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This paper aims to examine the effect of high-involvement work systems (HIWSs) on completing work and avoiding distraction as two dimensions of presenteeism. It also investigates competence as a mediator of the effect of HIWS on presenteeism.

Data were collected from 343 Bangladeshi bank employees using an online survey. The partial least squares-structural equation modelling (PLS-SEM) was employed to assess the abovementioned linkages.

The findings demonstrate HIWS directly avoid distraction but do not significantly impact the completing work dimension of presenteeism. The findings also indicate that competence mediates the effect of HIWS on completing work but not on avoiding distraction.

Drawing on the job demands-resources (JD-R) model, this study empirically demonstrates the contrasting role of HIWS in completing work and avoiding distraction related to presenteeism. It also provides a novel perspective on the unexplored mediating mechanism of competence on the relationship between HIWS and presenteeism and offers new directions for HIWS and presenteeism research.

The purpose of this study is to determine the competency characteristics required for the employment of master’s degree students in educational technology.

A combined qualitative and quantitative method was used to consult multiple experts through a modified Delphi method. Competency characteristics were extracted from Chinese recruitment apps, national recruitment websites and university training programs. Ten senior teacher experts who teach educational technology master’s students were consulted through a questionnaire consultation to validate the proposed competency model. The weights of competency characteristics were determined through a combination of the analytic hierarchy process and entropy method.

The results show that when recruiting educational technology master’s students, more emphasis is placed on operational skills. The majority of companies tend to assess practical abilities rather than theoretical knowledge. Relevant knowledge of educational technology, psychology, computer science and education is considered to be the basic knowledge components of educational technology master’s students, while professional skills are the core skills required for their positions. Therefore, universities need to focus on training, educational technology graduate students in these areas of competence. The study also found that professional qualities (such as physical and mental fitness) and personality traits (interpersonal communication and interaction) receive more attention from companies and are essential competencies for educational technology master’s students.

A competence model for educational technology master’s students is proposed, which includes aspects such as knowledge, personal skills/abilities, professional qualities and personality traits. The competence elements included in this model can serve as reference indicators for universities to cultivate the competence of educational technology master’s students, as well as reference points for recruiting units to help them select talents. This represents a new dimension in research related to the employment of educational technology master’s students. The study enriches the research objects and competence dictionary in the field of competence research.

The advancement of digital technological breakthroughs in the construction industry is dependent on connecting the attributes of the intended consumers to the technologies. Thus, this study aims to look at the relationship between construction app acceptance and the digital qualities of construction professionals (CPs) to determine whether understanding the connection can assist predict construction app user behaviour.

This study’s theoretical approach was derived from the European Union digital competence model, which supports the hypothesis that the traits associated with digital competence enable digitally competent CPs to embrace construction apps. Six hypotheses were developed to investigate the theories, and multiple linear regression analysis was used to predict the acceptance of construction apps based on the CP’s attributes.

The investigation’s findings revealed that the CP’s attributes can explain at least 50% of the proportion of variance in 34 construction apps. The use of a smartphone (Mean Score = 3.30; Factor Loading = 0.609), technological orientation (Mean Score = 3.55; Factor Loading = 0.663), information technology skills (Mean Score = 3.48; Factor Loading = 0.649), information on construction innovation (Mean Score = 3.73; Factor Loading = 0.528) and interest in R&D (Mean Score = 3.48; Factor Loading = 0.531) are the digital characteristics that can essentially forecast the acceptance of construction apps. The data backs up the notion that CPs would gain digital competency before accepting construction apps. This is because a digitally savvy CP will most likely embrace construction apps.

Frameworks for accelerating digital technologies and innovations in the construction industry have been unveiled in this study. The research also gives recommendations for the evaluation, design and implementation of a more attractive construction app. This study also has implications for investigating the impacts of risk aversion, personal connection, social influence, technological curiosity and digital nativity as predictors of construction app uptake.

The findings of this study serve as an index for prioritising digital traits for CPs and characterising a digitally proficient construction professional. The findings provide recommendations for organising, training and supporting construction personnel’ digital competencies. The research is useful for developing and implementing instructional digital training programmes.

