Over the past 20 years, self-service technology (SST) has become prevalent as a service delivery option. Today, SST investments are commonplace in many industries and technologies, and can have a considerable potential impact on investment and service quality and satisfaction. To ensure that SST options reach full potential, firms need to understand what customer traits and situational factors are related to the propensity to use SSTs. This study uses linear regression primarily and logistic regression and loglinear analysis secondarily to examine and confirm the relationships among the technology acceptance model (TAM) variables (perceived usefulness, perceived ease-of-use, and behavioral intent) and: (a) demographic predictors (age, gender, income, education, and ethnicity); (b) psychographic tech readiness predictors (optimism, innovativeness, discomfort, and insecurity); (c) situational predictors (wait time and crowding). A majority consensus among the three analysis methods concludes that the demographic of age and the situational factors of wait time and crowding have significant relationships with all three TAM variables. Psychographic tech readiness variables could not be concluded to have significance with TAM variables. The identification of these three observable variables' having direct relationships with SST use intention, SST perceived usefulness, and SST perceived ease-of-use appears valid and generalizable, and has significant implications for SST practitioners and for future SST adoption research.
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