Maghsoud Amiri; Seyyed Habibullah Rahmati; Masoud Taheri
Abstract
Supplier selection is a key issue in supply chain management. Today’s intense competition has forced organizations to adopt effective improvement paradigms, including lean, agile, green, resilient, and sustainable (LARGS). Integrating fuzzy logic with multi-criteria decision-making models enables ...
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Supplier selection is a key issue in supply chain management. Today’s intense competition has forced organizations to adopt effective improvement paradigms, including lean, agile, green, resilient, and sustainable (LARGS). Integrating fuzzy logic with multi-criteria decision-making models enables accurate responses to both qualitative and quantitative uncertainties. This study aims to evaluate and rank suppliers within the LARGS supply chain of the Firooz Hygienic Group. The research is qualitative–quantitative, inductive, and applied. Ten supply chain experts from the Firooz Group were selected through purposive sampling. Since decision-making involves risk and uncertainty, the Mamdani fuzzy inference system was applied, modeling each paradigm’s criteria with triangular membership functions. To optimize the rule structure, 42 effective and non-redundant rules were selected from 243 initial rules based on strength and coverage indices, reducing model complexity and improving inference accuracy. These final rules were combined with the Fuzzy TOPSIS method to rank suppliers.Results showed the performance ranking as follows: S7 > S5 > S1 > S6 > S8 > S3 > S2 > S4. Suppliers performed better in “agility” and “sustainability” and weaker in “resilience,” reflecting the current focus of the supply market in the detergent industry. The findings can assist supply chain managers in improving key LARGS indicators. Moreover, the proposed model can be adapted to other industries and service sectors by adjusting evaluation criteria and input variables according to operational conditions. Industry-specific calibration of variables, rules, and weighting schemes ensures model validity and decision accuracy across different contexts.
Asma Bakhtiari Tavana; Maghsoud Amiri; Amir Yousefli; Mohammad Taghi Taghavifard
Abstract
The transportation of biological specimens constitutes a challenging routing problem in healthcare logistics. Due to the perishable nature of specimens, adherence to transportation requirements regarding time, temperature, and physical conditions is essential. This problem focuses on route planning and ...
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The transportation of biological specimens constitutes a challenging routing problem in healthcare logistics. Due to the perishable nature of specimens, adherence to transportation requirements regarding time, temperature, and physical conditions is essential. This problem focuses on route planning and scheduling for the collection and transfer of specimens in the shortest possible time without compromising their quality. Despite the critical importance of this issue in healthcare systems and the publication of numerous studies, no systematic review has yet been conducted to provide a comprehensive overview of the current state of prior research. The present study, adopting a systematic literature review approach, seeks to identify, classify, and analyze the existing body of research to highlight research gaps and underexplored topics. Accordingly, after the design of a search protocol, retrieval, and screening of articles, 32 articles were finally selected and analyzed. The findings revealed that the development of dynamic and multi-objective models, the utilization of real-time decision-making, the broader application of innovative technologies such as drones, the Internet of Things, blockchain, and big data analytics, as well as the incorporation of machine learning algorithms, are among the most significant fields that could accelerate research progress in the field of routing and scheduling for biological specimen transportation. By mapping the current state and identifying research gaps, this systematic review provides a sound scientific foundation for future studies and for enhancing the efficiency of biological specimen transportation networks.
Aida Fallahpour Mobaraki; Mostafa Ebrahimpour Azbari; Maghsoud Amiri; keikhosro Yakideh
Abstract
The catch-up process plays a fundamental role in empowering companies and industries in a country to reduce the gap with global leaders. This study was conducted with the aim of designing and presenting a catch-up model for Iran's pharmaceutical industry. In terms of objective, this study is applied ...
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The catch-up process plays a fundamental role in empowering companies and industries in a country to reduce the gap with global leaders. This study was conducted with the aim of designing and presenting a catch-up model for Iran's pharmaceutical industry. In terms of objective, this study is applied research, while methodologically, it adopts a qualitative approach. Data were collected through literature review and semi-structured interviews with 15 experts from the pharmaceutical industry using snowball sampling technique. After integrating and synthesizing similar themes, the findings revealed 3 global themes (governance and policy-making, organizational requirements, and industrial network requirements), 9 organizing themes (supportive and developmental policies, regulation of laws and policies, governance risks and constraints, learning and knowledge absorption, production and product empowerment, organizational management and resources, market strategies and drivers, collaboration and interactions in industry, and industry infrastructure and environment), and 51 basic themes. Furthermore, to assess the reliability and validity of the research, Holsti's coefficient of 0.987 was obtained. Finally, the catch-up thematic network of Iran's pharmaceutical industry was presented. The results of this research can clarify the path for formulating effective and strategic policies and programs aimed at reducing the gap with industry frontrunners and developing pharmaceutical companies.
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