The efficient use of natural resources and the quality of the environment are the main priorities of sustainable development. The purpose of this paper is to demonstrate the role of reverse logistics in the context of sustainable development, starting from the premise that it combines environmental and economic objectives and aims to minimize the wastage of resources through the reuse of products and packaging. In the current context, the circular economy must be approached by considering the methods of waste collection and reuse, with reverse logistics playing an essential role in creating environmental, economic, and social benefits. The growing population obviously determines the increase in the consumption of resources, which inevitably leads to the increasing generation of packaging and packaging waste. This study aimed to highlight the evolution of recycling rates at the level of the EU member states, starting from the stability objectives of the European Commission for the years 2025–2030. Starting from the Eurostat database, for the 27 member states of the European Union, regarding the recovery rate, recycle rate, and waste generation kg_per_capita related to the period of 2009–2020, we extrapolated the trends of the recycling rate of packaging for the period of 2021–2030 with the help of the Prophet model. Using the Prophet forecasting program, we identified states from the European Union that will meet the stability targets set by the European Commission for the years 2025 to 2030, considering the need to develop a circular economy.

Sustainable development involves constant efforts to reduce pollution by using resources as efficiently as possible. One of the sources of pollution is waste from packaging, recovery, and of course, the possibility of recycling them. The research theme of this paper is the reverse logistics of plastic packaging, which allows the realization of the idea of circular economy and green logistics, which promotes the idea of sustainable development. The EU is strongly committed to issues related to the management of plastic packaging and waste to reduce environmental pollution and achieve circularity goals. Through this article, we aim to highlight the degree to which the EU member states are included in the plastic packaging recycling targets for the year 2030. To highlight the evolution trend for the recycling rate of plastic packaging, we used an advanced forecasting model that runs a series of variables in order to draw up a forecast as accurate as possible. After highlighting the recycling rates for plastic packaging at the level of the EU member states, we proceeded to outline some recommendations in order to encourage the EU member states to make the recycling process more efficient. The current study continues the series of studies dealing with the problem of recycling, but it covers a topic not addressed until this moment, namely the behavior of the citizen regarding the recycling activity seen through the prism of national culture. The current study aims to strengthen the specialized literature in this field and to offer innovative solutions that appeal to the respective national cultures regarding the availability of the populations of the EU member states to address the problem of recycling plastic packaging, not only from a legislative perspective but also from a cultural one. In conclusion, this study generates a model of approach to government policies regarding the recycling of plastic packaging considering the types of national cultures prevailing in the EU member countries, with this being possible by grouping the countries into culturally homogenous clusters. In this way, the environmental policies enunciated by governments can be adapted to convey the message in a more personal way, considering the cultural differences between the EU member states.

In the digital age, e-commerce has become a critical part of modern economies, shaping global economic growth and the pursuit of the Sustainable Development Goals (SDGs). This study uses robust statistical methods to explore the complex relationships between traditional trade, e-commerce, and key economic and sustainability indicators. The General Linear Model (GLM), factor analysis, and linear regression reveal that conventional trade remains vital for GDP growth, even though e-commerce clearly influences SDG performance. The study emphasizes the catalytic role of e-commerce in advancing sustainability by showing how treating it as a dependent variable speeds up SDG progress through Brown, Holt, and ARIMA forecasting models. Additionally, cluster analysis uncovers a strong link between higher SDG scores and increased e-commerce activity, with countries scoring better on sustainability often having more companies in the digital economy and earning more online. This research provides a comprehensive understanding of how e-commerce can support global sustainability goals, along with integrated policy recommendations that promote digital transformation and long-term environmental and social resilience.

Environmental protection and climate change are the most debated issues, both in economic research and in EU legislative regulations. This work is also focused on these issues and aims to analyze the evolution of GHG emissions from transport, the main contributor to total emissions. The novelty of this research aligns with the EU climate policy established within the European Green Deal’s “Fit for 55” package, aiming for a 55% reduction in net greenhouse gas emissions by 2030 (compared to 1990 levels), and the broader objective of climate neutrality by 2050 as outlined in the European Climate Law. The study’s originality lies in the selection of variables that can influence the reduction of emissions and the anticipation of future developments using the Prophet model, for the period 2024–2050. The estimates obtained allowed the construction of clusters to identify EU member states that will record reductions in GHG emissions in the analyzed period and will be able to represent models for other economies. The results obtained are beneficial for decision-makers at European and national levels and highlight the need for urgent action to reduce emissions and limit the negative effects of climate change.

The rapid expansion of artificial intelligence (AI) is revolutionizing economic systems by reshaping production, labor organization, and productivity patterns. In the construction industry, which remains highly labor-intensive, project-based, and structurally heterogeneous across European countries, AI can support productivity, planning, safety monitoring, cost estimation, and decision-making. However, its implementation also poses specific challenges, including fragmented workflows, heterogeneous construction sites, limited digital skills, poor data interoperability, high adoption costs, resistance to organizational change, and temporary adjustment costs that may delay the visibility of productivity gains. In this paper, we evaluate the effect of Artificial Intelligence (AI) on labor productivity in the construction sector of European Union countries, taking into account labor input and sector output, and search for structural trends from a systems perspective. AI adoption is defined as the share of construction businesses that use at least one AI technology. Productivity is estimated per worker and per hour using a dataset of EU countries from 2023 to 2024. The effects of AI adoption, labor input, and output on productivity are evaluated using multivariate log-linear regressions in SPSS. Hierarchical and K-means clustering reveal groups of countries with comparable digital and labor performance. The results demonstrate that construction output is the key driver of labor productivity. In contrast, AI adoption shows a small, negative association with productivity, consistent with short-term adjustment costs in the early stages of digital transformation. Cluster analysis reveals diverse country profiles in AI use, productivity, and labor intensity. Overall, the findings underscore the need for a gradual approach to managing digital change in construction, supported by complementary organizational and skills-based measures.