This study is unusual in that it provides clear insights on construction apps as well as variables for building great user-experience apps for CPs, which are both limited in the literature.

The development of project managers and leadership has been highlighted as crucial for improving project success and performance, resulting in a rise of interest in project leadership research over the last two decades. While several qualitative reviews have been conducted, there have been limited quantitative and systematic reviews on project leadership. This study fills this gap by portraying the knowledge landscape and tracking the evolution of project leadership research from 1998 to 2022 through bibliometric approaches.

Based on 816 records, including 793 articles extracted and selected from the Web of Science database and specific journals, and 23 articles selected from three non-SCI/SSCI indexed journals, the authors used CiteSpace and bibliometrix R-package to depict visualizations of the trajectory of co-cited references, the landscape of co-occurred keywords and emerging trends in project leadership via reference co-citation analysis, keyword co-occurrence analysis and thematic mapping.

The bibliometric analyses enabled the authors to understand the conceptual aspects of project leadership and its theoretical background. Three stages of the intellectual bases were identified and tracked: the infancy phase (1998–2007), the growth phase (2008–2014) and the new development phase (2015–2022). The results of keyword co-occurrence analysis indicated that the research focus evolved from investigating traits and competences to examining the effects of traditional leadership behaviors, and then considering context-specific leadership. The findings of thematic mapping and theoretical interpretation illustrate the potential directions of the competence comparison, new and appropriate leadership, and the interaction between leadership and context.

This study advanced the field by providing a systematic review of project leadership, developing potential future directions for project leadership research and providing practical implications for career development and training.

The current study intends to synthesise the prior studies on employability skills among work-ready professionals in higher education through bibliometric and network visualisation tools. This study also identifies the gaps in the existing literature that still need to be filled and maps the course for future investigation.

The current study examined research papers on employability skills among work-ready professionals in higher education to evaluate global patterns and the top authors, institutions, journals, and nations contributing to this field. The authors analysed eight hundred eighty-five papers from the Scopus database between 1982 and 2023 for the study. Open-source bibliometric tools like Biblioshiny were used in the study to examine the body of literature and to spot new directions for future research.

The study’s findings indicate that since 2008, researchers, academics, and policymakers have paid more attention to employability skills among work-ready professionals, and 2019 is the year seeing the highest no. of publications. Across the globe, 2077 authors contributed to the articles, papers, and journals published in the particular domain. Regarding location, the United Kingdom is the world’s most productive nation, with 342 articles produced. Similarly, Australia, India, and Malaysia are the leading nations that have contributed to the field. Both keywords significantly contribute to scientific knowledge.

The gaps in this study will serve as a reference point for researchers conducting future studies in this field. Additionally, the result of this analysis offers a roadmap for higher education to enhance graduate employability by embedding necessary skills into them.

There has not been a bibliometric analysis concerning employability skills among Work-ready professionals in the existing literature; hence, this article is innovative. This study is the first attempt at integrating the concept. The study also gives an overview of potential directions for future research in this discipline.

The study aims to study the effect of non-cognitive ability in human capital on the wages of rural migrant workers in China. The study also examines the mechanisms by which career choice, career development and social capital influence.

Based on the new human capital theory, this paper empirically investigates the effects and mechanisms of rural migrant workers' non-cognitive ability on wages using the 2018 China Family Panel Studies database and Stata 17.0 for construct validation and hypothesis testing.

The results showed that non-cognitive ability has a significant positive effect on rural migrant workers' wages. Subsequently, the mechanism of non-cognitive ability was examined. In further analysis, the study found that non-cognitive ability has a greater effect on the wages of vulnerable individuals (females, low and medium skills) among the rural migrant workers.

The originality of this study is to break through the existing research perspectives, overcome the limitations of scholars' existing research perspectives focusing on the employment and competitiveness of rural migrant workers in China and explore the factors affecting the rural migrant workers' wages from the perspective of non-cognitive ability as a new entry point by combining psychology. At the same time, the study design is more rigorous, avoiding the measurement error of variables.

This paper aims to explore the potential of implementing an action competence teaching model as a framework for achieving sustainable development goals (SDGs) in higher education. The paper seeks to draw insights from the students on the potential of this teaching model.

