Engineering researchers’ data reuse behaviours: a structural equation modelling approach
| Pages | 1141-1161 |
| Published date | 06 November 2017 |
| Date | 06 November 2017 |
| DOI | https://doi.org/10.1108/EL-08-2016-0163 |
| Author | Yeon Kyoung Joo,Youngseek Kim |
| Subject Matter | Information & knowledge management,Information & communications technology,Internet |
Engineering researchers’data
reuse behaviours: a structural
equation modelling approach
Yeon Kyoung Joo
Department of Digital Media, Myongji University, Seoul, Republic of Korea, and
Youngseek Kim
School of Information Science, University of Kentucky, Lexington, Kentucky, USA
Abstract
Purpose –The purpose of this researchis to investigate the factors that influence engineering researchers’
data reuse behaviours.
Design/methodology/approach –The data reuse behaviour model of engineering researchers was
investigated by using a survey method.A national survey was distributed to engineering researchers in the
USA, and a total of 193 researchersresponded.
Findings –The results showedthat perceived usefulness, perceived concerns and norms of data reusehave
significant relationships with attitudes toward data reuse. Also, attitudes toward data reuse and the
availability of data repositories were found to have significant influences on engineering researchers’
intentionto reuse data.
Research limitations/implications –This research used a combined theoretical framework by
integrating the theory of planned behaviour (TPB) and the technology acceptance model (TAM). The
combination of the TPB and the TAM effectively explainedengineering researchers’data reuse behaviours
by addressingindividual motivations, norms and resourcefactors.
Practical implications –This research has practical implications for promoting more reliable and
beneficial data reuse in the engineeringcommunity, including encouraging positive motivationstoward data
reuse, buildingcommunity norms of data reuse and settingup more data repositories.
Originality value –As prior research on data reuse mainly used interviews, this research used a
quantitative approachbased on a combined theoretical framework and includeddiverse research constructs
which were not tested in the previous research models. As one of the initial studiesinvestigating data reuse
behaviours inthe engineering community, the current researchprovided a better understanding of data reuse
behavioursand suggested possible ways to facilitate engineeringresearchers’data reuse behaviours.
Keywords User studies, Data repositories, Institutional repositories, Data sharing,
Metadata standards, Data reuse, Engineering researchers,
Paper type Research paper
1. Introduction
Technological advances in modern research have opened up new opportunities for data
sharing and data reuse research. Researchers today have more opportunity to use publicly
available shared data or reuse other researchers’data (Borgman, 2012;Davis and Vickery,
2007;Tenopir et al., 2011). Such data sharing and reuse opportunities can be useful for
researchers to validate their findings, identify errors and enrich academic discussions by
The authors acknowledge the CoS Pivot (ProQuest) for allowing them to use their scholar database in
recruiting survey respondents for this research.
Researchers’
data reuse
behaviours
1141
Received16 August 2016
Revised26 January 2017
Accepted25 March 2017
TheElectronic Library
Vol.35 No. 6, 2017
pp. 1141-1161
© Emerald Publishing Limited
0264-0473
DOI 10.1108/EL-08-2016-0163
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0264-0473.htm
exploring new research questions that were not asked in the original research (Borgman,
2012;Tenopir et al., 2011). However,regardless of the importance and value of data sharing
and reuse, relatively little scholarly attentionhas been given to data sharing and data reuse
(Faniel et al., 2016;Yoon, 2016;Zimmerman, 2008). Furthermore, most existing studies on
data reuse deal with hard science(Tenopir et al., 2015), health science (Yoon, 2016) or social
science (Faniel et al., 2016), leaving the field of engineering largely unexplored. As a result,
there is not a clear understandingof what factors promote or impede engineers’data sharing
or data reuse behaviours. Given this, this research study attempts to examine engineering
researchers’datareuse behaviours, an active format of data sharing.
Although earlier studies mainly dealt with the design and development of technical
systems, engineering studies in more recent years include a wider range of topics, such
as management as well as traditional design and development (Buede and Miller, 2016).
In consideration of this trend in engineering, the present study defines engineering
research as an academic discipline focusing on diverse aspects of design, development,
implementation and use of mechanical and technical systems (Downey, 2005). This
definition of engineering research also covers a number of engineering disciplines,
including electrical engineering, mechanical engineering, environmental engineering,
computer engineering, civil engineering, industrial engineering, chemical engineering
and more.
This study investigates possible factorsthat can influence engineering researchers’data
reuse behaviours. Specifically,this research investigates what factors influence engineering
researchers’data reuse behaviours, and to what extent those factors influence those
behaviours. To this end, a review of the related literatureprovided a theoretical framework,
from which was developed a research model and hypotheses, and an evaluation of the
research model was conducted using data analysis of survey responses from 193
engineering researchersin the USA.
2. Literature review
Regardless of the importance of data reuse in the modern scholarly debate, only a limited
number of studies have explored data reuse behaviours within specific disciplinary
communities, including environmental engineering (Van House et al., 1998), social science
(Niu, 2009;Yoon, 2016), ecology (Zimmerman, 2008), archaeology (Faniel et al., 2013a) and
astronomy (Carlson and Anderson, 2007). Furthermore, such studies on data reuse often
used qualitative research methods(Niu, 2009;Yoon, 2016;Zimmerman, 2008) or descriptive
surveys to describe researchers’motivations for data reuse (Faniel et al., 2016;Tenopiret al.,
2015). As a result, the findings of the previous studies are often limited to episodic
information or a field-restricted understanding of data reuse, which makes it hard to
generalize the findings in a broader context, such as the field of engineering. Some of the
possible factors that previous studies found to influence data reuse behaviours in other
fields will be reviewed to test if these factors can influencedata reuse behaviours in the field
of engineering as well.
The perceived benefits of data reuse are revealedto be a main motivator of researchers’
data reuse behaviour (Faniel and Jacobsen, 2010;Niu, 2009;Yoon, 2015). A recent study
(Yoon, 2015), for example, revealed that social scientists reuse data because data reuse is
cost-effective. That is, researchers can explore additional research questions in a cost-
effective way when they reuse data, as data are already collected. Similarly, Niu (2009)
reported that the perceivedusefulness of data is a key factor in data reuse. According to Niu,
data reusers prioritize the informativevalue of data when they decide to use secondary data.
If researchers believe that existing data are related to their research and, therefore, are
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