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This research paper aim at providing a new approach of calculating the destinations competitiveness index. How can these variables been aggregated in other to reflect the realities of very distinct productive environments? We assume that: The weighting of variables provides a better measure of destinations competitiveness. Base on the Neo-Technological theory, after a life cycle differentiation, we used a panel data approach to calculate the weight of each variable as the spearman correlation coefficient of its contribution to tourism inflows growth. After integrating these weights, we came to the point that by applying an appropriate weight to its components, we end up having a competitiveness index that significantly improve the correlation between competitiveness and tourism inflows growth.