Discovery of behavioral patterns in online social commerce practice

Xiaoyun Jia, Ruili Wang, James H. Liu, Chuntao Jiang

Research output: Journal PublicationReview articlepeer-review

10 Citations (Scopus)

Abstract

Discovery of behavioral patterns in online social commerce practice becomes important in this digital era. In this article, we propose a systematic approach to behavioral pattern discovery, and apply it in an emerging online social commerce venue: live streaming. We investigate behavioral patterns in gifting encouragement in live streaming to understand online social commerce practice. Our proposed approach is based on multiple triangulation, including data source triangulation (i.e., streamers, viewers, and actual behavior) and data collection method triangulation (i.e., interviews, focus groups, and observations). Through multiple triangulation, four behavioral patterns of gifting encouragement are discovered: (i) requesting a certain gift for providing a particular service, (ii) creating a raffle, (iii) eliciting competition between individuals, and (iv) eliciting competition between groups. This research reveals the special behavioral patterns in live streaming, and thus increases our knowledge of social commerce practices. This research provides a systematic approach to discover online behavioral patterns, and provides practical implications in live streaming platforms, especially in marketing and platform design. This article is categorized under: Application Areas > Business and Industry.

Original languageEnglish
Article numbere1433
JournalWiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Volume12
Issue number1
DOIs
Publication statusPublished - 1 Jan 2022
Externally publishedYes

ASJC Scopus subject areas

  • General Computer Science

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