This paper investigates the complexities of self-service technology (SST) adoption, recognizing the pivotal role of demographics in shaping consumer attitudes and behaviors. Through a comprehensive methodology involving initial interviews, measurement tool development, and statistical analysis, a novel factorization of SST adoption dimensions is revealed, emphasizing utility, engagement, and functionality. Surprisingly, while established constructs like perceived trust remain consistent, the model explains over 77.70 percent of behavioral intention variance, with utility, engagement, functionality, and resistance to change emerging as critical indicators. Moderation analysis highlights the influence of familiarity, technological anxiety, and age, underscoring the importance of tailoring SST experiences to diverse demographic cohorts. These findings not only enrich our understanding of consumer behavior but also provide actionable recommendations for designing user-centric SST systems. Ultimately, this research contributes to the refinement of self-service technologies, ensuring their relevance and efficacy in a rapidly evolving technological landscape.