A configuration approach to explain corporate environmental responsibility behavior of the emerging economies firms at industry 4.0

Jorge Heredia, John R. McIntyre, Cathy Rubiños, Ernesto Santibañez, Alejandro Flores

Producción científica: Contribución a una revistaArtículo de revista revisión exhaustiva

7 Citas (Scopus)

Resumen

The fundamental integration of corporate environmental responsibility (CER) driven by the increasing irreversibility of climate change has been evolving but still is insufficient in emerging economies. Hence, our objectives are to know the combinational effect of the factors to determine a firm's high allocation of monetary resources to environmental issues and understand the role of the digital transformation process in the era of Industry 4.0 and its interaction with the internal-external variables proposed. In this sense, we conducted a comparative analysis of two representative emerging economies in Latin America, considering the external context of the companies (countries' competitiveness levels). We perform a fuzzy-set qualitative comparative analysis (fsQCA) to focus on multiple conjectural causations that lead to the same outcome. The results show that small firms in a less competitive country carry out high environmental expenditures based on value creation rather than the regulatory environment. On the other hand, large firms in a highly competitive country carry out high environmental commitments to enhance legitimacy and improve external image. Finally, we found that the relationship between digitalization adoption and corporate environmental responsibility depends on a country's informality level. Thus, countries with high informality cannot successfully impact digitization and generate sustainable solutions.

Idioma originalInglés
Número de artículo136383
PublicaciónJournal of Cleaner Production
Volumen395
Fecha en línea anticipada13 feb. 2023
DOI
EstadoPublicada - 1 abr. 2023

Nota bibliográfica

Funding Information:
Special acknowledgment to the Center of research at Universidad del Pacífico for supporting this research and the assistant researcher Jorge Peña Contreras for support on data processing.

Publisher Copyright:
© 2023 Elsevier Ltd

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