Digital Marketing: A Scientometric Review

Abstract

The internet has offered marketers a new way to be more creative, resulting in more openness and transparency in marketing. The proliferation of digital media platforms and the commercial use of the internet have changed the business landscape. This study uses ScientoPy to analyze the global evolution of digital marketing research. It is grounded in the eminent Scopus and Web of Science databases. The parameters examined in this study were the number of publications, the most productive author, the analysis of the author’s keywords, popular sources, and institutional information. This study discovered a rising trend in digital marketing research in both the Scopus and WoS databases. “Machine Learning” has exploded in popularity during 2019 and 2020. “Digital Marketing” is inextricably linked to “Social Media”, “Big Data”, “Marketing Communication”, “Machine Learning”, and “Sentiment Analysis”, all of which gained traction in 2018 and beyond. Bucharest University of Economic Studies in Romania has become the most prolific research institution on digital marketing. The findings of this study enabled readers and future researchers to identify the primary research areas, keywords, related studies, and the most notable institutions and researchers. Besides, this study provides readers and future researchers with a global perspective on hot topics in digital marketing. It offers various analyzes for well-organized information utilization. This study also illustrates recent digital marketing research trends to inform practitioners, future researchers, and policymakers about developing digital marketing research theories and practices that merit scrutiny.

Trends in E-Commerce And Social Media Research in Asia: Five Years of Scientometric and Content Analysis

“…ScientoPy was used to conduct the temporal scientometric analysis in this article. Temporal analysis allows us to determine the origin of a new phenomenon and its evolution into a trend or trending issue (Abdullah et al, 2023;Ruiz-Rosero, Ramirez-Gonzalez, & Viveros-Delgado, 2019). Our advanced review paradigm, combining scientometrics and content analysis, provides a comprehensive and in-depth review (Li et al, 2022).…”