We investigate the outcomes of digital and technology-driven change on products, processes, and organizations. 

First, we investigate how emerging digital technologies, such as automation and artificial intelligence, shape innovation-related decision-making in firms. We focus on how the mere fact that a context has been affected by technological change (e.g., automated assembly line using robots and AWe versus human assembly line) affects individuals' creativity. We also try to find out how and why non-human sources of ideas (AI, robots) systematically bias idea evaluation. Lastly, We use data science approaches (e.g., neural networks) to model idea evaluation in idea management systems, ultimately supporting decision-makers in evaluating new ideas' value.

Second, we investigate how information technology enables innovation in continuous improvement and collaborative idea management systems in organizations. Idea management systems are administrative procedures for collecting, judging, and compensating ideas for improvements conceived by the organization's employees. In this sub-stream, we investigate the factors that affect the likelihood, quantity, and quality of ideas being submitted to idea management systems. For example, we investigate how disruptions and rejections shape these outcomes. We also examine other important variables for such systems' performance, such as evaluation time and cost.

Third, we research technology-driven innovation where an existing solution (i.e., a technology) is recombined with new problems and needs. This type of innovation is called exaptation and is based on artifacts and technologies in use being repurposed for different use. Breakthrough innovations that represent technology-driven exaptations are Viagra, the CD-ROM, or shockwave lithotripsy. Exaptation accounts for a large share of innovative activity (e.g., a third of all inventions in the pharmaceutical sector). Despite its importance for economic growth, exaptive innovation has received much less attention than other types of innovation. This sub-stream aims to further understand a firm's exaptive innovation behavior.

Some example research questions we are addressing in the stream on digital and technology-driven innovations are:

• Do cross-functional teams create more and better ideas in collaborative idea management systems?
• Does automation affect the number of ideas created by shopfloor workers?
• Do consumers evaluate ideas differently if an AI has created them?