TY - JOUR
T1 - Exploring Determinants of Semantic Web Technology Adoption from IT Professionals' Perspective
T2 - Industry Competition, Organization Innovativeness, and Data Management Capability
AU - Kim, Dan J.
AU - Hebeler, John
AU - Yoon, Victoria
AU - Davis, Fred
N1 - Funding Information:
The research of first author has been supported by the National Research Foundation of Korea Grant funded by the Korean Government ( NRF-2017S1A3A2066149 ).
Funding Information:
Dan J. Kim is Professor of Information Technology and Decision Sciences at University of North Texas. His research interests are in multidisciplinary areas such as information security (InfoSec) and privacy, information assurance, and trust in electronic commerce. Recently he has focused on InfoSec Self-Efficacy, Web Assurance Seal Services, and Trust in e-collaborations. His research work has been published or in forthcoming more than 150 papers in refereed journals, peer-reviewed book chapters, and conference proceedings including ISR, JMIS, JAIS, EJIS, CACM, CAIS, DSS, IJHIC, IJEUC, IEEE Transactions on Professional Communication, Electronic Market, IEEE IT Professional, Journal of Global Information Management, and International Journal of Mobile Communications, ICIS, HICSS, AMCIS, INFORMS, ICEC, ICA, and so on. He has been awarded the National Science Foundation CyberCorps: SFS grant for multi-years, 2012 Emerald management Review Citations of Excellence Awards, 2010 Best Published Paper Award in ISR, an Emerald Literati Network 2009 - Outstanding Paper Award, the ICIS 2003 Best Paper-First Runner-up Award, and the AMCIS 2005 Best Research Paper Award at AMCIS 2005.
Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2018/9
Y1 - 2018/9
N2 - The scale and complexity of big data quickly exceed the reach of direct human comprehension and increasingly require machine assistance to semantically analyze, organize, and interpret vast and diverse sources of big data in order to unlock its strategic value. Due to its volume, velocity, variety, and veracity, big data integration challenges overwhelm traditional integration approaches leaving many integration possibilities out of reach. Unlocking the value of big data requires innovative technology. Organizations must have the innovativeness and data capability to adopt the technology and harness its potential value. The Semantic Web (SW) technology has demonstrated its potential for integrating big data and has become important technology for tackling big data. Despite its importance to manage big data, little research has examined the determinants affecting SW adoption. Drawing upon the technology–organization–environment framework as a theory base, this study develops a research model explaining the factors affecting the adoption of SW technology from IT professionals' perspective, specifically in the context of corporate computing enterprises. We validate the proposed model using a set of empirical data collected from IT professionals including IT managers, system architects, software developers, and web developers. The findings suggest that perceived usefulness, perceived ease of use, organization's innovativeness, organization's data capability, and applicability to data management are important drivers of SW adoption. This study provides new insights on theories of organizational IT adoption from IT professionals' perspectives tailored to the context of SW technology.
AB - The scale and complexity of big data quickly exceed the reach of direct human comprehension and increasingly require machine assistance to semantically analyze, organize, and interpret vast and diverse sources of big data in order to unlock its strategic value. Due to its volume, velocity, variety, and veracity, big data integration challenges overwhelm traditional integration approaches leaving many integration possibilities out of reach. Unlocking the value of big data requires innovative technology. Organizations must have the innovativeness and data capability to adopt the technology and harness its potential value. The Semantic Web (SW) technology has demonstrated its potential for integrating big data and has become important technology for tackling big data. Despite its importance to manage big data, little research has examined the determinants affecting SW adoption. Drawing upon the technology–organization–environment framework as a theory base, this study develops a research model explaining the factors affecting the adoption of SW technology from IT professionals' perspective, specifically in the context of corporate computing enterprises. We validate the proposed model using a set of empirical data collected from IT professionals including IT managers, system architects, software developers, and web developers. The findings suggest that perceived usefulness, perceived ease of use, organization's innovativeness, organization's data capability, and applicability to data management are important drivers of SW adoption. This study provides new insights on theories of organizational IT adoption from IT professionals' perspectives tailored to the context of SW technology.
KW - IT professionals' perspective technology adoption
KW - Innovation diffusion theory
KW - Semantic web
KW - Technology-organization-environment framework
UR - http://www.scopus.com/inward/record.url?scp=85049303358&partnerID=8YFLogxK
U2 - 10.1016/j.chb.2018.04.014
DO - 10.1016/j.chb.2018.04.014
M3 - Article
AN - SCOPUS:85049303358
VL - 86
SP - 18
EP - 33
JO - Computers in Human Behavior
JF - Computers in Human Behavior
SN - 0747-5632
ER -