Objective of the study: To propose a structured protocol to support the evaluation of studies that use PLS-SEM in innovation research, especially in emerging market contexts.
Methodology/approach: The study adopts a theoretical-methodological approach based on a critical review of the literature on PLS-SEM, systematizing practical guidelines for the evaluation of quantitative studies.
Originality/Relevance: The widespread diffusion of PLS-SEM in innovation research has been accompanied by criticism related to the mechanical use of the method, with an excessive focus on statistical metrics and less attention to the coherence between theory, operationalization, and inferences. In emerging markets, data limitations, the use of proxies, and measurement challenges amplify this complexity.
Main results: The article organizes evaluation criteria distributed across the main stages of PLS-SEM studies, from the justification of the method to the interpretation of results, presenting evaluative checklists to support more consistent methodological reviews. The protocol incorporates current methodological recommendations, such as the assessment of out-of-sample predictive power (PLSpredict/CVPAT) and the diagnosis of common method bias through full collinearity VIF.
Theoretical/methodological contributions: The study proposes an integrated evaluation protocol, reinforcing the articulation between theory, conceptual model, operationalization of constructs, and interpretation of results.
Social/management contributions: The protocol can support reviewers, editors, and authors in peer review, desk review, and methodological self-assessment, contributing to greater consistency in empirical innovation research.
Objective of the study: To propose a structured protocol to support the evaluation of studies that use PLS-SEM in innovation research, especially in emerging market contexts. Methodology/approach: The study adopts a theoretical-methodological approach based on a critical review of the literature on PLS-SEM, systematizing practical guidelines for the evaluation of quantitative studies. Originality/Relevance: The widespread diffusion of PLS-SEM in innovation research has been accompanied by criticism related to the mechanical use of the method, with an excessive focus on statistical metrics and less attention to the coherence between theory, operationalization, and inferences. In emerging markets, data limitations, the use of proxies, and measurement challenges amplify this complexity. Main results: The article organizes evaluation criteria distributed across the main stages of PLS-SEM studies, from the justification of the method to the interpretation of results, presenting evaluative checklists to support more consistent methodological reviews. The protocol incorporates current methodological recommendations, such as the assessment of out-of-sample predictive power (PLSpredict/CVPAT) and the diagnosis of common method bias through full collinearity VIF. Theoretical/methodological contributions: The study proposes an integrated evaluation protocol, reinforcing the articulation between theory, conceptual model, operationalization of constructs, and interpretation of results. Social/management contributions: The protocol can support reviewers, editors, and authors in peer review, desk review, and methodological self-assessment, contributing to greater consistency in empirical innovation research. Read More