The role of business intelligence and digital capabilities in driving SME innovation in Latin America
Purpose This study proposes a theoretical model to evaluate the direct and mediating relationships between business intelligence resources and digital capabilities and between strategic capabilities and small and medium-sized enterprises (SME) innovation across five Latin American countries. Design/methodology/approach Partial least squares structural equation modeling (PLS-SEM) was used to evaluate a general model with an entire sample of 480 SMEs from five Latin American countries for 2022. Findings The main findings show that business intelligence resources and digital capabilities positively affect SMEs’ innovation and mediate the relationship between strategic capabilities and innovation in the entire sample of Latin American SMEs. Research limitations/implications Business intelligence resources and digital capabilities simultaneously promote innovation among SMEs in Latin American countries. Therefore, the development of public policies and organizational strategies should focus on enhancing the acquisition of business intelligence resources and developing digital capabilities. Institutional and market differences may explain the variations between countries. Originality/value This study contributes to the analysis of the relationship between resources and capabilities within the digital economy context of Latin American SMEs and in five specific countries. Specifically, it examines the direct and mediating effects of business intelligence resources and digital capabilities on the link between SMEs’ strategic capabilities and innovation.
Authors
- Cristián Geldés (ORCID: https://orcid.org/0000-0003-2391-1854)
- Mauricio Castillo‐Vergara (ORCID: https://orcid.org/0000-0002-3368-6497)
- Ronald Mora
- Juan Carlos Leiva (ORCID: https://orcid.org/0000-0001-9653-4629)
Institutions
- Instituto Tecnológico de Costa Rica (CR)
- Alberto Hurtado University (CL)
Publication Details
- Journal
- Revista de Gestão
- Published
- 2025-10-20
- DOI
- https://doi.org/10.1108/rege-01-2025-0018
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00