Digital transformation and firm performance in innovative SMEs: The mediating role of business model innovation
Joan Merín-Rodrigáñez,
Àngels Dasí and
Joaquín Alegre
Technovation, 2024, vol. 134, issue C
Abstract:
This study investigates the consequences of digital transformation (DT) over performance in the case of innovative Small and Medium-sized Enterprises (SMEs). SMEs represent a heterogeneous kind of company in terms of capabilities. By focusing on their innovative character as a boundary condition, we increase our understanding of this relationship. We further research the mediating role of business model innovation (BMI) in the relationship between DT and performance. A sample of 434 innovative Spanish SMEs is used to test the research model through Partial Least Squares Structural Equation Modelling (PLS-SEM). We find that BMI partially mediates the positive relationship between DT and performance. This finding extends our understanding of BMI as an alignment tool and a blueprint for innovative SMEs channeling their investments in DT towards the improvement of performance. Finally, we put forward managerial implications and propose future avenues of research.
Keywords: Digital transformation; Business model innovation; Firm performance; Innovative SMEs (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0166497224000774
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:techno:v:134:y:2024:i:c:s0166497224000774
DOI: 10.1016/j.technovation.2024.103027
Access Statistics for this article
Technovation is currently edited by Jonathan Linton
More articles in Technovation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().