Extending the Valence Framework: Factors Influencing Malaysians' Intention to Adopt Facial Recognition Payment Systems

Abstract

This study examines factors influencing Malaysians' intention to adopt facial recognition payment systems by extending the Valence Framework. Despite increasing global adoption of this technology, Malaysia has shown slower uptake, creating a need to understand the specific factors shaping consumer acceptance in this market. Data were collected through an online survey from 250 respondents across Malaysia's Central, Eastern, Northern, and Southern regions. The survey instrument measured seven potential adoption factors: perceived risk, technophobia, perceived complexity, relative advantage, initial trust, perceived playfulness, and need for uniqueness. Multiple linear regression analysis was employed to test the hypothesized relationships using SPSS software. The regression model explained 73.1% of variance in adoption intention. Five factors—perceived risk (β=-0.236, p<0.001), relative advantage (β=0.193, p=0.002), initial trust (β=0.443, p<0.001), perceived playfulness (β=0.161, p=0.002), and need for uniqueness (β=0.130, p=0.001)—significantly influenced intention to use facial recognition payment systems. Contrary to expectations, technophobia and perceived complexity showed no significant relationship with adoption intention. Initial trust emerged as the strongest positive predictor, while perceived risk was the most significant barrier to adoption. This study contributes to technology adoption literature by empirically testing an extended Valence Framework in the context of biometric payment systems in Malaysia. The findings reveal that emotional and social factors (perceived playfulness and need for uniqueness) play significant roles alongside traditional adoption factors, providing a more comprehensive understanding of consumer decision-making in emerging financial technologies. These insights offer practical guidance for financial service providers and technology developers seeking to increase adoption of facial recognition payment systems in the Malaysian market.