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Quality function deployment (QFD) is an effective method to convert customer requirements (CRs) into design requirements (DRs) by constructing house of quality (HOQ). With the rapid growth of the e-commerce market, it is a new challenge to utilize the available online reviews to facilitate the implementation of QFD. Therefore, this paper proposes a novel QFD model from the perspective of group decision making (GDM) and social network analysis (SNA), then applies the proposed model to product design under Chinese e-commerce scene. Firstly, this paper extracts CRs from online reviews on e-commerce platforms, and the initial HOQs can be constructed. Then a bilateral negotiation GDM method based on SNA is carried out to generate a consensus-based HOQ, and therefore the final priorities of DRs can be obtained. Finally, a case study is provided to illustrate the applicability, and some discussions and comparative analysis are also conducted. The result indicates that the proposed method can generate effective and stable results for QFD implementation in real-world e-commerce scenario. [ABSTRACT FROM AUTHOR]

To group decision-making (GDM) under social network, the interactions are no longer limited to pairwise but can take higher-order interaction, which can affect the consensus process. The higher-order interaction can be represented in simplicial complex. Therefore, under social network, this paper deeply explores a new higher-order interaction-based adjustment model in the simplicial complex. Firstly, we identify simplicial complex by utilizing the consensual objective and subjective trust information, and determine the decision maker weights. Then, we design the stability of simplex from the system structure and select the adjustment alternative and decision maker to construct the adjustment model based on the consensus and the stability of simplex. Considering the simplex structure, inspired by spreading dynamics model of simplex, we propose strengthening mechanism and competing mechanism of higher-order evaluation interaction. Further, this paper establishes a higher-order interaction-based minimum adjustment model. Because of the connectedness of simplicial complex, decision makers between simplices may occur the spontaneous interaction. In this case, we construct a global stability of simplicial complex to improve the minimum adjustment model. Finally, we use an example to expound the feasibility of our method, and design also a comparative analysis to demonstrates its advantages. In general, our method can significantly improve the consensus level and changes the adjustment decision maker selection from the system structure. • This paper deeply investigates higher-order interaction-based group consensus model in the simplicial complex. • We construct the stability of simplex and combine the consensus index to choose the adjustment decision maker. • The global stability of the simplicial complex is used to tackle the spontaneous adjustment for the consensus reaching model. [ABSTRACT FROM AUTHOR]

The clinical diagnosis decision-making process of integrated traditional Chinese medicine and Western medicine is essentially a type of group decision-making (GDM) problem, which is transparently characterized by the multiformity of data types and the diversity of knowledge structures among experts. However, most existing GDM methods are designed based on single data types and cannot address GDM problems involving multiple data types and diversified attributes. Moreover, the preference-approval structure provides a simple framework to simulate the preference information regarding an individual's ranking and approval. But it only considers two categories: approval and disapproval, without accounting for the indecision of individuals. In reality, three-way decision (TWD) is common. Given the deficiencies above, this paper puts forward a novel preference-approval structure-based three-way group consensus decision-making approach for a class of GDM problems with the characteristics of incompleteness, multi-granularity, diversity, and compound. To represent the information in these complex GDM problems, we firstly present the concept of incomplete multi-granularity diversified compound decision systems (IMGDCDSs). Secondly, according to the data characteristics, we construct a non-additive TWD model over the framework of granular computing. On the one hand, using the reference point of each attribute, an acquisition method of relative loss functions is given by considering three kinds of states. On the other hand, we present a new fuzzy measure to calculate non-additive conditional probabilities. The above work enriches the existing TWD theory. Based on the three-way classification and ranking results obtained, this paper subsequently defines a preference-approval structure and establishes a new group consensus decision-making approach. Thereby, the TWD model is integrated into preference-approval structures, which further enriches the GDM theory. More importantly, some existing group consensus methods are special cases of our study. Whereafter, we demonstrate the feasibility of the approach using an illustrative example. Finally, the stability and effectiveness of the approach are verified through an empirical study in the context of medical diagnosis. • Incomplete multi-granularity diversified compound decision systems are presented. • A non-additive three-way decision (TWD) model is constructed. • The TWD model and preference-approval structures are integrated. • A new group consensus approach is applied to medical diagnosis. • The effectiveness of the approach is verified by an empirical analysis. [ABSTRACT FROM AUTHOR]

