Quantifying consumers' cost-value trade-offs on on-demand food delivery services: value-of-time framework and partitioned pricing

• Main Authors: Ma, Bohao, Wong, Yiik Diew, Teo, Chee-Chong, Sun, Shanshan
• Other Authors: School of Civil and Environmental Engineering
• Format: Article
• Language: English
• Published: 2024
• Subjects: Engineering; On-demand food delivery; Value of time
• Online Access: https://hdl.handle.net/10356/180703
• Institution: Nanyang Technological University

Purpose: This study aims to quantitatively characterize consumers' value-cost trade-offs in on-demand food delivery (ODFD) services. On the value side, the study endeavors to monetize the convenience value of ODFD with a Value-of-Time (VOT) framework, while on the cost side, this study investigates the implication of ODFD's partitioned pricing structure with the theoretical tenet of Attribution Theory. Design/methodology/approach: A stated choice experiment is developed and distributed to an online panel in Singapore with 580 valid responses collected. The data is then analyzed with a mixed logit model. Findings: The results show that cost, time, and health-related factors significantly influence consumers' dining channel choices. In terms of time, consumers' differentiated time sensitivities are revealed. Specifically, consumers are most sensitive to walking time, followed by waiting time at food establishments and at their own places. Also, the food type and dining locations affect consumers’ time perceptions. Regarding cost, consumers exhibit an inflated price sensitivity toward food premiums compared to delivery fees. Originality/value: This study addresses the lack of quantitative investigations into the value-cost tradeoffs in ODFD services. ODFD's convenience values are quantified and monetized with a novel VOT-based framework. Besides, the study sheds light on the underexplored partitioner pricing scheme with the theoretical tenet of the Attribution Theory. Overall, the research provides behavioral insights to support practitioners' operational decision-making.