Vol.12, No.2, May 2023.                                                                                                                                                                               ISSN: 2217-8309

                                                                                                                                                                                                                    eISSN: 2217-8333

 

TEM Journal

 

TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS

Association for Information Communication Technology Education and Science


Big Data as a Stakeholder of the Firm’s Innovation Process

 

Zornitsa Yordanova

 

© 2023 Zornitsa Yordanova, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)

 

Citation Information: TEM Journal. Volume 12, Issue 2, Pages 1038-1047, ISSN 2217-8309, DOI: 10.18421/TEM122-50, May 2023.

 

Received: 05 November 2022.

Revised:   12 February 2023.
Accepted:  14 April 2023.
Published: 29 May 2023.

 

Abstract:

 

Big data has already been used successfully by firms for innovation development and has been involved in many business processes to render them more efficient and productive. The innovation process is one of the most critical processes in firms related to all others at the firm level and beyond mostly due to its impact on a firm’s overall performance and potential. The innovation process is highly data-dependent, so it is exceedingly impacted by the development of emerging technologies and big data in particular. In this study, we are exploring how big data is affecting the firm’s innovation process and how it is incorporated into each of its process steps to facilitate its demands. To examine the overall picture of the multidisciplinary topic, we conduct both a bibliometric analysis and a systematic analysis of the scientific literature in order to define the scope of the current application of big data within the innovation process. Furthermore, we identify under-researched topics to indicate future research directions.

 

Keywords – innovation process, big data, innovation management, technology management, bibliometric analysis.

 

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