Abstract
The traditional trust adoption problem data comes from the questionnaire survey. The accuracy and objectivity are not high, and the practical application value is limited. The output of the research is usually the subjective factors affecting trust, and the deep reasons for low user trust are not deeply explored. This study aims to propose a new set of consumer wearable service quality trust integration model based on big data, deeply integrate the two different research fields of big data mining and trust adoption, and quantitatively describe how wearable service quality characteristics, privacy environment, business characteristics, personality characteristics and other factors affect consumers’ trust and adoption of wearable services.
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Gu, Z., Ma, H., Liu, X. (2022). The Integrated Model Based on Big Data for Wearable Service Quality Trust. In: Salvendy, G., Wei, J. (eds) Design, Operation and Evaluation of Mobile Communications. HCII 2022. Lecture Notes in Computer Science, vol 13337. Springer, Cham. https://doi.org/10.1007/978-3-031-05014-5_17
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DOI: https://doi.org/10.1007/978-3-031-05014-5_17
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