The study adopted a quantitative research design in exploring the potential of an action competence teaching model. This study used self-report measures to obtain insights into the objective of the study.

The action competence teaching model was seen as useful in equipping students with knowledge about a problem, confidence and willingness to act. However, some issues like the design of the projects, teamwork and instructional practices were identified and discussed.

To the best of the authors’ knowledge, this study is the first to implement an action competence teaching model to help draw insights from students on its potential. This paper documents certain aspects of action competence that require attention before being implemented in higher education. This information so far lacking in scientific literature contributes to ongoing discussions on SDGs while unveiling strengths and weaknesses to be considered.

The current gap between the required and available artificial intelligence (AI) professionals poses significant challenges for organisations and academia. Organisations are challenged to identify and secure the appropriate AI competencies. Simultaneously, academia is challenged to design, offer and quickly scale academic programmes in line with industry needs and train new generations of AI professionals. Therefore, identifying and structuring AI competencies is necessary to effectively overcome the AI competence shortage.

A probabilistic topic model was applied to explore the AI competence categories empirically. The authors analysed 1159 AI-related online job ads published on LinkedIn.

The authors identified five predominant competence categories: (1) Data Science, (2) AI Software Development, (3) AI Product Development and Management, (4) AI Client Servicing, and (5) AI Research. These five competence categories were summarised under the developed AI competence framework.

The AI competence framework contributes to clarifying and structuring the diverse AI landscape. These findings have the potential to aid various stakeholders involved in the process of training, recruiting and selecting AI professionals. They may guide organisations in constructing a complementary portfolio of AI competencies by helping users match the right competence requirements with an organisation's needs and business objectives. Similarly, they can support academia in designing academic programmes aligned with industry needs. Furthermore, while focusing on AI, this study contributes to the research stream of information technology (IT) competencies.

The main purpose of this study is aimed to estimate the mediating role of student engagement in the structural relationships between students' field of study choice, learning readiness and academic competence of undergraduate students in higher education.

In the study process, a correlational design was employed. Data were collected from 419 participants who were selected through a simple random sampling technique. Structural equation modeling (SEM) was used to analyze the data.

The study findings showed neither field of study choice nor learning readiness has a significant direct effect on student's academic competence. However, when student engagement, entered the relationships between “field of study choice and academic competence” as well as “learning readiness and academic competence”, the indirect effects became significant. Both conditions, therefore, suggesting student engagement had a full mediation role in the structural relationship models.

Based on the results, it can be concluded that student engagement is shown as one of the key variables used to comprehend how students develop competence in the teaching-learning process. Hence, teachers and academic administrators could use engagement as a strong instrument to optimize students' learning and academic competence to enhance their academic success.

The aim of this study was to shed some light on the extent to which digital literacy, epistemological belief and reading motivation and engagement predict pre-service teachers’ capabilities in teaching 21st century skills.

21st Century Skills Teaching Scale, Internet based Epistemological Beliefs Scale, Internet based Reading Motivation and Engagement Scale as well as Digital Literacy Scale were used to collect the data. A total of 512 pre-service teachers from four universities in Türkiye participated in the study. Descriptive statistics, correlation and structural equation model fitness tests were performed by using SPSS 24.0 and AMOS 22.0.

First, the results of the correlations analysis indicated that there were statistically significant positive correlations among measured variables. Second, the results of the path and SEM model fit tests demonstrated that all the model fit indices of X2/df, TLI, CFI, RMSEA met the acceptable criteria and were shown to be an adequate model structure. Finally, the results demonstrated strong evidence for predicting effects of digital literacy, epistemological belief as well as reading motivation and engagement on teaching 21st century skills.

This study is limited by the fact that the evidence relies solely on pre-service teachers' self-reporting. Secondly, although the hypothesised model explained 45.2% variance of pre-service teachers’ competence in the 21st century skills, 54.8% of it remains unexplained.

The results of this study suggest important implications for teaching programs as they underscore the importance of digital literacy on epistemological beliefs, reading motivation and competence in teaching 21st century skills.