Critical Factors Influencing the Intention to Adopt m-Government Services by the Elderly

Md. Shamim Talukder, Raymond Chiong, Brian Corbitt, Yukun Bao

Source Title: Research Anthology on Supporting Healthy Aging in a Digital Society

ISBN13: 9781668452950|ISBN10: 1668452952|EISBN13: 9781668452967

DOI: 10.4018/978-1-6684-5295-0.ch056

MLA

Talukder, Md. Shamim, et al. "Critical Factors Influencing the Intention to Adopt m-Government Services by the Elderly." Research Anthology on Supporting Healthy Aging in a Digital Society, edited by Information Resources Management Association, IGI Global, 2022, pp. 1028-1050. https://doi.org/10.4018/978-1-6684-5295-0.ch056

APA

Talukder, M. S., Chiong, R., Corbitt, B., & Bao, Y. (2022). Critical Factors Influencing the Intention to Adopt m-Government Services by the Elderly. In I. Management Association (Ed.), Research Anthology on Supporting Healthy Aging in a Digital Society (pp. 1028-1050). IGI Global. https://doi.org/10.4018/978-1-6684-5295-0.ch056

Chicago

Talukder, Md. Shamim, et al. "Critical Factors Influencing the Intention to Adopt m-Government Services by the Elderly." In Research Anthology on Supporting Healthy Aging in a Digital Society, edited by Information Resources Management Association, 1028-1050. Hershey, PA: IGI Global, 2022. https://doi.org/10.4018/978-1-6684-5295-0.ch056

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Abstract

While the elderly population is growing rapidly, acceptance and use of m-government services by them are far below expectation. Previous studies on acceptance and use of m-government services have predominantly focused on younger citizens with skills and experience of information technologies. Drawing upon the dual factor model, this study investigates the enablers and inhibitors of the elderly's m-government service adoption behavior. Four constructs from the unified theory of acceptance and use of technology (UTAUT), namely, performance expectancy, effort expectancy, facilitating conditions, social influence; and self-actualization are treated as enablers, while user resistance to change, technology anxiety, and declining physiological conditions are regarded as inhibitors. Results show that adoption of m-government by the elderly is significantly influenced by all tested enablers and inhibitors, except for social influence. This study contributes by providing an integrative model of technology acceptance for the elderly along with practical implications for policy makers.