ABSTRACT
In consideration of the different importance degrees that may be assigned to all possible linguistic terms, this paper investigates a novel three-way group decision-making method based on the probabilistic linguistic term set (PLTS) information systems. We first construct PLTS information systems based on multiple attributes. Considering the reliabilities of the experts, we determine the weights of the experts by the similarities of the information provided by the expert with regard to other experts. Subsequently, using the evidential reasoning (ER) method, we aggregate the information provided by all experts and obtain the conditional probability of each object. The introduction of the ER rules and the weights of experts successfully solve the problem of conflict between the evaluation information. Then an approach is presented to calculate loss functions and thresholds, which reduces the subjectivity of the decision-making process. Next, the decision result of each object is deduced based on the minimum-loss principle. Finally, a case study about the selection of mask foundries during the COVID-19 is used to demonstrate the effectiveness of our proposed method. And the superiority of our proposed method are proved by comparative analysis. © 2023, The Author(s) under exclusive licence to Taiwan Fuzzy Systems Association.
ABSTRACT
In the last few decades, technological advancements in the power sector have accelerated the evolution of the smart grid to make the grid more efficient, reliable, and secure. Being a consumer-centric technology, a lack of knowledge and awareness in consumers may lead to consumer opposition, which could imperil the grid modification process. This research aims to identify and prioritize the factors that can be considered barriers to technology acceptance for smart grid development in India. This study follows an integrated approach of literature review, AHP, and FERA. In the present work, 17 barriers have been identified and ranked on the basis of the social, technical, and economic paradigm. This study finds the impact of government policies and stakeholders' involvement in consumers' acceptance of smart grid technology and its importance towards improving the quality of life of Indians. The government should play as the main proponent. The present work will contribute to developing and upgrading the basic framework for the smart grid in a developing country like India. Copyright © 2022, IGI Global.
ABSTRACT
In the last few decades, technological advancements in the power sector have accelerated the evolution of the smart grid to make the grid more efficient, reliable, and secure. Being a consumer-centric technology, a lack of knowledge and awareness in consumers may lead to consumer opposition, which could imperil the grid modification process. This research aims to identify and prioritize the factors that can be considered barriers to technology acceptance for smart grid development in India. This study follows an integrated approach of literature review, AHP, and FERA. In the present work, 17 barriers have been identified and ranked on the basis of the social, technical, and economic paradigm. This study finds the impact of government policies and stakeholders' involvement in consumers' acceptance of smart grid technology and its importance towards improving the quality of life of Indians. The government should play as the main proponent. The present work will contribute to developing and upgrading the basic framework for the smart grid in a developing country like India.
ABSTRACT
Rapid development of maritime transportation networks meets international trade demands while rendering them in high risk and disruption concerns particularly at ports being the bottlenecks of the whole flows. Port operations calls for an effective approach to assess ports vulnerability and to ensure the resilience of their associated maritime supply chains (MSC). However, traditional quantitative risk analysis reveals challenges due to data incompleteness and ambiguity, and operational and environmental uncertainty when being applied in ports vulnerability analysis. This paper aims to develop a novel port vulnerability assessment (PVA) framework, which can guide and realise a standardised vulnerability analysis process for the ports from different geographies involving in the same MSC and hence the resources can be better managed from a global network level for optimal resilience of the chain. It is especially important for the shipping and port industries which are in nature international and desires strong international uniform standardization. The fuzzy theory, evidential reasoning (ER) approach, and expected utility theory are combined in a holistic way to form the proposed PVA framework. The new framework is validated and demonstrated by using a case study in which five key ports along an established MSC in China are investigated. The findings can be used as a stand along method to compare the vulnerability levels of the ports in an MSC and/or integrated with decision optimisation methods for rational safety resource distribution from a supply chain perspective.
ABSTRACT
The Coronavirus Disease 2019 (COVID-19) has popularized since late December 2019. In present, it is still highly transmissible and has severe impact on the public health and global economy. Due to the lack of specific drug and the appearance of different variants, the selection of the antiviral therapy to treat the patients with mild symptom is of vital importance. Hence, in this paper, we propose a novel behavioral Three-Way Decision (3WD) model and apply it to the medicine selection decision. First, a new relative utility function is constructed by considering the risk-aversion behavior and regret-aversion behavior of human beings. Second, based on the relative utility function, some new rules are defined to calculate the thresholds and conditional probabilities in 3WD and some corresponding theorems are explored and proved. Next, a new information fusion mechanism in the framework of evidential reasoning algorithm is developed. Then, the decision results are obtained based on the Bayesian decision procedure and the principle of maximum utility. Finally, an example with large-scale data set and an example about medicine selection for COVID-19 are provided to show the implementation process and effectiveness of the proposed method. Comparative analysis and sensitivity analysis are also performed to illustrate the superiority and the robustness of the current proposal.
ABSTRACT
Customer opinions on a product or retailer can be assessed through analyzing their textual reviews submitted to online communities. While the attitudinal information of a text post can be gauged by studying the sentiment words used, a method has to be sought for more effectively evaluating the sentiment strengths, because different writers may have varied interpretations on a word’s sentiment. The objective of this paper is to develop a new integrated approach by adopting Sentiment Analysis and Evidential Reasoning for the online retailers’ timely evaluation of the public sentiments toward different product alternatives. The finding of the study has established the benefit of efficiently evaluating the customers’ feedback toward products and monitoring the changes of customer preferences on product attributes over time. The results obtained from the proposed approach are superiority to other decision-making tools. [ FROM AUTHOR] Copyright of Journal of Industrial & Production Engineering is the property of Taylor & Francis Ltd 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
Container shipping makes significant contribution to the global economy and is confronted with various hazards and risks especially during the COVID-19 pandemic. These risks can disrupt resilient container shipping service, leading to further deterioration of the global economy. Hence, it is vital to develop resilient container shipping service, which is associated with being on-time, safe, and hassle-free. Theoretically, this research identifies 28 root risks using the PESTLE framework, conducts risk assessment using a hybrid method comprising failure modes and effects analysis, evidential reasoning, and rule-based Bayesian network. A three-hierarchy Bayesian network model is established. The results reveal that economic, political, and technical risks are the most threatening risks affecting resilient container shipping service. Moreover, the holistic container shipping risk is most sensitive to environmental risks. Managerially, this research provides container shipping companies with guidance of drafting risk mitigation plans with economic risks and political risks as priorities.
ABSTRACT
Epidemic diseases (EDs) present a significant but challenging risk endangering public health, evidenced by the outbreak of COVID-19. Compared to other risks affecting public health such as flooding, EDs attract little attention in terms of risk assessment in the current literature. It does not well respond to the high practical demand for advanced techniques capable of tackling ED risks. To bridge this gap, an adapted fuzzy evidence reasoning method is proposed to realize the quantitative analysis of ED outbreak risk assessment (EDRA) with high uncertainty in risk data. The novelty of this article lies in (1) taking the lead to establish the outbreak risk evaluation system of epidemics covering the whole epidemic developing process, (2) combining quantitative and qualitative analysis in the fields of epidemic risk evaluation, (3) collecting substantial first-hand data by reviewing transaction data and interviewing the frontier experts and policymakers from Chinese Centers for Disease Control and Chinese National Medical Products Administration. This work provides useful insights for the regulatory bodies to (1) understand the risk levels of different EDs in a quantitative manner and (2) the sensitivity of different EDs to the identified risk factors for their effective control. For instance, in the case study, we use real data to disclose that influenza has the highest breakout risk level in Beijing. The proposed method also provides a potential tool for evaluating the outbreak risk of COVID-19.