Artículo

Enhanced methodology to assess business research community serving extended realities movement

Resumen

Virtual, augmented, and mixed reality, known collectively as extended realities (XR), have the potential to transform businesses but research service is required. This report explores the productivity of XR-related in business research. This paper has enhanced the traditional bibliometric approach by integrating it with a mathematical supplement, Expedited Analytical Hierarchy Process (EAHP). This enhanced methodology allows for a nuanced evaluation of research service productivity and offers direction for future research efforts. Productivity is evaluated in terms of the effectiveness and efficiency of research results, so creating a bibliometrics index for commenting on research effectiveness and evaluating research efficiency criteria from a publication standpoint, the work added to the field. Analysis of the collected scientometrics data show the field is not yet optimally productive, leading to a call for increased focus on future research. Besides, the utilization of EAHP’s systematics way to convert the data into a future research direction, with mixed reality found to require more attention than other XRs. A complementary literature analysis step highlights the practical application of XRs in business and the growing importance of the XR-owned worlds, metaverses. As a result, this study found evidence to argue that the services provided by the business research community are not optimally productive when dealing with the XR movement, and it calls for more attention to support businesses.
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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