Organizational Psychological Resources, Green Innovation, and Sustainable Business Resilience: An Exploratory Study of Formalized Firms in Northern Peru
Edwin Martín García-Ramírez, Emma Veronica Ramos-Farroñan, Alexander Fernando Haro-Sarango, Oscar Manuel Vela-Miranda, Pedro Manuel Silva-León, Alberto Alejandro Martínez-QuezadaOrganizational resilience has become a strategic priority for firms facing environmental, economic, and institutional disruptions, particularly in resource-constrained regional business contexts. This exploratory study examined the association between organizational psychological resources and sustainable business resilience through the mediating role of green innovation in formalized firms in northern Peru. A quantitative, cross-sectional design was applied to data from 130 firms, each represented by a manager or coordinator. The model included three latent constructs—organizational psychological resources, green innovation, and sustainable business resilience—measured through 27 Likert-scale indicators and analyzed using covariance-based structural equation modeling with the WLSMV estimator in lavaan. The results showed high measurement consistency, with standardized loadings between 0.898 and 0.988, Cronbach’s alpha values from 0.985 to 0.990, composite reliability above 0.992, and AVE above 0.929. The structural model showed satisfactory fit and indicated positive associations between organizational psychological resources and green innovation, and between green innovation and sustainable business resilience. The indirect effect was significant, suggesting partial mediation. However, the exceptionally high explained variance for sustainable business resilience (R2 = 94.5%) suggests that common method bias, multicollinearity, or construct overlap may have inflated the associations, and thus the specific coefficients should be interpreted with caution. The findings should be understood as context-specific, hypothesis-generating preliminary evidence that requires replication in larger, independent, and multi-source samples.