Towards Employee-Driven Idea Mining: Concept, Benefits, and Challenges

organizations strive for innovation in order to be economically competitive, meet customer needs, or improve their efficiency. Numerous approaches have been developed in recent years for this purpose. One is idea mining, which is technically based on text mining but aims to capture (new) innovation ideas from predominantly user-generated content on the Internet. In addition to weblogs and blogs, major social networks such as Twitter, Facebook, and Instagram are also used as data sources. These sites contain an immense amount of data in the form of user comments in unstructured text form. This data can relate to organizations or their offerings, such as products and services, and can be collected, analyzed, and evaluated using text mining techniques. In this paper, we present a concept for collecting large amounts of unstructured text data that is processed (semi-) automatically and from which valuable innovation ideas can be derived. The concept is integrated into an employee-driven digital innovation process. Furthermore, we shed light on the benefits but also the challenges of (employee-driven) idea mining and thus provide further starting points for research and aspects to be considered for practice.