Bibliometric studies in management and related fields are growing exponentially due to the need to systematize and summarize the growing body of publications. To do so, scholars mostly retrieve publications and metadata from either Scopus or Web of Science. Only a few bibliometric studies merge the two databases to conduct a single integrated analysis. Recent studies demonstrated the benefits of merging data from Scopus and Web of Science and presented methods for the merging. In this paper we build upon a recent method to simplify some of the key steps of merging datasets when using the R package Bibliometrix to perform bibliometric analyses. The result is a user friendly, accessible, three-step method that allows researchers to save time without compromising the integrity of the data, and the analysis. Our method is particularly beneficial for a wider application as it does not require coding skills, and neither proprietary nor shareware software.
A user-friendly method to merge Scopus and Web of Science data during bibliometric analysis / Caputo, Andrea; Kargina, Mariya. - In: JOURNAL OF MARKETING ANALYTICS. - ISSN 2050-3318. - 2022, 10:1(2022), pp. 82-88. [10.1057/s41270-021-00142-7]
A user-friendly method to merge Scopus and Web of Science data during bibliometric analysis
Caputo, AndreaPrimo
;
2022-01-01
Abstract
Bibliometric studies in management and related fields are growing exponentially due to the need to systematize and summarize the growing body of publications. To do so, scholars mostly retrieve publications and metadata from either Scopus or Web of Science. Only a few bibliometric studies merge the two databases to conduct a single integrated analysis. Recent studies demonstrated the benefits of merging data from Scopus and Web of Science and presented methods for the merging. In this paper we build upon a recent method to simplify some of the key steps of merging datasets when using the R package Bibliometrix to perform bibliometric analyses. The result is a user friendly, accessible, three-step method that allows researchers to save time without compromising the integrity of the data, and the analysis. Our method is particularly beneficial for a wider application as it does not require coding skills, and neither proprietary nor shareware software.File | Dimensione | Formato | |
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