• Large groups need to seek decision representatives to participate in consensus negotiations. • Local and global influence can be estimated based on centrality metrics of social networks. • Representatives codetermined by strong and weak ties lead to faster consensus formation. In the era of social media, the issue of large-scale group decision-making (LSGDM) is becoming increasingly prominent. The complexity of large group interactions increases rapidly with the expansion of the group size. Current research has often used cluster analysis to reduce the dimensionality of LSGDM, but the decision agents following dimensionality reduction are not clearly defined, which hinders the practical application of LSGDM methods. This paper studies the LSGDM through the context of community representatives which are determined by combining strong and weak ties. The participation of such representatives in subsequent decision-making can reduce negotiation costs and efficiently form a consensus from both global and local perspectives. To identify these community representatives, this study improves the traditional Laplacian centrality, calculates the local and global centrality of individuals, and defines metrics for measuring representatives. The opinion dynamics model is used to verify the effectiveness of the LSGDM model with community representatives. The karate club network is used to illustrate the application of the proposed LSGDM model. Simulation and comparative analysis results show that the proposed model takes less time to reach consensus than traditional ones. Furthermore, there is no complete linear relationship between the representative size and the time taken to reach group consensus. [ABSTRACT FROM AUTHOR]

• Study describes the comprehensive process of conceptualization of family support workforce skills in different professions and social sectors. • Several related research are applied: websites content analysis, systematic reviews and Delphi study. • Core and field-specific skills become family supportive when they are applied in the contexts of strength and relationship-based approach as well as both – whole family and child-centered approach. • Implications lead to construction of a coherent model of family support skills with consideration and validation of links and relationships between the components of the model. Professionals working in different areas of family support have diverse conceptual assumptions and epistemological frameworks. Thus, a common conceptualization of family support workforce skills presents major research and practical challenge. Beyond general recognizability, a growing knowledge base and interests, there is still no generally accepted concept of what family support is as a practice, policy, and theoretical construct. This paper attempts to conceptualize the skills for the practice of family support in different professions and social sectors through several research approaches. Initially, we analyzed the content of websites with international organizations' resources about skills in family support. Second, we systematically reviewed literature using the PRISMA method. Last, we reviewed literature, including professional handbooks and publications. The content analysis and systematic literature reviews indicate that as an interdisciplinary concept, family support workforce skills are generally familiar, but not defined nor specified and differentiated from other skills used in the broad field of work with families. So, to deepen the knowledge on family support workforce skills and reach a reliable consensus, the Delphi method was used with a series of questionnaires at different stages of research. Results indicate that specific core and field-specific skills become family supportive when they are applied in the contexts of strength and relationship-based approach as well as both – whole family and child-centred approach. That has opened up new possibilities for more precise definitions, recognisability and transferability of family support skills and construction of a conceptual model. [ABSTRACT FROM AUTHOR]

• Adverse childhood experiences (ACEs) screeners can be verbal or self-administered. • We used 2 contemporaneous surveys to compare prevalence of caregiver-reported ACEs. • The telephone survey had higher ACEs disclosure rates compared to paper/web survey. • Findings support the importance of verbal communication to identify ACEs exposure. Adverse childhood experiences (ACEs) are traumatic experiences that increase people's susceptibility to adverse physical health, mental health, and social consequences in adulthood. Screening for ACEs in primary care settings is complicated by a lack of consensus on appropriate methods for identifying exposure to ACEs. It is unclear whether self-report methods could increase disclosure of ACEs as compared to interview-based methods. This study compares data on the prevalence of ACEs from two publicly available surveys conducted on the same population of children's caregivers: the 2019 Ohio subsample of the web/mail-based National Survey of Children's Health and the telephone-based 2019 Ohio Medicaid Assessment Survey. We find higher disclosure of caregiver-reported child exposure to ACEs in the telephone interview survey, highlighting the importance of the role of verbal communication in developing a safe and trusting relationship in the disclosure of trauma. [ABSTRACT FROM AUTHOR]

