Can big data analytics capability promote firm innovation? A moderated mediation model of organizational learning and market orientation

Abstract

Purpose

The empirical results of the pivotal relationship between big data analytics capability (BDAC) and firm innovation remain inconclusive, necessitating a comprehensive understanding of the mediator and moderator through which firms can realize the potential innovation benefits of BDAC. Invoking the indirect perspective of dynamic capability theory, we constructed a moderated mediation model in which organizational learning mediates the impact of BDAC on firm innovation; the mediation effect of organizational learning is contingent upon market orientation.

Design/methodology/approach

Our hypotheses were tested using hierarchical regression and bootstrapping methods with a sample of 227 large- and medium-sized manufacturing firms in China.

Findings

The results reveal that both exploratory and exploitative learning fully mediate the link between BDAC and firm innovation. The mediation effect of exploitative learning is positively contingent upon market orientation; however, market orientation does not positively moderate the mediation effect of exploratory learning.

Originality/value

Our moderated mediation model is one of the first to provide a fine-grained understanding of the process through which BDAC is transformed into firm innovation as well as the conditions under which this mediating mechanism may work effectively, thereby further elucidating the theoretical black box regarding the BDAC-firm innovation link and resolving existing debates in the literature regarding why BDAC does not always yield positive outcomes.

Citation

Song, M. and Liao, Y. (2024), "Can big data analytics capability promote firm innovation? A moderated mediation model of organizational learning and market orientation", Baltic Journal of Management, Vol. 19 No. 5, pp. 531-548. https://doi.org/10.1108/BJM-05-2024-0245