Purpose: We introduce decision support tools aimed at optimizing perishable food supply chain management, effectively balancing conflicting objectives such as the exporter’s product collection cost and the importer’s profit. This involves considering factors like perishability, selling price, discount rate, and order quantity to achieve optimal outcomes.Design/methodology/approach: This study considered a three-echelon supply chain comprising farmers, a single exporter, and a single importer providing a single, random-lifetime, perishable product under deterministic customer demand. The proposed mathematical model derived the optimal order quantity, selling price, and discount rate for the entire supply chain. This integrated optimization model treats both demand and supply sides as a multi-objective problem, employing a nonlinear program and a two-stage capacitated vehicle routing problem formulation. Numerical examples and a case study focusing on Thailand durian supply chain were conducted to illustrate the approach of the proposed model.Findings: Taking into account both the importer’s profit and the exporter’s product collection cost, the proposed integrated supply chain model and tools maximize profitability, minimizes waste, and meets demand by optimizing perishable product collection costs and proposing a discount system for selling prices.Research limitations/implications: Limited to a single perishable product in a three-echelon international food supply chain. Future research can explore different products and supply chain contexts.Practical implications: The tools enhance decision-making for supply chain managers, improving efficiency, reducing costs, and enhancing customer satisfaction in the perishable food industry.Social implications: The proposed model aids in local workforce management by forecasting required manpower for upcoming seasons. By factoring in product quality and pricing, it ensures customers receive fresh products at fair prices. Furthermore, the near-zero waste concept enhances storage conditions at importers' facilities, contributing to improved environmental hygiene.Originality/value: The integrated model and decision support tools offer a novel approach to address complexities and conflicting objectives in perishable food supply chains, providing practical insights for researchers and practitioners.

This research focuses on the development of an island recycle waste management system to address challenges in managing waste transportation and recycling data on islands in Thailand. The system was designed to support digital data recording, including waste types and quantities, transportation costs, and the real-time uploading of verification evidence to a centralized database. The study applies a mixed-methods approach that integrates a TAM-based quantitative analysis with a qualitative user. The study applied the technology acceptance model (TAM) to analyze user satisfaction regarding perceived usefulness (PU) and perceived ease of use (PEOU). Data collected from participating shops on target islands were analyzed to evaluate system acceptance, which was found to be moderate to high. The system shows indications of reducing errors; however, objective error-rate comparisons were not collected and are now acknowledged as a limitation. The system streamlined processes and enhanced data management efficiency, although some users encountered issues such as menu complexity and unfamiliarity with technology. Proposed enhancements include adding features tailored to elderly shop owners, integrating image processing technology to support document scanning, developing multimedia user guides, and organizing hands-on training sessions as part of the intervention rather than recommendations alone. This study aims to promote sustainable waste management on islands and to refine the system to better suit diverse user contexts. It also serves as a prototype for future system development.

Ambulance response time is a critical factor in saving lives and is heavily influenced by ambulance placement strategies. Currently, Nang Lae Subdistrict is served by only one ambulance, yet the managing agency does not systematically analyze high-frequency accident zones or areas with frequent emergency calls. This oversight raises concerns about whether the current ambulance station provides optimal coverage. To address this, call data from all ambulance dispatches over four months (July–November 2023) were analyzed. The findings revealed 96 cases within a 5-kilometer radius of Nang Lae Subdistrict Municipality and 18 cases within a 10-kilometer radius. Cluster analysis was conducted to determine optimal ambulance placement, identifying two potential locations approximately 1.55 km apart. These results can inform strategic improvements in ambulance deployment, particularly during high-demand periods such as festivals, where accident rates surge and faster response times are crucial. Additionally, the study observed instances of ambulances servicing areas beyond their designated zones, suggesting a need for better resource allocation.