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Experts may adjust their assessments through communication and mutual influence, and this dynamic evolution relies on the spread of internal trust relationships. Due to differences in educational backgrounds and knowledge experiences, trust relationships among experts are often incomplete. To address such issues and reduce decision biases, this paper proposes a probabilistic linguistic multi-attribute group decision consensus model based on an incomplete social trust network (InSTN).

In this paper, we first define the new trust propagation operators based on the operations of Probability Language Term Set (PLTS) with algebraic t-conorm and t-norm, which are combined with trust aggregation operators to estimate InSTN. The adjustment coefficients are then determined through trust relations to quantify their impact on expert evaluation. Finally, the particle swarm algorithm (PSO) is used to optimize the expert evaluation to meet the consensus threshold.

This study demonstrates the feasibility of the method through the selection of treatment plans for complex cases. The proposed consensus model exhibits greater robustness and effectiveness compared to traditional methods, mainly due to the effective regulation of trust relations in the decision-making process, which reduces decision bias and inconsistencies.

This paper introduces a novel probabilistic linguistic multi-attribute swarm decision consensus model based on an InSTN. It proposes a redefined trust propagation and aggregation approach to estimate the InSTN. Moreover, the computational efficiency and decision consensus accuracy of the proposed model are enhanced by using PSO optimization.

Twin support vector machine (TSVM) is an effective machine learning technique. However, the TSVM model does not consider the influence of different data samples on the optimal hyperplane, which results in its sensitivity to noise. To solve this problem, this study proposes a twin support vector machine model based on fuzzy systems (FSTSVM).

This study designs an effective fuzzy membership assignment strategy based on fuzzy systems. It describes the relationship between the three inputs and the fuzzy membership of the sample by defining fuzzy inference rules and then exports the fuzzy membership of the sample. Combining this strategy with TSVM, the FSTSVM is proposed. Moreover, to speed up the model training, this study employs a coordinate descent strategy with shrinking by active set. To evaluate the performance of FSTSVM, this study conducts experiments designed on artificial data sets and UCI data sets.

The experimental results affirm the effectiveness of FSTSVM in addressing binary classification problems with noise, demonstrating its superior robustness and generalization performance compared to existing learning models. This can be attributed to the proposed fuzzy membership assignment strategy based on fuzzy systems, which effectively mitigates the adverse effects of noise.

This study designs a fuzzy membership assignment strategy based on fuzzy systems that effectively reduces the negative impact caused by noise and then proposes the noise-robust FSTSVM model. Moreover, the model employs a coordinate descent strategy with shrinking by active set to accelerate the training speed of the model.

Building upon the framework of glocalization, the purpose of this paper is to summarize the development of National Basketball Association (NBA) in Chinese market, explore its successful and unsuccessful places, and propose strategies of glocalization for the NBA as well as other overseas sport leagues.

The current case study was organized by summarizing the developmental history of NBA in China, analyzing its current promotional practices, investigating into its marketing strategies, and extrapolating practical references for other sport leagues aiming to penetrating into the Chinese marketplace.

The current case study concluded that when facing the current challenges, the NBA needs to bring authentic American cultural commodities while adding Chinese characteristics to accommodate local fans. Meanwhile, the NBA management needs to continue seeking ways to work out and through the differences in government models and cultural contexts between China and USA. In addition, this study suggested that the research framework of glocalization would be an ever intriguing inquiry needed for other sport organizations or leagues seeking expansion to overseas markets.

A thorough case study with the NBA that has achieved huge successes in Chinese markets will provide valuable implications for sport leagues to broaden their overseas markets.

Employee green behavior (EGB) is a type of pro-environment behavior at the workplace strategized by organizations to attain sustainable development goals. While organizations have prioritized eco-friendly practices to attain sustainability objectives, EGB has emerged as an essential area of research. Considering the need for sustained employee green behavior, it is important to understand what stimulates such behaviors in an organization. Therefore, we propose a theoretical model grounded in social exchange theory to assess the effect of organizational commitment on employee green behavior, work-related use of social media, social well-being and psychological well-being.

A questionnaire-based survey approach was used to collect data from 203 employees of Indian manufacturing and service industries. Partial least square structural equation modeling (PLS-SEM) analysis was applied to examine the proposed hypothesis.

The results revealed positive and significant effects of organizational commitment on psychological well-being, social well-being, work-related social media use and employee green behavior. Further, psychological well-being mediates the association between work-related social media use and employee green behavior.

This is one of the first studies to examine the effect of organizational commitment on employee green behavior to the best of our knowledge. Additionally, the findings empirically establish organizational commitment, work-related social media use and psychological well-being as antecedents to employee green behavior, thus offering novel insights and theoretically contributing to the employee green behavior, well-being and organizational literature.