Driving innovation through big open linked data (BOLD): Exploring antecedents using interpretive structural modelling

Yogesh K. Dwivedi (), Marijn Janssen (), Emma L. Slade (), Nripendra P. Rana (), Vishanth Weerakkody (), Jeremy Millard (), Jan Hidders () and Dhoya Snijders ()
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Yogesh K. Dwivedi: Swansea University
Marijn Janssen: Delft University of Technology
Emma L. Slade: Swansea University
Nripendra P. Rana: Swansea University
Vishanth Weerakkody: Brunel University
Jeremy Millard: Brunel University
Jan Hidders: Vrije Universiteit Brussel
Dhoya Snijders: Researcher Data & Society, The Dutch Study Center for Technology Trends (STT)

Information Systems Frontiers, 16 pages

Abstract: 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.

Keywords: Big data; Open data; Linked data; Innovation; Interpretive structural modelling (search for similar items in EconPapers)
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Citations: View citations in EconPapers (23)

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DOI: 10.1007/s10796-016-9675-5

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