Publication Type

PhD Dissertation

Version

publishedVersion

Publication Date

5-2023

Abstract

Customers' waiting experiences are crucial in service and retail systems, and this thesis investigates their impact in various contexts. In the service system, long waiting time causes customers' no-show behavior, and negative feedback from existing customers, which in turn results in low conversion and loss of revenue for service providers. However, waiting is not always a negative presence. In the online retail system, with the innovation of the sales model, long waiting can earn more time for online retailers to ease the logistics pressure although it may reduce customers' willingness to pay at the same time. Against this backdrop, in the first essay, we investigate the influence of customers' waiting preference and no-show behavior on appointment systems in the service system. Secondly, this dissertation looks at the pricing incentivization of customers' waiting in online retail systems. Finally, we empirically measure the impact of financial incentives on last-mile operations to reduce customers' expected waiting time for delivery.

In the first essay, we conduct two lab experiments and build models to examine the impact of waiting on customer's appointment selection and no-show behavior in appointment systems. Appointment systems are widely adopted in many service organizations. The simplest and most common format is the Equally-Spaced (ES) system, in which the inter-appointment times between consecutive arrivals are equal. One major drawback of such a system is the long expected waiting time for later arrivals, which makes later appointment positions unappealing to customers. As a result, customers who take these positions are more likely to abandon their appointments, leading to a higher no-show rate. To address this issue, we examine a novel Equal-Waiting (EW) scheduling system under which the expected waiting times are equal across appointments. Through a series of controlled lab experiments, we establish that the EW system increases the attractiveness of later appointments and that customers who are willing to take these appointments are more likely to show up. We then incorporate this individual-level preference and no-show behavior into models to evaluate its impact on the system-level performance. We find that, compared with the traditional ES system, the EW system can significantly increase customers' show-up rate and improve system utilization.

In the second essay, we focus on the pricing incentivization of customers' waiting in a new flash-sale model, which is widely used by many platforms such as JD.com, and Lazada on seasonal promotions like Double 11. In flash sales, customers first pay the deposit and then wait several days to make the final payment. The product will be shipped out after the final payment is made. The deposit determines the discount strength that the customer can enjoy due to the Double Deposit Inflation and provides a signal to the retailer on potential demands, allowing the retailer to reduce the logistical cost incurred from bottlenecked demand surges. The waiting occurring during the transaction process may reduce customers' willingness to pay. However, it can earn more time for the online retailer to ease the logistics pressure so that the logistics cost can be further reduced. Considering these important features in flash sales, we propose a pricing optimization model and jointly decide the optimal deposit and the product’s full price. We identify the value of introducing the flash-sale channel for the retailer and the conditions under which the value can be realized. We also provide the optimal flash-sale duration. In addition, our findings indicate the importance of considering the production cost in the optimal pricing strategy, especially for the linear demand function. In the case study, we calibrated our model with real data from an e-commerce company in China, and the results from a 5-fold cross-validation show that our model can predict demand well. Besides, by applying the pricing strategy proposed in this paper, we can dramatically improve the profit.

The third essay delves into the impact of financial incentives on last-mile operations. Riders' responsiveness is crucial for service quality in last-mile delivery. To address the frequently-occurred low responsiveness due to driver shortage or order congestion, most delivery platforms adopt financial incentives to attract more drivers. However, empirical research on the effectiveness of financial incentives and their spillover effects is lacking. Thus, the third essay examines the impact of financial incentives on last-mile operations, using transactional datasets obtained from a crowdsourced delivery platform.

Specifically, we employ a regression discontinuity design to identify the causal influence of financial incentives on drivers' order acceptance speed. Our results show that financial incentives significantly reduce the driver's order acceptance duration by 16.6%. Furthermore, temporal effects suggest the platforms can strategically terminate financial incentives ahead of schedule, as the impact will persist for a certain period of time. From a network perspective, we also examine the spillover impact of the neighboring stores' financial incentives on the performance of the focal store. Interestingly, our findings reveal opposing impacts that depend on the focal store's status. Specifically, the nearest store's financial incentives cause longer driver's order acceptance duration at the focal store without financial incentives; however, the opposite spillover effect is observed when the focal store also offers financial incentives. To better understand the underlying mechanisms, we identify the siphon effect and clustering effect as the key drivers of this phenomenon. This study contributes both theoretical and practical implications to the field of last-mile delivery.

Keywords

appointment systems, no-show, waiting time, behavioral experiment, flash sales, joint optimization model, data-driven, financial incentives, network, last-mile operations

Degree Awarded

PhD in Business (Ops Mgmt)

Discipline

Business Administration, Management, and Operations | Operations and Supply Chain Management

Supervisor(s)

LIM, Yun Fong

First Page

1

Last Page

177

Publisher

Singapore Management University

City or Country

Singapore

Copyright Owner and License

Author

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