A PLS-SEM approach to understanding the relationship between global competitiveness and environmental performance: the moderating role of perceived corruption

This research aims to investigate the moderating role of corruption on the relationship between global competitiveness and environmental performance using data from the Global Competitiveness Index, the Corruption Perceptions Index, and the Environmental Performance Index. A novel PLS-SEM approach is employed to test the study’s model. This non-parametric method, utilized in structural equation modeling with secondary data, focuses on deriving meaningful results from limited datasets. The study finds that increased global competitiveness and reduced corruption enhance environmental performance. Additionally, greater transparency amplifies the positive impact of competitiveness on environmental outcomes. To the authors’ knowledge, while a limited number of studies in the existing literature highlight the relationship between competition and environmental considerations, no comprehensive model has been identified that concurrently examines all three variables. This study fills a key gap in the literature by examining how nations’ global competitiveness, reflecting their efforts to advance in the global arena, influences environmental performance, with corruption potentially moderating this relationship. Utilizing macro-level data within a formative PLS-SEM framework, the research generates novel empirical insights. It transforms indices, drawn from international organizations’ surveys of knowledgeable respondents across countries, into variables to explore macro-level effects arising from micro-level decisions.