An important perceived benefit of self-service technology has been its potential to reduce customer waiting-times. The purpose of this study was therefore to examine under which conditions the introduction of self-service technology in a service delivery process could reduce actual waiting-times and improve service levels. A simulation study showed that waiting-times and service levels in a hotel check-in process were influenced by the number of resources available to customers, the number of customers arriving to receive service, the processing speed of the self-service kiosk and the failure rate of the self-service kiosk. Specifically, results showed that longer self-service kiosk processing times and higher failure rates led to longer waiting-times, especially when customer demand was high. The authors recommend that service providers considering self-service technology implementation pay careful attention to the design and performance of the self-service technology.
Waiting lines are a common occurrence in many service settings where capacity is fixed as peak-time demand can exceed the available supply. For example, hotel guests arriving in the evening to check-in may encounter a full lobby, while restaurant patrons may have to wait for a table during lunch time. As waiting lines have been associated with reduced service evaluations (Taylor, 1994), negative perceptions of service quality (Dube-Rioux et al., 1989), and reduced satisfaction (Katz et al., 1991), having to wait makes a customer's first experience of a service is a negative one (Baker and Cameron, 1996, Dickson et al., 2005 and Maister, 1985). Consequently, waiting-time reduction has been a major objective of service providers.
Service providers have several strategies available to them to reduce customers’ waiting-times. In theory, service providers could eliminate waiting lines by setting their capacity to peak demand (Dickson et al., 2005). However, most of this capacity would remain idle and would result in an unsustainable cost structure. Therefore, a more practical approach has been to use queuing theory and other operations management techniques to find the optimal point where the cost of providing service and customers’ waiting-time are simultaneously minimized (Dickson et al., 2005, Hwang and Lambert, 2008 and Lambert and Cullen, 1987).
A more recent and cost-effective approach to reduce waiting-times has been to introduce self-service technologies (SSTs) into the service delivery process. SSTs have been defined as technological interfaces that allow customers to produce services without a service employee's involvement (Meuter et al., 2000). For example, hotel guests can bypass the front desk and use a self-service kiosk (SSK) to check-in and receive their key cards without the direct contribution of a service employee (Dabholkar, 1996 and Weijters et al., 2007). The simultaneous reduction of waiting-times and operating costs has been used by the self-service industry as a selling point for SSKs (Avery, 2008 and IBM, 2009). However, there is no empirical evidence that introducing an SST alternative to the existing service delivery process can indeed help firms reduce waiting-times (Oh and Jeong, 2009).
An intuitive application of queuing theory suggests that adding a resource to the existing service delivery system would increase its capacity and therefore reduce waiting-times (Lambert and Cullen, 1987). Nevertheless, the addition of an SST alternative to the existing service delivery process can transform even the simplest system into a complex one with conditional logic and interactions. For example, a customer wanting to check-in will decide whether to use the SSK based on the lengths of the SSK and service employee waiting lines. The next customer arriving will encounter a different system, based on the previous customer's choice. While research on customer usage of SST has examined what influences customers’ choice between service delivery alternatives (Weijters et al., 2007), the effect of this choice on system waiting-times is unclear. Similarly, previous research has examined the impact of SST failures on customers’ satisfaction (Reinders et al., 2008 and Weijters et al., 2007), but not their impact on system performance.
The purpose of this study was, therefore, to test if the introduction of SST in a service delivery process could reduce actual waiting-times and improve service levels. This study extends the SST literature by investigating whether a commonly held assumption of SST implementation holds true. This topic is particularly relevant for the hospitality industry. Self-service check-in in hotels has recently received attention in both the academic (Oh and Jeong, 2009) and practitioner literature (Avery, 2008). Furthermore, the 2010 Hospitality Technology SST survey found that 94% of responding hotel managers wanted to implement SST to improve customer satisfaction (Blair, 2010) while 68% of customers believed SST would reduce waiting lines, making this a timely topic for investigation.
