Abstract
Global competitiveness refers to a nation's ability to boost its economic growth and advancement. The Global Competitiveness Index (GCI), introduced by the World Economic Forum, serves as a tool to evaluate how individual countries perform across 12 key competitiveness pillars. United Nations member states are committed to achieving the Sustainable Development Goals (SDGs) by 2030, addressing economic, social, and environmental aspects of sustainability. This research employs a data-driven Bayesian Belief Network-based method to identify crucial GCI pillars, considering their positive and negative impacts on sustainability performance. Notably, ‘health’, ‘infrastructure’, and ‘skills’ are identified as pivotal GCI pillars with the potential to adversely affect sustainability performance. Conversely, ‘innovation capability’, ‘labor market’, and ‘skills’ are highlighted for their positive influence on overall sustainability performance. This is the first study to explore the link between competitiveness pillars and sustainability performance in a probabilistic network framework, providing valuable insights for policymakers aiming to enhance both competitiveness and sustainability.
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