Modeling Digital and Sustainable Innovation Pathways in Tijuana’s Business Ecosystem (#752)

Authors

Rosales-Soto, Alejandra

Mendoza-Ibarra, Veronica

Encinas-Grijalva, Maria Del Socorro

Abstract

– In the context of accelerating digital transitions and growing sustainability pressures, firm´s ability to simultaneously advance Digital Transformation (DT) and Sustainable Transformation (ST)- referred to as dual transformation- has become a critical determinant of inclusive and resilient development. Yet, empirical evidence on how these processes unfold jointly within emerging and border-region economies remains limited. This study contributes to innovation-for-development research by modeling firm-level dual transformation readiness within the business ecosystem of Tijuana, Mexico. Using a validated self-diagnosis instrument, data was collected in 2023 from 148 firms operating in Tijuana, encompassing diverse firm sizes, export orientations, certification status, and organizational responsibility structures. A descriptive analysis approach reveals that, on average, sustainability transformation maturity exceeds digital transformation maturity, indicating uneven capability development across two dimensions. Considerable heterogeneity is observed across firms with midsize and non-exporting firms exhibiting higher overall dual transformation maturity, while exporting oriented, large and certified firms tend to cluster at lower maturity levels. The findings suggest that dual transformation is shaped less by formal compliance mechanisms and international market exposure and more by organizational capabilities, governance arrangements, and strategic autonomy. By providing an empirically grounded maturity model, this research contributes to innovation systems scholarship and offers policy-relevant insights for supporting inclusive upgrading and sustainable development in regions operating at the margins of global value chains. Future research may extend this framework through inferential, longitudinal, and predictive approaches to capture dynamic transformation trajectories over time.