ABSTRACT
The global COVID-19 pandemic had a complex impact on the supply chain system. Manufacturing companies always strive to be able to face corporate competition and become superior with one of them through selecting the right supplier. Suppliers have the highest risk in a company, especially during the COVID-19 pandemic era, but with the correct selection of suppliers, the company can provide strength in global competition. The purpose of this research is to be able to solve the problem of sustainable supplier selection in a garment industry in Indonesia during the COVID-19 pandemic through the integration method between AHP and MOORA. AHP as a method that has been proven in many studies, in this study is used to determine the weight of each criterion. Furthermore, MOORA as a method that has good selectivity in choosing the best alternative will be used in the selection process. 12 criteria with 5 alternatives are used to determine the best supplier. The contribution of this research is the integration of the AHP and MOORA methods and the determination of important criteria in the era of the COVID-19 Pandemic. The results show that the criteria for the area with the level impact of COVID-19 (C12) have the greatest weight and supplier 3 becomes the first ranked supplier or the best supplier. The integration method between AHP and MOORA is easy to use and can choose the right sustainable supplier during the COVID-19 pandemic. © 2023 American Institute of Physics Inc.. All rights reserved.
ABSTRACT
The unprecedented outbreak of COVID-19 has left many multinational enterprises facing extremely severe supply disruptions. Besides considering triple-bottom-line requirements, managers now also have to consider supply disruption due to the pandemic more seriously. However, existing research does not take these two key objectives into account simultaneously. To bridge this research gap, based on the characteristics of COVID-19 and similar global emergency events, this article proposes a model that aims to solve the problem of sustainable supplier selection and order allocation considering supply disruption in the COVID-19 era. It does so by using a multi-stage multi-objective optimization model applied to the different stages of development and spread of the pandemic. Then, a novel nRa-NSGA-II algorithm is proposed to solve the high-dimensional multi-objective optimization model. The applicability and effectiveness of the proposed model is illustrated in a well-known multinational producer of shortwave therapeutic instruments.JEL Classification: M11
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
Investment in education technology (EdTech) is a complex decision problem for universities during the post-Covid era. With the objective to assess the quality and adoptability of education supply chain, a novel analytical evaluation model approach is proposed, based on quality function deployment and combinative distance-based assessment. To deal with uncertainty in the evaluation process, fuzzy theory is integrated into the model. To establish the house of quality matrix, technology-based stakeholders' requirements were identified and classified in four dimensions: economic and financial, technology adoption, sustainability, competencies. Moreover, nine supplier criteria were assumed. Based on expert evaluations, the results suggest that financial credit and supplier collaboration are the most prominent attributes to evaluate suppliers, while environmental commitment is sorted as the least important criterion. The results reveal that the three dominant suppliers, which provide the best response to the identified criteria, are providers of cloud service technology. © 2022
ABSTRACT
Investment in education technology (EdTech) is a complex decision problem for universities during the post-Covid era. With the objective to assess the quality and adoptability of education supply chain, a novel analytical evaluation model approach is proposed, based on quality function deployment and combinative distance-based assessment. To deal with uncertainty in the evaluation process, fuzzy theory is integrated into the model. To establish the house of quality matrix, technology-based stakeholders' requirements were identified and classified in four dimensions: economic and financial, technology adoption, sustainability, competencies. Moreover, nine supplier criteria were assumed. Based on expert evaluations, the results suggest that financial credit and supplier collaboration are the most prominent attributes to evaluate suppliers, while environmental commitment is sorted as the least important criterion. The results reveal that the three dominant suppliers, which provide the best response to the identified criteria, are providers of cloud service technology.
ABSTRACT
In the past ten years, sustainable supply chain management (SSCM) attach great importance due to consumers, for-profit and profitless organizations, laws and regulations to the social and corporate responsibilities of consumers, so it has been recognized by practitioners and scholars. Supplier selection, environmental effect like a lockdown, and social cooperation and other SSCM programs can play an important part in realizing the triple bottom line (TBL) of economic, environmental, social assistances. In supply chain management (SCM), the sustainable supplier selection (SSS) and firm performance plays an important role. Traditionally, when evaluating SSS performance, organizations will consider a new framework to obtain the overall criteria/sub-criteria of the sustainability index by encapsulating sustainability. In this paper 12 sub-criteria for 3 pillars of sustainability as economic, environment and social performance is collected. Although there are many articles on SSS and evaluation, so far, research on sustainability issues is very limited. This study endeavours to propose a fuzzy multi-criteria approach to discuss SSCM planning, and studies the issue of determining a current model for SSS in the supply chain during COVID-19 based on the TBL method. For express the linguistic value of the subjective preference of experts we use triangular fuzzy numbers. By using fuzzy numbers to find standard weights for qualitative performance evaluation, then fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is proposed to find the ranking of SSS. However, COVID-19 has a negative role in SSS and in firm performance. The situation of lockdown due to COVID-19 has a negative effect on the performance of the organizations. An example is given of the proposed method. © 2022, Politechnika Lubelska. All rights reserved.
ABSTRACT
Over the years, sustainable supplier selection (SSS) has become increasingly popular among scholars and practitioners as a viable means to actualize supply chain sustainability. Little, however, is known about the impact of the COVID-19 pandemic on sustainable supplier selection particularly in the manufacturing sector. In this paper, we present pandemic response strategies as a significant aspect of the COVID-19 pandemic's impact and investigate the relative importance of such strategies in SSS implementation. Drawing upon a rich data pool from the Nigerian manufacturing sector, we proposed an integrated multi-criteria decision making (MCDM) methodology to analyse the interrelationships between the COVID-19 pandemic response strategies and Triple-Bottom-Line (TBL) criteria for SSS. Our analysis shows that economic criteria and pandemic response strategies are the highest ranked in terms of relative importance and thereby pinpoints the need for manufacturing firms to emphasize such during SSS implementation in the COVID-19 pandemic. Specifically, quality, cost, use of personal protective equipment and use of information technologies for customer demand prediction are inferred as highly significant in SSS implementation in the COVID-19 pandemic era. Furthermore, the efficiency of the proposed methodology was validated by a comparative analysis with other MCDM methods. Therefore, this study presents implications on the significance of pandemic response strategies in SSS and thereby enriches literature on the COVID-19 pandemic's impact on supply chains.