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This study aims to dissect and understand the latent themes of Islamic work ethic (IWE) and explore the driving factors of IWE research.

Structural topic modeling (STM), a sophisticated machine learning technique, was used to analyze a corpus of 205 articles sourced from the Scopus database. These articles cover the 36 years of research on IWE, from 1988 to 2024. Moreover, negative binomial regression was applied to examine the driving factors of IWE research.

The STM analysis unfolds ten topics in conjunction with IWE including individual success, workplace dynamics, organizational work ethics, knowledge management, employee citizenship behavior, financial ethics, job satisfaction, organizational commitment, performance enhancement and leadership. The further STM outputs included word clouds, prevalence proportions, correlation matrix, heatmap, relationship of topics with metadata, topic prominence in the publishing journals and, finally, illustrating trends and future prospects of research on IWE. The results of negative binomial regression reveal that number of authors, article age, journal indexing, authors from multiple countries and number of references are strong drivers of fostering research in IWE, by having significant positive impacts on total citations.

The insights from this study provide valuable guidance for businesses and organizations looking to integrate IWE principles into their operations. By promoting values such as fairness, hard work and ethical behavior, organizations can foster a more inclusive and morally grounded workplace culture. This, in turn, may lead to enhanced employee satisfaction, greater organizational commitment and improved overall performance. Additionally, the emphasis on ethical practices can contribute to broader societal benefits, such as increased trust in business practices and a stronger alignment with social responsibility initiatives.

This is a unique study that explores the latent themes and characteristics of the IWE literature through STM and provides insights on the future research directions. In addition, this study also examines the driving factors of IWE research.

This study aims to review the content of academic libraries’ websites with specific reference to the general information, services, information resources, features and functionalities, instructional tools to support teaching, learning and research for the patrons and users, and the visibility or activeness of the navigational tools on the websites.

The study focused on six categories of tertiary institutions: public universities, technical universities, chartered private universities, university colleges, colleges of education and nursing and midwifery schools. From each category, the researchers purposively selected five different institutions with library websites. Thus, 30 library websites were reviewed and analyzed for this study.

The review disclosed a generally low content and information on the websites in terms of the availability of information resources and collections; the types of services available at the libraries via the websites; the features and functionalities of the websites; the instructional tools to support teaching, learning and research for the patrons and users; and the visibility or activeness of the navigational tools on the websites. Despite this, the public universities displayed more and above average information, services, information resources, instructional tools and navigational tools on their library websites, followed by the technical universities, chartered private universities and university colleges. Conversely, the colleges of education and nursing and midwifery schools were to a large extent unable to provide information relating to electronic resources, instructional tools and navigational tools.

The study was limited to 30 library websites from all six categories of tertiary institutions in Ghana. From the study, the management of the universities and the libraries must appreciate the significant role of websites in providing information and resources in support of teaching, research and learning at the institutions. In this regard, they need to provide the necessary support and resources for the effective deployment and operationalization of websites.

To the best of the author’s knowledge, this study is the first of its kind as no study seeks to provide a comprehensive analysis of the content of academic libraries’ websites with specific reference to the general information, services, information resources, features, functionalities, instructional tools to support teaching, learning and research for the patrons and users, and the visibility or activeness of the navigational tools on the websites.

(1) developing a dynamic and progressive software defect prediction model to successfully manage novel and huge amounts of software defect data and lessen the computational time. (2) to avoid the great diminish of static batch learning algorithms efficiency once the amount of data achieves a certain level.

This study explores the proficiency of the incremental classification based approach to elaborate anincremental software defect prediction system which helps recognizing and treating real-time software data streams.

The proposed method, as demonstrated by experimental results, is clearly competitive with the relevant two-class classifiers currently in use for software defect diagnosis. Detailed experimental findings clearly demonstrated the performance and efficiency of the suggested software defect detection approach: Incremental Discriminant-based Support Vector Machine (IDSVM) to differentiate between defective and non-defective objects.

To the best of our knowledge, this is the first a real-time prediction method that investigates incremental classification in software defect prediction research