Exploring Food Delivery Riders Need-Based Segments: A Mixed-Method Approach
Abstract
On-demand food delivery (ODFD) services are crucial in logistics, connecting restaurants with consumers. However, delivery riders face high turnover rates. Despite their vital roles, little is known about the factors affecting rider retention. This study identifies key factors influencing ODFD riders’ intentions to stay and categorizes different rider segments. Using a mixed-method approach, Study 1 explores 13 retention factors through a thematic analysis of 120 qualitative surveys. Study 2 ranks these factors and identifies four need-based segments via maximum difference scaling (MDS) analysis of 412 surveys. The study highlights the heterogeneous needs of ODFD riders and suggests targeted retention strategies.
Department(s)
Marketing
Document Type
Article
DOI
10.1080/15332969.2024.2435742
Keywords
hierarchical Bayes analysis, need-based segment, On-demand food delivery, retention factors
Publication Date
1-1-2025
Recommended Citation
Yun, Gawon; Zhang, Jiayuan; and Zhang, Ruoqing, "Exploring Food Delivery Riders Need-Based Segments: A Mixed-Method Approach" (2025). Faculty Scholarship. 270.
https://bearworks.missouristate.edu/articles00/270
Journal Title
Services Marketing Quarterly
