Disentangling the relationship between omnichannel integration and customer trust: a response surface analysis

Research output: Journal PublicationArticlepeer-review

5 Citations (Scopus)

Abstract

Purpose – This study aims to examine whether customer trust is influenced by the congruence and incongruence between customers’ perceptions of two types of omnichannel integration—perceived transactional integration (PTI) and perceived relational integration (PRI). We further considered the perceived effectiveness of e-commerce institutional mechanisms (PEEIM) as the boundary
condition of omnichannel integration’s effect.

Design/methodology/approach – Drawing upon the stereotype content model, this study hypothesizes the influences of PTI and PRI on customer trust wherein PEEIM moderates the relationships. The research model was empirically examined based on the responses surface analysis of survey data collected from 311 omnichannel customers.

Findings – Results showed that when PTI and PRI are congruent, customers are inclined to trust brands that have high levels of PTI and PRI rather than low levels of PTI and PRI. Moreover, the incongruence between PTI and PRI is positively related to customer trust. PEEIM was found to weaken the congruence effect while strengthening the incongruence effect. We also examined customer distrust as another relational outcome to provide a robust check.

Originality/value – This study uncovers customer cognition of omnichannel integration and examines the influences on customer trust, therefore contributing to our understanding of omnichannel integration’s effect from the customer perspective. Findings from this research provide insights for brand managers on deploying channel integration strategies and institutional mechanisms to manage customer trust.
Original languageEnglish
Pages (from-to)1077-1103
Number of pages27
JournalInternet Research
Volume34
Issue number3
DOIs
Publication statusPublished - 21 May 2024

Keywords

  • Perceived transactional integration
  • Perceived relational integration
  • Stereotype content model
  • Trust and distrust
  • Response surface analysis

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