This study empirically examines the complex relationship between materialism and economic motivation, proposing an inverted U-shaped relationship. The research analyzes three dimensions of materialism: happiness pursuit, social recognition, and uniqueness, and their impact on economic motivation. The findings suggest that materialism, when balanced, positively influences economic motivation without causing adverse effects. This relationship remains consistent across demographic characteristics and life satisfaction levels, challenging the traditional negative view of materialism. The implications of these findings extend to marketing strategies, policy design, and infrastructure development, offering actionable insights for real-world contexts. This research underscores the importance of balancing materialistic values to foster sustainable economic growth and well-being.

The global significance of the energy crisis and the need for a sustainable European electricity system have intensified interest in renewable energy sources. This study aims to explore the attitudes toward solar energy systems among the population of the North Transdanubian region, which is crucial for companies in the region specializing in solar system installation. The research sheds light on trends in energy prices, potential strategies for addressing the energy crisis, and the regulatory environment for solar systems in Hungary and Austria, focusing on the Burgenland region. The study is divided into two main sections: secondary and primary research. The secondary research presents various applications of renewable energy sources, especially solar energy, and examines energy pricing trends in the two countries, with particular emphasis on the payback period and the impact of changes in energy prices. The primary research is also divided into two parts: the first examines the satisfaction of customers who already use solar systems, and the second focuses on the attitudes of potential customers toward solar investments. The findings provide a comprehensive view of both current users’ and prospective investors’ perspectives on solar energy systems. The practical significance of this research lies in identifying development opportunities for companies, advancing energy efficiency goals, and supporting sustainability efforts.

The successful execution of large-scale infrastructure projects is essential for economic growth and societal development, but these projects are too often beset with financial risks. The main financial risks related to infrastructure projects, including cost overrun, funding uncertainty, currency fluctuation, and regulatory change are examined in this research. The study identifies and assesses the magnitude and frequency of these risks by combining surveys and analysis of financial reports. The findings show that current risk management strategies, including hedging, contingency funds, and public-private partnerships, are often unsuitable to respond to the specific needs of financial uncertainties. The research suggests the need for an all-encompassing financial risk management framework that relies on real-time data analysis and a cocktail of risk assessment tools. Additionally, the development of strategic tailored approaches to address financial risk recovery depends on proactive stakeholder engagement. This research complements the existing literature on risk management in infrastructure projects by highlighting the financial dimensions of risk management and suggesting future research on advanced financial tools and technologies. Ultimately, large-scale infrastructure project sustainability and success contribute to economic stability and societal well-being can only be achieved through effective financial risk management.

In the context of globalization and urbanization, rural development faces many challenges, such as population loss and uneven distribution of resources. This paper analyzes the similarities and differences in sustainable rural development strategies between China and Europe through a comparative perspective. China has optimized land use by relying on land policy innovations, such as the household contract responsibility system and the “separation of three rights”, as well as the construction of small towns; while Europe focuses on private ownership and market mechanisms, and supports agricultural and rural development through the Common Agricultural Policy (CAP). Using literature review, comparative research and policy analysis, the study shows that the policy innovations in China and Europe, each with its own focus, have been effective in promoting agricultural output and rural social development. Particularly noteworthy is that the “three rights” policy has increased agricultural productivity through the liberalization of management rights, while the European CAP has contributed to the diversification of the rural economy and environmental protection through continuous reforms. This study emphasizes that through policy innovation and international cooperation, combining the strengths of China and Europe, it is possible to provide a new model of sustainable development for the global countryside. Specifically, through the establishment of Sino-European R&D centers for agricultural science and technology, exchange of talents, and cooperation in green infrastructure development, technology transfer and application can be accelerated, cultural exchange and understanding can be promoted, and the sustainable development agenda for global rural areas can be jointly advanced.

In the current digital age, financial development has seen substantial shifts, particularly in buying and selling activities that are now facilitated by digital technology or electronic transactions (e-commerce), which offer convenience at relatively low costs. However, micro, small, and medium enterprises (MSMEs), which play a crucial role in the economy, must adapt to these advancements to sustain and grow their businesses. Despite the widespread adoption of e-commerce, many MSMEs have yet to fully capitalize on this technology. Limited knowledge often leads to hesitation in embracing e-commerce opportunities. Consequently, this study seeks to explore how innovation, information management, and e-commerce adoption impact MSME performance and its implications for business sustainability. The research targets MSME owners and managers in the Jabodetabek area (Jakarta, Bogor, Depok, Tangerang, and Bekasi) and nearby regions, with a sample of 420 individuals selected through random sampling. Data was collected through an online survey (Google Forms) administered to MSME management. The survey items were tested for validity and reliability, and the data analysis was conducted using various regression analyses with SEM-PLS and Smart-PLS3. The study’s findings highlight the following key points: 1) E-commerce adoption significantly enhances information management, which supports MSME sustainability; 2) E-commerce adoption also improves performance through better information management, further promoting MSME sustainability; 3) While technology is important, e-commerce adoption is the primary factor driving MSME sustainability, with technology serving as a secondary factor.

This paper is the third in a series focused on bridging the gap between secondary and higher education. Our primary objective is to develop a robust theoretical framework for an innovative e-business model called the Undergraduate Study Programme Search System (USPSS). This system considers multiple criteria to reduce the likelihood of exam failure or the need for multiple retakes, while maximizing the chances of successful program completion. Testing of the proposed algorithm demonstrated that the Stochastic Gradient Boosted Regression Trees method outperforms the current method used in Lithuania for admitting applicants to 47 educational programs. Specifically, it is more accurate than the Probabilistic Neural Network for 25 programs, the Ensemble of Regression Trees for 24 programs, the Single Regression Tree for 18 programs, the Random Forest Regression for 16 programs, the Bayesian Additive Regression Trees for 13 programs, and the Regression by Discretization for 10 programs.