Browsing by Author "Damavandi, Sara"

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Decision Support System Using Rough DEMATEL for Evaluating Blockchain Adoption in Food Bank Supply Chain
(Elsevier Sci Ltd, 2026) Abbasi, Sina; Berardi, Laura; Damavandi, Sara
Food banks (FBs) play a vital role in food security by recovering surplus food and redistributing it to people who lack reliable access to sufficient nutrition. However, FBs face persistent operational challenges, particularly in balancing supply and demand. This study presents a novel approach to examining blockchain technology (BT) adoption within the food bank supply chain (FBSC) to boost food donation efficiency, enabling real-time inventory tracking, reliability, and strengthening compliance with food safety regulations. We identified the key barriers, categorized them into external and internal dimensions, and analyzed them using a pairwise comparison survey based on insights from academics and experts (N = 21) within the food bank network (FBN). The decision-making trial and evaluation laboratory (DEMATEL) methodology was used to model and quantify the causal relationships among these barriers. To address subjectivity and ambiguity in expert opinions during group decision-making, rough theory was integrated with DEMATEL, providing a reliable approach to managing conflicting perspectives and uncertainty. Results indicate that the lack of access to technology is the most significant barrier hindering the implementation and growth of blockchain adoption in FBSC. Also, the lack of regulation and legislation related to donated food was assigned the minimum normalized weight, indicating it has the least influence on the system. Further, a lack of government support for implementing BT represents another critical barrier, reflecting the early stage of BT development. The study offers valuable insights to support FBs and policymakers in developing long-term sustainability strategies.
Citation - WoS: 10
Citation - Scopus: 9
Designing a green forward and reverse logistics network with an IoT approach considering backup suppliers and special disposal for epidemics management
(ELSEVIER, 2025) Sina Abbasi; Sara Damavandi; Amirhossein Radmankian; Kian Zeinolabedinzadeh; Yigit Kazancoglu; Zeinolabedinzadeh, Kian; Damavandi, Sara; Abbasi, Sina; RadmanKian, Amirhossein; Kazancoglu, Yigit
This paper proposes a mathematical model for the green forward and reverse logistics network (LN) examining the impact of epidemics such as coronavirus (COVID-19) and human metapneumovirus (HMPV) on this network. Alongside managing the network a new support center and dedicated infectious waste recycling and disposal facilities have been established. A mixed-integer linear programming (MOMILP) approach is employed for modeling a green forward and reverse LN during epidemics. This study presents two problem-solving techniques: the LP-metric method for small problems and the whale optimization algorithm (WOA) for medium and largescale issues. The positive and negative effects of epidemics on environmental and economic aspects of the objective functions were assessed. This study's contribution and novelty compared to previous research lie in the introduction of backup supply centers particularly waste disposal centers and the comparison of normal and epidemic conditions for disaster management using the IoT approach.