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The purpose of this paper is to investigate the effect of nano-alumina sealant sealing treatment on corrosion behavior of the Fe-based amorphous coatings deposited on 304 stainless steel plates by atmospheric plasma spraying (APS) with different hydrogen flow rates.

The surface morphology and microstructure of the unsealed and sealed coatings were characterized by scanning electron microscopy and X-ray diffraction. The corrosion resistance of the coatings was investigated by potentiodynamic polarization test and electrochemical impedance spectroscopy experiment in 3.5 Wt.% NaCl solution.

Results show that a few microcracks and pores exist in the as-sprayed Fe-based amorphous coatings. The pores on the surface of the coatings after sealing treatment have been filled with nano-alumina sealant, which can effectively prevent corrosive medium from entering into coatings. Electrochemical tests results show that the corrosion resistance of the coatings before sealing treatment decreases with the increase of hydrogen flow rate and is significantly improved by sealing treatment.

The effect of nano-alumina sealant sealing treatment on corrosion resistance of APS-sprayed Fe-based amorphous coatings is revealed. The corrosion resistance of the as-sprayed Fe-based amorphous coating can be significantly improved by nano-alumina sealant sealing treatment because of the blocking effect of nano-alumina sealant on corrosive medium, which confirms that the application of nano-alumina sealant sealing treatment is of a practical option to improve corrosion resistance of as-sprayed thermal sprayed coatings.

The purpose of the paper is to conduct an exploratory study that proposes a personalized knowledge integration platform for digital libraries which can provide users with personalized information and knowledge services.

A prototype system (PIKIP_DL) is designed and developed with two types of service, i.e. personalized information/knowledge service and personalized subject category service. Evaluation of the PIKIP_DL by domain specialists and software experts is conducted. Comments are implications are addressed.

The main findings include the following: the proposed system can help suggest materials that readers are interested in for DL; the proposed system can help construct knowledge contents in a hierarchical structure; and a common recommendation concerning knowledge structure from the reviewers is that the proposed system should add a self‐organizing knowledge map function that would allow users to view knowledge subjects in a graphic manner.

The results from the evaluation of reviewers revealed that the proposed PIKIP_DL is acceptable to the integration of both personalized information service and personalized knowledge subject service. This implies that librarians and DL software agents should place emphasis on integrated service development to attract the attention of their users. Towards this goal, they could explain that personalized services (e.g. material recommendation, message recommendation, knowledge subject materials) with a mechanism of multi‐resource integration can help provide DL resources according to users' needs and wants, and in consequence to enhance DL service efficacy.

The research describes the importance of information/knowledge integration with respect to its support on the learning and study methods of users, and has developed a personalized knowledge integration platform as a mechanism that provides a personalized information service and a personalized knowledge subject category service. By employing Apriori algorithm and association rules as the data mining mechanism, personalized information recommendations are derived from circulation data, and a knowledge subject category is integrated from online sharing knowledge by participants.

The purpose of this paper is to examine the determinants of user satisfaction in the context of academic web digital library (DL). A model based on the re-specified information system success model was developed and tested using the structural equation modeling (SEM) technique.

The study employed survey research methodology with self-administered questionnaire as the research instrument. The questionnaire was developed based on the instruments used by previous researchers. The population of the study was students enrolled for the bachelor’s degree in the Faculty of Information Management, Universiti Teknologi MARA, Malaysia. These students were chosen because of researcher’s easy access to the sampling frame. Descriptive analysis and inferential analysis which include SEM were executed using IBM SPSS and AMOS statistical software.

The findings indicate that information quality, systems quality, service quality, perceived usefulness, perceived ease of use and cognitive absorption are significant predictor of users’ satisfaction with the web DL.

Instead of collecting data from students from various faculties, this study only covered students enrolled in one faculty. In the same light, as the respondents were from one faculty, they only report their experience of using one DL. Given these limitations, the results obtained are narrowed in terms of generalizability. The second limitation of the study is related to the predictor variables which only focussed on six variables only.

From the practical viewpoint, the instrument that has been developed can be used as a diagnostic tool for continuous improvements of the DL.

