Classifying and comparing community innovation in Idea Management Systems

Abstract

The Idea Management Systems are a tool for collecting ideas for innovation from large communities. One of the problems of those systems is the difficulty to accurately depict the distinctive features of ideas in a rapid manner and use them for judgement of proposed innovations. Our research aims to solve this problem by introducing annotation of ideas with a domain independent taxonomy that describes various characteristics of ideas. The findings of our study show that such annotations can be successfully transformed into new metrics that allow the comparison of ideas with similar successfulness as the metrics already used in Idea Management Systems but greater detail. The presented results are based on experiments with over 50000 ideas gathered from case studies of four different organisations: Dell, Starbucks, Cisco and Canonical.