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This study aims to quantitatively consolidate the research conducted over the past four decades on how internal branding activities drive employee commitment. It summarizes several operationalizations of internal branding and tests the moderating effect of employee’s personal characteristics and job characteristics on the relationship between internal branding and employee commitment.

This paper uses meta-analysis as the research methodology. The analysis includes a sample of 65 studies (from 62 published works), yielding 226 effect sizes (coded into 82 composite effect sizes) over an aggregated sample of 21,706 respondents.

This study finds that brand communication, brand-centered human resource management (HRM), training and development, organizational support and culture, brand-centered leadership and an excellent reward system are the key operationalizations of internal branding. Furthermore, employee’s personal (education, age and gender) and job (tenure, work status and level of customer orientation) characteristics significantly moderate the internal branding–employee commitment relationship.

Limited empirical literature on some of the internal branding operationalizations such as brand-centered HRM and rewards has curbed the scope of moderator analysis.

This paper proposes some effective ways of implementing internal branding strategies and provides support for boundary conditions that brand managers should consider to strengthen the impact of internal branding activities on employee commitment.

As per the authors’ knowledge, this paper is among the few quantitative consolidations of four decades of research on the internal branding–employee commitment relationship.

The purpose of this paper is to measure the relationship of technology acceptance model (TAM) variables (PEOU and PU) with behavioral intention (BI) and attitude in mobile and digital libraries context. This study also examines the relationship of external variables (information quality and system quality) with TAM variables (PEOU and PU) in mobile and digital libraries context.

This meta-analysis was performed through PRISMA-P guidelines. Four databases (Google Scholar, Web of Science, Scopus and LISTA) were used for searching, and the search was conducted according to defined criteria.

Findings of this study revealed a large effect size of PU and PEOU with BI. There was also a large effect size of PU and PEOU with attitude. A medium effect size was found between SysQ → PU, InfoQ → PU and SysQ → PEOU. However, there was a small effect size between InfoQ and PEOU.

To the best of the authors’ knowledge, there was no study published till the time of conducting this meta-analysis. Hence, this study fills the literature gap. This study also confirms that TAM is a valid model in the acceptance and use of technology in mobile and digital libraries context. Thus, the findings of the present study are helpful for developers and designers in designing and developing mobile library apps. It will also be beneficial for library authorities and system librarians in designing and developing digital libraries in academic settings.

The purpose of this study is to investigate the relationships between the information system success model constructs including information quality (IQ), system quality (SysQ) and service quality (ServQ) with user satisfaction (US) and intention to use (IU).

A meta-analysis approach was used to achieve the objectives. For this purpose, the PRISMA-P guideline was used, and a search strategy was designed to search in three indexing databases including Google Scholar, Scopus and LISTA.

The findings of this research revealed that IQ, SysQ and ServQ are positively related to US and IU regarding library systems. The strength of the relationship between IQ and IU, IQ and US, ServQ and US and SysQ and US was high.

This study is a unique addition to the literature, as it provides a collective and comprehensive conclusion regarding different information systems’ (ISs) success in libraries. Therefore, it fills the literature gap. The findings also work as guidelines for system developers, designers and library high-ups to consider IQ, SysQ and ServQ while designing and developing ISs for libraries.

This study aims to examine the moderating effect of cultural conditions on the relationship between environmental performance and environmental disclosure.

The authors used meta-analysis technique to examine 100 effect sizes from 43 studies published between 1982 and 2023 to integrate the existing results and to detect causes contributing to variability of results across studies.

There is a significant positive relationship between environmental performance and environmental disclosure. Further, the authors found that cultures with long-term orientation positively moderated the relationship, whereas cultures with high uncertainty avoidance and indulgence negatively moderated it.

This study did not account for the problem of endogeneity between environmental performance and environmental disclosure because most of the already published studies included in the authors’ meta-analysis did not address this issue.

