A qualitative study of the applicability of technology acceptance models to senior mobile phone users

Van Biljon, J. and Renaud, K. (2008) A qualitative study of the applicability of technology acceptance models to senior mobile phone users. In: International Workshop on Modeling Mobile Applications and Services, Barcelona, Spain, 20-23 Oct 2008, pp. 228-237. (doi: 10.1007/978-3-540-87991-6_28)

Abstract

This paper investigates the factors that influence mobile phone adoption by the older user. Technology adoption is a process, with the adopter progressing from a state of ignorance of the technology to embracing it and considering it a necessity. Full progression can only occur if the adopter fully accepts the technology. If not, he or she is unlikely to progress towards wholehearted adoption and remain a reluctant user or discard the technology altogether. Many theoretical models explain the dynamics of technology acceptance by proposing particular predictive factors and are based on quantitative studies built on the responses of students or economically active adults. This begs the question: Do existing technology acceptance models incorporate the factors that lead to mobile phone adoption and use by older adults? We consulted findings from studies of senior mobile phone users and extracted a number of issues concerning needs, uses and limitations, which we verified by means of structured interviews with senior mobile phone users. We compare these qualitatively derived issues with the factors from existing quantitative models. This led to the identification of a two-dimensional adoption matrix where verified acceptance factors, derived from the experiences and opinions of our participants, are mapped against a recognised adoption process, highlighting the fact that current models only partly predict adoption and acceptance by the senior mobile phone user.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Renaud, Professor Karen
• Authors: Van Biljon, J., and Renaud, K.
• College/School: College of Science and Engineering > School of Computing Science
• ISSN: 0302-9743