Exploring the Effect of Corporate Communication on Social Capital Through PLS-SEM Approach

This paper explores the communication strategy that can generate social capital when a business cluster publishes and interacts on the X platform (formerly Twitter). The methodology follows a replicable process, in which data were collected directly from the platform and analysed at the level of content according to communication characteristics and at the level of interactions represented by mentions given or received. The interaction network was constructed to extract more information to calculate social capital. Communication variables are strategies that group communication characteristics. A conceptual model was proposed: it was evaluated by the partial least squares structural equation modelling (PLS-SEM) technique, and its predictive capability was studied using PLSpredict. The results indicate explanatory effects among the variables analysed and high predictive power for the dependent variables of the proposed model. This suggests that designing communication strategies and prioritizing specific characteristics, can improve the performance of social capital. This work highlights implications and opportunities for future studies that could provide value in decision-making among marketing academics and practitioners.