Both sociability and usability were important to improve members’ satisfaction with knowledge sharing in AVCs. Specifically, social interaction ties, trust, reciprocity, shared vision, perceived ease of use and perceived usefulness are antecedents of members’ satisfaction, which in turn positively affects their continuance intention of knowledge sharing in AVCs.

This study provided insights that can help AVCs’ administrators develop effective strategies that could encourage continued knowledge sharing behavior through promoting members’ satisfaction.

While the socio-technical framework has mainly been used to study initial adoption and participation of knowledge sharing. This study proposed a socio-technical model to move a step forward by explaining the exact roles of sociability and usability in terms of promoting members’ satisfaction and identifying its critical effect on their continuance intention to share knowledge in AVCs, leading to a more comprehensive picture of members’ satisfaction and continuance intention of knowledge sharing in AVCs.

To determine the factors influencing the perception of undergraduate students toward research–teaching nexus and also to examine its impact on the attitude of the students.

The study used a quantitative design to examine the perceptions of students in higher education institutions in India. Descriptive and inferential statistics were used to describe the data and test the hypothesis. The data was collected using a structured questionnaire for a sample of 188 students from higher education institutions (HEIs). Further, in line with the purpose of the study and to test the hypotheses, the study used descriptive statistics, exploratory factor analysis and multivariate regression analysis.

The study demonstrates that the factors influencing the perception of undergraduate students toward research teaching nexus were identified using principal component analysis (PCA) with varimax rotation, conducted on 27 measurement items. In addition, the results of the multivariate regression analysis indicated that research-based, research-tutored and research motivation dimensions, significantly impact the graduate students' perception of research–teaching nexus.

The outcomes of this research may become valid input to HEI regulators, researchers and teachers while framing the policies and implementation of the same about the pertinent issues discussed in the paper. Further, it contributes to the existing theory that teaching–research quality and level of motivation are also the predominant factors influencing the teaching–research nexus among students. In addition, the outcome of this paper also supports HEIs to achieve the United Nations Sustainable Development Goals (UNSDGs) at large.

This study contributes to the ongoing debate and scarce literature on research–teaching nexus at the higher education level. The factors derived in this paper propose a framework for aligning teaching and research in academic programs to create high-quality human resource in the nation.

Hazard warning schemes provide efficient hazard recognition and promote project safety. Nevertheless, these schemes perform poorly because the warning information is calibrated for individual characters and is not prioritized for the entire system. This study proposes a hazard warning scheme that prioritizes hazard characters from the inspection process based on the inspectors' experience.

First, hazard descriptions were decomposed into their characters, forming a double-layer network. Second, warning schemes based on cascading effects were proposed. Third, character-based warning schemes were simulated for various experiences.

The results show that when a specific hazard is detected, the degree centrality is the most effective parameter for prioritization, and hazard characters should be prioritized based on betweenness centrality for experienced inspectors, whereas degree centrality is preferred for novice inspectors.

The warning scheme theoretically supplements the information-processing theory in construction hazard warnings and provides a practical warning scheme with priority for the development of automated hazard navigation systems.

The purpose of this paper was to improve the frictional wear resistance properties of piston skirts caused by the low viscosity lubricant by studying the tribological performance of three novel coating materials.

Comparative tribological examinations were performed in a tribological tester using the ring-block arrangement under two viscosity lubricants, the loading force was applied as 100 N, the speed was set to 60 r/min and the testing time was 180 min.

Under low viscosity lubricant, the friction coefficient and wear of the three coatings all increase, and the friction coefficient and wear of the PTFE coating are the largest, while the MoS₂ coating has the lowest friction coefficient and wear. Under low viscosity lubricant, the friction coefficient of the MoS₂ coating is 2.1%–5.4% and 20.0%–24.3% lower than that of the SiO2 and PTFE coating, respectively. The friction coefficient and wear fluctuation rate of the MoS₂ coating is the smallest when the lubricant viscosity decreases, which indicates that the MoS₂ coating has excellent stability and adaptability under low viscosity lubricant.

To reduce the piston skirt wear caused by low viscosity lubricant in heavy-duty diesel engines, the friction and wear adaptability of three novel composite coating materials for piston skirts were compared under 0 W-20 low viscosity lubricant, which could provide a guidance for the application of wear-resistant materials for heavy-duty diesel engine piston skirt.