University of Worcester Worcester Research and Publications
 
  USER PANEL:
  ABOUT THE COLLECTION:
  CONTACT DETAILS:

Customers’ experiences of fast food delivery services: uncovering the semantic core benefits, actual and augmented product by text mining

Teichert, T., Rezaei, Sajad ORCID: https://orcid.org/0000-0001-7942-0611 and Correa, J.C. ORCID: https://orcid.org/0000-0002-0301-5641 (2020) Customers’ experiences of fast food delivery services: uncovering the semantic core benefits, actual and augmented product by text mining. British Food Journal, 122 (11). pp. 3513-3528. ISSN 0007-070X

[img]
Preview
Text
Rezaei-9428-Customers-experiences-of-fast-food-delivery-services-uncovering-the-semantic-core-benefits-actual-and-augmented-product-by-text-mining.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (978kB) | Preview

Abstract

Purpose
This study conceptualizes food delivery services as service mix decisions (SMDs) and illustrates a data-driven approach for the analysis of customers' written experiences.

Design/methodology/approach
Web scraping, text mining techniques as well as multivariate statistics are combined to uncover the structure of the three tiers of SMD from consumers' point of view.

Findings
The analyses reveal that fast food delivery is not primarily about speed but that there are four distinct experiential factors to be considered for SMDs. Fast food delivery services are associated both with the actual product (i.e. product issues and brand satisfaction) and with the augmented product (payment process and service handling).

Originality/value
Findings demonstrate the relevance of SMDs in omnichannel food retail environments and guide researchers in multistage analyses of consumers' online food reviews.

Item Type: Article
Additional Information:

Staff and students at the University of Worcester can access the full-text of the online published article via the official URL. External users should check availability with their local library or Interlibrary Requests Service.

Uncontrolled Discrete Keywords: user-generated content, text mining, food delivery, IRWRG
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: College of Business, Psychology and Sport > Worcester Business School
Related URLs:
Depositing User: Sajad Rezaei
Date Deposited: 13 May 2020 11:17
Last Modified: 15 Feb 2023 14:33
URI: https://eprints.worc.ac.uk/id/eprint/9428

Actions (login required)

View Item View Item
 
     
Worcester Research and Publications is powered by EPrints 3 which is developed by the School of Electronics and Computer Science at the University of Southampton. More information and software credits.