Full Description
This book assesses the main interrelationships between economic growth processes, life cycle sustainability assessment approaches, and new technologies in the framework of digital transition. In other words, it aims to highlight how sustainability assessment methodologies and artificial intelligence can better support different actors for more sustainable economic growth. Readers of the book would benefit from diverse perspectives on the contributions of evaluation methodologies and digital technologies to more sustainable economic growth. This is important especially for students, policymakers and public institutions. Economic growth is analysed using the concepts of sigma and beta convergence from neoclassical theory and the Verdoorn law of Keynesian development. For sustainability assessments, the book considers methodologies associated with social life cycle assessment and life cycle cost analysis. In the context of digital technologies, special emphasis is given to machine anddeep learning approaches.
Contents
Chapter 1: Economic growth: Sigma and beta convergence processes worldwide.- Chapter 2: Clubs of convergence: Insights from the main groups of countries.- Chapter 3: World trends: Differences and similitudes between absolute and conditional convergence.- Chapter 4: Constant, decreasing, or increasing returns to scale: Evidence from the Verdoorn and Kaldor laws.- Chapter 5: Circular and cumulative processes in economic growth: The importance of the external demand.- Chapter 6: Interrelationships between economic growth and sustainability: Highlights from the literature.- Chapter 7: Sustainable development: Contributions from life cycle cost analysis.- Chapter 8: Social life cycle assessment: Relationships with the economic growth.- Chapter 9: Machine and deep learning: Their roles in the context of the economic growth processes and sustainability assessment.- Chapter 10: Economic growth, sustainability assessment and artificial intelligence: Combinations among these three dimensions.