From the theoretical viewpoint, the study has developed an empirical based framework that depicts critical factors influencing DL satisfaction. Researchers specializing on the assessment of DL effectiveness can consider adopting the framework for future studies. Alternatively, the framework can be further extended by integrating other variables such as users’ characteristics or organizational characteristics.

This paper aims to explore the latest study of the emerging data-driven approach in the area of FinTech. This paper attempts to provide comprehensive comparisons, including the advantages and disadvantages of different data-driven algorithms applied to FinTech. This paper also attempts to point out the future directions of data-driven approaches in the FinTech domain.

This paper explores and summarizes the latest data-driven approaches and algorithms applied in FinTech to the following categories: risk management, data privacy protection, portfolio management, and sentiment analysis.

This paper details out comparison between different existed works in FinTech with traditional data analytics techniques and the latest development. The framework for the analysis process is developed, and insights regarding the implementation, regulation and workforce development are provided in this area.

To the best of the authors’ knowledge, this paper is first to consider broad aspects of data-driven approaches in the application of FinTech industry to explore the potential, challenges and limitations of this area. This study provides a valuable reference for both the current and future participants.

The purpose of this study is to investigate the potential of using computer vision and deep learning (DL) techniques for improving safety on construction sites. It provides an overview of the current state of research in the field of construction site safety (CSS) management using these technologies. Specifically, the study focuses on identifying hazards and monitoring the usage of personal protective equipment (PPE) on construction sites. The findings highlight the potential of computer vision and DL to enhance safety management in the construction industry.

The study involves a scientometric analysis of the current direction for using computer vision and DL for CSS management. The analysis reviews relevant studies, their methods, results and limitations, providing insights into the state of research in this area.

The study finds that computer vision and DL techniques can be effective for enhancing safety management in the construction industry. The potential of these technologies is specifically highlighted for identifying hazards and monitoring PPE usage on construction sites. The findings suggest that the use of these technologies can significantly reduce accidents and injuries on construction sites.

This study provides valuable insights into the potential of computer vision and DL techniques for improving safety management in the construction industry. The findings can help construction companies adopt innovative technologies to reduce the number of accidents and injuries on construction sites. The study also identifies areas for future research in this field, highlighting the need for further investigation into the use of these technologies for CSS management.

The aim of this paper is to highlight the impact of distributed leadership (DL) on exploitative and exploratory innovations through the mediating effects of organizational trust (OT) and tacit and explicit knowledge sharing (KS).

Focusing on a quantitative approach, an empirical study was performed within a sample of information and communication technology Tunisian firms. The data collected was analyzed through the Partial Least Squares (PLS) method.

Findings revealed that DL is a driver of tacit and explicit KS, and exploitative and exploratory innovations. It also highlighted that tacit KS is associated with these two types of innovation. In this line, results showed that tacit KS plays a mediating effect between DL and exploitative and exploratory innovations. Moreover, our research highlighted that DL has a positive impact on OT that in turn boosts tacit and explicit KS.

This paper investigates the links between DL and exploitative and exploratory innovations within knowledge intensive firms (KIFs) that have never been studied in the literature within the context of business firms. This paper pioneers the examination of the mediating roles of explicit and tacit KS and OT in these links as well. This paper highlights the importance of DL for KIFs and sheds the light on how this collectivist approach of leadership creates an atmosphere of trust and fosters tacit and explicit KS to boost exploitative and exploratory innovations.

Toward sustainable development, radical green innovation (RGI) is necessary. Despite extensive research on the factors influencing green innovation, few studies have been conducted on the precursors. Based on upper echelons (UE) theory, dynamic capability (DC) theory, “stimulus-organism-response” (SOR) theory, social information processing (SIP) theory and cognitive appraisal (CA) theory of emotion, the study explores how digital leadership (DL) affects RGI and investigates the mediating effects of green organizational identity (GOI) and the moderating effects of digital threat (DT) and technology for social good (TSG), as well as the multiple concurrent causalities that trigger high RGI.

The method of combining structural equation model (SEM) and fuzzy-set qualitative comparative analysis (fs QCA) is adopted in the study. Data from 233 questionnaires were collected at two different time points.

