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The substantial cost of employee cyberloafing to organizations calls for research into exploring the factors that influence such behavior. Drawing upon social cognitive theory, the authors develop a theoretical model that unpacks when and why leader forgiveness induces employee cyberloafing. Specifically, the authors identify moral disengagement as a linking mechanism and employee empathic concern as a key boundary condition in the association between leader forgiveness and employee cyberloafing behaviors.

The authors conducted multilevel analyses to examine the authors' hypotheses by utilizing a sample of 71 supervisors and 306 direct reports.

Results showed that leader forgiveness encouraged employee cyberloafing via moral disengagement among employees with low empathic concern, whereas the indirect effect was not present among those with high empathic concern.

The authors contribute to the literature on cyberloafing and leader forgiveness. First, this study extends the cyberloafing research by considering leader forgiveness as an enabler, challenging the dominant notion that positive leader behaviors (e.g. leader mindfulness) constrain employee cyberloafing while negative leader behaviors (e.g. abusive supervision) elicit it. Second, although past studies have predominantly concentrated on the positive outcomes of forgiveness, the current research contributes to the balanced and comprehensive understanding of leader forgiveness by linking leader forgiveness with employee cyberloafing.

This article aims to understand users' information needs in the metaverse communities and to analyze the similarities and differences between their information needs and those of users in Internet communities.

This study conducted semi-structured interviews with users in the metaverse communities to gather raw data. Grounded theory research methods were employed to code and analyze the collected interview data, resulting in the extraction of 40 initial concepts, 15 subcategories and 5 main categories. Based on Maslow’s hierarchy of needs theory, this paper constructs the hierarchical model of users' information needs in the metaverse communities. It compares the differences between users' information needs in the metaverse and Internet fields.

The user’s information needs in the metaverse communities are divided into two types: deficiency needs and growth needs. Deficiency needs have two levels. The first level is the demand for basic information resources. The second level is the users demand for information assistance. Growth needs have three levels. The first level is the need for information interactions. The second level is the need for community rules. The ownership information in the community rules can provide proof of user status, assets and so on. The third level is the need for users to contribute and share their own created information content.

This article presents the latest research data from in-depth interviews with users in the metaverse communities. It aims to help builders and managers of metaverse communities understand users' information needs and improve the design of virtual communities.

This paper aims to focus on the research progress of intelligent self-healing anti-corrosion coatings in the aviation field in the past few years. The paper provides certain literature review supports and development direction suggestions for future research on intelligent self-healing coatings in aviation.

This mini-review uses a systematic literature review process to provide a comprehensive and up-to-date review of intelligent self-healing anti-corrosion coatings that have been researched and applied in the field of aviation in recent years. In total, 64 articles published in journals in this field in the last few years were analysed in this paper.

The authors conclude that the incorporation of multiple external stimulus-response mechanisms makes the coatings smarter in addition to their original self-healing corrosion protection function. In the future, further research is still needed in the research and development of new coating materials, the synergistic release of multiple self-healing mechanisms, coating preparation technology and corrosion monitoring technology.

To the best of the authors’ knowledge, this is one of the few systematic literature reviews on intelligent self-healing anti-corrosion coatings in aviation. The authors provide a comprehensive overview of the topical issues of such coatings and present their views and opinions by discussing the opportunities and challenges that self-healing coatings will face in future development.

This study aims to investigate the effect of post-treatment on anti-corrosion performance of Al coating on the surface of Ti-6Al-4V (TC4) fastener.

The Al coatings with different layer structures were prepared on TC4 by middle-frequency and direct-current combined magnetron sputtering. The cross-sectional morphology and surface roughness of coatings were characterized by scanning electron microscope and atomic force microscope. The corrosion resistance was evaluated by electrochemical method. The monolayer coating was post-treated by Alodine chemical conversion, Ar⁺ bombardment and a combination of two methods above.

The results show that the interfaces in bilayer and trilayer coatings reduce the defects. Ar⁺ bombardment reduces the corrosion current density, and Alodine chemical conversion leads to a higher pitting corrosion potential. The combined post-treatment has the highest polarization resistance.

The corrosion resistance of the Al coating is enhanced as the layer quantity increases. The combination of two post-treatments, Ar⁺ bombardment and Alodine chemical conversion, could achieve an overall improvement in corrosion resistance of Al coating.

Facilitated by image retouch tools, social media influencers can digitally enhance their self-image in product recommendation posts. This paper proposes that image enhancement may serve as a cue for the audience to assess the authenticity of the influencer (“true to oneself”), which further affects the influencer's product recommendation effectiveness (i.e. attitudes toward the post and recommended product).

Experiment 1 examines the effect of image enhancement on consumers' perceived influencer authenticity and product recommendation effectiveness. Experiment 2 considers the moderating role of post type, examining the effects in informational versus storytelling posts.

Consumers perceived an influencer to be more authentic when the image is not enhanced; in turn, consumers reported more favorable attitudes toward the post and the recommended product upon reading the post. The effects are moderated by post type: the effect of image enhancement (through perceived influencer authenticity) exists in posts using an informational message format but is attenuated for those using a storytelling message format.

This research enriches the literature on authenticity cues by documenting a novel visual cue and contributes to influencer marketing by identifying a nuanced interactive effect between image enhancement and post type on recommendation effectiveness.

This study aims to investigate the spatial distribution of housing prices and identify the affecting factors (independent variable) on the cost of residential units (dependent variable).

The method of the present study is descriptive-analytical and has an applied purpose. The used statistical population in this study is the residential units’ price in Tehran in 2021. For this purpose, the average per square meter of residential units in the city neighborhoods was entered in the geographical information system. Two techniques of ordinary least squares regression and geographically weighted regression have been used to analyze housing prices and modeling. Then, the results of the ordinary least squares regression and geographically weighted regression models were compared by using the housing price interpolation map predicted in each model and the accurate housing price interpolation map.

Based on the results, the ordinary least squares regression model has poorly modeled housing prices in the study area. The results of the geographically weighted regression model show that the variables (access rate to sports fields, distance from gas station and water station) have a direct and significant effect. Still, the variable (distance from fault) has a non-significant impact on increasing housing prices at a city level. In addition, to identify the affecting variables of housing prices, the results confirm the desirability of the geographically weighted regression technique in terms of accuracy compared to the ordinary least squares regression technique in explaining housing prices. The results of this study indicate that the housing prices in Tehran are affected by the access level to urban services and facilities.

Identifying factors affecting housing prices helps create sustainable housing in Tehran. Building sustainable housing represents spending less energy during the construction process together with the utilization phase, which ultimately provides housing at an acceptable price for all income deciles. In housing construction, the more you consider the sustainable housing principles, the more sustainable housing you provide and you take a step toward sustainable development. Therefore, sustainable housing is an important planning factor for local authorities and developers. As a result, it is necessary to institutionalize an integrated vision based on the concepts of sustainable development in the field of housing in the Tehran metropolis.