Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/13355
Title: Driving innovation through big open linked data (BOLD): Exploring antecedents using interpretive structural modelling
Authors: Dwivedi, YK
Janssen, M
Slade, EL
Rana, NP
Weerakkody, V
Millard, J
Hidders, J
Snijders, D
Keywords: Big Data;Open Data;Linked Data;Innovation;Interpretive Structural Modelling
Issue Date: 2016
Publisher: Springer
Citation: Information Systems Frontiers, pp. 1 - 16, (2016)
Abstract: 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.
URI: http://bura.brunel.ac.uk/handle/2438/13355
DOI: http://dx.doi.org/10.1007/s10796-016-9675-5
ISSN: 1387-3326
Appears in Collections:Brunel Business School Research Papers

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