This study's findings indicate that the four dimensions of DL can positively influence RGI and GOI partially mediates between the four dimensions of DL and RGI. DT has a negative moderating effect between DL and GOI, while TSG is positively regulated between them, DT and TSG linkage moderates the partial mediating effect of GOI in DL and RGI. Further, fs QCA is used to analyze the causal complexity of DL dimensions and GOI to RGI and nine effective configuration paths are identified. It is found that the synergy of digital thinking ability (DTA), digital detection ability (DDA), digital social ability (DSA), digital reserve ability (DRA) and GOI is crucial to high RGI. Among them, GOI core appears the most times, indicating that GOI plays a vital role in improving enterprise RGI.

This study expands the literature on leadership and innovation by constructing a framework of “DL-GOI-RGI” and exploring the transmission of GOI and the boundary effect of DT and TSG. The study used fs QCA and SEM to better understand the statistical associations and the set relations between the conjunctions and conditions.

This study aims to provide a systematic review of the existing literature on the applications of deep learning (DL) in hospitality, tourism and travel as well as an agenda for future research.

Covering a five-year time span (2017–2021), this study systematically reviews journal articles archived in four academic databases: Emerald Insight, Springer, Wiley Online Library and ScienceDirect. All 159 articles reviewed were characterised using six attributes: publisher, year of publication, country studied, type of value created, application area and future suggestions (and/or limitations).

Five application areas and six challenge areas are identified, which characterise the application of DL in hospitality, tourism and travel. In addition, it is observed that DL is mainly used to develop novel models that are creating business value by forecasting (or projecting) some parameter(s) and promoting better offerings to tourists.

Although a few prior papers have provided a literature review of artificial intelligence in tourism and hospitality, none have drilled-down to the specific area of DL applications within the context of hospitality, tourism and travel.

To the best of the authors’ knowledge, this paper represents the first theoretical review of academic research on DL applications in hospitality, tourism and travel. An integrated framework is proposed to expose future research trajectories wherein scholars can contribute significant value. The exploration of the DL literature has significant implications for industry and practice, given that this, as far as the authors know, is the first systematic review of existing literature in this research area.

Drawing upon the job demands-resources (JD-R) model, this research examines the contribution of distributed leadership (DL) to ambidextrous innovation and the mediating roles of employees' eudaimonic well-being (EWB) and hedonic well-being (HWB) in this link. It also investigates the moderating effect of employees' age in the relationship between DL and EWB and HWB.

The author formulated a series of hypotheses that we tested based on a survey of 329 middle managers working in Tunisian ICT firms and through the partial least square-structural equation modelling method.

This research provides empirical evidence of the mediating effects of EWB and HWB between DL and ambidextrous innovation. The multi-group analysis performed shows that employees' age moderates the links between DL and EWB and HWB. These relationships are significant and positive for Generation X and Generation Y and not for Baby-Boomers.

Despite the importance of the DL style, this variable has been studied mainly within educational institutions. This research pioneers the investigation of the mediating effect of HWB and EWB between DL and ambidextrous innovation in the business context. A major implication is that, through a DL style, managers can nurture the well-being of employees of different ages and promote ambidextrous innovation.

This paper aims to identify the factors affecting continued use of digital libraries in a military context.

Semi-structured interviews with four focus groups consisting of 21 respondents, who are military education instructors and librarians, were carried out. This qualitative approach study adopted content analysis methods that were designed to contrast and make comparisons based on the participants’ responses. The valid responses were analyzed using NVivo 12 Plus.

Using semi-structured interviews, this study presents five dimensions of critical success factors generated from the analysis of the content of the qualitative data. The dimensions highlighted are as follows: perceived quality factors; perceived instrumental support; perceived ease of use; users’ expectation and users’ satisfaction; and net benefits and perceived usefulness.

This study is only focussing on military education instructors and librarians in the vicinity of four regions in Peninsular Malaysia. For practical implications, it provides an understanding of how the organization could sustain the continued use of a military-context digital library (DL).

This study makes a new practical contribution to DL information systems’ successful implementation practices in a military context. This study also serves as a guideline for the organizational stakeholders to have a better understanding of their knowledge and the digitalization environment. The findings of this study provide an understanding of how the organization could sustain the continued use of digital libraries in a military context.

This study fills the void in the literature by investigating the DL use in the context of a military setting.