The role of information for the customer journey in mobile food ordering apps

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)
151 Downloads (Pure)

Abstract

Purpose
This study aims to determine how to influence the customer journey of mobile food ordering applications (MFOAs) users. It researches how available information could influence customers’ intention to use MFOAs platforms in the prepurchase stage and explores the potential of personalized information to improve customer satisfaction with these services in the postpurchase stage.

Design/methodology/approach
This research followed a mixed design, combining qualitative (focus groups) and quantitative (online survey) research and using both content analysis and partial least squares structural equation modeling.

Findings
Two types of available information (firm-generated information and online customer reviews) had a positive influence on the behavioral intention to use MFOAs. Additionally, findings showed that different web personalization strategies, namely, content personalization, functional personalization and system-driven personalization, were useful tools to create customer satisfaction with this type of platform.

Research limitations/implications
The study discusses limitations regarding the sample and sampling process, indicator variables and measures.

Practical implications
The present research provides actionable insights for online food delivery providers.

Originality/value
This study addresses a research gap in the literature and provides a novel and richer understanding of customer behavior toward mobile food delivery platforms. Also, it adds to the personalization research by identifying and testing a range of web personalization strategies.

Keywords
Original languageEnglish
Pages (from-to)574-591
Number of pages18
JournalJournal Of Services Marketing
Volume37
Issue number5
Early online date2 Nov 2022
DOIs
Publication statusPublished - 4 May 2023

Keywords

  • Customer journey
  • Mobile food ordering applications
  • Web personalization
  • User-generated information
  • Firm-generated information
  • Customer satisfaction

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