Bibliometrics frequently seeks to identify core research areas, subject terms, and journals. Common methods include core/periphery models, subject specialization indices, and Bradford's Law of scattering. This study explores Bradford's Law to determine core ICT subject terms within IKM literature. The proliferation of ICT applications across sectors has led to significant scholarly output, particularly in the latter part of the 2011-2020 decade. Onyancha (2018) highlighted ICT's emergence as a leading research topic in Library and Information Science (LIS), with knowledge management also gaining significant traction. Analyzing ICT application in IKM, a burgeoning LIS subfield, and identifying its core subject terms is timely, given knowledge management's increasing reliance on ICTs. Content analysis helps delineate subject terms, gauge research interest, assess information resource organization, determine disciplinary growth, and improve information retrieval. This study uses Bradford's Law to achieve these goals within the context of IKM literature.

Most Bradford's Law studies focus on journal productivity to identify core journals in specific fields. Recent applications include examining journal citations and assessing citation distribution patterns to determine core cited journals. There have also been attempts to extend Bradford's Law beyond its traditional focus. Tsay (2008) analyzed subject changes between citing and cited literature in digital libraries, revealing that while citing core journals focused on ICT application in libraries, cited journals covered digital libraries, general LIS, and library technology. Giap et al. (2014) applied Bradford's Law to evaluate a library's book collection, showing that while the subject heading distribution didn't perfectly fit Bradford's law, it presented a close approximation.

This study utilized EBSCO Discovery and EBSCOhost's LISTA and LISS databases to extract data. A search combining terms like "Information and Communication Technologies" and "knowledge management" yielded 9479 articles published between 1998 and 2017. The extracted subject terms were analyzed using Bibexcel software to generate term occurrence frequencies. The methodology followed procedures outlined by Andrés (2009) and Singh and Bebi (2014) for applying Bradford's Law. Subject terms and corresponding articles were ranked. Bradford's constant (k) was calculated for each study period (1998-2002, 2003-2007, 2008-2012, 2013-2017) using the formula: x = (exYm)/P, where y is Euler's number, Ym is the maximum number of records for the highest-ranked subject term, and p is the number of zones (set at four). The number of core subject terms (ro) for each period was calculated using: ro = T(κ-1)/(x-1), where T is the total number of subject terms, x is Bradford's constant, and p is the number of zones. The number of subject terms in subsequent zones was calculated using: r₁ = r₀ x k¹, r₂ = r₀ x k², r₃ = r₀ x k³. The core subject terms were then identified from the ranked list for each time zone. Bradford's multiplier (κ) was computed for each zone by dividing the number of subject terms in the subsequent zone by the number in the previous zone to assess the fit of the data to Bradford's Law. The ratio of subject terms across Bradford zones was also calculated to determine the proportionality to the pattern 1:n:n²:n³.

The study revealed variations in the number and composition of core ICT subject terms across different time periods. From 1998 to 2017, the number of core terms in Bradford's nucleus fluctuated: 7 (1998–2002), 36 (2003–2007), 86 (2008–2012), and 39 (2013–2017). The core subject terms varied significantly across periods, reflecting shifts in research focus and the interdisciplinary nature of ICTs and KM. Tables 2-5 detail the core subject terms for each period, highlighting the changing emphasis on specific applications and aspects of ICTs within IKM. The analysis showed a consistent dominance of ICT applications in fields like medicine, business and commerce, education, decision sciences, and industrial management throughout the study period. Tables 2 through 5 show the core subject terms for each time period, illustrating the shift in focus over time. For example, in 1998-2002, technology and information services dominated, while the period 2003-2007 was characterized by terms related to business management and decision-making. Later periods (2008-2012 and 2013-2017) saw the emergence of terms related to social networks and specific technological applications in medicine. The study found that the dispersion of ICT subject terms largely aligns with Bradford's Law, as evidenced by the consistent multipliers across zones (Table 6) and the ratios approximating Bradford's distribution (Table 7). However, the article distribution across zones did not perfectly adhere to the 1:n:n²:n³ pattern.

The findings indicate the evolving nature of ICT applications in IKM research. The shifting core subject terms highlight the dynamic interplay between technological advancements and research focus within the field. The significant presence of ICT applications in various sectors (medicine, business, education, etc.) reflects the broad impact of ICTs on information and knowledge practices. The study's confirmation that subject term dispersion aligns with Bradford's Law supports the law's applicability in identifying core concepts beyond traditional journal analysis. The variations in core subject terms over time may be attributed to several factors such as evolving subject domains, changes in research interests, the interdisciplinary nature of ICTs and KM, and changes in indexing practices.

This study successfully applied Bradford's Law to identify core ICT subject terms within IKM literature, demonstrating the law's utility for subject analysis in this specific field. The findings highlight the evolving nature of the field, with consistent shifts in core concepts over time. Further research could explore Bradford's Law's applicability in other subject domains and units of analysis, providing richer insights into its versatility and limitations.

The study's reliance on a specific set of databases (EBSCO) might limit the generalizability of the findings. The specific search terms used could also influence the results, potentially omitting relevant publications. The study period's end in 2017 means the analysis does not capture recent technological advances and trends in ICTs and KM.