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, Dhoya Snijders

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

60 Citations (Scopus)
318 Downloads (Pure)


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.

Original languageEnglish
Pages (from-to)197-212
Number of pages16
JournalInformation Systems Frontiers
Issue number2
Early online date13 Jul 2016
Publication statusPublished - Apr 2017

Structured keywords

  • Smart Networks for Sustainable Futures


  • Big data
  • Innovation
  • Interpretive structural modelling
  • Linked data
  • Open data

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