Artículo

Social Impact Assessment: a Bibliometric Survey

Resumen

Study objectives: in order to present the scientific scenario on the assessment of social impact in the academic area of administration and business, thus making it possible to create new data on what is being researched and what are the future directions of research in relation to social impact indicators. Methodology: it was used the bibliometric survey method of publications present in the Web of Science database, through citation, co-citation and bibliographic analyzes. Afterwards, this method is combined with a systematic review of literature of studies from administration and business area. Main results: the bibliometric results demonstrate an increase in the number of publications, the main authors on the subject in relation to the number of articles and citations, the universities with more studies, and the areas of study with more publications on the subject. While the systematic review demonstrated that the studies greatest challenge is to understand how to measure the social impact, with the context displaying an important role for the measurement of this theme. Academic contributions: it was possible to provide guidance, active and objective, regarding the main achievements of the research theme, as well as its main characteristics and future challenges. In addition, on the articles of administration and business area, suggestions for future studies were provided, focusing mainly on more practical examples than on theoretical discussions. Practical contributions: the present bibliometric review helps to understand where further development and attention is needed in discussions on such a relevant topic for different actors in society.
Hidayat, Erwin Yudi (57205439013); Hastuti, Khafiizh (56485990500); Muda, Azah Kamilah (23390362900)
Artificial intelligence in digital image processing: A bibliometric analysis
2025
10.1016/j.iswa.2024.200466
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212984349&doi=10.1016%2fj.iswa.2024.200466&partnerID=40&md5=14c2a82f6cb46e9efa80c050fc79c24f
Faculty of Computer Science, Universitas Dian Nuswantoro, Semarang, 50131, Indonesia; Dinus Research Group for AI in Medical Science (DREAMS), Universitas Dian Nuswantoro, Semarang, 50131, Indonesia; Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka, 76100, Malaysia
All Open Access; Gold Open Access
Scopus
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