The evolution of business ecosystems: A text mining-based analysis of innovation and competition (1993–2023)
DOI:
https://doi.org/10.31489/2025ec1/52-62Keywords:
ecosystem, business, digitalization, diversification, text mining, python, innovationAbstract
Discussions about ecosystems are mostly relevant in current time, due to the fact that ecosystem approach is becoming more recognized and more applied in the modern world. In this article the attempt was made to identify the basic direc-tions of ecosystem development in the context of business, innovation and competition. The main trends of this phe-nomena by time intervals were determined. As an analytical tool the authors’ application called “Friendly text mining” which is based on the “NLTK” package of programming language python was put into service. From the Scopus data-base journals 600 articles for the period from 1993 to 2023 were selected and processed. These findings have shown a significant increase in ecosystem related research, especially since 2014, digitalization, platform-based professional models and variations have been associated with the growing renowned strategy. Analysis also highlights the reduction of traditional cluster-based research, indicating that ecosystems are gradually changing clusters as an impressive struc-ture to understand inter-firm cooperation and competition. In addition, this study recognizes statistically significant rela-tionships between key words such as “ecosystem”, “platform”, “digitalization”, “digitalization”, and “innovation”, which underscores each other’s interconnected nature in contemporary business research. This study contributes to lit-erature by showing the effectiveness of text mining methods, providing a scalable and systematic approach to the evolu-tion of the educational discourse. Future research should find the structural mobility of ecosystems, their impact on in-dustry change, and the role of emerging technologies in their evolution
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