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The social side of innovation: peer influence in online brand communities

  • Nan Wang
  • , Tian Lv
  • , Liya Wang*
  • , Aifang Guo
  • , Zhenzhong Ma
  • *Corresponding author for this work
  • Beijing Technology and Business University
  • Beijing Jiaotong University
  • Zhejiang Sci-Tech University
  • University of Windsor

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: Online brand communities (OBCs) are important platforms to obtain consumers' ideas. The purpose of this study is to examine how peer influence and consumer contribution behavior simulate innovative behaviors in OBCs to increase idea quality. Design/methodology/approach: Using a firm-hosted popular online brand community – Xiaomi Community (MIUI), the authors collected a set of data from 6567 consumers and then used structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to empirically test the impact of peer influence and consumer contribution behaviors on idea quality in OBCs. Findings: The results of this study show that both peer influence breadth and depth have a positive effect on idea adoption and peer recognition, wherein proactive contribution behavior positively mediates these relationships, and responsive contribution behavior negatively mediates the impact of peer influence breadth and peer influence depth on peer recognition. A more detailed analysis using the fsQCA method further identifies four types of antecedent configurations for better idea quality. Originality/value: Based on the attention-based view and the theory of learning by feedback, this study explores the factors that affect idea quality in the context of social networks and extends the research of peer influence in the digital age. The paper helps improve our understanding of how to promote customer idea quality in OBCs.

Original languageEnglish
Pages (from-to)2994-3016
Number of pages23
JournalManagement Decision
Volume61
Issue number10
DOIs
StatePublished - 24 Oct 2023
Externally publishedYes

Keywords

  • Attention-based view
  • Idea quality
  • Learning by feedback
  • Peer influence
  • Social networks

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