Understanding the corpus of mobile payment services research: an analysis of the literature using co-citation analysis and social network analysis

Authors

DOI:

https://doi.org/10.4301/S1807-1775202017002

Keywords:

Mobile Payment Services, Citation, Co-citation, Social Network Analysis

Abstract

Mobile Payment Services have advanced in the last two decades, gaining the attention of experts and researchers from around the world. A number of reviews and literature analysis studies have been carried out, aimed at analysing the numerous dimensions of mobile payment services; however, no researcher has attempted a co-citation analysis to scrutinise and comprehend the core knowledge structures that are integral parts of mobile payment services studies. Therefore, in order to fill this research gap, this research article aims to interpret the corpus of mobile payment services research, which was published during the period of 1997 to June 2017. Bibliometric and Social Network Analysis (SNA) methods were employed to formulate the core intellectual structure of research targeting mobile payment services. The Web of Knowledge (WoK) database was the key source from where 406 articles and 3,424 citations were obtained. These documents were analysed using co-citation analysis. UCINET was used to enlist the keynote research papers in the realm of mobile payment services as per factor analysis, citation and co-citation analysis, multidimensional scaling and centrality measurement. Seven core clusters of mobile payment services research emerged as a critical finding of this study; these clusters include (1) Adoption and usage; (2) Trust, risk and security; (3) Application; (4) Scheme; (5) Protocol; (6) Architecture; (7) Mobile payment corporation. The findings of this research study provide crucial guidelines for practitioners and researchers involved in this field.

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Published

2020-05-14

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Articles

How to Cite

Understanding the corpus of mobile payment services research: an analysis of the literature using co-citation analysis and social network analysis. (2020). Journal of Information Systems and Technology Management, 17, e202017002. https://doi.org/10.4301/S1807-1775202017002