Assessment of Investment Attractiveness in European Countries by Artificial Neural Networks: What Competences are Needed to Make a Decision on Collective Well-Being?

Abstract

A rich volume of literature has analysed country investment attractiveness in a wide range of contexts. The research has mostly focused on traditional economic concepts—economic, social, managerial, governmental, and geopolitical determinants—with a lack of focus on the smartness approach. Smartness is a social construct, which means that it has no objective presence but is “defined into existence”. It cannot be touched or measured based on uniform criteria but, rather, on the ones that are collectively agreed upon and stem from the nature of definition. Key determinants of smartness learning—intelligence, agility, networking, digital, sustainability, innovativeness and knowledgeability—serve as a platform for the deeper analysis of the research problem. In this article, we assessed country investment attractiveness through the economic subjects’ competences and environment empowering them to attract and maintain investments in the country. The country investment attractiveness was assessed by artificial intelligence (in particular, neural networks), which has found widespread application in the sciences and engineering but has remained rather limited in economics and confined to specific areas like counties’ investment attractiveness. The empirical research relies on the case of assessing investment attractiveness of 29 European countries by the use of 58 indicators and 31,958 observations of annual data of the 2000–2018 time period. The advantages and limitations of the use of artificial intelligence in assessing countries’ investment attractiveness proved the need for soft competences for work with artificial intelligence and decision-making based on the information gathered by such research. The creativity, intelligence, agility, networking, sustainability, social responsibility, innovativeness, digitality, learning, curiosity and being knowledge-driven are the competences that, together, are needed in all stages of economic analysis.

A Study on the Impact of Digital Finance on Regional Productivity Growth Based on Artificial Neural Networks

“…The role of financial development in promoting economic growth has been unanimously recognised by scholars at home and abroad [ 1 – 3 ] and it was found that the scale and function of finance can effectively stimulate long-term economic growth as well as total factor productivity growth through their studies. The main emphasis is on a kind of guiding effect of financial development on supply, that is, with the growth rate of economic development as well as the complexity of economic structure, social demand for financial aspects will further stimulate the development of the economy, and financial development and economic growth are causally related to each other [ 4 – 6 ].…”

Complex thinking through a Transition Design-guided Ideathon: testing an AI platform on the topic of sharing economy

“…Forty-seven documents were identified. Documents related to the health area (Lamberti et al, 2019;McNamara et al, 2019;Shorey et al, 2019;Rajadhyaksha, 2020;Zhao et al, 2020;Cheng et al, 2022;Creed et al, 2022;Liaw et al, 2022;Lokala et al, 2022;Shah et al, 2023), industry (Barykin et al, 2020;Mokhtarname et al, 2020;Sandner et al, 2020;Dmitrievsky et al, 2022;Obermayer et al, 2022;Zakharkina et al, 2022), education (Hrich et al, 2019;Tsalapatas et al, 2019;Cortés et al, 2020;Paba-Medina et al, 2020;Raj et al, 2020;Yang et al, 2020;Demchenko et al, 2021;Hurajová, 2021;Jiang, 2021;Petrescu et al, 2021Ghnemat et al, 2022Polak et al, 2022;Ramírez-Montoya et al, 2022;Rataj and Wojcik, 2022), science (Bruneckiene et al, 2019;Desnos et al, 2022;Ramírez-Montoya et al, 2022;Zhu et al, 2022), evaluation (Kiran et al, 2019;Prom et al, 2019;Konys, 2020;Bachiri and Mouncif, 2023;Rashidi Fathabadi et al, 2023), engineering (Kaspar and Vielhaber, 2019;Telnov and Korovin, 2019)...…”

Smart economic development patterns in Europe: interaction with competitiveness

“…Such soft determinants as entrepreneurship (Korez-Vide and Tominc, 2016; Kumar and Dahiya, 2017), learning (Jucevicius and Juceviciene, 2015), managerial discretion (Haj Youssef and Teng, 2019), clusters and networking (Evans, 2019) are distinguished as the determinants of SED. The smartness approach is essential to improve governance and economic efficiency (Caragliu et al , 2011), increase investment attractiveness (Bruneckienė et al , 2019; Snieska et al , 2019), sustainable development (Martin et al , 2018; Gazzola et al , 2019) and competitiveness (Kumar and Dahiya, 2017). The smartness approach in economic development has a significant effect on industrial theory (Piirainen et al , 2017) and urban development theory by developing smart (Gazzola et al , 2019) or ubiquitous (Lee et al , 2008) cities and on institutional theory by developing networking among corporate and governmental institutions (Bakici et al , 2013; Mora et al , 2018).…”