Identification of seminal works in the spectrum of knowledge management system through Reference Publication Year Spectroscopy (RPYS). Issue 1 (2nd January 2020)

• Record Type: Journal Article
• Authors: Khan, Daud; Malik, Basharat Ahmad; Ali, Naushad
• Is Part Of: Collnet journal of scientometrics and information management. Volume 14:Issue 1(2020)
• Page Start: 163
• Page End: 176
• Publication Date: 2020-01-02
• Subjects: Knowledge management system -- Citation analysis -- Scientometrics -- Reference publication year spectroscopy; Science -- Periodicals; Science indicators -- Periodicals; Information science -- Periodicals; Social sciences -- Periodicals; 505
• DOI: 10.1080/09737766.2020.1833691
• Languages: English
• ISSNs: 0973-7766

Abstract

Abstract : The aim of the present study is to identify the seminal works in the spectrum of knowledge management system (KMS) by employing a recently developed scientometric technique viz. Reference Publication Year Spectroscopy (RPYS). Preliminary data of the study was extracted from Web of Science by using two phrases i.e., "Knowledge Management System" and "Knowledge Management Systems" to search in terms of topic (comprising the four parts: title, author keywords, abstract and KeyWords Plus). The search was confined to the time span from 1974 to 2017 which formulated a dataset of 1541 documents covering 37826 cited references. The seminal publications were associated with peak years of 1958, 1959, 1962, 1966, 1967, 1975, 1986, 1991, 1995 and 1998. In the second historical analysis, N_TOP10 indicator of CREx-plorer further identified seven landmark publications related to KMS. Landmark publications were described as those belonging to the top 10% of the most frequently cited publications for more than 15 years. In essence, this study identified 18 seminal/landmark works in the continuum of KMS. Moreover, the results of the investigation on seminal/ landmark works revealed that the subject of KMS is rooted in the areas of anatomy, economics, entrepreneurship, information systems, operations management, computer science, and management science. The results of this study could be useful for researchers, practitioners working in the spectrum of KMS.