Won Sang Lee (p)

Carolina Serpieri

Focusing on technological innovation and convergence is important for the AI domain, one of the emerging areas. This paper examines the technological capabilities in a region that could foster the occurrence of AI related technological convergence by using triadic patents. Graph analysis and survival analysis are conducted to discover AI associated convergences and their occurrences over periods. Findings from this research indicate that the active exchange of diverse but original technologies could facilitate the occurrences of technological convergence with AI in a region. This research could shed light on the establishment of R&D strategy for AI convergent technologies. This study could contribute to the dissemination and utilization of AI technologies in terms of the regional innovation system.

Sergey Nikitenko, Elena Goosen, Michael Korolev (p)

Won Sang Lee

The world is in the preliminary stage of another industrial revolution, which is tearing down the technological structure and destroying settled economical connections. It has already led to a life cycle shortening for products and technologies, has sharply accelerated the processes of emergence and implementation of innovations, and has led to instability and uncertainty. In these circumstances, it is crucial to search for new trajectories of regional development, based on a clear forecast and assessment of the region’s readiness to implement high-tech developments and transition to a new specialization.
Determining the degree of a technology feasibility, which includes assessing the degree of technology maturity and the possibility of its effective implementation in a particular region. This problem is especially acute in regions specializing in the extraction of fossil energy resources. The energy transition demands quick solutions to environmental problems and a change in the region’s specialization. This is largely due to the early stage of technology development, with the closed nature of value chains that have developed in the extractive industries, and therefore, the difficulty of implementing the associated diversification of the region’s economy.
The purpose of the report is to search and assess the degree of feasibility of promising critical technologies associated with the extractive industries and capable of creating conditions for the implementation of related diversification of the region.
Assessment of the degree of maturity and applicability of technologies for developing forecasts of scientific and technological development, including long-term ones, is actively carried out within the framework of technological foresight at the national, industry and corporate levels. The novelty of the proposed approach lies in assessing the applicability of introducing technologies for diversifying the economy and changing the trajectory of development of a resource-based region, considering the established value chains and the prospects for the emergence of new development factors - “new innovators”.
When conducting the study, the authors used the following research methods: patent analysis using patent analytics tools Orbit Intelligence, and fuzzy logic methods FAHP, FIS.

The paper is prepared within the framework of the Mirror Laboratory “Transformation of value chains in the coal and related industries in the context of the global energy transition and sanction pressure on the Russian economy” (joint project with the Center for Studies of Structural Policy of National Research University Higher School of Economics)

Haitham Natsheh (p), Mercedes Segarra Cipres

Michael Korolev

Initially focused on the digital transformation of manufacturing processes, Industry 4.0, also known as the fourth industrial revolution, has expanded its presence to different areas of organisations. The literature reflects this expansion and growing interest as demonstrated by an explosion in the number of articles on Industry 4.0 and the diversity of disciplines that have studied it. This large amount and variety of information requires a systematic literature review to clarify ideas on the concepts and definitions of Industry 4.0, as well as deepen the analysis of the barriers and drivers to implement Industry 4.0 in a sustainable and efficient way. The objective of this work is to carry out a systematic review of the literature with the aim of achieving a rigorous and objective summary of the Industry 4.0 phenomenon, through the identification of already existing trends and practical implications of the barriers and drivers of the industry 4.0 and analyse the different types of benefits that they represent for companies in terms of competitiveness, economic benefits and sustainability. As well as the costs that its implementation implies for companies, since an inappropriate implementation leads to an increase in costs and a reduction in the benefits obtained.

Our study conducts a systematic literature review of articles published in the field of Industry 4.0, focusing on its barriers and drivers until December 2023. The study presents theoretical and practical implications, identifies gaps in the literature, and suggests future research directions. Based on this systematic literature review, we propose a sectoral diagnosis tool to facilitate the implementation of Industry 4.0. The tool aims to minimise the impact of barriers and maximise the effectiveness of drivers, thereby facilitating the integration of technologies into the organisation.

Amit Batabyal (p), Karima Kourtit, Peter Nijkamp

Haitham Natsheh

We analyze aspects of economic growth in a stylized, high-tech region Γ with two distinct features. First, the residents of this region are high-tech because they possess skills. Using the language of Richard Florida, these residents comprise the region’s creative class and hence they possess creative capital. Second, the region is high-tech because it uses an artificial intelligence (AI)-based technology and we explicitly model the use of this technology. In this setting, we first derive expressions for three growth related metrics. Second, we use these metrics to show that the economy of high-tech region Γ converges to a balanced growth path (BGP). Third, we compute the growth rate of output per effective creative capital unit on this BGP. Fourth, we study how heterogeneity in initial conditions influences outcomes on the BGP by introducing a second high-tech region Δ into the analysis. At time t=0, two key savings rates in region Γ are twice as large as in region Δ. We compute the ratio of the BGP value of income per effective creative capital unit in region Γ to its value in region Δ. Finally, we compute the ratio of the BGP value of skills per effective creative capital unit in region Γ to its value in region Δ.

Carolina Serpieri, Nicola Pontarollo (p)

Amit Batabyal

In this study, we use machine learning techniques to estimate and predict the resilience of local governments to shocks. Resilience has been tackled from both the resistance and recoverability dimension for approximately 8,000 Italian municipalities with reference to the 2008 economic crisis, testing several explanatory variables. Then, using machine-learning techniques, we identify the contribution of each of them to the model (SHAP values) and estimate the resilience capacity of the Italian municipalities. Finally, the trained model will be applied to predict their resilience to the COVID-19 pandemic crisis.