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Gamification is an emerging technique of applying game elements to difficult and tedious learning activities to make them fun and exciting. This study aims to review the scientific landscape of the library’s readiness to adopt gamification with context to application in teaching and learning purposes based on computational tools. The present research also aims to study the growth of literature on gamification, to identify the most contributing authors, countries, affiliations and journals and collaboration status with different geographical settings. The study will also identify the most influential paper on the area with the highest citation and Altmetric Attention Score (AAS) as well as analyzing the keywords for locating the research trend in the subject area.

The study has adopted Scientometric and Altmetric approach by considering the research outputs of a decade (2013–2022) from Scopus database. First, the required data has been searched using appropriate keywords forming the search strategy by running title–abstract–keywords considering the limitation in the system. The exported data is systematically visualized for performing science mapping like the collaboration of authors, countries, organizations and co-occurrence of keywords using VOSviewer. For finding the Altmetrics score and Mendeley readership of the influential research works, the system Dimension.ai is further used.

The study found 928 records indicating an exponential growth over the years with total 2,750 authors. Samuel Kai Wah Chu from the University of Hong Kong, China, is the most contributed author. Spain and the USA are highly productive countries, but there needs to be a strong collaboration pattern among authors. It is found that gamification is widely applied in education discipline than any other. Some of the libraries have already implemented gamification tools for learning purposes in their services. The research on gamification still lacks social media attention and needs to be promoted more through various social media platforms for greater visibility.

The study explores the global scientific literature to identify the library’s awareness of implementing gamification tools in their services for teaching and learning purposes. As per the author’s knowledge, no such study has been conducted until date with such aims and objectives through the application of both Scientometrics and Altmetrics approaches.

The purpose of this study was to examine the relationship between environmental pressure, green logistics strategy (GLS) and sustainability performance as well as the moderating role of competitive intensity in the relationship between environmental pressure and GLS in the context of the Ghanaian Manufacturing firms.

The study included a thorough review of the literature and an empirical questionnaire-based data collection with responses from 220 participant manufacturing firms in Ghana. The data collected was statistically analysed using the PLS-SEM software.

The findings of the study indicated that environmental pressure positively influences the implementation of GLS. Again, it was revealed that there is a significant relationship between GLS and sustainability performance. Likewise, the study also found that environmental pressure significantly influences sustainability performance. Also, competitive intensity was found to moderate the relationship between environmental pressure and GLS.

This study gives insight into GLS and sustainability performance and also suggested that when managers in manufacturing industries adopt green practices as a result of environmental pressure, sustainability performance will be achieved. The geographic scope of the study area and time constraints were some of the research's limitations.

Although there have been studies carried out on the subject of green logistics, this study is the first of its kind to examine the relationship between environmental pressure, GLS and sustainability performance within the context of developing economies such as Ghana. Also, this study shows how intense competition in the market can moderate the adoption of GLS.

This paper aims to investigate the factors influencing trade artisans’ choice of skills selection as apprentice’s trainee in the Ghanaian construction sector and to identify and address the challenges associated with traditional apprenticeship. Trade artisans with technical know-how in construction and general workplace skills from the traditional apprenticeship training (TAT) in the area of construction were selected from selected sites and training centers.

This paper adopted the purposive sampling technique with the aim of gathering knowledge from individuals with expertise in the research area, particularly trade craftsmen who have been trained through the TAT system and are directly involved in construction-related works. Partial least square structure equation modelling (PLS-SEM) analytical approach and principal component analysis were used to reduce the dimensionality of the data set and preserve as much information as possible.

Three major components, namely, personal and social interest, job assessment and stability and family and faith were identified as the variables that influence an artisan's choice of a skill trade. These influenced the choice of apprenticeship training by young trainees in choosing apprenticeship as a mode of training. Personal interest, living situation of artisans and parents’ educational attainment are the most influencing factors that determine artisans’ choice of selected trades. Moreover, the study also shed light on the challenges inherent in traditional apprenticeship systems, such as the lack of formal technical education, limited access to modern technology and information and poor working conditions.

The study underscores the imperative for stakeholders to enhance apprenticeship programmes within the construction sector. This involves providing more stable job opportunities, improving working conditions and offering access to modern technology and information. Such enhancements not only attract more young individuals to apprenticeship training but also ensure the sustainability and relevance of the workforce in meeting industry demands.

The study finally developed a model that could be used as a foundation for future PLS-SEM evaluation and identified the factors that influence the selection of apprenticeship training by trade artisans.

This paper aims to systematically review the literature on knowledge leakage through social networks in the past decade to find existing gaps, identify potential risk factors while, ultimately, proposing ways of mitigating these factors.

