The Expectation Trap in Errand Delivery: How Pre-usage Value Anticipation Shapes the Service Experience and Customer Satisfaction
This study reveals that on-demand errand delivery platforms often create an "Expectation Trap" where rigid algorithmic promises negatively impact customer satisfaction by causing users to project anticipated value onto opaque service experiences, though this effect can be mitigated by intrinsic motivation and more flexible time estimates.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
Every day, millions of people open an app to send a stranger to pick up a forgotten document, buy a specific gift, or deliver a prescription. They see a promise on the screen: a precise time, perhaps thirty minutes, when the item will arrive. This promise is not made by a human manager but is calculated instantly by an algorithm. For years, service researchers have believed that when a company meets or beats a promise, the customer feels happy. This idea, known as expectation confirmation, suggests that satisfaction comes from comparing what you expected with what you actually got. If the service is better than expected, you are pleased; if it is worse, you are disappointed. However, this traditional view assumes that customers can watch the service happen and judge it on its own merits. In the world of on-demand errand delivery, the process is hidden. The customer sees only a moving icon on a map, with no view of the rider navigating traffic or finding the right shop. This invisibility creates a unique psychological situation where the standard rules of satisfaction may no longer apply.
A team of researchers set out to understand how people judge these invisible services. They focused on a specific type of service called errand delivery, where a gig worker completes a personal task for a fee. The researchers surveyed 1,176 customers in Guangzhou, China, asking them about their feelings before they used the service and again two weeks after they had used it. They wanted to know if the precise time promised by the algorithm helped or hurt the customer's final satisfaction. They also investigated whether some people are better at handling these situations than others, specifically looking at how a person's inner drive to control their own experience and their comfort with new technology changes the outcome.
The study revealed a surprising and counterintuitive phenomenon the authors call the "Expectation Trap." When an algorithm displays a precise time, such as "28 minutes," it creates a rigid mental baseline in the customer's mind. Because the customer cannot see the work being done, they cannot adjust their expectations based on what is actually happening. Instead, they are forced to rely entirely on that initial number. The researchers found that this precision is a double-edged sword. While a high promise might make a customer feel good initially, it actually lowers their final satisfaction. Meeting the exact time promised brings only a sense of relief, not happiness, because the customer views it as the bare minimum. Any slight delay, which is invisible until the very end, feels like a significant failure. The data showed that this negative effect of the rigid promise was so strong that it outweighed all the positive feelings generated by the service itself. In short, the more precise and demanding the algorithmic promise, the less satisfied the customer tends to be, even if the delivery is technically successful.
The researchers also discovered how customers cope with this trap. They found that people who are naturally motivated to take charge of their own lives and find meaning in their actions are better at escaping this dissatisfaction. These individuals do not just passively wait for the algorithm to work; they actively construct their own experience. They might use the waiting time to do something productive, or they might empathize with the rider, assuming the delay is due to traffic rather than poor service. This internal drive allows them to build satisfaction from their own actions rather than relying solely on the algorithm's promise. Interestingly, the study found that being highly curious about technology or eager to try new gadgets did not always help. In fact, customers who were deeply engaged with the technology features sometimes formed even more rigid expectations, making them more vulnerable to the trap. The most satisfied customers were those who were internally motivated but did not over-invest in the technological details of the service.
This research challenges the common belief that faster and more precise algorithms always lead to happier customers. It suggests that in services where the work is hidden from view, the precision of the promise can become a psychological burden. The study indicates that the way a service is presented matters as much as the service itself. If a platform displays a single, exact time, it sets a trap that is difficult to escape. The authors suggest that showing a range of times, such as "25 to 35 minutes," might be a better approach. This small change could signal to the customer that the time is an estimate rather than a guarantee, giving them a wider mental space to feel satisfied. The findings offer a clear lesson for both companies and users: in a world of invisible services, the most satisfying experience may not come from the most precise promise, but from a promise that allows for human uncertainty.
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