Search Results (4)

Background: The transition from linear to circular supply chains (CSC) is critical for advancing sustainability, resilience, and resource efficiency, while supporting the UN Sustainable Development Goals (SDGs). However, existing studies rarely integrate internal operational performance with external PESTEL factors under the Benefits, Opportunities, Costs, and Risks (BOCR) perspective, limiting the ability to prioritize circular strategies holistically. Methods: This study develops a decision-making framework that combines the Best-Worst Method (BWM) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS), enabling reliable prioritization of interdependent sustainability criteria. Results: A case analysis in the chemical industry demonstrates the applicability of the framework, enhancing transparency and reducing subjectivity in CSC evaluation. Findings highlight quality as the key operational attribute and social as the dominant PESTEL dimension, reinforcing the integration of internal and external factors toward SDG-oriented strategies. Conclusions: The study contributes theoretically by bridging operational and contextual dimensions in CSC evaluation under the BOCR perspective, and methodologically by advancing hybrid MCDM applications to address uncertainty. Managerially, the framework provides a structured tool for aligning circular supply chain strategies with organizational objectives and SDGs, supporting decision-making that strengthens environmental sustainability, stakeholder legitimacy, and resilience. Full article

Background/Objectives: The COVID-19 pandemic underscored the need for adaptive public health strategies and effective decision-making tools to optimize clinical responses and policy measures based on regional contexts. This study aims to identify key criteria for developing a patient-centered strategy to enhance the resilience of Romania’s healthcare system during the pandemic. Methods: This research introduces a Multi-Criteria Decision Analysis (MCDA) model using the Simple Multiple Attribute Assessment Technique (SMART) to integrate quantitative and qualitative data, providing decision-makers with a structured tool for improving healthcare resilience. A survey of 412 Romanian healthcare professionals identified critical risks and opportunities. The study followed a two-phase approach: first, analyzing expert perceptions to determine key challenges; second, applying a mixed-methods evaluation to prioritize resilience-building strategies. Results: Four main challenges emerged: (1) healthcare workforce shortages causing excessive workload and stress, (2) poor communication and systemic inefficiencies limiting patient access, (3) weak crisis management due to delayed control measures, and (4) regulatory gaps leading to fragmented responses. Proposed solutions included workforce training, improved communication, telemedicine integration, increased financial support, and a unified legal framework. The SMART method facilitated the structured prioritization of these measures, with long-term system sustainability emerging as the most effective strategy for preventing future crises. Conclusions: This study demonstrates the value of integrating MCDA into healthcare decision-making, offering a scalable model for policymakers to enhance crisis response and resource allocation. By incorporating expert insights and patient needs, the proposed framework strengthens healthcare system preparedness, contributing to informed, patient-centered decision-making and long-term resilience. Ultimately, our findings not only contribute to the existing literature but may also open new directions to facilitate informed, patient-centered decision making, thereby strengthening the resilience of healthcare systems in crisis situations. Full article

With rising electricity prices, industries are trying to exploit opportunities to reduce electricity costs. Adapting to fluctuating energy prices offers the possibility to save electricity costs without reducing the performance of the production system. Production planning and control play key roles in the implementation of the adjustments. By taking into account the price forecasts for the electricity markets in addition to machine utilization, work in process, and throughput time, an energy-oriented production plan is set up. The electrical energy is procured based on this plan and the associated load profile. Deviations from the forecast and the purchased amount of electricity lead to high penalties, as they can destabilize the energy system. For manufacturing companies, this means that machine failures and other unexpected events must be dealt with in a structured manner to avoid these penalty costs. This paper presents an approach to selecting, classifying, and integrating suitable measures from existing risk treatment paths into the production schedule. The selection of measures is based on a hybrid multi-criteria decision-making method in which the three relevant criteria, namely, cost, energy flexibility, and risk reduction, are weighted by applying both an analytic hierarchy process and entropy, and they are then prioritized according to multi-attribute utility theory. In the following, the subdivision into preventive and reactive measures is made in order to choose between the modification of the original plan or the creation of backup plans. With the help of mathematical optimization, the measures are integrated into the production schedule by minimizing the cost of balancing energy. The approach was implemented in MATLAB^® and validated using a case study in the foundry industry. Full article

The most critical decisions usually involve several decision makers with different roles and opportunities to commit key resources. Several group decision-making (GDM) approaches can support the identification of a joint or compromise decision in less conflicting settings, where there is a group of subjects (e.g’, partners) who pursue a common overall objective. However, considering the uncertainty in future events and complexity of modern-day systems, decision processes do not always produce beneficial results or give the participants a positive perception of their role in the process. Group decision-making should then take into consideration some aspects that might insure future resilience and sustainability, particularly the achievement of the objectives in view of future risks and the transparency and participation that are needed to limit problems in the implementation phase of the decision. The literature survey presented in this study identified a research gap regarding GDM. Differently from traditional GDM, which was first discussed in the early 1980s and whose body of knowledge is pretty defined, resilient and sustainable GDM (R&S GDM) is fairly new. The main objective of this study is then identifying the main attributes for supporting sustainable and resilient group decisions. To this aim, a preliminary focused systematic review was conducted to study the existing group decision-making methods in the literature and how the concepts of sustainability and resilience have been employed. After defining the search keywords and exclusion criteria for the individuation of the articles, the first screening process was carried out and the most relevant articles were selected. The last steps of the systematic review were the classification of the articles and the full paper examination to extract the main factors of R&S GDM. Seven attributes were listed as the key factors of R&S GDM. In light of those factors, a group decision process concerning an injection moulding line in Tajikistan was investigated. The case study highlighted that over self-confidence, information flow and transparency were the main reasons for faulty decisions, thus suggesting that information system and information fluidity play an important role in R&S GDM. Finally, the most important managerial implications of R&S GDM are reported. Full article