2026-05-27T12:55:19Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/450972026-02-09T12:33:43Zcom_10630_2254col_10630_37953
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
De-las-Heras-Rosas, Carlos Javier
author
Herrera-Ballesteros, Juan
author
Mota Veiga, Pedro
author
Silva Rodrigues, Rui
2026-02-02T09:34:22Z
2025-12-23
de las Heras-Rosas, C., J. Herrera-Ballesteros, P. M. Veiga, and R. S. Rodrigues. 2026. “ Company Location, Business Environment and Digital Maturity as Drivers of Environmental Innovation in Business.” Business Strategy and the Environment 1–22. https://doi.org/10.1002/bse.70539
0964-4733
1099-0836
https://hdl.handle.net/10630/45097
10.1002/bse.70539
Environmental protection has emerged as a global priority in the contemporary context. As pivotal actors in the transition towards sustainable development, companies play a crucial role through the adoption of environmental innovations. This study investigates how organisational characteristics—specifically geographical location, business environment and digital maturity—influence the adoption of environmental innovations, employing machine learning models to develop a robust predictive framework. Although previous research has highlighted the relevance of these factors, their specific dynamics and interactions remain insufficiently explored. Drawing on data from Flash Eurobarometer 486, which comprises information from 16,365 firms across 27 EU Member States and 12 additional countries, this analysis examines how geographical context and internal capabilities shape environmental innovation performance, with particular attention given to the moderating role of firm size. The study leverages machine learning algorithms, including logistic regression, random forests and gradient boosting machines, to capture complex relationships and address challenges such as overfitting. The results demonstrate that location, business environment and digital maturity significantly influence environmental innovation. Moreover, company size moderates these relationships, either amplifying or attenuating their effects, thus providing a nuanced understanding of how firms can optimise their characteristics to advance sustainable practices. By integrating machine learning techniques into the analysis, this research contributes to the literature on environmental innovation by offering a systematic approach to identifying key drivers. These findings hold critical implications for policymakers and business leaders seeking to enhance sustainability through innovation.
eng
Attribution 4.0 International
Medio ambiente - Protección
Auditoría ambiental
Company Location, Business Environment and Digital Maturity as Drivers of Environmental Innovation in Business
journal article
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