A descriptive analysis of significant factors influencing the behavioral intention to adopt robot kiosks/service robots in service stores: Integrating the UTAUT and higher-order SERVQUAL approach

Abstract

• Robot kiosk for service is accepted by consumers in the Philippines. • The higher-ordered structural equation model considered in this study was established as a framework. • Tangibles, empathy, and responsiveness were primary domains under SERVQUAL. • Well-designed, responsive, and empathetic robot kiosks improve customer engagement. • Performance and effort expectancy, and social influence were determinants of satisfaction. Robot kiosks have emerged as a promising innovation with the potential to enhance service delivery. However, their adoption remains limited, underscoring the need for a deeper understanding of the factors influencing their acceptance and use. Moreover, the country has been adopting and promoting the United Nations Sustainable Development Goals by considering these AI-enabled robots among service industries, yet no studies have yet evaluated the satisfaction, adoption, and overall service quality of these robots. This study investigated the growing adoption and impact of robot kiosks across various service sectors in the Philippines, addressing the critical need for technological advancement in enhancing service delivery. Being the first study to be conducted among robot kiosks and service robots in the Philippines, the objective was to analyze the factors influencing the acceptance, adoption, and overall service quality of robot kiosks and service robots with data collected from 412 users in service industries. Utilizing the integrated Unified Theory of Acceptance and Use of Technology (UTAUT) model and SERVQUAL 5 dimensions higher-ordered structural equation modeling approach, the study found that tangibles (β: 0.807), empathy (β: 0.782), responsiveness (β: 0.765), assurance (β: 0.711), reliability (β: 0.646), and behavioral intention (β: 0.104) significantly affected customer satisfaction. Moreover, performance (β: 0.162) and effort expectancy (β: 0.156), social influence (β: 0.112), and service quality (β: 0.549) are key determinants of adoption. However, facilitating conditions (p-value = 0.283) were not found to be a significant predictor. The research highlights that well-designed, responsive, and empathetic robot kiosks improve customer engagement and satisfaction, but challenges like limited infrastructure may hinder broader implementation. These findings suggest that strategic deployment of robot kiosks can drive technological innovation, enhance service quality, and support socio-economic development in developing countries like the Philippines. The study’s significance lies in providing actionable insights for businesses and policymakers to optimize robot kiosk usage and advance the integration of AI technologies in the service sectors.