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The current state of big data analytics research in marketing: A systematic review using TCCM approach

Christine Ye
한국마케팅과학회 (Korean Scholars of Marketing Science)|2024.06|Journal of Global Scholars of Marketing Science(마케팅과학연구) (全球营销科学学报)|제34권 제3호|pp. 393-415|DOI 10.1080/21639159.2023.2275792

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systematic reviewmarketingbibliometric analysisTCCMBig data analytics
주제분류경영학

초록

There has been an explosive interest in big data analytics among marketing academics. Despite the growing scholarly interest, there has been a lack of effort in reviewing the past studies on this topic. Based on bibliometric analyses and drawing on the Theory-Context -Characteristics-Methods (TCCM) framework, the current study provides a comprehensive understanding of the common theories, contexts (i.e. industries and countries), characteristics (i.e. key variables and their relationships), and methods (i.e. research methods and analytical techniques) employed in this research domain. Through a systematic review of 64 articles, four distinct themes were identified. Analyses also revealed a general divide in findings between studies that used different research methodologies (i.e. big data vs. traditional method). The current research concludes with implications and directions for future research.

Abstract

There has been an explosive interest in big data analytics among marketing academics. Despite the growing scholarly interest, there has been a lack of effort in reviewing the past studies on this topic. Based on bibliometric analyses and drawing on the Theory-Context -Characteristics-Methods (TCCM) framework, the current study provides a comprehensive understanding of the common theories, contexts (i.e. industries and countries), characteristics (i.e. key variables and their relationships), and methods (i.e. research methods and analytical techniques) employed in this research domain. Through a systematic review of 64 articles, four distinct themes were identified. Analyses also revealed a general divide in findings between studies that used different research methodologies (i.e. big data vs. traditional method). The current research concludes with implications and directions for future research.

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