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The effects of knowledge spillovers, digital capabilities, and innovation on firm performance: A moderated mediation model.

Authors :
Ferreira, João J.M.
Fernandes, Cristina I.
Veiga, Pedro Mota
Source :
Technological Forecasting & Social Change; Mar2024, Vol. 200, pN.PAG-N.PAG, 1p
Publication Year :
2024

Abstract

Despite the growing importance of implementing digital technologies in business contexts, empirical research relating to digital capabilities, innovation, and business performance still remains scarce, particularly relevant in these times of disruption. This study proposes a mediated-moderated framework to describe, according to the level of economic development of the country of firm location, the direct and indirect effects (mediated by digital capabilities and innovation) of knowledge spillovers on firm performance. We carried out a quantitative study deploying the longitudinal World Bank Enterprise Surveys for 2019, 2020 and 2021 in a dataset that included 27,727 firms from 41 countries and territories. We applied the partial least square structural equation modelling (PLS-SEM) methodological approach to test the mediated-moderated model that explains business performance. The results identify how knowledge spillovers positively influence firm performance through digital capabilities and innovation. Furthermore, we empirically demonstrate that the national level of economic development moderates the direct and indirect impacts of knowledge spillovers on firm performance. • Our study advances on knowledge spillover theory. • We present a mediated-moderated framework to assist the effects of knowledge spillovers on firm performance. • This study examines how digital capabilities impact the relationship between knowledge spillovers and company performance. • Our research shows how knowledge spillovers drive innovation and improve firms' performance, leading to value creation. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00401625
Volume :
200
Database :
Supplemental Index
Journal :
Technological Forecasting & Social Change
Publication Type :
Academic Journal
Accession number :
175032921
Full Text :
https://doi.org/10.1016/j.techfore.2023.123086