Expert insights into mesolevel industrial ecosystems: pathways for economic transformation
Autor: | Evgenii Mityakov, Evgenii Mityakov, Natalia Kulikova |
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Jazyk: | angličtina |
Rok vydání: | 2024 |
Předmět: | |
Zdroj: | International Journal of Industrial Engineering and Management, Vol 15, Iss 3, Pp 213-224 (2024) |
Druh dokumentu: | article |
ISSN: | 2217-2661 2683-345X |
DOI: | 10.24867/IJIEM-2024-3-358 |
Popis: | This study introduces a novel framework for classifying mesolevel industrial ecosystems, focusing on their roles in reindustrialization and proactive import substitution. The research aims to address the gap in existing literature by offering a detailed categorization of these ecosystems, considering various dimensions like sectoral composition, geographic scope, and nature of linkages among participants. The study employs an expert survey methodology, targeting 180 specialists across different sectors to identify industrial ecosystems with the highest potential for fostering economic transformation. The hierarchical classification methodology used is meticulously detailed, and the rationale behind the selection of survey par- ticipants and questions is explained. The survey findings revealed that inter-sectoral and open ecosystems are particularly effective in promoting reindustrialization and proactive import substitution. The results also emphasized the significance of network-structured ecosystems and highlighted the preference for digital and strategic networks business models, alongside half-open innovation models. The study concludes that mesolevel industrial ecosystems play a pivotal role in economic transformation, particularly in the context of reindustrialization and import substitution. Openness, networking, and inter-sectoral collaboration are identified as key traits of ecosystems that significantly contribute to these goals. The paper also suggests potential areas for future research, such as the integration of digital technologies and environmental sustainability considerations in ecosystem classifications. |
Databáze: | Directory of Open Access Journals |
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