The concept of well-being is multifaceted, influenced by a range of factors, including economic, social, perceptual, and personal, and varies considerably between individuals, countries, and continents. The objective of this research paper is to achieve an efficient grouping of countries according to several indicators that measure overall happiness. The indicators utilized in this study, derived from the World Happiness Report, are as follows: Life Ladder, Log GDP (Gross Domestic Product) per capita, Social Support, Healthy Life Expectancy at Birth, Freedom to Make Life Choices, Generosity, Perceptions of Corruption, Positive Affect, and Negative Affect. Consequently, following the identification, filtering, and collection of data on the countries in the study, cluster analysis, discriminant analysis, and neural network training were employed to obtain a classification of the countries into heterogeneous groups with a minimum error rate. Finally, for Romania, scenarios and policies were developed to facilitate ascent from the initial class to a class with a superior level of well-being.

With the onset of the COVID-19 pandemic, society has increasingly relied on alternative ways to procure goods, leading to an e-commerce boom. This study analyzes the performance of small and medium-sized enterprises (SMEs) that are active in e-commerce in Romania and provides recommendations for entrepreneurs to improve their efficiency. Through unsupervised learning techniques, three classes are identified according to company performance: (1) a class of high-performing companies whose entrepreneurs took the risk of investing in the business, (2) a class of medium-performing companies that maintained their position in the market and (3) a class of financially weak companies whose managers adopted risk-averse, defensive policies. Furthermore, we present scenarios for moving companies from a lower-performing class to a higher-performing class. The research identifies the strategies that managers need to adopt in order to stimulate the activity of e-commerce companies, provides foreign investors a rubric for making investment decisions, and offers a starting point for an entrepreneurship course in academia.

The COVID-19 pandemic has accelerated the digitization of the logistics industry, exceeding the expectations of some companies. Ensuring customer satisfaction throughout the online ordering and delivery process has major implications for their profitability and market position. This study aims to classify firms in the logistics sector based on their financial accounting performance and determine if software designed for the logistics sector can improve their performance. By using advanced data analysis methods such as cluster analysis and neural network training, the study identifies three distinct classes. One company from a lower class was given a scenario for implementing digitization, improving its performance indicators, and enabling its movement to a higher class. The practical implications of the study are related to the domestic and international business environment, providing an overview of the logistics sector in Romania and a direction for growth for companies operating in the sector.