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Social interaction in comment sections has become a key factor for backers' decision making in crowdfunding platforms. However, current research on the two-way social interaction in crowdfunding is insufficient, and there exist inconsistent conclusions. This study focuses on the social interaction between creators and backers and explores its influence on the successful exit of crowdfunding projects.

The extended Cox model is used for the empirical analysis of 1,988 crowdfunding projects on the Modian (www.modian.com) platform, a crowdfunding platform for cultural and creative projects in China. The two-way social interaction is reflected in comment quantity and sentiment, as well as reply rate.

Results reveal an inverted U-shaped relationship between comment quantity/sentiment and the successful exit of crowdfunding projects. This relationship is strengthened by high reply rate.

This study focuses on comment quantity and sentiment. The inverted U-shaped results reconcile previous conclusions. Replies from creators are regarded as a separate factor, and their moderating role is explained. The study research proves the importance of social interaction in crowdfunding platforms and provides suggestions for backers, creators and platform managers.

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 chapter provides an overview of the potential use of Intelligent Transport Systems (ITS) and associated artificial intelligence (AI) techniques in the land transport sector in an attempt to achieve related United Nations Sustainable Development Goals (SDGs) targets. ITS applications that have now been extensively tested worldwide and have become part of the everyday transport toolkit available to practitioners have been discussed. AI techniques applied successfully in specific ITS applications such as automatic traffic control systems, real-time image processing, automatic incident detection, safety management, road condition assessment, asset management and traffic enforcement systems have been identified. These methods have helped to provide traffic engineers and transport planners with novel ways to improve safety, mobility, accessibility and efficiency in the sector and thus move closer to achieving the various SDG targets pertaining to transportation.

This study longitudinally investigated the predictors and mediators of adolescent smartphone addiction by examining the impact of parental smartphone addiction at T1 on adolescent smartphone addiction at T3, as well as the separate and sequential role of adolescent self-esteem and depression at T2 as mediating factors.

This study used a hierarchical regression and the PROCESS macro (Model 6) to investigate research model by collecting 3,904 parent-adolescent pairs. Panel data were collected from three waves of the Korean Children and Youth Panel Survey (KCYPS).

First, the result showed that parental smartphone addiction at T1 significantly and positively predicted adolescent smartphone addiction at T3. Second, the serial mediation analysis revealed that the impact of parental smartphone addiction at T1 on adolescent smartphone addiction at T3 was mediated by adolescent self-esteem and depression at T2 independently and serially.

The findings enhance our comprehension of the impact of parental smartphone addiction, adolescent self-esteem and depression, on adolescent smartphone addiction.

Independent directors are important corporate decision participants and makers. Based on the Chinese cultural background, this paper interprets the listing order of independent directors as independent directors’ status, exploring their influence on the corporate research and development (R&D) behavior.

This paper studies A-share listed firms in China from 2008 to 2018 as the sample. The main method is ordinary least square (OLS) regression. We also use other methods to deal with endogenous problems, such as the firm fixed effect method, change model method, two-stage instrumental variable method, and Heckman two-stage method.

(1) Higher independent directors’ status attribute to more effective exertion of supervision and consultation function, and positively enhance the corporate R&D investment. The increase of the independent director’ status by one standard deviation will increase the R&D investment by 4.6%. (2) The above effect is more influential in firms with stronger traditional culture atmosphere, higher information opacity and higher performance volatility. (3) High-status independent directors promote R&D investment by improving the scientificity of R&D evaluation and reducing information asymmetry. (4) The enhancing effect of independent director’ status on R&D investment is positively associated with the firm’s patent output and market value.

This paper contributes to understanding the relationship between the independent directors’ status and their duty execution from an embedded cultural background perspective. The findings of the study enlighten the improvement of corporate governance efficiency and the healthy development of the capital market.

Aluminum alloy is considered an ideal material in aerospace, automobile and other fields because of its lightweight, high specific strength and easy processing. However, low hardness and strength of the surface of aluminum alloys are the main factors that limit their applications. The purpose of this study is to obtain a composite coating with high hardness and lubricating properties by applying GO–PVA over MAO coating.

A pulsed bipolar power supply was used as power supply to prepare the micro-arc oxidation (MAO) coating on 6061 aluminum sample. Then a graphene oxide-polyvinyl alcohol (GO–PVA) composite coating was prepared on MAO coating for subsequent experiments. Samples were characterized by Fourier infrared spectroscopy, X-ray diffraction, Raman spectroscopy and thermogravimetric analysis. The friction test is carried out by the relative movement of the copper ball and the aluminum disk on the friction tester.

Results showed that the friction coefficient of MAO samples was reduced by 80% after treated with GO–PVA composite film.

This research has made a certain contribution to the surface hardness and tribological issues involved in the lightweight design of aluminum alloys.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0427/

Recently, online learning and online environments have become even more important. Students' engagement, fear of missing out and Internet addiction are seen as interrelated components that affect students' online teaching and learning process. In this context, university students' engagement, fear of missing out and Internet addiction in online environments, the relationship among them and students' demographic characteristics, online environment usage status and Internet usage profiles as their predictors are examined in this study.

This is a relational study and is carried out with 179 university students. Personal information form, student's engagement, fear of missing out and Internet addiction scales were used as data collection tools. Descriptive statistics, t-test, one-way ANOVA, correlation, hierarchical linear multiple regression analysis are used for the analysis.

According to the results, variables related to students' demographic characteristics, online environment usage status and Internet usage profiles together significantly predict the students' engagement, fear of missing out and Internet addiction in online environments. When students think positively about taking courses online, their engagement increases accordingly and their fear of missing out levels decrease. Increase in student's academic achievement leads to decline in Internet addiction.

