In the last few decades, humans have consumed more resources than in all of previous history. Hence, we are living in times in which the topic of environmental protection is a global concern. The paper aims to conduct a systematic literature review on consumer behavior, as well as identifying the main factors that interfere with consumer behavior toward green products. A total of 37 studies were found and systematized using inclusion and exclusion criteria. The papers were selected only if they featured research on consumer perceptions of green products. Using this search strategy, a literature analysis was performed based on papers extracted from Web of Science, Emerald Insights, Springer Link, and Science Direct. As a result, various factors that influence consumer behavior toward green products were identified, such as social norms, natural environmental orientation, the company’s perceived green image, green product characteristics, perceived risks and inconvenience of buying green products, perceived benefits of buying green products, institutional trust, sociodemographic characteristics, and consumer confidence. Even though completing a systematic literature review is not something new in academic research, the novelty of this paper is found in its theme: consumer behavior toward green products. Although the analyzed articles highlight quite varied reasons, the articles emphasize that the green products should take into account the needs, expectations, and perceptions of customers.

Water contamination, particularly by heavy metals originating from industrial processes, presents a significant threat to environmental sustainability and socio-economic development. Activated carbon (AC) has garnered considerable attention as a treatment due to its exceptional adsorption properties, characterized by a high surface area (273–827 m²/g), significant total pore volumes (0.27–0.69 ml/g), and well-defined micropores (8.2–12.4 nm), alongside tunable surface chemistry. Research efforts have focused on enhancing the synthesis, activation, and modification of AC to optimize its effectiveness in heavy metal removal from water. Studies consistently demonstrate that modified AC exhibits promising adsorption kinetics, often fitting well with Langmuir and pseudo-second-order physical adsorption models. Moreover, the economic viability of modified AC is underscored by its non-toxic nature, affordability, and sustainability. Experimental investigations reveal that AC can achieve substantial heavy metal removal efficiencies, ranging from 75 to 96%, contingent upon factors such as dosage, solution pH, surface properties, and contaminant concentrations. Despite advancements, widespread adoption of AC-based water treatment technologies remains largely confined to industrial settings. Key research priorities include the development of cost-effective and scalable synthesis methods for AC, particularly utilizing non-biodegradable feedstocks. Additionally, there is a pressing need for comprehensive studies assessing the efficacy of AC in real-world wastewater treatment scenarios. This review critically examines the role of AC in water treatment technologies, highlighting research gaps and delineating future research directions to advance sustainable and efficient water purification strategies.

The logistics landscape in e-commerce is undergoing a profound transformation toward sustainability and autonomy. This paper explores the implementation of autonomous maritime and last-mile transportation solutions to optimize the entire logistics chain from factory to customer. Building on the lessons learned from the maritime industry’s digital transformation, the study identifies key features and proposes a forward-looking autonomous maritime and last-mile transportation system. Emphasizing the role of geospatial technologies, the proposed system employs GIS-based electronic route optimization for efficient goods delivery, integrating onboard and ashore GIS-based sensors for enhanced location precision. A case study was built to analyze the implementation of autonomous means of transport along the route of a product from factory to customer. The integration of autonomous systems shows substantial improvements in logistics performance. Synchromodal logistics and smart steaming techniques can be utilized to optimize transportation routes, resulting in reduced fuel consumption and emissions. The findings reveal that autonomous maritime and last-mile transport systems can significantly enhance the efficiency, flexibility and sustainability of e-commerce logistics. The study emphasizes the need for advanced technological integration and provides a comprehensive framework for future research and practical applications in the logistics industry.

Use of the geospatial technologies and its implications in the maritime transport and logistics

The integration of AI tools like ChatGPT in education has sparked debates on their benefits and limitations, particularly in subjects requiring region-specific knowledge. This study examines ChatGPT’s ability to generate accurate and contextually rich responses to assignments in Romanian history and geography, focusing on topics with limited digital representation. Using a document-based analysis, this study compared ChatGPT’s responses to local archival sources, monographs, and topographical maps, assessing coverage, accuracy, and local nuances. Findings indicate significant factual inaccuracies, including misidentified Dacian tribes, incorrect historical sources, and geographic errors such as misplaced landmarks, elevation discrepancies, and incorrect infrastructure details. ChatGPT’s reliance on widely digitized sources led to omissions of localized details, highlighting a fundamental limitation when applied to non-digitized historical and geographic topics. These results suggest that while ChatGPT can be a useful supplementary tool, its outputs require careful verification by educators to prevent misinformation. Future research should explore strategies to improve AI-generated educational content, including better integration of regional archives and AI literacy training for students and teachers. The study underscores the need for hybrid AI-human approaches in education, ensuring that AI-generated text complements rather than replaces verified academic sources.

The electrical conductivity and dielectric characteristics were investigated across a frequency range of 200–5 MHz and a temperature range of 318 K to 433K for MgTi ₂ O ₅ nanoparticles (NPs). The electrical conductivity data displayed two dominant conduction mechanisms: a quantum mechanical tunneling model (QMT) and the correlated barrier hopping model (CBH). The activation energy values derived from the Direct Current (DC) Conductivity were 0.15 and 0.27 eV. In addition, the activation energy values derived from the Alternating Current (AC) Conductivity decreased as frequency increased from 0.13 to 0.014 eV due to the improvement of electronic jumps among localized states. Additionally, dielectric investigation of MgTi ₂ O ₅ NPs within the frequency range from (200 – 5 MHz) and the temperature range from (318K–433K) revealed that both real (ε ₁ ) and imaginary (ε ₂ ) components of a dielectric permittivity decrease as the frequency increased and increased as a temperature increased due to thermal motion of electrons, which is related to the polarization mechanism.