Social media analytics and product innovation: mediating effects of knowledge exploration and exploitation competences

Abstract

Purpose

Prior research on business analytics has advanced substantially our understanding of how social media analytics affect business performance. However, the specific value of social media analytics to product innovation has not been fully explored and appreciated. To address this important issue, the present study draws on the resource-based view and the knowledge-based view to examine (1) whether the use of social media analytics strengthens radical product innovation to a greater extent than it does incremental product innovation and (2) how knowledge-exploration competence and knowledge-exploitation competence mediate the influence of social media analytics on radical and incremental product innovation.

Design/methodology/approach

This study tested the proposed model using data collected from 205 manufacturing firms. Structural equation modeling was applied to test the research hypotheses using LISREL 8.80 software program.

Findings

The statistical findings provide compelling evidence that the use of social media analytics is more likely to lead to radical product innovation than to incremental product innovation. In addition, knowledge-exploration competence only partially mediates the relationship between social media analytics and radical product innovation. Knowledge-exploitation competence not only partially mediates such a relationship, but also fully mediates the link between social media analytics and incremental product innovation.

Originality/value

This study contributes to the social media analytics and innovation literature by offering novel theoretical and empirical insights into how firms can leverage the value of social media analytics to create superior product innovation.

Citation

Cheng, C.C.J. and Sheu, C. (2024), "Social media analytics and product innovation: mediating effects of knowledge exploration and exploitation competences", International Journal of Operations & Production Management, Vol. 44 No. 1, pp. 229-259. https://doi.org/10.1108/IJOPM-08-2022-0537