TY - GEN
T1 - Determinants of big data adoption and success
AU - Al-Qirim, Nabeel
AU - Tarhini, Ali
AU - Rouibah, Kamel
N1 - Publisher Copyright:
© 2017 Associat ion for Comput ing Machinery.
PY - 2017/8/10
Y1 - 2017/8/10
N2 - This research investigates the large hype surrounding big data (BD) and Analytics (BDA) in both academia and the business world. Initial insights pointed to large and complex amalgamations of different fields, techniques and tools. Above all, BD as a research field and as a business tool found to be under developing and is fraught with many challenges. The intention here in this research is to develop an adoption model of BD that could detect key success predictors. The research finds a great interest and optimism about BD value that fueled this current buzz behind this novel phenomenon. Like any disruptive innovation, its assimilation in organizations oppressed with many challenges at various contextual levels. BD would provide different advantages to organizations that would seriously consider all its perspectives alongside its lifecycle in the pre-adoption or adoption or implementation phases. The research attempts to delineate the different facets of BD as a technology and as a management tool highlighting different contributions, implications and recommendations. This is of great interest to researchers, professional and policy makers.
AB - This research investigates the large hype surrounding big data (BD) and Analytics (BDA) in both academia and the business world. Initial insights pointed to large and complex amalgamations of different fields, techniques and tools. Above all, BD as a research field and as a business tool found to be under developing and is fraught with many challenges. The intention here in this research is to develop an adoption model of BD that could detect key success predictors. The research finds a great interest and optimism about BD value that fueled this current buzz behind this novel phenomenon. Like any disruptive innovation, its assimilation in organizations oppressed with many challenges at various contextual levels. BD would provide different advantages to organizations that would seriously consider all its perspectives alongside its lifecycle in the pre-adoption or adoption or implementation phases. The research attempts to delineate the different facets of BD as a technology and as a management tool highlighting different contributions, implications and recommendations. This is of great interest to researchers, professional and policy makers.
KW - Big data analytics
KW - Big data challenges.
KW - Big data strategy
KW - Big data success factors
UR - http://www.scopus.com/inward/record.url?scp=85039062862&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85039062862&partnerID=8YFLogxK
U2 - 10.1145/3127942.3127961
DO - 10.1145/3127942.3127961
M3 - Conference contribution
AN - SCOPUS:85039062862
T3 - ACM International Conference Proceeding Series
SP - 88
EP - 92
BT - Proceedings of 2017 International Conference on Algorithms, Computing and Systems, ICACS 2017
PB - Association for Computing Machinery
T2 - 2017 International Conference on Algorithms, Computing and Systems, ICACS 2017
Y2 - 10 August 2017 through 13 August 2017
ER -