Research on online shopping contextual cues: refining classification from text mining
Asia Pacific Journal of Marketing and Logistics
ISSN: 1355-5855
Article publication date: 15 May 2023
Issue publication date: 22 November 2023
Abstract
Purpose
Contextual cues have become a hot research topic in the field of mobile consumer behavior, owing to the continuous rise of digital marketing. However, the complex online shopping scene makes it challenging to directly identify the association between the characteristics of contextual cues and consumer behavior. Presently, few studies have only systematically extracted and refined the types and characteristics of contextual cues. The purpose of this study is to explore the types and mechanisms of contextual cues in online shopping scenarios.
Design/methodology/approach
This study uses the word2vec algorithm, grounded theory and co-occurrence cluster method, along with online shopping word-of-mouth (WOM) text and consumer behavior theory, in order to explore different types of contextual cues and its efficiency from 5,619 comment corpus.
Findings
This study puts forward the following conclusions. (1) From the perspective of online shopping, contextual cues comprise aesthetic perception cues, value perception cues, trust-dependent cues, time perception cues, memory attention cues, spatial perception cues, attribute cues and relationship cues. (2) Based on the online shopping scenarios, contextual cues and their interaction effects exert an effect on consumer satisfaction, recommendation, purchase and return behavior.
Originality/value
The study conclusions are helpful to further reveal the deep association between contextual cues and consumer behavior in the process of online shopping, thus providing practical and theoretical enlightenment for enterprises to not only effectively reshape the scene but also promote the consumers' active purchase behavior.
Keywords
Acknowledgements
This research is supported by the Fundamental Research Funds for the Central Universities (N2223007, N2223020).
Compliance with ethical standards: This paper and all authors have complied with ethical standards, and the authors are willing to accept all responsibility for any violation of ethical standards in the study.
Conflict of Interest: The authors declare that we have no conflicts of interest.
Citation
Wang, L., Gao, H. and Zhao, Y. (2023), "Research on online shopping contextual cues: refining classification from text mining", Asia Pacific Journal of Marketing and Logistics, Vol. 35 No. 11, pp. 2704-2726. https://doi.org/10.1108/APJML-10-2022-0847
Publisher
:Emerald Publishing Limited
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