This research provides regulators and policymakers insights on the influence of cultural factors on environmental disclosure and performance, critical information to consider when adopting, or revising social and environmental policy and regulations within a country.

To the best of the authors’ knowledge, this is the first meta-analysis study examining different cultural dimensions influencing the relationship between environmental performance and environmental disclosure and contributes new knowledge to the literature on determinants of environmental disclosure.

This paper aims to meta-analyze the results of the prior studies related to the relationship of human capital and financial performance in Islamic banking.

To examine the relationship between human capital and financial of Islamic banks, 23 empirical studies having sample of 15,607 are considered for the meta-analysis. Moreover, different measures related to financial performance including return on assets (ROA), return of equity (ROE) and Tobin’s Q have been taken as moderating for further subgroup analysis.

The results of meta-analysis reveal a positive correlation between human capital and financial performance with an effect size of 0.268. The subgroup analyses showed significant positive associations of human capital with ROA and ROE, insignificant with Tobin’s Q.

This study suggests Islamic banking should prioritize human capital development, maintain consistency and adopt a long-term perspective. Future research should consider context-specific factors and harmonize human capital and financial performance measurements for consensus.

Reducing aircraft fuel consumption has become a paramount research area, focusing on optimizing operational parameters like speed and altitude during the cruise phase. However, the existing methods for fuel reduction often rely on complex experimental calculations and data extraction from embedded systems, making practical implementation challenging. To address this, this study aims to devise a simple and accessible approach using available information.

In this paper, a novel analytic method to estimate and optimize fuel consumption for aircraft equipped with jet engines is proposed, with a particular emphasis on speed and altitude parameters. The dynamic variations in weight caused by fuel consumption during flight are also accounted for. The derived fuel consumption equation was rigorously validated by applying it to the Boeing 737–700 and comparing the results against the fuel consumption reference tables provided in the Boeing manual. Remarkably, the equation yielded closely aligned outcomes across various altitudes studied. In the second part of this paper, a pioneering approach is introduced by leveraging the particle swarm optimization algorithm (PSO). This novel application of PSO allows us to explore the equation’s potential in finding the optimal altitude and speed for an actual flight from Algiers to Brussels.

The results demonstrate that using the main findings of this study, including the innovative equation and the application of PSO, significantly simplifies and expedites the process of determining the ideal parameters, showcasing the practical applicability of the approach.

The suggested methodology stands out for its simplicity and practicality, particularly when compared to alternative approaches, owing to the ready availability of data for utilization. Nevertheless, its applicability is limited in scenarios where zero wind effects are a prevailing factor.

The research opens up new possibilities for fuel-efficient aviation, with a particular focus on the development of a unique fuel consumption equation and the pioneering use of the PSO algorithm for optimizing flight parameters. This study’s accessible approach can pave the way for more environmentally conscious and economical flight operations.

No study has investigated the effects of different parameters on publication bias in meta-analyses using a machine learning approach. Therefore, this study aims to evaluate the impact of various factors on publication bias in meta-analyses.

An electronic questionnaire was created according to some factors extracted from the Cochrane Handbook and AMSTAR-2 tool to identify factors affecting publication bias. Twelve experts were consulted to determine their opinion on the importance of each factor. Each component was evaluated based on its content validity ratio (CVR). In total, 616 meta-analyses comprising 1893 outcomes from PubMed that assessed the presence of publication bias in their reported outcomes were randomly selected to extract their data. The multilayer perceptron (MLP) technique was used in IBM SPSS Modeler 18.0 to construct a prediction model. 70, 15 and 15% of the data were used for the model's training, testing and validation partitions.

There was a publication bias in 968 (51.14%) outcomes. The established model had an accuracy rate of 86.1%, and all pre-selected nine variables were included in the model. The results showed that the number of databases searched was the most important predictive variable (0.26), followed by the number of searches in the grey literature (0.24), search in Medline (0.17) and advanced search with numerous operators (0.13).

