This research presents a comprehensive bibliometric review of the role of Artificial Intelligence (AI) and Machine Learning (ML) in enhancing production efficiency and fostering sustainable development. With the increasing focus on sustainability, AI and ML technologies have emerged as pivotal tools for optimizing industrial processes, improving resource management and minimizing environmental impacts. The study analyzes key ML algorithms in various production settings. This study conducts systematic bibliometric analysis using the Scopus database and Bibliometrix R package, examining global trends, key collaborations, and thematic focuses on AI and ML applications in production efficiency and sustainable development. Novel contributions include uncovering underexplored ethical dimensions of AI adoption and emphasizing the pivotal role of SMEs and developing economies in advancing sustainable practices. Key research trends identified include the integration of AI with sustainable energy management, circular economy practices, and precision agriculture. Furthermore, the analysis reveals geographical contributions, with countries like China, the United States, and the United Kingdom leading in research output and impact. Despite the promising advancements, the review identifies gaps in ethical considerations, especially in data privacy and labor market implications, and suggests avenues for future research, including the implementation of AI and ML in developing economies and Small and Medium Enterprises (SMEs).

The understanding of a country's past is important in the process of analyzing a country's present. Through the study of Bulgarian history, the researcher developed a relatively good understanding of the country's image at the beginning of the period in question (1989-2002). The evidence supports the unexpected finding that historical links do not affect a company's decision to invest in another country. Furthermore, there is support for the conclusion that political unwillingness to make significant reforms together with the inefficiency of the post-communist Bulgarian government rather than Bulgarian political instability led to delays in structural reform and delayed progress in privatization, limited foreign direct investment (FDI) inflows, and thus to a delay in the overall Bulgarian transition process. Moreover, the cultural closeness and/or distance of multinational enterprises' (MNEs') countries of origin vis-à-vis the host country remain questionable, and they have been used either as incentives or as obstacles to MNEs' investment decisions depending on the specific industries and on the specific products. On the other hand, the geographical distance of Bulgaria from advanced Western countries is an important barrier that partially explains low Western investment interest in Bulgaria.

The end of the twentieth century in Central and Eastern Europe (CEE) will be remembered for the collapse of centrally planned economies, civil wars, and political turmoil that gave birth to new countries. These countries, including Serbia, started an economic transition process and integration with the rest of Europe and at the same time experienced one of the key components of economic integration—foreign direct investments. Being a newly developing country, Serbia has not yet been given the proper attention by industry surveys. According to the results of this study, key motives of foreign investors to enter the manufacturing sector in Serbia are technological and workforce suitability for the easy and profitable transfer of manufacturing capacities, combined with a favorable location that can support regional growth.

Greece's slow recovery from the severe economic depression caused by the great global financial and economic crisis that erupted in late 2000s was interrupted by the effects of COVID-19 pandemic on economic activity. This chapter looks into the factors shaping Greece's competitive position and discusses the potential to achieve a V-shaped recovery at the end of the pandemic.