TY - JOUR
T1 - Factors driving business intelligence adoption: an extended technology-organization-environment framework
AU - Subramaniam, Radhakrishnan
AU - Palakeel, Prashobhan
AU - Arunmozhi, Manimuthu
AU - Sridharan, Manikandan
AU - Marimuthu, Uthayakumar
N1 - This is an open access article under the CC BY-SA license.
PY - 2024/6
Y1 - 2024/6
N2 - Business intelligence (BI) is a vital component for businesses of all scales, offering actionable insights crucial for timely decision-making. This technology has become integral across diverse enterprises. Recognizing the factors influencing BI adoption is imperative, and this article employs the organization, complexity, knowledge, technology, user perception and experience, economic, environmental, and social (OCKTUEES) framework to identify key aspects. Building upon the TOE framework, it pinpoints significant variables, emphasizing the importance of factors like user perception and experience, technology, social, economical, and environmental. Employing structural equation modelling on primary data yields actionable insights to address BI adoption challenges. Analysis reveals the user perception and experience, technology, social, economic, and environmental as the top factors. However, the organization appears vulnerable, necessitating a mitigation strategy for successful BI adoption. The study predicts insignificant variables requiring mitigation, such as high costs, inadequate resources, organizational size, security and privacy concerns, risk of open-source adoption, and perception of analytics impacting jobs. This research aids those navigating the BI implementation journey.
AB - Business intelligence (BI) is a vital component for businesses of all scales, offering actionable insights crucial for timely decision-making. This technology has become integral across diverse enterprises. Recognizing the factors influencing BI adoption is imperative, and this article employs the organization, complexity, knowledge, technology, user perception and experience, economic, environmental, and social (OCKTUEES) framework to identify key aspects. Building upon the TOE framework, it pinpoints significant variables, emphasizing the importance of factors like user perception and experience, technology, social, economical, and environmental. Employing structural equation modelling on primary data yields actionable insights to address BI adoption challenges. Analysis reveals the user perception and experience, technology, social, economic, and environmental as the top factors. However, the organization appears vulnerable, necessitating a mitigation strategy for successful BI adoption. The study predicts insignificant variables requiring mitigation, such as high costs, inadequate resources, organizational size, security and privacy concerns, risk of open-source adoption, and perception of analytics impacting jobs. This research aids those navigating the BI implementation journey.
KW - Adoption framework
KW - BI drivers
KW - Business intelligence
KW - Organizational adoption
KW - Technology adoption
KW - TOE
UR - http://www.scopus.com/inward/record.url?scp=85190988611&partnerID=8YFLogxK
UR - https://ijeecs.iaescore.com/index.php/IJEECS/article/view/36653
U2 - 10.11591/ijeecs.v34.i3.pp1893-1903
DO - 10.11591/ijeecs.v34.i3.pp1893-1903
M3 - Article
AN - SCOPUS:85190988611
SN - 2502-4752
VL - 34
SP - 1893
EP - 1903
JO - Indonesian Journal of Electrical Engineering and Computer Science
JF - Indonesian Journal of Electrical Engineering and Computer Science
IS - 3
ER -