Search results

This study aims to investigate scholarly works on higher education management from emerging economies. It investigates how higher education management has evolved in emerging economies.

This study is quantitative, and the authors retrieved the metadata from the Web of Science, an extensive pool of interdisciplinary peer-reviewed literary databases for bibliometric analysis.

The results show the strengths, weaknesses and prospects of higher education institutions (HEIs) in developing countries based on the scholarly output in various journals.

Though the study contributed to the knowledge and expansion of literature in HEIs research, it was only limited to the Web of Science database.

Policymakers and practitioners who want to improve the efficiency and viability of HEIs in developing countries can find a helpful guide in the form of a framework for higher education management in developing countries.

It is important to note that the bibliometric impact of higher education management in developing countries might vary depending on various factors, including the quality and relevance of the research, the level of funding and resources available for research and the level of international collaboration, among others.

This study provides a comprehensive overview of the research landscape in higher education management in developing countries by identifying the most influential authors, institutions and countries and the key research topics and trends. This information can be helpful for researchers, policymakers and practitioners who seek to understand the state of research in the field and identify gaps in knowledge.

The data economy mainly relies on the surveillance capitalism business model, enabling companies to monetize their data. The surveillance allows for transforming private human experiences into behavioral data that can be harnessed in the marketing sphere. This study aims to focus on investigating the domain of data economy with the methodological lens of quantitative bibliometric analysis of published literature.

The bibliometric analysis seeks to unravel trends and timelines for the emergence of the data economy, its conceptualization, scientific progression and thematic synergy that could predict the future of the field. A total of 591 data between 2008 and June 2021 were used in the analysis with the Biblioshiny app on the web interfaced and VOSviewer version 1.6.16 to analyze data from Web of Science and Scopus.

This study combined findable, accessible, interoperable and reusable (FAIR) data and data economy and contributed to the literature on big data, information discovery and delivery by shedding light on the conceptual, intellectual and social structure of data economy and demonstrating data relevance as a key strategic asset for companies and academia now and in the future.

Findings from this study provide a steppingstone for researchers who may engage in further empirical and longitudinal studies by employing, for example, a quantitative and systematic review approach. In addition, future research could expand the scope of this study beyond FAIR data and data economy to examine aspects such as theories and show a plausible explanation of several phenomena in the emerging field.

The researchers can use the results of this study as a steppingstone for further empirical and longitudinal studies.

This study confirmed the relevance of data to society and revealed some gaps to be undertaken for the future.