This study investigates the impact of toll road construction on 59 micro, small, and medium enterprises in Kampar, Pekanbaru, and Dumai cities. The research aims to analyze the economic and environmental effects of infrastructure expansion on businesses’ profitability and sustainability, providing insights for policymakers and stakeholders to develop mitigation strategies to support MSMEs amidst ongoing infrastructure development. Structural equation modeling, spatial environmental impact analysis, and qualitative data analysis using five-level qualitative data analysis (FL-QDA) were all used together in a mixed-methods approach. Data collection involved observations, interviews, questionnaires, and geospatial analysis, including the use of a Geo-Information System (GIS) supported by drone reconnaissance to map affected areas. The study revealed that the toll roads significantly enhanced connectivity and economic growth but also negatively impacted local economies (β = 0.32, R² = 0.60, P-value ≤ 0.05). and the environment (β = 0.34, P-value ≤ 0.05), as 49% of respondents experienced a 50% decrease in profitability. To mitigate the risk of impact, policymakers should prioritize the principle of prudence to evaluate the significance of mitigation policy implementation (β = 0.144, P-value ≥ 0.05). In a nutshell, toll road construction significantly impacts MSMEs’ business continuity, necessitating an innovative strategy involving monitoring and participatory approaches to mitigate risk.

This research explores the dynamic intersection of sustainable design, cultural heritage, and community enterprise, focusing on the innovative utilization of post-harvest sugar cane leaves in bamboo basketry production from various provinces in Thailand. This study aims to investigate how design anthropology principles can enhance community enterprises’ resilience and sustainability by employing a qualitative case study approach. Findings reveal that while traditional bamboo basketry reflects the region’s rich cultural heritage, a shift towards sustainable practices offers environmental benefits and economic opportunities. Design anthropology informs the development of culturally relevant products, fostering market competitiveness and preserving traditional craftsmanship. Moreover, government policies play a pivotal role in supporting or hindering the growth of community enterprises, with soft power initiatives holding promise for promoting cultural heritage and sustainability. Collaboration between policymakers, design anthropologists, and local stakeholders is essential for developing inclusive policies that empower communities and foster sustainable development. Overall, integrating sustainable design practices and cultural insights holds significant potential for enhancing the resilience and effectiveness of community enterprises, ensuring a prosperous and sustainable future for both the industry and the communities it serves. This study is a testament that design anthropology provides a powerful framework for addressing complex social and environmental issues through the lenses of culture and design.

Rambutan (Nephelium lappaceum L.) was introduced to Mexico in 1959. Currently there is an estimated planted area of 835.96 ha and a production of 8,730.27 tons. The fruit is mainly consumed fresh, but quickly loses its external appearance due to dehydration and browning, which limits its commercialization, an alternative may be minimal processing and adjuvant treatments that extend the shelf life. The objective of this work was to evaluate the effect of coating with cactus mucilage (Opuntia ficus-indica), in the preservation of minimally processed rambutan stored at 5 °C, in two types of packaging. The rambutan was sanitized with chlorinated water (80 ppm), the epicarp was removed and batches were formed for each treatment. The factors were type of container (polyethylene bag and polystyrene container), coating (with and without coating) and time (0, 3, 6, 6, 10 and 12 d). The coating consisted of mucilage obtained from developing cladodes (15–21 cm), applied by dipping. All treatments were stored at 5 ℃. Total soluble solids (TSS), firmness (N) and color (L*, a*, b*, chroma and hue angle) were evaluated at each storage period. Also, 40 untrained judges (47% male and 53% female) evaluated sensory acceptability, consumption intention and acceptance/rejection. The results showed significant effect (p ≤ 0.05) of package type on firmness, chroma and hue angle. Coating had an effect on L* value and product acceptability. Consumption intention was higher, and was maintained for 10 days, in fruits with coating and packaged in polyethylene bags, stored at 5 ℃.

In the Fourth Industrial Revolution (4IR) era, the rapid digitalisation of services poses both opportunities and challenges for the banking sector. This study addresses how adopting artificial intelligence (AI) and online and mobile banking advancements can influence customer satisfaction, particularly in Kaduna State, Nigeria. Despite significant investments in AI and digital banking technologies, banks often struggle to align these innovations with customer expectations and satisfaction. Using Structural Equation Modeling (SEM), this research investigates the impact of customer satisfaction with online banking (C_O) on AI integration (I_A) and mobile banking convenience (C_M). The SEM model reveals that customer satisfaction with online banking significantly influences AI integration (path coefficient of 0.40) and mobile banking convenience (path coefficient of 0.68). These results highlight a crucial problem: while technological advancements in banking are growing, their effectiveness is highly dependent on customer satisfaction with existing digital services. The study underscores the need for banks to prioritise enhancing online banking experiences as a strategic lever to improve AI integration and mobile banking convenience. Consequently, the research recommends that Nigerian banks develop comprehensive frameworks to evaluate and optimise their technology integration strategies, ensuring that technological innovations align with customer needs and expectations in the rapidly evolving digital landscape.

The Oued Kert watershed in Morocco is essential for local biodiversity and agriculture, yet it faces significant challenges due to meteorological drought. This research addresses an urgent issue by aiming to understand the impacts of drought on vegetation, which is crucial for food security and water resource management. Despite previous studies on drought, there are significant gaps, including a lack of specific analyses on the seasonal effects of drought on vegetation in this under-researched region, as well as insufficient use of appropriate analytical tools to evaluate these relationships. We utilized the Standardized Precipitation Index (SPI) and the Normalized Difference Vegetation Index (NDVI) to analyze the relationship between precipitation and vegetation health. Our results reveal a very strong correlation between SPI and NDVI in spring (98%) and summer (97%), while correlations in winter and autumn are weaker (66% and 55%). These findings can guide policymakers in developing appropriate strategies and contribute to crop planning and land management. Furthermore, this study could serve as a foundation for awareness and education initiatives on the sustainable management of water and land resources, thereby enhancing the resilience of local ecosystems in the face of environmental challenges.

The major goal of decisions made by a business organization is to enhance business performance. These days, owners, managers and other stakeholders are seeking for opportunities of modelling and automating decisions by analysing the most recent data with the help of artificial intelligence (AI). This study outlines a simple theoretical model framework using internal and external information on current and potential clients and performing calculations followed by immediate updating of contracting probabilities after each sales attempt. This can help increase sales efficiency, revenues, and profits in an easily programmable way and serve as a basis for focusing on the most promising deals customising personal offers of best-selling products for each potential client. The search for new customers is supported by the continuous and systematic collection and analysis of external and internal statistical data, organising them into a unified database, and using a decision support model based on it. As an illustration, the paper presents a fictitious model setup and simulations for an insurance company considering different regions, age groups and genders of clients when analysing probabilities of contracting, average sales and profits per contract. The elements of the model, however, can be generalised or adjusted to any sector. Results show that dynamic targeting strategies based on model calculations and most current information outperform static or non-targeted actions. The process from data to decision-making to improve business performance and the decision itself can be easily algorithmised. The feedback of the results into the model carries the potential for automated self-learning and self-correction. The proposed framework can serve as a basis for a self-sustaining artificial business intelligence system.