In practice, examining the related variables about students in terms of engagement to the learning environment, fear of missing out and Internet addiction could bring a new perspective to studies on problematic use of the Internet and technology such as nomophobia and digital distraction. The results of this study reveal how and which components to be focused on for increasing the university students' engagement, reducing Internet addiction and fear of missing out in online learning environments.

The findings of this study provide a versatile perspective with the variables of student participation, fear of missing out, Internet addiction and their predictors in online learning environments, which are becoming widespread and increasingly important today and shed light on future researches.

In a boundary layer ingestion (BLI) propulsion system, the fan operates continuously under distorted inflow conditions, leading to an increment of aerodynamic loss and in turn impacting the potential fuel burn reduction of the aircraft. Usually, in the preliminary design stage of a BLI propulsion system, it is essential to assess the impact of fuselage boundary layer fluids on fan aerodynamic performances under various flight conditions. However, the hub region flow loss is one of the major loss sources in a fan and would greatly influence the fan performances. Moreover, the inflow distortion also results in a complex and highly nonlinear mapping relation between loss and local physical parameters. It will diminish the prediction accuracy of the commonly used low-fidelity computational approaches which often incorporate traditional physics-based loss models, reducing the reliability of these approaches in evaluating fan performances. Meanwhile, the high-fidelity full-annulus unsteady Reynolds-averaged Navier–Stokes (URANS) approach, even though it can give rather accurate loss predictions, is extremely time-consuming. This study aims to develop a fast and accurate hub loss prediction method for a BLI fan under distorted inflow conditions.

This paper develops a data-driven hub loss prediction method for a BLI fan under distorted inflows. To improve the prediction accuracy and applicability, physical understandings of hub flow features are integrated into the modeling process. Then, the key physical parameters related to flow loss are screened by conducting a sensitivity analysis of influencing parameters. Next, a quasi-steady assumption of flow is made to generate a training sample database, reducing the computational time by acquiring one single sample from the highly time-consuming full-annulus URANS approach to a cost-efficient single-blade-passage approach. Finally, a radial basis function neural network is used to establish a surrogate model that correlates the input parameters and the output loss.

The data-driven hub loss model shows higher prediction accuracy than the traditional physics-based loss models. It can accurately capture the circumferentially and radially nonuniform variation trends of the losses and the associated absolute magnitudes in a BLI fan under different blade load, inlet distortion intensity and rotating speed conditions. Compared with the high-fidelity full-annulus URANS results, the averaged relative prediction errors of the data-driven hub loss model are kept less than 10%.

The originality of this paper lies in developing a new method for predicting flow loss in a BLI fan rotor blade hub region. This method offers higher prediction accuracy than the traditional loss models and lower computational time cost than the full-annulus URANS approach, which could realize fast evaluations of fan aerodynamic performances and provide technical support for designing high-performance BLI fans.

The purpose of this paper is to propose a system dynamic simulated process model for maintenance work management incorporating the Fourth Industrial Revolution (4IR) technologies.

The extant literature in physical assets maintenance depicts that poor maintenance management is predominantly because of a lack of a clearly defined maintenance work management process model, resulting in poor management of maintenance work. This paper solves this complex phenomenon using a combination of conceptual process modeling and system dynamics simulation incorporating 4IR technologies. A process for maintenance work management and its control actions on scheduled maintenance tasks versus unscheduled maintenance tasks is modeled, replicating real-world scenarios with a digital lens (4IR technologies) for predictive maintenance strategy.

A process for maintenance work management is thus modeled and simulated as a dynamic system. Post-model validation, this study reveals that the real-world maintenance work management process can be replicated using system dynamics modeling. The impact analysis of 4IR technologies on maintenance work management systems reveals that the implementation of 4IR technologies intensifies asset performance with an overall gain of 27.46%, yielding the best maintenance index. This study further reveals that the benefits of 4IR technologies positively impact equipment defect predictability before failure, thereby yielding a predictive maintenance strategy.

The study focused on maintenance work management system without the consideration of other subsystems such as cost of maintenance, production dynamics, and supply chain management.

The maintenance real-world quantitative data is retrieved from two maintenance departments from company A, for a period of 24 months, representing years 2017 and 2018. The maintenance quantitative data retrieved represent six various types of equipment used at underground Mines. The maintenance management qualitative data (Organizational documents) in maintenance management are retrieved from company A and company B. Company A is a global mining industry, and company B is a global manufacturing industry. The reliability of the data used in the model validation have practical implications on how maintenance work management system behaves with the benefit of 4IR technologies' implementation.

This research study yields an overall benefit in asset management, thereby intensifying asset performance. The expected learnings are intended to benefit future research in the physical asset management field of study and most important to the industry practitioners in physical asset management.

This paper provides for a model in which maintenance work and its dynamics is systematically managed. Uncontrollable corrective maintenance work increases the complexity of the overall maintenance work management. The use of a system dynamic model and simulation incorporating 4IR technologies adds value on the maintenance work management effectiveness.

This paper seeks to examine how leaders shape employee creativity by using interpersonal emotion management (IEM) strategies. Drawing on the social information processing (SIP) theory, the authors argue that psychological safety translates leader problem-focused IEM into employee creativity, an impact which is moderated by organizational justice.

Data were collected in two waves from 201 employees and their leaders in China. Regression analysis was used to test the hypotheses.

Leader problem-focused IEM is positively related to employee creativity, and this relationship is mediated by psychological safety. Organizational justice positively moderates the relationship between leader problem-focused IEM and psychological safety as well as the indirect relationship between leader problem-focused IEM and employee creativity via psychological safety.

This paper identifies a novel and useful predictor of employee creativity from the perspective of leader problem-focused IEM and provides practical insights for organizations regarding ways of improving employee creativity.