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Multi-Device Use: Understanding the Motivations behind Switching between Multiple Devices during a Task.

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Title: Multi-Device Use: Understanding the Motivations behind Switching between Multiple Devices during a Task.
Authors: Chen, Chi-Wen1 (AUTHOR) chchen@csudh.edu, Koufaris, Marios2 (AUTHOR)
Source: International Journal of Human-Computer Interaction. Jul2020, Vol. 36 Issue 12, p1178-1193. 16p. 9 Charts.
Subjects: Tasks, Questionnaire design
Abstract: Multi-device use has become a popular pattern of device use in recent years. However, empirical studies pertaining to motivations behind intention to use multiple devices have been limited. The objective of this study focuses on answering an essential question: given that heterogeneous devices are available to users, why do users use multiple devices rather than a single device to complete a task? Both Task-Technology Fit Theory and mental workload paradigm are considered to develop eight hypotheses and build the research framework. A trip-planning scenario was designed and used in the questionnaire to understand the factors that motivate users to use multiple devices. A total of 217 subjects completed the questionnaire. The results show that perceived task fit with multi-device use forms users' attitudes toward and expected satisfaction with multi-device use. Furthermore, users' attitudes toward multi-device use trigger their intentions to use multiple devices. Additionally, perceived complexity of multi-device use hinders users from perceiving good task fit with multi-device use. Implications for theory, practice, and future research directions are discussed. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Multi-Device Use: Understanding the Motivations behind Switching between Multiple Devices during a Task.
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  Data: <searchLink fieldCode="AR" term="%22Chen%2C+Chi-Wen%22">Chen, Chi-Wen</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> chchen@csudh.edu</i><br /><searchLink fieldCode="AR" term="%22Koufaris%2C+Marios%22">Koufaris, Marios</searchLink><relatesTo>2</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Human-Computer+Interaction%22">International Journal of Human-Computer Interaction</searchLink>. Jul2020, Vol. 36 Issue 12, p1178-1193. 16p. 9 Charts.
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  Data: Multi-device use has become a popular pattern of device use in recent years. However, empirical studies pertaining to motivations behind intention to use multiple devices have been limited. The objective of this study focuses on answering an essential question: given that heterogeneous devices are available to users, why do users use multiple devices rather than a single device to complete a task? Both Task-Technology Fit Theory and mental workload paradigm are considered to develop eight hypotheses and build the research framework. A trip-planning scenario was designed and used in the questionnaire to understand the factors that motivate users to use multiple devices. A total of 217 subjects completed the questionnaire. The results show that perceived task fit with multi-device use forms users' attitudes toward and expected satisfaction with multi-device use. Furthermore, users' attitudes toward multi-device use trigger their intentions to use multiple devices. Additionally, perceived complexity of multi-device use hinders users from perceiving good task fit with multi-device use. Implications for theory, practice, and future research directions are discussed. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/10447318.2020.1726106
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              Text: Jul2020
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