This study adopted Preferred Reporting Items for Systematic reviews and Meta-Analysis as guide for searching relevant scholarly publications. Subject-specific and -related research papers were obtained from three databases, namely, Scopus, Web of Science and EBSCOhost. The review data was generated from the search results while adopting specific criteria to either accept or reject a particular publication during the search process.

Technological, operational and human knowledge factors are some of the risks resulting from knowledge leakage. Highlights of the paper include strategies for mitigating these factors, including continuous training, creating awareness, banning social media usage at work and reinforcing nondisclosure policies. This study also found potential gaps from the literature, categorized as topical, geographical, industrial, theoretical, methodological and conceptual gaps while proposing ways of addressing these gaps using specific research questions. These questions set the direction for future studies on knowledge leakage and social networks.

Implications of the findings are laid out, particularly the idea of developing actionable managerial plans for preventing knowledge leakage from occurring in organizations in the first place. The systematic, rigorous, transparent and methodological procedures used throughout the entire research process strongly suggest that the findings and conclusions are legitimate. While the findings were not drawn arbitrarily, they potentially offer windows of opportunities for bridging the six potential gaps identified in this paper.

Crack detection of pavement is a critical task in the periodic survey. Efficient, effective and consistent tracking of the road conditions by identifying and locating crack contributes to establishing an appropriate road maintenance and repair strategy from the promptly informed managers but still remaining a significant challenge. This research seeks to propose practical solutions for targeting the automatic crack detection from images with efficient productivity and cost-effectiveness, thereby improving the pavement performance.

This research applies a novel deep learning method named TransUnet for crack detection, which is structured based on Transformer, combined with convolutional neural networks as encoder by leveraging a global self-attention mechanism to better extract features for enhancing automatic identification. Afterward, the detected cracks are used to quantify morphological features from five indicators, such as length, mean width, maximum width, area and ratio. Those analyses can provide valuable information for engineers to assess the pavement condition with efficient productivity.

In the training process, the TransUnet is fed by a crack dataset generated by the data augmentation with a resolution of 224 × 224 pixels. Subsequently, a test set containing 80 new images is used for crack detection task based on the best selected TransUnet with a learning rate of 0.01 and a batch size of 1, achieving an accuracy of 0.8927, a precision of 0.8813, a recall of 0.8904, an F1-measure and dice of 0.8813, and a Mean Intersection over Union of 0.8082, respectively. Comparisons with several state-of-the-art methods indicate that the developed approach in this research outperforms with greater efficiency and higher reliability.

The developed approach combines TransUnet with an integrated quantification algorithm for crack detection and quantification, performing excellently in terms of comparisons and evaluation metrics, which can provide solutions with potentially serving as the basis for an automated, cost-effective pavement condition assessment scheme.

Against the background of the I50 paradigm, this paper queries in what ways blockchain and blockchain-based applications deployed in the smart city context facilitate the integration of the I50 paradigm in smart urban contexts.

A mixed methods approach is applied. First, by means of desk research and thematic literature review, a conceptual model integrating the I50 paradigm, smart city and blockchain-based solutions is built. Second, science mapping bibliometric analysis (SciMat) based on keywords’ co-occurrence is applied to a sample of 491 research articles to identify key domains of blockchain-based applications’ use in smart city. Third, a semi-systematic literature review complements insights gained through SciMat. Fourth, the findings are interpreted through the precepts of the conceptual model devised earlier.

The key blockchain-based applications in smart cities pertain to two domains, i.e. the foundational, service facilitation-oriented domain, including security (and safety), networks, computing, resource management and the service delivery-oriented domain, including mobility, energy and healthcare. Blockchain serves as the key building block for applications developed to deliver functions specific to each of the thus identified domains. A substantial layering of blockchain-based tools and applications is necessary to advance from the less to the more complex functional domains of the smart city.

At the conceptual level, the intricacies of the (making of the) I50 paradigm are discussed and a case for I50 – smart city – blockchain nexus is made. Easton’s input–output model as well as constructivism is referenced. At the empirical level, the key major domains of blockchain-based applications are discussed; those that bear the prospect of integrating the I50 paradigm in the smart city are highlighted. At the methodological level, a strategic move is made aimed at restoring the literature review’s role as subservient to the key line of exploration, to justify and ultimately support it, rather than to showcase the literature review as the ultimate purpose for itself.

Despite endeavors to alleviate construction and demolition waste and the indications that the process of deconstruction has the potential to steer waste reduction initiatives, there has not been a progressive increase in the adoption of Design for Deconstruction (DfD) in the global south, especially Ghana. This paper aims to identify and analyze the barriers to implementing DfD in developing countries.

