With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that consid...With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.展开更多
Due to people’s increasing dependence on social networks,it is essential to develop a consensus model considering not only their own factors but also the interaction between people.Both external trust relationship am...Due to people’s increasing dependence on social networks,it is essential to develop a consensus model considering not only their own factors but also the interaction between people.Both external trust relationship among experts and the internal reliability of experts are important factors in decision-making.This paper focuses on improving the scientificity and effectiveness of decision-making and presents a consensus model combining trust relationship among experts and expert reliability in social network group decision-making(SN-GDM).A concept named matching degree is proposed to measure expert reliability.Meanwhile,linguistic information is applied to manage the imprecise and vague information.Matching degree is expressed by a 2-tuple linguistic model,and experts’preferences are measured by a probabilistic linguistic term set(PLTS).Subsequently,a hybrid weight is explored to weigh experts’importance in a group.Then a consensus measure is introduced and a feedback mechanism is developed to produce some personalized recommendations with higher group consensus.Finally,a comparative example is provided to prove the scientificity and effectiveness of the proposed consensus model.展开更多
Background: The aim of this study is to gain a better understanding of the true importance of trust in clinical practice by looking at how it is formed, how it affects clinical practice, and how to improve it. Methods...Background: The aim of this study is to gain a better understanding of the true importance of trust in clinical practice by looking at how it is formed, how it affects clinical practice, and how to improve it. Methods: Using the PRISMA-ScR checklist, a review of the literature was performed to identify research evaluating the importance of trust in the doctor-patient relationship. After thorough screening and removal of duplicates, 21 articles were used in the literature review. Results: The classifying themes that emerged in the selected articles were What Makes Trust and Effects of Trust. The theme of What Makes Trust garnered two subthemes as well: Impact of Doctor-Patient Relationship on Trust and Impact of Shared Decision-Making on Trust. Further to that, the overarching themes found were slightly more specific. They were Traits of Trust, Mistrust and Barriers to Trust, Positive Effects of Trust and the Effects of a Lack of Trust. We found that the best way to improve trust was to improve communication between the patient and the doctor. Additionally, we found that the biggest barrier to a trusting doctor patient relationship was a stigmatised condition, followed by a perception of a financially-motivated doctor. Finally, we found that a lack of trust can prevent patients from seeking and receiving proper treatment. Conclusions: With a better understanding of how trust is built and the extent of the role it plays in clinical practice, we hope that this growing knowledge can improve the practice of many doctors in the future. It is certain that more research needs to be done in this area, especially focusing on vulnerable and stigmatised populations such as chronic pain patients.展开更多
To describe the dynamic propcrty of trust relationship, wt propose atime-related trust model and extend Joang's subjective logic to fit for time-related trust model.The extension includes prepositional conjunction...To describe the dynamic propcrty of trust relationship, wt propose atime-related trust model and extend Joang's subjective logic to fit for time-related trust model.The extension includes prepositional conjunction, disjunction and negation for traditional logic anddiscounting and consensus operators that are evidential operators specially designed for thepropagation and computation of trust relationships. With the extension of subjective logic fortime-related trust, our time-related trust modelis suitable to model the dynamic trust relationshipin practice. Finally an example of reputation assessment is offered to demonstrate the usage of ourtrust model.展开更多
基金The work was supported by Humanities and Social Sciences Fund of the Ministry of Education(No.22YJA630119)the National Natural Science Foundation of China(No.71971051)Natural Science Foundation of Hebei Province(No.G2021501004).
文摘With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.
基金the National Natural Science Foundation of China(71871121).
文摘Due to people’s increasing dependence on social networks,it is essential to develop a consensus model considering not only their own factors but also the interaction between people.Both external trust relationship among experts and the internal reliability of experts are important factors in decision-making.This paper focuses on improving the scientificity and effectiveness of decision-making and presents a consensus model combining trust relationship among experts and expert reliability in social network group decision-making(SN-GDM).A concept named matching degree is proposed to measure expert reliability.Meanwhile,linguistic information is applied to manage the imprecise and vague information.Matching degree is expressed by a 2-tuple linguistic model,and experts’preferences are measured by a probabilistic linguistic term set(PLTS).Subsequently,a hybrid weight is explored to weigh experts’importance in a group.Then a consensus measure is introduced and a feedback mechanism is developed to produce some personalized recommendations with higher group consensus.Finally,a comparative example is provided to prove the scientificity and effectiveness of the proposed consensus model.
文摘Background: The aim of this study is to gain a better understanding of the true importance of trust in clinical practice by looking at how it is formed, how it affects clinical practice, and how to improve it. Methods: Using the PRISMA-ScR checklist, a review of the literature was performed to identify research evaluating the importance of trust in the doctor-patient relationship. After thorough screening and removal of duplicates, 21 articles were used in the literature review. Results: The classifying themes that emerged in the selected articles were What Makes Trust and Effects of Trust. The theme of What Makes Trust garnered two subthemes as well: Impact of Doctor-Patient Relationship on Trust and Impact of Shared Decision-Making on Trust. Further to that, the overarching themes found were slightly more specific. They were Traits of Trust, Mistrust and Barriers to Trust, Positive Effects of Trust and the Effects of a Lack of Trust. We found that the best way to improve trust was to improve communication between the patient and the doctor. Additionally, we found that the biggest barrier to a trusting doctor patient relationship was a stigmatised condition, followed by a perception of a financially-motivated doctor. Finally, we found that a lack of trust can prevent patients from seeking and receiving proper treatment. Conclusions: With a better understanding of how trust is built and the extent of the role it plays in clinical practice, we hope that this growing knowledge can improve the practice of many doctors in the future. It is certain that more research needs to be done in this area, especially focusing on vulnerable and stigmatised populations such as chronic pain patients.
文摘To describe the dynamic propcrty of trust relationship, wt propose atime-related trust model and extend Joang's subjective logic to fit for time-related trust model.The extension includes prepositional conjunction, disjunction and negation for traditional logic anddiscounting and consensus operators that are evidential operators specially designed for thepropagation and computation of trust relationships. With the extension of subjective logic fortime-related trust, our time-related trust modelis suitable to model the dynamic trust relationshipin practice. Finally an example of reputation assessment is offered to demonstrate the usage of ourtrust model.
