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Top1. Introduction
Today, wait time reduction is a global challenge in ride-sharing mobile applications (Luo et al., 2015; Peng et al., 2020). However, there is little scientific research on understanding and managing mobile waiting. Ride-sharing applications are booming around the world. As of December 2018, China has 190 million ride-sharing users, and the market is still expanding (Peng et al., 2020). In Germany, “Mitfahrgelenheit”, one of the largest ridesharing websites, offers nearly 900 thousand ride-sharing options online in real time. In 2017, Moscow had one sharing car for every 5,000 residents, while Washington led with one sharing car for every 692 residents, and it is still spreading around the world. Thereby, reducing wait time for ride-sharing applications has become a global marketing and e-commerce problem.
Perceived waiting time is critical in short-waiting applications, such as ride-sharing applications. Public data show that the arrival time of their services is usually within an hour, and the majority of the application users wait less than 15 minutes (Ai De Chu Xing, 2018). Because of the short arrival time of the services, customers may constantly check the application’s interface and keep an eye on the time of delivery (Kondrateva et al., 2020). For example, when customers use a ride-sharing application to take a taxi, from the time they click on the interface of the application to the beginning of the service, they may constantly check their mobile phones and keep an eye on when they purchased services will arrive. In this case, users keep watching the screen and it is easy to notice and record the passage of waiting time, the longer they wait the less satisfaction they feel and is more likely to lead user’s application abandonment behavior (Voorhees et al., 2009; Khedhaouria et al., 2016). So, the management of waiting time in short-waiting applications is important. However, previous studies ignore this point.
Waiting is a ubiquitous and inseparable part of people’s life and service experience, which negatively influences people’s overall evaluations of products, services, and stores (Voorhees et al., 2009; Al-Otaibi et al., 2018). It has been confirmed that waiting can bring pressure and dissatisfaction to customers (Hamidi & Moradi, 2017; Li & Chen, 2019). The actual waiting time exists objectively in the transaction, while perceived waiting time is the subjective judgment of the customer. Previous studies mainly focus on how to reduce the actual waiting time of customers, such as opening more cash registers during peak hours, hiring more employees during peak season, and queuing to provide services (e.g., Dennis & Taylor, 2006; Li & Chen, 2019). In some cases, it is difficult to reduce the actual waiting time, such as during the peak of consumer spikes in consumption. Sometimes, the decrease in actual waiting time does not affect satisfaction, but the perception of waiting time does (Thompson et al., 1996).
Scholars have found that perceived waiting time may be more useful and more controllable. Perceived waiting time is more suitable in measuring the length of waiting time and has a greater impact on satisfaction than the actual waiting time (Rose, 2005). Thus, the previous researchers propose various solutions to reduce perceived waiting time, such as adding various fillers, text, music, animation, and games on the website’s interactive interface, which have been proved to significantly reduce the perception of the wait (Lee et al., 2012; Oh & Sundar, 2015; Colleen, 2015). However, the current research on the influence of interactive interface on perceived waiting time focuses on websites (Mou et al., 2020), and there is a lack of research on mobile services.