In many service industries, customers have to wait for service. When customers have a choice, this waiting may influence their service experience, sojourn time, and ultimately spending, reneging, and return behavior. Not much is known however, about the system-wide impact of waiting on customer behavior and resulting revenue. In this paper, we empirically investigate this by analyzing data obtained from 94,404 customers visiting a popular Indian restaurant during a 12 month period. The results show that a longer waiting time relates to reneging behavior, a longer time until a customer returns, and a shorter dining duration. To find out the impact of the consequences of waiting time, we use the empirical findings and data collected in a simulation experiment. This experiment shows that, without waiting, the total revenue generated by the restaurant would increase by nearly 15% compared to the current situation. Stimulating customers to reserve could enable restaurants to reap part of this benefit. Furthermore, the results of simulation experiments suggest that, within the boundaries of the current capacity, revenue could be increased by a maximum of 7.5% if more flexible rules were used to allocate customers to tables. Alternatively, by increasing the existing seating capacity by 20%, revenue could be boosted by 7.7% without the need to attract additional customers. Our findings extend the knowledge on the consequences of customer waiting, and enable service providers to better understand the financial and operational impact of waiting-related decisions in service settings.

Introduction

In the U.S. approximately 37 billion hours are spent on waiting in physical lines annually (Stone, 2012), which adds up to a wait between two and three years in the lifespan of an average American (Cox, 2005). This waiting takes place at a variety of service settings, such as restaurants, banks, amusement parks, retail stores, and healthcare facilities. Waiting for treatment in a healthcare facility might be unavoidable because of the lack of alternative options. In other service settings, however, customers are apparently consciously choosing to spend substantial amounts of time in line before they are served. Even though companies do not directly experience the costs of the discomfort incurred by their customers because of waiting, it is not clear to what extent these costs could have a direct and delayed impact on profitability through customer decisions and actions. In this paper, we empirically investigate several of the implicit consequences of letting customers wait, and we estimate the impact of these consequences in various scenarios using simulation. The importance of waiting in service practice is to a large extent reflected in the attention academia has devoted to the topic from different perspectives. From an operations perspective, waiting is commonly modeled as a cost function in which the wait results from a mismatch between demand and capacity that could be fixed by tweaking operational parameters (Osuna, 1985). Actual and perceived waiting can then be influenced by capacity, layout, and service and processing policy decisions (Luo et al., 2004; Nie, 2000). A large number of studies focus on the behavioral consequences of waiting by showing that long queues can impact aspects such as service evaluations and customer satisfaction (Davis and Maggard, 1990; Houston et al., 1998; Taylor, 1994), the perceived value of products and services (Debo et al., 2012; Koo and Fishbach, 2010; Kremer and Debo, 2015), and customer loyalty (Bielen and Demoulin, 2007; Dube et al., 1994). At the same time, empirical research and data collection in this domain is challenging. Whereas virtual queueing settings such as call centers are characterized by hi-tech environments in which data is abundantly available (Koole and Mandelbaum, 2002), studies involving physical queues primarily make use of survey data and self-reports (Munichor and Rafaeli, 2007; Rafaeli et al., 2002).