ABSTRACT
This research attempts to study the Supplier Selection and Order Allocation Problem (SSOAP) considering three crucial concepts, namely responsiveness, sustainability, and resilience. To do so, the current research develops a Multi-Stage Decision-Making Framework (MSDMF) to select potential suppliers and determine the quantity of orders. The first stage aims at computing the scores of the suppliers based on several indicators. To do this, a novel decision-making approach named the Stochastic Fuzzy Best–Worst Method (SFBWM) is developed. Then, in the second stage, a Multi-Objective Model (MOM) is suggested to deal with supplier selection and order allocation decisions. In the next step, a data-driven Fuzzy Robust Stochastic (FRS) optimization approach, based on the fuzzy robust stochastic method and the Seasonal Autoregressive Integrated Moving Average (SARIMA) methods, is employed to efficiently treat the hybrid uncertainty of the problem. Afterwards, a novel solution method named the developed Chebyshev Multi-Choice Goal Programming with Utility Function (CMCGP-UF) is developed to obtain the optimal solution. Moreover, given the crucial role of the Medical Equipment (ME) industry in society's health, especially during the recent Coronavirus disease, this important industry is taken into account. The outcomes of the first stage demonstrate that agility, cost, GHG emission, quality, robustness, and Waste Management (WM), respectively, are the most important criteria. The outcomes of the second stage determine the selected suppliers, utilized transportation systems, and established sites. It is also revealed that demand directly affects all the objective functions while increasing the rate of disruptions has a negative effect on the sustainability measures.
ABSTRACT
Supplier selection is regarded as the primary goal of supply chain management (SCM) because it affects its performance, productivity, pleasure, flexibility, and system speed in lockdown. A new method is proposed based on a multi-stage fuzzy sustainable supplier index (FSSI). Experts can use the triple bottom line (TBL) criteria to select the best supplier. In addition, the worst method is proposed based on trapezoidal membership and fuzzy membership functions, which can cover uncertainties and ambiguous environments. Because it collects the related criteria and sub-criteria and uses a direct fuzzy methodology, this research has impacted the SCM literature because it helps solve previous expert methods' computational difficulties. In addition, an ordered mean integration representation method has been implemented to prioritize the selection of the best supplier (SS) based on the sustainability performance of the best supplier, which improves the selection accuracy compared to the previous ranking method. This study can be used as a benchmark to determine which supplier is the best in sustainability. To provide the superiority and broad applicability of the proposed model, a practical case study was completed. On the other hand, the COVID-19 pandemic harms productivity, company performance, and selecting the best suppliers based on sustainability performance. The lockdown situation caused by the COVID-19 pandemic hurts company performance and management.
Subject(s)
COVID-19 , Decision Making , Humans , Pandemics , Communicable Disease Control , UncertaintyABSTRACT
Since the COVID-19 outbreak has led to drastic changes in the business environment, researchers attempt to introduce new approaches to improve the capability and flexibility of the industries. In this regard, recently, the concept of the viable supply chain, which tried to incorporate the leagile, resiliency, sustainability, and digitalization aspects into the post-pandemic supply chain, has been introduced by researchers. However, the literature shows that there is lack of study that investigated the viable supplier selection problem, as one of the crucial branches of viable supply chain management. Therefore, to cover this gap, the current work aims to develop a decision-making framework to investigated the viable supplier selection problem. In this regard, owing to the crucial role of the oxygen concentrator device during the COVID-19 outbreak, this research selects the mentioned product as a case study. After determining the indicators and alternatives of the research problem, a novel method named goal programming-based fuzzy best-worst method (GP-FBWM) is proposed to compute the indicators' weights. Then, the potential alternatives are prioritized employing the Fuzzy Vlse Kriterijumsk Optimizacija Kompromisno Resenje method. In general, the main contributions and novelties of the present research are to incorporate the elements of the viability concepts in the supplier selection problem for the medical devices industry and to develop an efficient method GP-FBWM to measure the importance of the criteria. Then, the developed method is implemented and the obtained results are analyzed. Finally, managerial and theoretical implications are provided. Supplementary Information: The online version contains supplementary material available at 10.1007/s00500-022-07572-0.
ABSTRACT
COVID-19's developing trend has put the waste management systems of governments all over the world in jeopardy. The increasing rise of infectious medical waste has now become a serious problem. This paper presents a multi-period multi-objective model for designing a medical waste management system during the COVID-19 pandemic. The model aims to reduce total costs of infectious medical waste management while also reducing the environmental impact of treatment centers, disposal centers, and transportation. It also aims to maximize the suitability of treatment technology based on social considerations and reduce the risk associated with processing and transporting COVID-19 waste. Different strategic and operational decisions are taken into account that include the selection of treatment technologies, the location of treatment and disposal centers, the flow of generated medical waste between facilities, and the number of vehicles required for the medical waste transport. The model tackles the uncertainty associated with model parameters, and it uses a credibility-based possibilistic programming method to deal with uncertainties. The suggested model is solved using an interactive fuzzy programming method and the importance of social indicators for selecting treatment technology is determined using the fuzzy best-worst approach. The effectiveness of the model is demonstrated by a practical case study in Shiraz, Iran. The numerical results can help system designers to achieve the most suitable trade-off between the sustainability goals and the safety viewpoint.
ABSTRACT
During the COVID-19 pandemic, masks have become essential items for all people to protect themselves from the virus. Because of considering multiple factors when selecting an antivirus mask, the decision-making process has become more complicated. This paper proposes an integrated approach that uses F-BWM-RAFSI methods for antivirus mask selection process with respect to the COVID-19 pandemic. Finally, sensitivity analysis was demonstrated by evaluating the effects of changing the weight coefficients of the criterion on the ranking results, simulating changes in Heronian operator parameters, and comparing the obtained solution to other MCDM approaches to ensure its robustness. [ FROM AUTHOR] Copyright of Informatica is the property of IOS Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Today, the tourism industry is one of the most dynamic developing sectors of the world economy and an important factor in the social and economic development of regions and countries. It is known as one of the three first-class profitable industries in the world, which in order to expand and develop requires the cooperation and agreement of environmental, cultural, economic, political and social factors at the community level, in this regard, the phenomenon what has now negatively affected the tourism industry in Iran and the world is the Corona (Covid-19) crisis. This study suggests an infrastructure for determining the factors affecting health tourism. Therefore, the newest multi-criteria decision-making method, fuzzy best-worst method was used to calculate the relative importance of indices and Fuzzy evaluation based on distance from average solution technique was applied as a multi-attribute decision-making method to rank effective factors in health tourism. The statistical population of this research consists of directors and experts in the tourism industry Mazandaran. Based on the results of this study, improving the level of tourist security in the province ranks first among other options for the economy itself.
ABSTRACT
Ever-changing conditions and emerging new challenges affect the ability of the healthcare sector to survive with the current system, and to maintain its processes effectively. In the healthcare sector, the conservation of the natural resources is being obstructed by insufficient infrastructure for managing residual waste resulting from single-use medical materials, increased energy use, and its environmental burden. In this context, circularity and sustainability concepts have become essential in healthcare to meliorate the sector's negative impacts on the environment. The main aim of this study is to identify the barriers related to circular economy (CE) in the healthcare sector, apply big data analytics in healthcare, and provide solutions to these barriers. The contribution of this research is the detailed examination of the current healthcare literature about CE adaptation, and a proposal for a big data-enabled solutions framework to barriers to circularity, using fuzzy best-worst Method (BWM) and fuzzy VIKOR. Based on the findings, managerial, policy, and theoretical implementations are recommended to support sustainable development initiatives in the healthcare sector.