The research aims to examine the antecedents of Fintech Peer-to-Peer (P2P) lending adoption in Indonesia by extending the UTAUT3 framework with financial risk tolerance and artificial intelligence literacy. It also explores the moderating role of green self-identity and gender differences in P2P lending adoption. Data were collected from 421 respondents in Indonesia using a non-probability voluntary response sampling approach and analyzed using the PLS-SEM method. The results indicate that performance expectancy, effort expectancy, social influence, and AI literacy have a positive and significant influence on behavioral intention toward P2P lending. Facilitating conditions positively and significantly affect use behavior. Green self-identity weakens the relationship between behavioral intention and use behavior. No significant gender differences were found in the correlations between behavioral intention, use behavior, and financial inclusion. This study advances the literature on financial innovation by bridging theory and practice in the context of AI-enabled Fintech P2P lending. By integrating empirical evidence with policy considerations, the findings highlight the importance of collaboration between regulators and Fintech providers in fostering responsible innovation. The results provide actionable implications for designing user-centered lending systems that enhance financial inclusion. In this regard, the study contributes to the advancement of inclusive digital finance and supports Indonesia’s broader strategic objective of expanding sustainable and equitable access to financial services.
The shift towards sustainability in European manufacturing has garnered heightened interest due to urgent environmental issues and the changing regulatory landscape established by the European Union. This systematic literature review, based on the PRISMA 2020 framework, examines the strategies employed by European manufacturing industries as they pursue digital and circular transformation pathways to enhance sustainability. By examining peer-reviewed articles published between 2013 and 2024, this research consolidates evidence from specific sources found in Scopus and Web of Science, enhanced by a compilation of 50 rigorous academic studies. Important themes highlight the fusion of Industry 4.0 and 5.0 technologies, the adoption of circular economy concepts, the facilitation of green finance, incentives shaped by policy, and the distinct challenges encountered in sectors like textiles, food supply, automotive, and urban smart manufacturing. The analysis shows that even though digital and circular strategies hold great promise for enhancing sustainability, their practical application is restricted by technological, financial, and organisational issues. The study argues that sustainability transitions are socio-technical processes requiring coherent policy mixes and capacity-building. In its conclusion, the paper offers recommendations for both research and policy, emphasising the crucial need for cohesive transition models, collaborative networks, urban production paradigms, and infrastructures that support small and medium-sized enterprises (SMEs).
Our research project aims to integrate inferential statistics into the Hungarian secondary school curriculum. Between 2019 and 2023, we developed and tested an experimental curriculum incorporating simulations and Excel-based calculations. This approach addresses broader challenges in understanding statistical inference and presents our strategies for designing an experimental seminar for in-service teachers. The underlying principles of the curriculum are inspired by Complex Mathematics Education, a long-term initiative rooted in the ideas of Tamás Varga. Using a pre-post-test design and semi-structured teacher interviews, we evaluated the curriculum’s feasibility. Feedback indicates that our revised approach and materials align well with the current Hungarian curriculum reform. Findings across the project’s phases suggest that, with adequate technical support and sufficient practice tasks, even complex statistical concepts can be successfully taught to beginners. This approach supports diverse learner profiles and accommodates varying levels of prior knowledge and ability across schools. The article presents key insights from our teacher-training efforts over three phases, involving a total of 32 educators.
A key issue in decision problems is the selection and use of the appropriate response scale. In this paper verbal expressions are converted into numerical scales for a subjective problem instance. In our experiment, we conducted a color selection test with 462 subjects by testing six colors on color-calibrated tablets in ISO standardized sensory test booths. The colors were evaluated both in a pairwise comparison matrix (indirect ranking with four-item verbal category scale) and on a direct scoring basis. We determined scales that provide the closest results on average and individually to the direct scoring, based on the eigenvector and the logarithmic least squares methods. All results show that the difference between verbal expressions is much smaller than the one used by most of the common numerical scales. As a sensitivity analysis, different discrepancy measures were investigated, and further experiments were also carried out. All the main findings were confirmed to be robust regarding the weight calculation technique, the discrepancy measure, and the problem instance as well. The results suggest that several methods (e.g., the AHP, and different ISO standards) need substantial revision. The respondents’ inconsistency was also analyzed with a repeated question regarding their preference between a given pair of colors. It is shown that most decision makers answer similarly for the second time, but there can be significant (even ordinal) differences. The respondents whose answers are further from the original tend to be more inconsistent in general.
The advancement of controlled environment agriculture (CEA) has amplified the importance of light quality in crop production, particularly for high-value horticultural crops like tomato (Solanum lycopersicum L.). The central research question is to analyse tomato targeted LED light settings focusing on seedling production, plant production and protection, nutritional value, tomato-specific light measurement, design, application, recommendations for growers, and future perspectives. This review synthesizes the latest technological developments in LED grow light applications for tomato cultivation, with a focus on light quality (spectral composition), light quantity (intensity), and light timing (photoperiod). In tomato cultivation, light intensity typically ranges from 200 to 400 mu mol center dot m-2 center dot s-1 with a 16-20 h photoperiod, supporting healthy early growth, while lower levels from 100 to 150 mu mol center dot m-2 center dot s-1 can sustain photosynthesis during seedling grafting. With an 18 h photoperiod, adding 2 h of night lighting further improved seedling health, biomass, and root activity. Emphasis is placed on how these parameters influence physiological processes and the accumulation of phytonutrients, while also addressing promising lighting strategies with roles in plant protection and post-harvest optimization. The highest lycopene and beta-carotene levels were obtained under a B:G:R ratio of 58:30:12 (460, 525, 630 nm) at 150 & micro;mol center dot m-2 center dot s-1. Blue light from 405 to 462 nm limits Botrytis spoilage, and UV-A/UV-C suppress Fusarium, Oidium, Penicillium. Key aspects of light design, monitoring, and measurement are also discussed, with emphasis on fresh tomato production. The most important light factors in different growing stages of tomato were identified. Coherences of light spectra, intensity, duration, LED-plant placement (geometry) and homogeneity aspects with productionbiological traits in fresh tomato CEA experiments were summarized. Plant protection LED applications were explored in depth. Future trends related to tomato CEA production driven by networked sensor systems (internet of things, IoT) based automated systems are discussed as well. Finally, LED light specific recommendations were proposed for tomato growers and consultants.
