Paper Number

1363

Abstract

Phenomena like the digital transformation lead to constantly changing economic requirements for companies and their underlying business models. The concept of an innovation capability maturity model is a possible approach to adapt to these changes by presenting solutions for the improvement of innovation potential, which in turn leads to higher turnover. Since existing one-size-fits-all conceptual development approaches of maturity models cannot depict the characteristics for a specific class (size and sector) of companies, we apply a data-driven development approach for the class of small industrial companies. Divided into a knowledge and organizational dimension, our findings reveal a total of 21 factor combinations, representing different levels of innovation capability maturity. By applying a set-theoretic approach for the identification of factor configurations leading to low, medium, and high innovation capability maturity, we furthermore propose the conceptual approach for an empirically driven set-theoretic maturity model development, yielding a design science method artifact.

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