This study explores the cognitive, demographic, and situational determinants of the preference for using self-service technologies over personnel-in-contact, with a focus on rational-experiential thinking styles [Epstein, S., Pacini, R., Denes-Raj, V., & Heier, H. (1996). Individual differences in intuitive-experiential and analytical-rational thinking styles. Journal of Personality and Social Psychology, 71(2), 390-405]. After an exploratory study of how service customers view service complexity, data are collected through a survey based on face-to-face interviews of adults who use seven different services; these data are analyzed using structural equation modeling. Findings show that (1) rational engagement has a strong positive effect on the preference for technology-based self-services; (2) persons high in experiential style prefer interactions with service personnel; (3) differential wait times have a significant influence on preference for technology; (4) service complexity moderates the influence of cognitive styles on preference for service technology; and (5) age has a negative influence on the preference for service technology.
Researchers recognize the critical importance of technology in the delivery of services, and empirical studies have investigated consumer differences in the use of technology-based self-services (Bitner et al., 2000, Dabholkar, 1996, Dabholkar, 1994, Dabholkar and Bagozzi, 2002, Meuter et al., 2005 and Meuter et al., 2000). Offering technology-based self-services, whether on- or off-site, can result in significant cost savings for companies (Barrett, 1997). As a consequence, many consumers are becoming increasingly familiar with self-service technologies (Burke, 2002). However, some consumers tend to avoid self-service technologies (SST), such as automated teller machines (ATMs) or self-service fuel dispensing, though they have been available for over 30 years and are now at a mature stage (Bateson, 1985 and Lee et al., 2003). The present research pertains to the preference of service consumers for personnel-in-contact versus SST and centers on service situations in which both delivery options are established service alternatives. From this perspective, the focus is not on investigating factors that explain the adoption of new service technology, such as self-scanning (Dabholkar, Bobbitt, & Lee, 2003). Rather, this research explores the role of cognitive styles in explaining the preference for using self-service technologies over personnel-in-contact and applies rational–experiential thinking styles (Epstein, Pacini, Denes-Raj, & Heier, 1996) for the first time in a service marketing context to conceptualize the major facets of how consumers process information. Epstein and colleagues' theory summarizes parallel effects related to the need for cognition (Cacioppo & Petty, 1982), as well as the need for interaction (Dabholkar, 1996), that previous research finds relevant or expects to be determinant factors in the use of technology-based self-services (see Dabholkar, 1996, Dabholkar and Bagozzi, 2002 and Langeard et al., 1981).
Additional causal factors affecting the preference for self-service technologies are demographic variables, especially age, waiting time, and service complexity (Shostack, 1987). Service complexity is expected to have a moderating effect in the influence of thinking styles on preference for SST, because higher service complexity is likely to accentuate the role of need for cognition (Cacioppo, Petty, Feinstein, Blair, & Jarvis, 1996) and make self-service technologies less attractive. Thus, we consider seven services that are classified by exploratory research into simple services (sending domestic mail, cash withdrawal, car refueling) and complex services (sending international parcels, financial transactions, local rail ticketing, long distance rail ticketing).
Section 2 reviews the literature on SST, cognitive styles, perceived service complexity, demographics, and situational determinants. Section 3 proposes a theoretical model. The research design, as well as measurement issues, is described in Section 4. Section 5 presents and discusses the empirical results of the model, based on confirmatory factor analysis of the scales used and structural equation modeling to test causal linkages between latent constructs. Finally, the last section examines the managerial implications of our findings, their limitations, and directions for future research.
This research has investigated cognitive, demographic, and situational determinants of consumer preference for SST over personnel-in-contact. The conceptual framework emphasizes the
influence of cognitive efforts needed to understand the service and use the technology on preference for SST. This study's findings support the relevance of rational-experiential thinking styles as a significant determinant of preference for SST, particularly in the case of complex services, for which consumers have to engage in effortful information processing. Finally, preference for SST appears quite significantly influenced by waiting time differentials between windows and SSTs, with the consequence that service providers willing to promote SSTs should ensure the wait differential remains in favor of the service echnology.
