Evaluating Barriers to Supply Chain Resilience in Vietnamese SMEs: The Fuzzy VIKOR Approach

This study aimed to determine and prioritize the critical barriers to supply chain resilience (SCR) in Vietnamese small and medium-size enterprises (SMEs), which play a crucial role in the global supply chain. Through a systematic literature review and expert consultation, 15 barriers to SCR were identified and evaluated by using the fuzzy VIKOR (ViseKriterijumska Optimizacija I Kompromisno Resenje) method. The findings provide novel insights into the challenges of enhancing resilience in the Vietnamese supply chain and categorize the barriers into three main categories: the resilience phase, strategy resilience, and the competencies required. The results indicated that a lack of financial resources and alternative sources of supply are the most pressing barriers related to the resilience phase group. In terms of strategy resilience, the lack of a skilled and competent workforce was found to be the most critical obstacle. Furthermore, government delays in supporting and enacting appropriate policies were found to be the most pressing issue related to the competencies required. These findings offer valuable recommendations for managers seeking to address these barriers and enhance the resilience of the Vietnamese supply chain after COVID-19. By prioritizing and solving these critical obstacles, Vietnamese SMEs can better prepare for and recover from potential challenges in the future. © 2023 by the authors.

Applications of XAI for Decision Making in the Manufacturing Domain

This chapter discusses an important topic in factory management, that of improving the understandability of AI applications for group multi-criteria decision making in manufacturing systems. Due to its long-term and cross-functional impact, decision making may be more critical to the competitiveness and sustainability of manufacturing systems than production planning and control. This chapter uses the example of choosing the right smart and automation technologies for factories during the COVID-19 pandemic. This topic is of particular importance as many factories are forced to close or operate on a smaller scale (using a smaller workforce), thus pursuing further automation. Artificial intelligence and Industry 4.0 technologies have many applications in this area, most of which can also be applied for other decision-making purposes in manufacturing systems. First, a systematic procedure was established to guide the group multi-criteria decision-making process. Applications of AI and XAI to identify targets are first reviewed. Subsequently, the application of AI and XAI to selection factors and development of criteria is presented. Artificial intelligence techniques are widely used to derive criteria priorities. Therefore, it is particularly important to explain XAI techniques and tools for such AI applications. Aggregating the judgments of multiple decision makers is the next focus, followed by the introduction of AI and XAI applications to evaluate the overall performance of each alternative. Taking fuzzy ranking preference based on similarity to ideal solution (FTOPSIS) as an example, the application of XAI techniques and tools in explaining comparison results using FTOPSIS is illustrated. Another AI technology used for the same purpose is fuzzy VIKOR. XAI techniques and tools for interpreting fuzzy VIKOR are also presented. Finally, several metrics are proposed to evaluate the effectiveness of XAI techniques or tools for decision making in the manufacturing domain. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Benchmarking sustainable E-commerce enterprises based on evolving customer expectations amidst COVID-19 pandemic.

The 2019 coronavirus disease (COVID-19) pandemic has seriously impacted the performance of all types of businesses. It has given a tremendous structural boost to e-commerce enterprises by forcing customers to online shopping over visiting physical stores. Moreover, customer expectations of the digital and operational capabilities of e-commerce firms are also increasing globally. Thus, it has become crucial for an e-commerce enterprise to reassess and realign its business practices to meet evolving customer needs and remain sustainable. This paper presents a comprehensive performance evaluation framework for e-commerce enterprises based on evolving customer expectations due to the COVID-19 pandemic. The framework comprises seven primary criteria, which are further divided into 25 sub-criteria, including two sustainability factors, namely, environmental sustainability and carbon emissions. The evaluation approach is then practically demonstrated by analyzing the case of three Indian e-commerce firms. The results are obtained using a multi-criteria decision-making (MCDM) method, namely, Fuzzy VIKOR, to capture the fuzziness of the inherent decision-making problem. Further, numerical analysis is conducted to evaluate and rank various e-commerce enterprises based on customer expectations and satisfaction benchmarks. The findings explain the most important criteria and sub-criteria for e-commerce businesses to ensure customer expectations along with their economic and environmental sustainability.

Fuzzy VIKOR approach to identify COVID-19 vulnerability region to control third wave in Assam, India

These days, the appraisal of the COVID-19 vulnerability has become a difficult errand for the whole world. The COVID-19 administration dynamic issue frequently includes numerous elective arrangements clashing standards. In this paper, we present a multi-criteria decision-making (MCDM) procedure based on the fuzzy VIKOR method to survey the COVID-19 vulnerability in the state of Assam, India. The trapezoidal fuzzy number is utilized to evaluate the rating of the loads for the set-up models. We have observed environment, social, and Medical factors after observing the spread of COVID-19. To study and to have comments, a committee of five experts has been formed from a different region of Assam to observe and comment to identify Coronavirus's weakest factors. For a better survey, we have divided the state into four areas namely Rural Area, Urban Area, Market Area in Rural Area, and Market Area in Urban Area. The current research looked at how the fuzzy VIKOR selects provinces for urgent adaptation needs differently than a traditional MCDM technique. © 2022 - IOS Press. All rights reserved.

