Eigelshoven, Felix | Ullrich, André | Thim, Christof

Studying the effects of crowdsourcing on Industry 4.0 using a text mining approach

Abstract

The ongoing digitalization and industrial revolution come along with changing work processes and new types of work organization. Subcontracted labor has often been used to bridge capacity gaps. Due to new competence requirements arising from technical and process innovations in the industrial setting crowdsourcing might provide the means to acquire and integrate these competences in a flexible, temporary way and open up new, decentralized innovation sources. Furthermore, not all required competences can be hold inside due to efficiency reasons. Thus, future-oriented companies must decide whether to systematically develop the competences of their employees by themselves or to outsource-crowdsource-value-adding processes and tasks. However, it is not clear how and to which extend crowdsourcing-based solutions can be systematically integrated into innovation and production processes. Furthermore, the diverse relationships between crowdsourcing and Industry 4.0 are not sufficiently understood for realizing entrepreneurial and societal benefits. Thus, the underlying research question is: What is the relationship between crowdsourcing and Industry 4.0 and how can synergies be levered? To Answer this question, the applied methodology combines a systematical literature review with a text mining approach for the analysis of large text bodies. The results of the study will provide a first benchmark on the frequency and type of use of crowdsourcing technologies. Moreover, this review provides a first guideline how and where to use crowdsourcing technologies in companies that are operating in the industry 4.0 sector.