Understanding the determinants of business intelligence system adoption stages. An empirical study of SMEs
| Published date | 05 February 2018 |
| DOI | https://doi.org/10.1108/IMDS-05-2017-0170 |
| Pages | 236-261 |
| Date | 05 February 2018 |
| Author | Borut Puklavec,Tiago Oliveira,Aleš Popovič |
| 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 |
Understanding the determinants
of business intelligence system
adoption stages
An empirical study of SMEs
Borut Puklavec
University of Ljubljana, Ljubljana, Slovenia
Tiago Oliveira
NOVA IMS, Universidade Nova de Lisboa, Lisbon, Portugal, and
AlešPopovič
University of Ljubljana, Ljubljana, Slovenia and
NOVA IMS, Universidade Nova de Lisboa, Lisbon, Portugal
Abstract
Purpose –The purpose of this paper is to provide a better understanding of the determinants of business
intelligence system (BIS) adoption stages. It develops and empirically tests a conceptual model for assessing
the determinants of BIS diffusion on the evaluation, adoption, and use stages in the context of small and
medium enterprises (SMEs).
Design/methodology/approach –Drawing on data from 181 SMEs the influence of technological,
organizational, and environmental factors on BIS adoption stages were analyzed using the PLS-SEM method.
Findings –The paper provides empirical insights about how technological, organizational, and
environmental factors affect individual BIS adoption stages.
Practical implications –The paper includes implications for managers and solution providers to
understand the influence of various determinants to more effectively conclude the adoption process.
Originality/value –This study represents important progress in the theoretical understanding of the role of
technological, organizational, and environmental factors across the different BIS adoption stages.
Keywords Small and medium enterprises (SMEs), Adoption stages, Business intelligence systems (BISs),
Diffusion of innovations (DOI) theory, Information technology/Information systems (IT/IS) adoption,
Technology-organization-environment (TOE) framework
Paper type Research paper
1. Introduction
Today’s firms generally operate in a complex and extensively competitive global
business environment. Such conditions force firms to set goals that include continuously
competingwithrivalsbyoperatingmoreefficiently and productively, and by reducing
operating costs (Chan and Chong, 2013). The widely recognized primary driver of
organizational productivity, i.e. technological innovation, will significant contribute to
firms’goals, but only when widely adopted (Zhu, Dong, Xu and Kraemer, 2006). Thus, it
is crucial for firms to understand the process and determinants of technology adoption
(Karahanna et al., 1999).
One innovation that can significantly contribute to the firm’s goals by improving
decision making is business intelligence systems (BISs) (Popovičet al., 2012). BISs were
developed as an IS innovation for offering data integration and analytical capabilities that
can provide valuable decision-making information for stakeholders at different
organizational levels (Turban et al., 2010; Yeoh and Popovič, 2016). We define BIS as
“quality information in well-designed data stores, coupled with software tools that provide
users timely access, effective analysis and intuitive presentation of the right information,
Industrial Management & Data
Systems
Vol. 118 No. 1, 2018
pp. 236-261
© Emerald PublishingLimited
0263-5577
DOI 10.1108/IMDS-05-2017-0170
Received 2 May 2017
Revised 23 July 2017
Accepted 8 September 2017
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
236
IMDS
118,1
enabling them to take the right actions or make the right decision”(Popovičet al., 2012).
In investigating business value of BIS, existing studies suggest that BISs enable enhancements
in firms’strategic planning, business processes, improvements of performance, and building of
competitive advantage (Popovičet al., 2014; Davenport et al., 2010; Negash and Gray, 2008)
whereas time savings and better information for supporting decision making are considered
the main direct benefits of BIS implementation (Watson et al., 2002).
Although there are similarities among different types of IS, prior BIS research reveals
key differences between BIS and other types of IS (Popovičet al., 2012). These divergences
are one of the main reasons for the need to examine the field of BIS adoption separately from
traditional IS adoption and to gain a better understanding of the determinants and their
effects on the BIS adoption process. To do so, firms must consider an integrative view of the
adoption process that builds on prior IS adoption studies and advances them to address
the specifics of BIS.
In the broader field of IS/IT adoption research,studies about BIS adoption are still scarce.
Moreover, extant research in the BIS milieu primarily focuses on large-sized firms (Popovič
et al., 2012; Wixomand Watson, 2010; Yeoh et al., 2008).Accordingly, in the present work,we
focus on BIS adoptionin small and medium enterprises (SMEs). These organizational entities
have been foundto importantly contributeto a country’s economic development,technological
advancement, and job creation opportunities (Ayyagari et al., 2011; Fink, 1998).
Further, our workaims to explain the process of BISadoption at the firm level, as opposed
to the more abundant research performed on IT acceptance at the individual level
i.e. acceptanceof innovations from individualswithin the firm). To the best of our knowledge,
this topical area of firm-level IT adoption is still under-researched. We contribute to the
existing body of knowledge by answering the call by Puklavec et al. (2014) to identify and
empirically testwhich determinants are importantfor BIS adoption in SMEs at the firm level.
The remainder of the paper is organized as following: the next section introduces the
innovation diffusion theory. Next, we present our research model and hypotheses, outline
the data sources, and explain our data analysis procedure. This is followed by our findings
on the key determinants of BIS adoption at the firm level in SMEs. In the “Discussion”
section, we explore the theoretical contributions and practical implications of our findings.
Finally, some inherent limitations and avenues for future research are given.
2. Theoretical development
2.1 BISs
Following a longer period of investments in setting up a technological foundation that
supports business processes and strengthens the efficiency of operational structure, most
firms have reached a point where the utilization of IT to support strategic decision making
became critical (Petrini and Pozzebon, 2009; Popovičet al., 2014). Perceived as a r esponse to
the growing needs foraccess to relevant information BISs havethe potential to maximize use
of information, thereby creating or enhancing competitive advantage (Popovičet al., 2014).
From the perspective of firm knowledge creation and through utilitarian view on IS, BISs
differentiate themselves from other IS through the authority to commence problem
articulationand discussion; and on data selection,by addressing various information needs of
decision makers at different organizational levels (Ferrari, 2011; Shollo and Galliers, 2013).
Such BIS capabilities play a strategicrole for the firms, where the decision-making processis
considered a critical success factor as it is by strategic management (Rossignoli et al., 2010).
2.2 Technology adoption
In the last decades, different prominent theories, frameworks, and models have shaped the
field of technology adoption, e.g. the technology acceptance model (Davis, 1989;
Davis et al., 1989), theory of planned behavior (Ajzen, 1991), unified theory of acceptance
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Determinants
of BIS
adoption
stages
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