Big Data-Enabled Solutions Framework to Overcoming the Barriers to Circular Economy Initiatives in Healthcare Sector.

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.

Recovery solutions for ecotourism centers during the Covid-19 pandemic: Utilizing Fuzzy DEMATEL and Fuzzy VIKOR methods.

Obviously, the Covid-19 pandemic has huge impact on most businesses and has caused serious and countless problems for them. Therefore, providing solutions for affected businesses to recover and improve their activities during pandemic times is inevitable. In this regard, ecotourism centers are one of the businesses that went through this problem and have faced significant dilemmas in their activities. Also, reportedly, there is no related research focusing on the recovery approaches to address these obstacles relating to these kinds of businesses during the pandemic. Therefore, all of these exhorted us to do the current research. In this paper, some practical and useful action plans for ecotourism centers are firstly developed to help these businesses. To obtain the action plans, some brainstorming sessions were held consisting of tourism experts, university professors, managers, owners, and some personnel of eco-tourism centers. In order to prioritize the defined action plans, four criteria are considered. Firstly, we compute the weights of the considered criteria by the Fuzzy DEMATEL and then they are prioritized using the Fuzzy VIKOR. The findings of the current study divulge that the AP2 "Standardization of the centers" and AP3 "Estimating demand number and increasing the capacity" and AP7 "Identifying other natural tourist attractions of the region" have the highest and lowest priority to be implemented.

Fuzzy-based multi-criteria decision analysis of environmental regulation and green economic efficiency in a post-COVID-19 scenario: the case of China.

The COVID-19 pandemic outbreak posed serious threats not only to global health but also to the worldwide development regime. The experts, economists, policymakers, and the governments expressed their pledges and determinations to adapt and mitigate climate change. Policymakers and governments have started adopting green growth and development strategies. The progress moves further to achieve green economic efficiency (GEE) to achieve economic, social, and environmental development. One of the major challenges has been promulgating and strictly implementing environmental regulations and policies vis-à-vis green growth and development. China, having the second largest economy, has started its voyage to achieve GEE. However, there are multiple challenges on the way to the green economy. The objective of the present stud is to analyze environmental regulation and GEE in China using fuzzy-based multi-criteria decision analysis. To serve this purpose, the study identifies 5 alternative strategies to achieve GEE while considering 10 criteria and 48 sub-criteria in the context of environmental regulations in China. The Fuzzy Analytical Hierarchy Process (AHP) has been employed to rank criteria and sub-criteria to the goal. The Fuzzy VIekriterijumsko KOmpromisno Rangiranje (VIKOR) method has been used to rank the alternative strategies of GEE. The proposed model unveiled resource efficiency and green purchasing as the best strategy to achieve GEE in the Chinese economy followed by local production. The study provides a comprehensive insight into the green development process to achieve GEE in the Chinese economy in the post-COVID-19 world.

Selection of the best healthcare waste disposal techniques during and post COVID-19 pandemic era.

In recent years, municipal authorities especially in the developing nations are battling to select the best health care waste (HCW) disposal technique for the effective treatment of the medical wastes during and post COVID-19 era. As evaluation of various disposal alternatives of HCW and selection of the best technique requires considering various tangible and intangible criteria, this can be framed as multi-criteria decision-making (MCDM) problem. In this paper, we propose an assessment framework for the selection of the best HCW disposal technique based on socio-technical and triple bottom line perspectives. We have identified 10 criteria on which the best HCW disposal techniques to be selected based on extant literature review. Next, we use Fuzzy VIKOR method to evaluate 9 HCW disposal alternatives. The effectiveness of the proposed framework has been demonstrated with a real-life case study in Indian context. To check the robustness of the proposed methodology, we have compared the results obtained with Fuzzy TOPSIS (Technique of Order Preference Similarity to the Ideal Solution). The results help the municipal authorities to establish a methodical approach to choose the best HCW disposal techniques. Our findings indicate that incineration is the best waste disposal technique among the available alternatives. Even if the dataset indicates 'incineration' is the best method, we must not forget about the environmental concerns arising from this method. In COVID time, incineration may be the best method as indicated by the data analysis, but "COVID" should not be an excuse for causing "Environmental Pollution".