This paper explores the question of how provider companies create and capture value from Big Data, drawing on a multiple-case study analysis of provider companies that offer solutions and services based on Big Data. The results illustrate a theoretical framework on value creation and capture by relying on Big Data and identifying two main innovation service strategies based on Big Data used by provider companies. In addition, this paper provides valuable insights as to how the network of involved stakeholders influences the design and implementation of the innovation service strategy by the provider companies.

Data-driven design methods are promising when it happens to broaden external stimuli, help during the design ideation phases. Prof. Jianxi Luo and his colleagues developed a knowledge-based expert system that provides design stimuli across the semantic, document and field levels at the same time and helps with concept generation. During the session, we will explore how this tool can be applied for research and practical work.

This paper proposes a unifying Open Innovation in Science (OIS) Research Framework, which captures the antecedents, contingencies, and consequences of open and collaborative practices along the entire process of generating and disseminating scientific insights and translating them into innovation. To conceptualise the framework, we employed a collaborative approach involving 47 scholars from multiple disciplines, highlighting both tensions and commonalities between existing approaches. The OIS Research Framework thus serves as a basis for future research, informs policy discussions, and provides guidance to scientists and practitioners.

The efforts of the research institute of a major Canadian energy company to provide training for innovation and creativity to initiate a radical innovation capability is studied. We rely on a longitudinal study over the span of 18 months, where we observed 128 hours of training and conducted 70 semi‐structured interviews with a sample of 40 researchers.

Case study is a widely adopted method in innovation management. However, there is a great diversity in the transparency and rigor in how case studies are conducted, downplaying their potential contribution to the cumulative scholarly knowledge. How can we uplift case studies as the method of choice for rigorous and impactful scholarship?