Significant efforts are being performed to make cities smarter and more sustainable. Therefore, there is a need to compare these efforts using evaluation frameworks. According to the literature review, the basic dimensions of smart cities are generally evaluated with the criteria of regional competitiveness, transportation, information and communication technology, economy, natural resources, human and social capital, quality of life and participation of citizens in the management of cities. In this paper, Analytical Network Process (ANP) is used to weight smart and sustainable city criteria. According to the results, while 'smart living' is the most important characteristic with a 35,459% priority, 'smart governance' is the last with 5,738%. The study covers 44 cities around the world and comparisons were made by TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). According to the results, Tokyo, London and New York are in the top three in the overall ranking. But none of these cities is among the top five in terms of smart governance, mobility and environmental dimensions. According to the results obtained, the article provides some recommendations for the cities. These results aim to help cities understand their situation relative to other cities and to see areas where policymakers need to strengthen.

All successful cities are the most developed and productive cities in their regions and countries in terms of economy and quality of life. In addition, it is observed that there are strong industries and enterprises in these regions and cities. Therefore, this study tries to evaluate the quality of life and the development of the industry together. The proposed method can be considered as a combination of operational research and GIS (Geographical Information System). The results of both approaches support each other. In addition, the innovative approaches of the sectors are evaluated by TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). Also, the article recommends SMEs (Small and Medium-Sized Enterprises) for sustainable economic growth. According to the results, the quality of life and socio-economic development has a very close relationship with the existence of investments and manufacturing companies. If the current development policy continues, the regions with low quality of life will continue to lag behind the other cities in terms of development. The study indicates that there are remarkable differences between eastern and western Turkey in terms of living standards and the contribution of SMEs to economic development.

In Turkey, current energy generations are not sufficient for the existing energy needs and besides, energy demand is expected to increase by 4–6 percent annually until 2023. Therefore, the government aims to increase the ratio of renewable energy resources (RES) in total installed capacity to 30 percent by 2023. By this date, total energy investments are expected to be approximately $110 billion. Turkey is the fastest growing energy market among the OECD countries. Therefore, Turkey is an attractive market for energy companies and investors. At this stage, site selection and deciding appropriate RES are the most important feasibility parameters for investment. In this study, “Site Selection in Turkey” issue for RES (solar, wind, hydroelectric, geothermal, biomass) is evaluated by the ELECTRE which is one of the Multi Criteria Decision Making (MCDM) methods. In addition, the reasons for choosing this method are explained according to the literature. The study emphasizes the importance of energy generation from renewable and sustainable sources and is concerned with improving the position of the country. The Turkish government offers many purchasing guarantees and high incentives, especially in the renewable energy sector. As a result of the analysis, the most suitable energy sources are presented according to the geography and energy potential of the regions. The study aims to inform energy firms and everyone related with RES about Turkey’s RES opportunities.

Science, technology and innovation (STI) policies are of great importance for countries to reach their sustainable development goals. Numerous global databases have many indicators that measure and compare the performance of STI policies of countries. However, many problems arise regarding how to identify, classify and systematically analyze these indicators in order to measure, monitor and improve the performance of STI. The study includes a literature review on global problems and new trends in STI policies, while mentioning the necessity of an internationally comparable STI indicator set, current STI indicator studies and efforts, and studies for each continent. In light of these, all the indicators selected are introduced in detail. The strengths and weaknesses of the countries in the study in terms of evaluation indicator values are indicated. After determining the indicator weights objectively with the entropy method, 40 countries are compared with TOPSIS, VIKOR, PROMETHEE I-II, ARAS, COPRAS, MULTIMOORA, ELECTRE, SAW and MAUT methods. In addition, countries that show similarities with each other are evaluated by cluster analysis, which is one of the data mining classification methods. This study offers a new and original approach with MCDM methods on this subject. Considering all the results obtained in the study together, these rankings are compared among themselves and with the rankings specified in the Global Innovation (2019) and Global Competitiveness (2019) indices, and it is seen that the results are consistent. In addition, it is possible to update and publish this study every year with updated data.

Artificial intelligence development and research leaders in business, industry, and nations gain a major competitive edge. Additionally, it is clear that nations with a well-established national artificial intelligence policy have an edge over others, both technologically and economically. To further their artificial intelligence capability, nations also seek to develop a strategy, vision, structure, and working environment that encourages collaboration between the public sector, private industry, and educational institutions. Artificial intelligence is thought to be a tool that will help bridge the gap between powerful and developing countries growing in the future. Using data from “The Global AI Index” for 2021, this study aims to examine and analyze the present state of artificial intelligence management in 62 nations in terms of talent, infrastructure, business environment, development and research government policy, and commercial efforts. The research used PROMETHEE, which is widely used in multi-criteria decision-making evaluations, and its geometric representation, the GAIA plane. This study also found that the United States of America is the world leader in artificial intelligence (AI) research and development as well as AI investment. The United Kingdom, China, Israel, Canada, the Netherlands, South Korea, and Germany all rank well. China is rapidly catching up to the USA. At the very bottom of the list are nations such as Armenia, Kenya, Egypt, South Africa, and Pakistan. Turkey’s values are more similar to those of nations towards the bottom of the list than of those in the top half. There is a significant gap between the top three countries and the rest of the world in all parameters included in the survey. Except for the ‘State Strategy’ category, Turkey scores quite low compared to the top-performing countries. Decision makers are expected to address the identified global challenges of the study by creating a more comprehensive national AI strategy, both financially and in terms of content.

The travel and tourism industry has numerous components that contribute to the economy and create new jobs since it is a service sector that incorporates other service networks. Furthermore, it acts as a catalyst in sustaining investment attractiveness and economic indicators such as closing the current account deficit. The Travel and Tourism Competition Index utilized in this research has four dimensions and fourteen indicators. In this research, the Entropy-based VIKOR approach, which is a Multi-Criteria Decision-Making method, Spearman Correlation analysis, and K-means clustering analysis were employed to propose a methodological novelty in this field. The study analyzed the competitiveness of significant European and Eurasian nations based on key indicators. According to country evaluations, Spain, France, Germany, the United Kingdom, Italy, and Switzerland differ from other countries in a positive sense and with a significant difference. Eastern European and Balkan nations are often at the bottom of the table. As a consequence of this study, it is expected that the results of future studies using other methodologies or methods will be compared with this study. At the same time, it is aimed to explain the relevant indicators and their dimensions.