Predicting Older Adults' Mobile Payment Adoption: An Extended TAM Model

Area of Science:

• Gerontology
• Human-Computer Interaction
• Information Systems

Background:

• Mobile payments (M-payment) adoption is growing globally.
• Understanding older adults' adoption barriers is crucial for digital inclusion.
• Existing models need integration to capture specific user segments.

Purpose of the Study:

• To identify key factors influencing older adults' behavioral intentions to use mobile payments.
• To integrate Technology Acceptance Model, Theory of Reasoned Action, Diffusion of Innovations, and perceived risk.
• To examine the role of trust in M-payment adoption among seniors.

Main Methods:

• A survey of 365 older adults (aged 55+) in central Taiwan.
• Utilized a combined theoretical model incorporating TAM, TRA, DOI, trust, and perceived risk.
• Partial Least-Squares Structural Equation Modeling (PLS-SEM) for data analysis.

Main Results:

• Attitude was the primary determinant of M-payment behavioral intention in older adults.
• Perceived usefulness, ease of use, and observability positively influenced attitude towards M-payment.
• Trust significantly impacted perceived usefulness and ease of use, influenced by performance and financial risks.

Conclusions:

• Enhancing perceived usefulness, ease of use, and observability is key to improving older adults' M-payment adoption.
• Addressing performance and financial risks is vital for building trust in M-payment systems for seniors.
• Integrated models provide a robust framework for understanding technology adoption in specific demographics.