Uncovering merchants’ willingness to wait in on-demand food delivery markets
While traditional on-demand food delivery services help restaurants reach more customers and enable doorstep deliveries, they also come with drawbacks, such as high commission fees and limited control over the delivery process. White-label food delivery services have emerged as an alternative, ready...
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| Main Authors: | , , , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2024
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/9309 https://ink.library.smu.edu.sg/context/sis_research/article/10309/viewcontent/UncoveringMerchantWillingnessToWait_av.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | While traditional on-demand food delivery services help restaurants reach more customers and enable doorstep deliveries, they also come with drawbacks, such as high commission fees and limited control over the delivery process. White-label food delivery services have emerged as an alternative, ready-to-use platform for restaurants to arrange delivery for customer orders received through their applications or websites, without the constraints imposed by traditional on-demand food delivery platforms or the need to develop an in-house delivery operation. Although several studies have investigated consumer behavior when using traditional on-demand food delivery services, there is limited research on merchants’ behavior when adopting white-label food delivery services. In this research, we develop a non-parametric survival model to estimate merchants’ willingness to wait when using white-label food delivery services and examine how various factors, such as delivery fees, the number of placed orders, and average waiting time, affect merchants’ willingness to wait, drawing on a dataset of both delivered and canceled orders from a crowd-sourcing delivery platform in Singapore. The empirical results show that merchants’ willingness to wait has a non-linear relationship with their average waiting time; it initially increases and then decreases with average waiting time. Moreover, the relationship between merchants’ willingness to wait during the pick-up stage and their average waiting times in the matching stage follows a similar non-linear trend. Merchants who have experienced lengthy waiting times on average in the matching stage tend to be less patient in the pick-up stage. This research sheds light on the stage-specific dynamics of merchants waiting behavior in white-label delivery service and provides insights for delivery platforms to optimize their operational strategies and enhance user experiences. |
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