Beyond digital transformation: a multi-mixed methods study on big data analytics capabilities and innovation in enhancing organizational performance

Maria Orero-Blat (), Daniel Palacios-Marqués (), Antonio Luis Leal-Rodríguez () and Alberto Ferraris ()
Additional contact information
Maria Orero-Blat: Universitat de València, Avda Tarongers S/N
Daniel Palacios-Marqués: Universitat Politècnica de València
Antonio Luis Leal-Rodríguez: Universidad de Seville
Alberto Ferraris: Department of Business Administration, University of Turin

Review of Managerial Science, 2025, vol. 19, issue 2, No 9, 649-685

Abstract: Abstract Digital transformation (DT) and Big Data Analytics Capabilities (BDAC) enable SMEs to adapt to rapidly changing markets, innovate, and maintain relevance in the digital age. This research explores the impact of DT on SME performance through the lens of BDAC and innovation, from a multi-methods approach and applying the dynamic capabilities view. It asserts that simply investing in DT doesn't ensure enhanced performance. Analyzing 183 Spanish SMEs from various sectors, the study highlights the need for creating specific conditions that enable DT to positively impact performance. The integration of PLS-SEM and fsQCA methodologies provides a comprehensive analysis of BDAC as pivotal in optimizing SME performance through DT, emphasizing the necessity of strategic alignment with innovation. This nuanced approach, combining the predictive power of PLS-SEM and the configurational insights of fsQCA, demonstrates that investment in DT alone is insufficient without fostering conditions conducive to innovation. Our empirical insights offer actionable guidance for managers utilizing BDA or contemplating technological investments to elevate firm performance which go in the direction of increasing their innovation capabilities. Additionally, these findings equip policymakers with a nuanced understanding, enabling the design of tailored measures promoting DT in SMEs anchored in the nuances of BDAC and innovation capabilities.

Keywords: Digital transformation; Big data analytics capabilities; Innovation; Performance; PLS-SEM; fsQCA (search for similar items in EconPapers)
JEL-codes: L16 M15 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11846-024-00768-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:rvmgts:v:19:y:2025:i:2:d:10.1007_s11846-024-00768-8

Ordering information: This journal article can be ordered from
http://www.springer.com/business/journal/11846

DOI: 10.1007/s11846-024-00768-8

Access Statistics for this article

Review of Managerial Science is currently edited by R. Ewert and W. Kürsten

More articles in Review of Managerial Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().