Driving Innovation through Big Open Linked Data (BOLD): Exploring Antecedents using Interpretive Structural Modelling
View/ Open
Main article (766.9Kb)
Download
Publication date
2016Author
Dwivedi, Y.K.Janssen, M.
Slade, E.L.
Rana, Nripendra P.
Weerakkody, Vishanth J.P.
Millard, J.
Hidders, J.
Snijders, D.
Rights
© 2016 The Authors. This article is published open access at Springerlink.com. Available at Springer via http://dx.doi.org/10.1007/s10796-016-9675-5Peer-Reviewed
YesOpen Access status
openAccess
Metadata
Show full item recordAbstract
Innovation is vital to find new solutions to problems, increase quality, and improve profitability. Big open linked data (BOLD) is a fledgling and rapidly evolving field that creates new opportunities for innovation. However, none of the existing literature has yet considered the interrelationships between antecedents of innovation through BOLD. This research contributes to knowledge building through utilising interpretive structural modelling to organise nineteen factors linked to innovation using BOLD identified by experts in the field. The findings show that almost all the variables fall within the linkage cluster, thus having high driving and dependence powers, demonstrating the volatility of the process. It was also found that technical infrastructure, data quality, and external pressure form the fundamental foundations for innovation through BOLD. Deriving a framework to encourage and manage innovation through BOLD offers important theoretical and practical contributions.Version
Accepted manuscriptCitation
Dwivedi YK, Janssen M, Slade M, Rana NP, Weerakkody V, Millard J, Hidders J and Snijders D (2016) Driving Innovation through Big Open Linked Data (BOLD): Exploring Antecedents using Interpretive Structural Modelling. Information Systems Frontiers. 19(2): 197–212.Link to Version of Record
https://doi.org/10.1007/s10796-016-9675-5Type
Articleae974a485f413a2113503eed53cd6c53
https://doi.org/10.1007/s10796-016-9675-5