Journal article 1261 views 167 downloads
Driving innovation through big open linked data (BOLD): Exploring antecedents using interpretive structural modelling
,
Marijn Janssen,
Emma Slade,
Nripendra Rana ,
Vishanth Weerakkody,
Jeremy Millard,
Jan Hidders,
Dhoya Snijders
Information Systems Frontiers, Volume: 19, Issue: 2, Pages: 197 - 212
Swansea University Authors:
Yogesh Dwivedi , Emma Slade, Nripendra Rana
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DOI (Published version): 10.1007/s10796-016-9675-5
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...
| Published in: | Information Systems Frontiers |
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| ISSN: | 1387-3326 1572-9419 |
| Published: |
Springer Science and Business Media LLC
2017
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa29215 |
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| 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. |
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| Keywords: |
Big data; Open data; Linked data; Innovation; Interpretive structural modelling |
| College: |
Faculty of Humanities and Social Sciences |
| Issue: |
2 |
| Start Page: |
197 |
| End Page: |
212 |