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- Gao, Shang, 1982-, et al.
(författare)
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The Adoption of Smartphones Among Older Adults in China
- 2015
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Ingår i: Information and Knowledge Management in Complex Systems. - Cham : Springer Berlin/Heidelberg. - 9783319162744 - 9783319162737 ; , s. 112-122
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Bokkapitel (refereegranskat)abstract
- This research aims to investigate the adoption of smartphones with older adults in China. Based on the literature review from previous research, a research model with eight research hypotheses is developed by extending UTAUT with a consideration of observability and compatibility from IDT, and perceived enjoyment and price value. This research model is empirically examined using survey data from a sample of 121 older adults in China. Five research hypotheses were positively significant supported, while three research hypotheses were rejected in this study. The results suggest that social influence, observability, compatibility, performance expectancy and perceived enjoyment, are important determinants for the use and adoption of smartphones with older adults in China.
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| 2. |
- Krogstie, John, et al.
(författare)
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A Semiotic Approach to Investigate Quality Issues of Open Big Data Ecosystems
- 2015
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Ingår i: Information and Knowledge Management in Complex Systems. - Cham : Springer Berlin/Heidelberg. - 9783319162744 ; , s. 41-50
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Bokkapitel (refereegranskat)abstract
- The quality of data models has been investigated since the mid-nineties. In another strand of research, data and information quality has been investigated even longer. Data can also be looked upon as a type of model (on the instance level), as illustrated e.g. in the product models in CAD-systems. We have earlier presented a specialization of the general SEQUAL-framework to be able to evaluate the combined quality of data models and data. In this paper we look in particular on the identified issues of ‘Big Data’. We find on the one hand that the characteristics of quality of big data can be looked upon in the light of the quality levels of the SEQUAL-framework as it is specialized for data quality, and that there are aspects in this framework that are not covered by the existing work on big data. On the other hand, the exercise has resulted in a useful deepening of the generic framework for data quality, and has in this way improved the practical applicability of the SEQUAL-framework when applied to discussing and assessing quality of big data.
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