With the rising global consumer demand for green and healthy food, the tea industry is facing unprecedented competitive pressure. Therefore, how to build tea enterprises with sustainable competitiveness has become a key issue facing the industry. This paper firstly reviews the concept of traceability systems and their evolution and, based on the theory of enterprise competitive advantage, explores the influence mechanism of traceability as a strategic resource on the long-term competitiveness of tea enterprises; secondly, it analyzes the multi-dimensional role of traceability on enterprise competitiveness from five aspects, namely, quality and safety control and guarantee, brand image shaping and trust construction, market dynamics response and consumer feedback, risk response and product recall, as well as technological innovation and efficiency enhancement; finally, combined with the above analysis, this paper constructs a theoretical framework for the competitiveness of tea enterprises, integrates the impact of traceability in different dimensions, and proposes a multi-level competitiveness enhancement model. Through this framework, tea enterprises can more comprehensively understand and grasp the close relationship between traceability and the long-term competitive advantage of enterprises and then make strategic adjustments according to their own actual situation so as to realize sustainable competitiveness enhancement in the future market competition.

This paper discusses the concept of creating a new reality using the approaches of smart cities to develop eco-cities, in which the necessary balance between nature and progress can be maintained. The authors propose that the concept of smart cities should be used as a tool for the creation of eco-cities, and argue that the positive synergies between the two will be strongest if the smart concept acts as a tool for the creation of eco. The core elements of a smart eco-city are identified as smart sustainable use of resources, a smart sustainable healthy community, and a smart sustainable economy. The results of the article were the foundation for the development concept for Vision Bratislava 2050—the vision and strategy for the development of the capital of the Slovak Republic. The authors also discuss the challenges of transforming cities into smart eco-formats, including the need for digital resilience in the face of potential cataclysms. They suggest that this is a promising area for further research into the concept of smart eco-cities.

Against the backdrop of anti-globalization rhetoric, this paper summarizes our joint book entitled Going Beyond Aid (Lin and Wang, 2017a) and discusses the prospects for development finance in the broad context of Belt and Road Initiative (BRI). Based on the New Structural Economics (Lin, 2010; 2011), here we focus on China’s demonstrated comparative advantages in infrastructure, e.g. in hydropower and high-speed railways (HSR). In addition, long-term orientation (LTO) and patient capital are latent comparative advantages that many Asian economies possess, and are critical for the Belt and Road Initiative. Only if these comparative advantages are utilized can these economies cooperate to potentially achieve win-win.

The paper considers an important problem of the successful development of social qualities in an individual using machine learning methods. Social qualities play an important role in forming personal and professional lives, and their development is becoming relevant in modern society. The paper presents an overview of modern research in social psychology and machine learning; besides, it describes the data analysis method to identify factors influencing success in the development of social qualities. By analyzing large amounts of data collected from various sources, the authors of the paper use machine learning algorithms, such as Kohonen maps, decision tree and neural networks, to identify relationships between different variables, including education, environment, personal characteristics, and the development of social skills. Experiments were conducted to analyze the considered datasets, which included the introduction of methods to find dependencies between the input and output parameters. Machine learning introduction to find factors influencing the development of individual social qualities has varying dependence accuracy. The study results could be useful for both practical purposes and further scientific research in social psychology and machine learning. The paper represents an important contribution to understanding the factors that contribute to the successful development of individual social skills and could be useful in the development of programs and interventions in this area. The main objective of the research was to study the functionalities of the machine learning algorithms and various models to predict the students’s success in learning.