The sustainable innovation engine

Purpose The purpose of this article is to present a model for sustainable innovation based on learning and knowledge. Design/methodology/approach Definitions of knowledge, innovation and learning are provided. Followed by a discussion on the link between knowledge and innovation, the concept of the nominal innovation probability space is introduced, built on the definitions of knowledge depth and knowledge diversity. Different learning styles are presented and how these can increase knowledge depth and knowledge diversity, improving a firm's position in the innovation probability space. A final description is provided of a model for the sustainable innovation engine. Findings The article finds that learning is essential to ensure sustainable innovation. Innovation probability is impacted by the organisation's knowledge depth and diversity. Learning styles are correlated to the firm's innovativeness and competitiveness. Experimentation as a learning style is essential for discontinuous innovation. Learning effectiveness is increased if supported by a knowledge management approach. Sustainable innovation requires a positive feedback loop between knowledge creation (learning) and innovation. Originality/value The article provides useful information on the introduction of the nominal innovation probability space based on a firm's knowledge depth and diversity; the concept of knowledge empathy; and the distinction between innovation and sustainable innovation and its importance for competitive and collaborative advantage.