A structured questionnaire survey was used to solicit the views of 240 design professionals in the Ghanaian construction industry (GCI). The questionnaire was developed by reviewing pertinent literature and complemented with a pilot review. Data were analyzed using descriptive and nonparametric statistics.

The findings revealed ten (10) significant impediments to implementing DfD within the construction industries in developing economies. These impediments revolve around cost, legal matters, storage, incentive and design-related matters. Key among these barriers is “For recovered materials, there are little performance guarantees,” “The absence of strict regulations regarding design for deconstruction,” “Lack of a large market enough for components that have been recovered,” “The need for building codes that address how to design with reused materials” and “Lack of effective design for deconstruction tools.”

The results of this research shed light on a relatively unexplored area within the construction sector, particularly in a developing country like Ghana. Furthermore, to the best of the authors’ knowledge, the study contributes fresh and supplementary knowledge and perspectives regarding the challenges in implementing DfD practices.

The widespread uptake of digital technology tools for online teaching and learning reached its peak during the nationwide lockdown triggered by the COVID-19 pandemic. It transformed the higher education institutions (HEIs) marketplace both in developed and developing countries. However, in this process of digital transformation, several HEIs, specifically from developing countries, faced major challenges. That threatened to affect their sustainability and performance. In this vein, this study conducts a bibliometric review to map the challenges during the COVID-19 pandemic and suggest strategies for HEIs to cope with post-pandemic situations in the future.

This comprehensive review encompasses 343 papers published between 2020 and 2023, employing a systematic approach that combines bibliometrics and content analysis to thoroughly evaluate the articles.

The investigation revealed a lack of published work addressing the specific challenges faced by the faculty members affecting their well-being. The study underscores the importance of e-learning technology adoption for higher education sustainability by compelling both students and teachers to rely heavily on social media platforms to maintain social presence and facilitate remote learning. The reduced interpersonal interaction during the pandemic has had negative consequences for academic engagement and professional advancement for both educators and students.

This has implications for policymakers and the management of HEIs, as it may prove useful in reenvisioning and redesigning future curricula. The paper concludes by developing a sustainable learning framework using a blended approach. Additionally, we also provide directions for future research to scholars.

This study has implications for policymakers and HEI management to rethink the delivery of future courses with a focus on education and institute sustainability. Finally, the research also proposes a hybrid learning framework for sustainability and forms a robust foundation for scholars in future research.

With the rapid development of social media, many organizations have begun to attach importance to social media platforms. This research studies the management and the use of social media in academic music libraries, taking the Center for Chinese Music Studies of the Chinese University of Hong Kong (CCMS) as a case study.

We conducted a sentiment analysis of posts on Facebook’s public page to analyze the reaction to the posts with some exploratory analysis, including the communication trend and relevant factors that affect user interaction.

Our results show that the Facebook channel for the library has a good publicity effect and active interaction, but the number of posts and interactions has a downward trend. Therefore, the library needs to pay more attention to the management of the Facebook channel and take adequate measures to improve the quality of posts to increase interaction.

Few studies have analyzed existing data directly collected from social media by programming based on sentiment analysis and natural language processing technology to explore potential methods to promote music libraries, especially in East Asia, and about traditional music.

The COVID-19 pandemic presented unprecedented challenges, particularly intensifying the financial and psychological burden for individuals with student loans in the United States. Firstly, this study examined the association between student loan ownership and financial well-being during the pandemic. Secondly, among student loan holders, we tested the association of financial anxiety and payment delinquency with COVID-19 shocks and financial knowledge. Lastly, we investigated the associations between the recipients of student loans and their financial well-being, anxiety and behaviors concerning student loans.

Utilizing data from the 2021 National Financial Capability Study, we explored how unprecedented economic disruptions have affected student loan holders' financial well-being, levels of debt anxiety and payment delinquency, considering financial knowledge as a critical factor. We conducted Ordinary Least Squares (OLS) and logistic regressions to examine the associations addressed in the purpose of the study.

The results of regression analyses indicate that individuals with student loans generally experienced lower financial well-being than those without loans. Among student loan holders, COVID-19 shocks were positively associated with student loan anxiety and payment delinquency. Additionally, subjective financial knowledge showed a positive association, while objective financial knowledge displayed a negative association with loan delinquency. Lastly, respondents who secured loans for themselves exhibited lower levels of financial well-being than other student loan holders.

This study represents one of the initial efforts to investigate the issues of financial well-being, debt anxiety and payment delinquency among student loan holders, along with their associations with the potential COVID-19 shocks they experienced. The research shed light on the acute financial stress and mental health challenges faced by student loan holders during global crises, highlighting the significance of effective policy development for student debt management and borrower support during times of economic uncertainty.