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Social network group decision-making (SNGDM) has rapidly developed because of the impact of social relationships on decision-making behavior. However, not only do social relationships affect decision-making behavior, but decision-making behavior also affects social relationships. Such complicated interactions are rarely considered in current research. To bridge this gap, this study proposes an SNGDM model that considers the interaction between social trust relationships and opinion evolution.

First, the trust propagation and aggregation operators are improved to obtain a complete social trust relationship among decision-makers (DMs). Second, the evolution of preference information under the influence of trust relationships is measured, and the development of trust relationships during consensus interactions is predicted. Finally, the iteration of consensus interactions is simulated using an opinion dynamics model. A case study is used to verify the feasibility of the proposed model.

The proposed model can predict consensus achievement based on a group’s initial trust relationship and preference information and effectively captures the dynamic characteristics of opinion evolution in social networks.

This study proposes an SNGDM model that considers the interaction of trust and opinion. The proposed model improves trust propagation and aggregation operators, determines improved preference information based on the existing trust relationships and predicts the evolution of trust relationships in the consensus process. The dynamic interaction between the two accelerates DMs to reach a consensus.

This paper analyzes the advance selling and pricing strategies of fresh products supply chain where the e-retailer provides wholesale contract or agency contract to the fresh products supplier.

This paper constructed a two-period sequential-move game of fresh products supply chain members.

This analysis showed that the supply chain members had different preferences for contracts under different market conditions. The advance selling of fresh products was not a decision of the seller, but also required the support of other supply chain members. And the advance selling strategy was not always beneficial to all supply chain parties. Under the two contracts, there were market conditions in which the profits of supply chain members were Pareto-improved through the implementation of advance selling.

The model presented in this study focuses solely on the context of monopoly, overlooking the competition from alternative suppliers or retailers. Consequently, exploring the competitive landscape within the fresh products supply chain, particularly in relation to pre-sale pricing, emerges as a crucial avenue for further investigation. By employing empirical research methods, valuable insights are gleaned, thereby significantly augmenting the existing body of relevant theories.

The decision to pre-sell fresh products should be based on market conditions. Supply chain members can control production costs and fresh products circulation losses to maximize profits.

From the perspective of game theory, this study analyzed the optimal advance selling and pricing strategies of fresh products supply chain members under two kinds of contracts. These results can provide practical implications for fresh products suppliers and e-retailers.

To overcome the limitations of traditional multi-attribute decision making (MADM) methods, which only provide deterministic rankings of decision objects, this paper proposes a novel multi-attribute 3WD model. This model presents three-parameter interval grey number decision-theoretic rough sets (TPIGNDTRSs), aiming to offer a reasoned interpretation of loss functions in grey environments and ensure objective assessment of conditional probabilities.

Firstly, the traditional equivalence relation is replaced with the probabilistic dominance relation (PDR), categorizing decision objects into two state sets in DTRS for more objective conditional probabilities. Secondly, as the three-parameter interval grey number (TPIGN) introduces the most probable value on the basis of the traditional two-parameter interval grey number, it provides a more comprehensive method for describing grey information. Consequently, integrating TPIGN into DTRS refines the interpretations of loss functions in grey environments. Finally, by utilizing two main sorting techniques, relative kernel and degree of accuracy ranking and possibility ranking, two types of 3WD rules with TPIGNDTRSs, are constructed.

This study has successfully developed and validated a new multi-attribute 3WD model. The model was tested in two distinct domains: evaluating innovation efficiency in high-tech enterprises and recommending movies in a practical case. The findings reveal that the model can effectively integrate relevant information of high-tech enterprises, provide the government with enterprise-level assessments, and gather consumer preferences to recommend the most suitable movies.

This study treats the loss function as grey information in the 3WD model but overlooks the grey nature of evaluation values, limiting its applicability. Additionally, the model’s reliance on subjective expert judgments and historical data to establish the loss function may affect its objectivity. The implications of this research are that the novel model overcomes traditional MADM limitations, enhancing decision-making quality and efficiency in complex and grey scenarios. The model’s successful application in evaluating high-tech enterprises and recommending movies illustrates its dual value in both theory and practice.

Initially, the model proposed in this study is of significant importance for the development of the 3WD field, as it successfully addresses the challenges of uncertain loss functions and unknown conditional probabilities in grey information environments. Moreover, by integrating the 3WD model with MADM problems, it has broken through the bottlenecks of traditional MADM methods, offering new perspectives and strategies for solving MADM issues. Therefore, this research not only advances theoretical research but also provides powerful tools for practical applications.

Despite the extensive body of research on absolute corporate social responsibility (CSR) performance, limited attention has been given to the distinct concepts of optimal and aggressive CSR engagement, as well as their associations with CSR awarding. This study aims to differentiate between optimal and aggressive CSR engagement and examine their relationship with CSR awarding while considering the moderating influence of board characteristics from the perspectives of stakeholder and agency theories.

This empirical analysis draws on an international dataset comprising 43,803 observations from nine sectors across 41 countries. We employ a least squares dummy variable regression approach that accounts for country, industry and year effects to conduct the analysis.

The results reveal that engagement in aggressive CSR activities beyond the optimal level leads to the generation of a social reputation through CSR awarding. However, the influence of board characteristics on this relationship is significant. Specifically, the presence of a dedicated CSR committee encourages CSR awarding in the context of aggressive CSR engagement. Conversely, board independence constrains the relationship between aggressive CSR engagement and CSR awarding. Notably, board gender diversity does not have a discernible impact on this connection.

Our evidence provides valuable insights to help firms seeking to enhance their social reputation through CSR activities better allocate their resources and avoid unnecessary financial commitments.

