Understanding age differences in PDA acceptance and performance

By Katrin Arning, Martina Ziefle. Computers in Human Behavior, 2007

357 citations recorded by the source corpus.

Subfields: Gender Studies, Information Systems and Management, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/cc78b1b04f69aab8e5ebd250da1d9eb35f2ab986

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Citations in the corpus

Technology acceptance model: a literature review from 1986 to 2013 (2014, background): “participants involved were often comparably young and had a quite high educational level [7].”
Perceived Convenience in an Extended Technology Acceptance Model: Mobile Technology and English Learning for College Students. (2012, background): “Chen and Chung (2008) designed a personalised English vocabulary learning system with PDAs as a supporting tool, based on item response theory and learning memory cycle.”
Is it love or loneliness? Exploring the impact of everyday digital technology use on the wellbeing of older adults (2017, background): “(male, aged 83, married, owned smart phone for 1 months) As Arning and Ziefle (2007) argue technical confidence is closely linked to performance for the older adult and so if a device provides technical difficulties, the older adult as evidenced above, begins to question their own worth.”
Predicting technology acceptance and adoption by the elderly: a qualitative study (2008, background): “Arning and Ziefle, [2] found evidence to support the moderating effect of individual variables such as age, gender, subjective technical confidence and computer expertise on the relationship between attitude towards a technology and performance.”
Antecedents of the adoption of the new mobile payment systems: The moderating effect of age (2014, background): “The age of customers/users has an important effect on their behavior (Arning & Ziefle, 2007; Hubona & Kennik, 1996; Liébana-Cabanillas, Martínez-Fiestas, Rejón-Guardia, & Muñoz-Leiva, 2012; Okazaki & Mendez, 2012).”
Ecological Momentary Interventions: Incorporating Mobile Technology Into Psychosocial and Health Behavior Treatments (2009, background): “Implementing EMI for older or elderly adults presents unique challenges with respect to intervention development, motivation, and physical limitations (Arning & Ziefle, 2007; Sterns, 2005).”
Demographic differences in perceived benefits from gamification (2014, background): “Furthermore, it has been shown that technology acceptance (Arning & Ziefle, 2007; Czaja et al., 2006) and perceived usability (Ijsselsteijn et al., 2007), which are affected by age (Arning & Ziefle, 2007; Czaja et al., 2006), play a major part in technology adoption and digital gaming.”
PERSPECTIVE: Older Adults' Adoption of Technology: An Integrated Approach to Identifying Determinants and Barriers (2015, background): “Pieces of evidence for the causal relationship between perceived usefulness and adoption were found for various technologies, including portable devices, e-commerce, and e-mail (Arning and Ziefle, 2007; McCloskey, 2006; Melenhorst, Rogers, and Bouwhuis, 2006; Porter and Donthu, 2006).”
Psychological factors influencing technology adoption: A case study from the oil and gas industry (2021, background): “, age, income, educational level) was outwith the scope of the study, it is possible that these may have influenced technology adoption decisions, as has been found for age effects in consumer technology acceptance (Arning and Ziefle, 2007), leaving a potential route for future research.”