The results of this study can help clinical researchers minimize publication bias in their studies, leading to improved evidence-based medicine.

To the best of the author’s knowledge, this is the first study to model publication bias using machine learning.

This paper seeks to investigate the differences in the teachers’ professional development (TPD) by mentorship in workplace. The authors examined the role of mentorship in the PD of teachers and conducted a meta-analysis of pertinent empirical data.

Using data from over 2,900 individuals, 66 experiments and 12 countries, the authors presented a meta-analysis of the association between workplace mentorship and TPD.

The authors concluded that mentoring activities could boost the TPD to some extent. It contributes positively to the discipline of science and language, kindergarten, individual mentoring and curriculum research. In addition, the periodicity should not exceed 1 year.

The results of the meta-analysis are restricted to short-term mentorship activities, and the sample size is modest. Building upon the findings from the literature review and meta-analysis, the authors delineated a research agenda for prospective investigations. This includes an imperative for further exploration into the nexus between mentoring and the PD of educators.

Based on the available literature and meta-analysis findings, the authors developed a framework for the “Experts in the classroom” TPD pattern.

This is the first meta-analysis evaluating the association between mentorship and TPD.

In response to growing concerns over the negative consequences of Internet addiction on adolescents’ mental health, coupled with conflicting results in this literature stream, this meta-analysis sought to (1) examine the association between Internet addiction and depressive symptoms in adolescents, (2) examine the moderating role of Internet freedom across countries, and (3) examine the mediating role of excessive daytime sleepiness.

In total, 52 studies were analyzed using robust variance estimation and meta-analytic structural equation modeling.

There was a significant and moderate association between Internet addiction and depressive symptoms. Furthermore, Internet freedom did not explain heterogeneity in this literature stream before and after controlling for study quality and the percentage of female participants. In support of the displacement hypothesis, this study found that Internet addiction contributes to depressive symptoms through excessive daytime sleepiness (proportion mediated = 17.48%). As the evidence suggests, excessive daytime sleepiness displaces a host of activities beneficial for maintaining mental health. The results were subjected to a battery of robustness checks and the conclusions remain unchanged.

The results underscore the negative consequences of Internet addiction in adolescents. Addressing this issue would involve interventions that promote sleep hygiene and greater offline engagement with peers to alleviate depressive symptoms.

This study utilizes robust meta-analytic techniques to provide the most comprehensive examination of the association between Internet addiction and depressive symptoms in adolescents. The implications intersect with the shared interests of social scientists, health practitioners, and policy makers.

The purpose of this study is to examine the relationship between cultural intelligence (CQ) and cross-cultural adjustment (CCA) using meta-analytic methods. The paper serves a dual purpose as it critically examines the CQ-CCA literature and provides summary effects using meta-analysis to determine how CQ and its facets affect CCA and its three dimensions.

A meta-analysis of 77 studies involving 18,399 participants was conducted to obtain the summary effects. The studies reporting the relationship of CQ and/or its facets with CCA or any of its dimensions were included in the analysis.

Results revealed that CQ (overall) and all individual CQs were positively and significantly related to CCA and its three subdimensions. Although CQ (overall) had a strong effect on CCA and moderate to strong effects on all the subdimensions of CCA, the strongest effect size was measured for the relationship of motivational CQ with CCA. Not only this, when individual CQs' relationships were assessed with the individual adjustment dimensions, the motivational aspect of CQ happened to be the most influencing factor, having a close to strong effect on interaction adjustment.

Since the study combines the results from numerous empirical research conducted over time, it avoids the limitations that an individual study has, which is carried out at a single point in time and on a limited sample.

This study adds to the academic research by critically reviewing the CQ-CCA literature. It also works as a guiding map for future research in the area. The study highlights the summary effects for each association between CQ and CCA and their dimensions, elucidating the mixed findings reported in previous research.