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 and deep learning approaches.

This paper investigates the main postulations of the R&D based growth models that innovation is created in the R&D sectors and it enables sustainable economic growth, provided that there are constant returns to innovation in terms of R&D. The analysis employs various panel data techniques and uses patent and R&D data for 20 OECD and 10 Non-OECD countries for the period 1981-97. The results suggest a positive relationship between per capita GDP and innovation in both OECD and non-OECD countries, while the effect of R&D stock on innovation is significant only in the OECD countries with large markets. Although these results provide support for endogenous growth models, there is no evidence for constant returns to innovation in terms of R&D, implying that innovation does not lead to permanent increases in economic growth. However, these results do not necessarily suggest a rejection of R&D based growth models, given that neither patent nor R&D data capture the full range of innovation and R&D activities.

BDEIM 2022 created an academic platform for academic communication and scientific innovation, brought together experts, scholars, and scientists in the fields of big data economy and information management from all over the world to present their research results and to exchange information, promoted the industrial cooperation of academic achievements, and facilitated the collaboration in the future among all the participants. The scope of the conference covered all areas of research in big data economy and information management, including Big Data Mining, Economic Statistics under Big Data, Sensor Network and Internet of Things, Computer Science and Internet, Network and Information Security, Database Technology, etc. The conference brought together about 150 participants, primarily from China, but also from USA, France, Portugal, and other countries. This volume contains the papers presented at the 3rd International Conference on Big Data Economy and Information Management (BDEIM 2022), held during December 2nd-3rd, 2023 in Zhengzhou, China.

This book examines the long term economic growth that has raised the West's material living standards to levels undreamed of by counterparts in any previous time or place. The authors argue that this growth has been driven by technological revolutions that have periodically transformed the West's economic, social and political landscape over the last 10,000 years and allowed the West to become, until recently, the world's only dominant technological force. Unique in the diversity of the analytical techniques used, the book begins with a discussion of the causes and consequences of economic growth and technological change. The authors argue that long term economic growth is largely driven by pervasive technologies now known as General Purpose (GPTs). They establish an alternative to the standard growth models that use an aggregate production function and then introduce the concept of GPTs, complete with a study of how these technologies have transformed the West since the Neolithic Agricultural Revolution. Early modern science is given more importance than in most other treatments and the 19th century demographic revolution is studied with a combination of formal models of population dynamics and historical analysis. The authors argue that once sustained growth was established in the West, formal models can shed much light on its subsequent behaviour. They build non-conventional, dynamic, non-stationary equilibrium models of GPT-driven growth that incorporate a range of phenomena that their historical studies show to be important but which are excluded from other GPT models in the interests of analytical tractability. The book concludes with a study of the policy implications that follow from their unique approach.

This book aims to contribute to the conceptual and practical knowledge pools in order to improve the research and practice on the sustainable development of smart cities by bringing an informed understanding of the subject to scholars, policymakers, and practitioners. This book seeks articles offering insights into the sustainable development of smart cities by providing in-depth conceptual analyses and detailed case study descriptions and empirical investigations. This way, the book will form a repository of relevant information, material, and knowledge to support research, policymaking, practice, and transferability of experiences to address aforementioned challenges. The scope of the book includes the following broad areas, with a particular focus on the approaches, advances, and applications in the sustainable development of smart cities: • Theoretical underpinnings and analytical and policy frameworks; • Methodological approaches for the evaluation of smart and sustainable cities; • Technological developments in the techno-enviro nexus; • Global best practice smart city case investigations and reports; • Geo-design and applications concerning desired urban outcomes; • Prospects, implications, and impacts concerning the future of smart and sustainable cities.