Driving innovation through big open linked data (BOLD): Exploring antecedents using interpretive structural modelling
研究了通过大数据开放链接数据（BOLD）实现创新的前因因素间关系，使用解释结构模型组织19个因素，发现技术基础设施、数据质量和外部压力是基础，对管理者和研究者有参考价值。
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.