When Significant Paths Mislead: Construct Redundancy in Integrated Social Media Marketing Models

Purpose–Integrated social media marketing (SMM) models estimated using partial least squares structural equation modelling (PLS-SEM) are increasingly used to identify the relative importance of multiple marketing drivers. However, these models often combine conceptually related constructs whose empirical distinctiveness is rarely examined beyond routine measurement diagnostics. This study investigates how construct redundancy influences the interpretation of structural relationships and proposes a framework for improving diagnostic and interpretive practice.

Design/methodology/approach–Building upon the literature on construct validity and PLS-SEM, this study develops a conceptual framework explaining two mechanisms through which construct redundancy arises: literal construct overlap and common-cause entanglement. An empirical illustration based on an integrated SMM model is used to identify the characteristic empirical signature of construct redundancy. These theoretical and empirical insights are then synthesised into a sequential diagnostic protocol linking measurement evaluation with structural interpretation.

Findings–The study demonstrates that construct redundancy should not be regarded solely as a measurement-quality issue. Instead, it undermines the interpretation of structural coefficients by weakening the assumption that latent constructs represent independent theoretical mechanisms. Construct redundancy leaves a recognisable empirical signature characterised by loss of construct distinctiveness and structural instability. Based on these findings, a sequential diagnostic protocol is proposed in which evidence from conceptual specification, measurement evaluation, and structural diagnosis jointly determines whether substantive interpretation of structural relationships is warranted.

Originality/value–Rather than introducing new statistical indices, this study reframes construct distinctiveness as an interpretive prerequisite for structural equation modelling. By connecting measurement evaluation with structural interpretation, it provides a coherent methodological framework for researchers, reviewers, and editors working with integrated PLS-SEM models.