Use contexts of personal computing devices: determinants of use context changes
| Published date | 04 December 2017 |
| Pages | 2431-2451 |
| Date | 04 December 2017 |
| DOI | https://doi.org/10.1108/IMDS-11-2016-0471 |
| Author | Jimin Kim,Goya Choi,Younghoon Chang,Myeong-Cheol Park |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
Use contexts of personal
computing devices: determinants
of use context changes
Jimin Kim and Goya Choi
School of Business and Technology Management,
Korea Advanced Institute of Science and Technology, Daejeon,
The Republic of Korea
Younghoon Chang
Division of Business and Management,
BNU-HKBU United International College, Zhuhai, Gunagdong, China, and
Myeong-Cheol Park
School of Business and Technology Management,
Korea Advanced Institute of Science and Technology, Daejeon,
The Republic of Korea
Abstract
Purpose –The purpose of this paper is to investigate the use contexts of personal computing devices in
multiple steps and conducts an in-depth analysis for the use context of smartphones. The determinants of use
context changes of smartphones are investigated using the technology-to-performance chain model.
Design/methodology/approach –In steps 1 and 2, a diary study method and 2014-2015 Korea media panel
research data provided by the Korea Information Society Development Institute are used. Correspondence
analysis, χ
2
independence tests, and standardized residual analyses were conducted. In step 3, this study
develops and validates a framework for use context changes using a survey method and structural
equation modeling.
Findings –The results show that the use context of personal computing devices is represented differently
and is clearly defined depending on the device used. Furthermore, the use context of smartphones has
changed significantly because of the rapid growth of smartphone users and diverse usage patterns of
smartphones. The research model results show that users expand the scope and frequency of smartphone use
when they experience improved performance in everyday tasks and feel that smartphone content and
functions could support everyday tasks better.
Originality/value –This study presents novel early stage research and presents empirical evidence and
propositions in both exploratory and confirmatory ways. The main contribution of this study is to provide
guidelines and general implications for other empirical studies on the use contexts of devices or information
technology services.
Keywords Smartphones, Technology-to-performance chain, Computing devices, Diary study method,
Use context
Paper type Research paper
1. Introduction
In recent years, information technology (IT) rapidly and dramatically has become a
ubiquitous, pervasive part of everyday life (Bødker et al., 2014). Among various changes,
increasing diversity of pervasive computing devices and applications will have an
increasingly important impact on users (Chaari et al., 2007). Such devices and applications
need contextual information, including the type and state of network connection, users’
location, and hours of use. Users of computing devices and IT services may exploit different Industrial Management & Data
Systems
Vol. 117 No. 10, 2017
pp. 2431-2451
© Emerald PublishingLimited
0263-5577
DOI 10.1108/IMDS-11-2016-0471
Received 2 November 2016
Revised 7 April 2017
Accepted 10 May 2017
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
This research was supported by Global PHD Fellowship Program through the National Research
Foundation of Korea (NRF) funded by the Ministry of Education (2014019086).
2431
Determinants
of use context
changes
aspects of devices or services and access different information in different context situations
(Chaari et al., 2007). For these reasons, there is a great need for studies and investigations on
computing use context. Substantial research has already been undertaken on how to use
context data in the development of systems and applications (Chaari et al., 2007). However,
context investigations in terms ofusers are insufficient and difficult to implement. Oneof the
major purposes of this study is to provide guidelines and general implications related to use
context studiesfrom users’perspective. In this study, the use contextsof personal computing
devices, changes in use contexts, and determinants of use context changes are investigated.
First, the use contexts of personal computing devices are investigated using a diary
study method with a large number of samples. This analysis provides understanding for not
only computing use context but also multi-device usage behavior. A recent emerging
phenomenon is multi-device ownership (Ivaturi and Chua, 2015). Many people employ
multiple computing devices simultaneously and display clear multi-device usages behavior
(Ivaturi and Chua, 2015). However, the environment of multi-device use has not been
explored clearly because it is an emerging phenomenon at this point. In reality, users’
context affects the use of computing devices. For example, users who have desktops or
laptops in their rooms or offices (i.e. multi-device owners) sometimes search for news
articles, shop online, or use social networking sites (SNSs) on their smartphones. In spite of
the small screen size of smartphones, users often perform these activities, and contextual
interpretations can be carried out to investigate this behavior. Furthermore, much research
that is related to multi-devices is still ongoing, but most studies have been conducted via a
series of one-on-one comparisons. In this study, five computing devices (i.e. desktops,
laptops, netbooks, tablet PCs, and smartphones) are investigated to derive the relationships
between use context factors and computing device use.
In the second stage, changes in use contexts are investigated for more sophisticated
interpretations. The usage patterns of computing devices, especially tablet PCs and
smartphones, are changing rapidly because of the rapid growth in 4G long-term-evolution
(LTE) subscribers and the increased number of mobile applications. Through chronological
changes in the use context, this research provides a better understanding of usage patterns
and environments. Furthermore, an in-depth analysis is conducted into the use context of
smartphones because such context differs compared to other devices in any year.
Based on the results of previous stages, the determinants of use context changes of
smartphones are investigated. This study focuses on users’tasks in everyday life and the fit
of tasks to smartphones. The technology-to-performance chain model, which highlights the
influencing relationships in task-technology fit (TTF), utilization, and performance impact,
is adopted to explain the determinants of use context changes. The results of this study are
expected to provide general guidelines for other empirical studies on the use contexts of
devices or IT services.
2. Literature review
2.1 Use contexts in personal computing devices
Use contexts, which are also mentioned in several works of literature as “context in use”or
“context of use,”areincreasingly very important(Maguire, 2001; Lee et al., 2005). Thisconcept
is highlighted as a key issue in human-computer interaction (HCI) and information systems
(Schmidt et al., 1999; Lee et al., 2005). Use contexts refer to the personal and environmental
factors thatmay influence a user when he or she usesa technology or service (Kim etal., 2002;
Lee et al., 2005). This definition highlights a characteristic of use context, that is, the use
contexts are contextual information from the user’s perspective (L ee et al., 2005).
Several studies have suggested various use context factors. Kim et al. (2002, 2005)
suggested that the use contexts of mobile internet consist of movement as a spatial factor,
behavioral goal, co-location, interaction with other people, visual and auditory distraction,
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IMDS
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