Cognitive Computing and Managing Complexity in Open Innovation Model

Conference paper

DOI: 10.1007/978-3-319-29058-4_19

Part of the Springer Proceedings in Business and Economics book series (SPBE)
Cite this paper as:
Freund R.J. (2017) Cognitive Computing and Managing Complexity in Open Innovation Model. In: Bellemare J., Carrier S., Nielsen K., Piller F. (eds) Managing Complexity. Springer Proceedings in Business and Economics. Springer, Cham

Abstract

Risk and uncertainty is an under-investigated feature of innovation and needs to be further studied because managing uncertainty and complexity can be regarded as a core practice of successful innovation management. It is argued that multiple competencies on several levels (individual, group, organization, and network) are able to negotiate complexity and uncertainty in open innovation models. On the other hand, computers and robots have made remarkable advances into the workforce in recent years. This chapter discusses opportunities and limitations of cognitive computing in open innovation business models and is organized as follows: The first section discusses different aspects and concepts of innovation. The second section highlights the key elements of closed innovation and open innovation. The third section analyses complexity and uncertainty in innovation process and management. Finally, the last section discusses opportunities and limitations of cognitive computing in open innovation models. The conclusion summarizes the basic thesis of the whole work.

Keywords

Innovation Open innovation Complexity Uncertainty Risk Innovation management Competencies Cognitive computing 

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Finkenweg 6BurgwaldGermany

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