The continuous advancements in artificial intelligence (AI) technology are facilitating its widespread integration across various sectors, prominently within agriculture. This evolving synergy is reshaping farming practices, specifically by innovating intelligent mechanisms to monitor and combat crop diseases through intelligent decision-making. Wheat assuming particular significance on the global agricultural stage. Addressing the concerning spread of the wheat soil-borne mosaic (WSBM), this paper employs modern methodologies to gauge the severity of virus infection in wheat through quantitative evaluation. Our contribution lies in the exploration of a group consensus model method within the context of interval type-2 fuzzy sets (IT2FSs). Navigating the intricacies of decision makers (DMs) reaching consensus, we address the challenge of selecting a consensus degree threshold by introducing random variables. Experimentally determining an objective consensus degree threshold. Then, we combine the Multi-Objective Optimization by Ratio Analysis plus the full MULTIplicative form (MULTIMOORA) method with Dempster-Shafer (D-S) evidence fusion theory. This result in an evidence fusion decision-making model rooted in IT2F information, offering enhanced stability. Leveraging the MULTIMOORA method for decision-making, we then fuse the outcomes through D-S evidence fusion theory, yielding stable decision results. Subsequently, we validate the feasibility of our established decision model within the context of WSBM. In conclusion, we subject it to sensitivity and comparative analyses, comparing it with other methods. This thorough evaluation aims to validate the effectiveness and feasibility of our proposed approach, providing insights into its potential applications and contributions in the realm of agricultural decision-making. • A scheme for detecting crop diseases through artificial intelligence is proposed. • A decision-making method fusing MULTIMOORA with D-S evidence theory is explored. • An agricultural group consensus decision rule in the IT2FS context is explored. • A method to optimize the consensus process by the additional adjustment is developed. [ABSTRACT FROM AUTHOR]

When building consensus in group decision making (GDM) under uncertainty, an important yet rarely studied issue is to find the Pareto solutions of multi-objective optimization model. This paper reports a two-objective (2Ob) optimization driven consensus model in GDM by describing the bipolarity of judgements through intuitionistic multiplicative preference relations (IMPRs). First, it is realized that the inherent property of IMPRs is the hesitancy degree. A novel inconsistency index of IMPRs is proposed by combining the effects of hesitancy degree and inconsistency of boundary matrices. Second, the compatibility measure between two IMPRs is utilized to quantify the consensus level (CL) of decision makers. The threshold of acceptable group CL is found to decrease with the order of IMPRs for the first time. A 2Ob optimization model is constructed by minimizing group inconsistency degree and group CL, respectively. Third, the method of equipping two flexibility degrees to each expert is proposed for optimizing individual IMPRs. It is interesting to find that the constructed granularity matrix is different from interval-valued IMPRs. A multi-objective particle swarm optimization algorithm is adopted to obtain a set of Pareto solutions to GDM problems. Case studies are carried out to illustrate the proposed consensus reaching model. The results help to identify how to provide flexible decisions in GDM under some complexity and uncertainty of a practical problem. • The consistency degree of IMPRs is measured by proposing a novel index. • The threshold of group CL is examined to be dependent on the order of IMPRs. • Two flexibility degrees are proposed to construct a two-objective consensus model. • A MOPSO algorithm is used to derive Pareto solutions of GDM problems. [ABSTRACT FROM AUTHOR]

• A systematic review was performed to determine if peer-reviewed publications of clinical trials in stereotactic body radiation therapy (SBRT) include sufficient technical data to ensure safe and robust implementation in real-world clinics. • The studies evaluated showed great variability and lacked information to reproduce the technical and dosimetric data, with none considered to be completely reproducible. • A list of recommendations based on the analysis was proposed to ensure adequate reproducibility of technical parameters in primary SBRT clinical trials. The results of phase II and III trials on Stereotactic Body Radiation Therapy (SBRT) increased adoption of SBRT worldwide. The ability to replicate clinical trial outcomes in routine practice depends on the capability to reproduce technical and dosimetric procedures used in the clinical trial. In this systematic review, we evaluated if peer-reviewed publications of clinical trials in SBRT reported sufficient technical data to ensure safe and robust implementation in real world clinics. Twenty papers were selected for inclusion, and data was extracted by a working group of medical physicists created following the ESTRO 2021 physics workshop. A large variability in technical and dosimetric data were observed, with frequent lack of required information for reproducing trial procedures. None of the evaluated studies were judged completely reproducible from a technical perspective. A list of recommendations has been provided by the group, based on the analysis and consensus process, to ensure an adequate reproducibility of technical parameters in primary SBRT clinical trials. Future publications should consider these recommendations to assist transferability of the clinical trial in real world practice. [ABSTRACT FROM AUTHOR]