This study advances the current understanding by exploring the relationship between aggressive CSR engagement and the recognition of CSR awards. Furthermore, it scrutinises the factors that dictate when such aggressive CSR engagement translates into enhanced social reputation, as evidenced by the attainment of CSR awards.

This study aims to investigate the cause of high-order wheel polygonization in a plateau high-speed electric multiple unit (EMU) train.

A series of field tests were conducted to measure the vibration accelerations of the axle box and bogie when the wheels of the EMU train passed through tracks with normal rail roughness after re-profiling. Additionally, the dynamic characteristics of the track, wheelset and bogie were also measured. These measurements provided insights into the mechanisms that lead to wheel polygonization.

The results of the field tests indicate that wheel polygonal wear in the EMU train primarily exhibits 14–16 and 25–27 harmonic orders. The passing frequencies of wheel polygonization were approximately 283–323 Hz and 505–545 Hz, which closely match the dominated frequencies of axle box and bogie vibrations. These findings suggest that the fixed-frequency vibrations originate from the natural modes of the wheelset and bogie, which can be excited by wheel/rail irregularities.

The study provides novel insights into the mechanisms of high-order wheel polygonization in plateau high-speed EMU trains. Futher, the results indicate that operating the EMU train on mixed lines at variable speeds could potentially mitigate high-order polygonal wear, providing practical value for improving the safety, performance and maintenance efficiency of high-speed EMU trains.

This study aims to examine how participation in the Belt and Road Initiative (BRI) affects province-level regional economic resilience. In the context of dual circulation – the new development paradigm proposed by the Chinese Government – participating in the BRI is an important means of connecting both international and domestic circulations and achieving high economic resilience. The complex causal relationship between participation in the BRI and province-level regional economic resilience is investigated.

Based on the complex system view, this study uses fuzzy set qualitative comparative analysis (fsQCA) to examine the impact on regional economic resilience when provinces participate in the BRI through unimpeded trade, infrastructure connectivity, financial integration and people-to-people bonds under the two conditions of attention allocation and buffering capacity. Qualitative textual analysis is applied to analyse provincial work reports, and relevant statistical data are used to measure the economic resilience from 2013 to 2020.

The authors identified three condition configurations that lead to a high regional economic resilience at province-level and one condition configuration that lead to no high-level regional economic resilience.

In-depth analyses of qualitative materials should be conducted to explain the systematic relationships among the conditions.

This research is of practical significance to the development of the theoretical framework and practices of the BRI in the context of dual circulation.

By adopting learning theory and a guanxi perspective, this study aims to investigate the effects of interpersonal guanxi (interpersonal networks or connections) and relationship learning on companies’ business performance when operating in a large emerging market.

Using a sample of 294 sales managers and salespeople in the Chinese hotel sector, the authors empirically test the authors' arguments through a structural equation modeling (SEM) approach.

The authors' findings indicate that strong interpersonal guanxi tends to generate more positive business performance. Furthermore, the authors find that relationship learning plays a mediating role in the association between interpersonal guanxi and hotel companies’ business performance in a Chinese context. Finally, the authors empirically explore the moderating effect of inter-firm dependence on the contribution of interpersonal guanxi to relationship learning. Findings demonstrate that this effect varies significantly based on inter-firm dependence, with interpersonal guanxi exhibiting a greater positive impact if such dependence is high.

This study enriches our understanding of interpersonal guanxi and of how companies can enhance the companies' business performance in an emerging market context.

This study aims to provide a new perspective and path to reduce the unsafe behavior of new generation of construction workers (NGCWs) in China. The purpose of this study is to explore the influencing mechanism of work-family balance on the unsafe behavior of NGCWs and test the mediating effect of job satisfaction and the moderating effect of group safety climate.

A theoretical model on the influencing mechanism of work-family balance on unsafe behavior of NGCWs was constructed through theoretical analysis. Research data were collected from 502 NGCWs via a questionnaire survey, and research hypotheses were testified with regression analysis.

The results show that work-family balance not only directly reduces NGCWs’ unsafe behavior but also indirectly reduces it through job satisfaction, which plays a partial mediating role. In addition to positively moderating the relationship between work-family balance and NGCWs’ unsafe behavior, group safety climate can also moderate the relationship between work-family balance and job satisfaction in a positive way.

This study provides practical implications for construction companies to reduce the unsafe behaviors of NGCWs from the perspective of work-family balance. Specifically, construction companies should adopt more flexible work rules, such as flexible organization and rotation systems, to increase their work autonomy. Meanwhile, construction companies need to improve the work environment and basic conditions for NGCWs, establish a reasonable salary system and provide attractive promotion opportunities to increase their job satisfaction. In addition, construction companies should provide active safety lectures and training, and supervisors should improve safety communication and interaction levels. Co-workers should remind workers about their safety attitudes and behaviors promptly. A good group safety climate will be created through the efforts of construction companies, supervisors and co-workers.

This study clarifies the influencing mechanism of work-family balance on the NGCWs’ unsafe behavior and further tests the partial mediating role of job satisfaction and the positively moderating effect of group safety climate on the influence relationship of work-family balance on job satisfaction and NGCWs’ unsafe behavior, which defines the boundary conditions of the relationship between work-family balance and NGCWs’ unsafe behavior, and promotes the effective integration of social exchange theory and theoretical system of influencing mechanism of construction workers’ unsafe behavior.

The digital economy has become a new engine for economic development, promoting the upgrading and transformation of traditional industries as well as fostering emerging industries and forms of business. Nonetheless, how does the digital economy affect innovation? The research objective is to explore the specific impact of the digital economy on innovation output.

This paper innovatively adopts the dynamic panel data model (DPDM) to carry out an empirical study on the impact of the digital economy on innovation output, through the observation of 30 provincial-level administrative regions in China. Furthermore, the paper innovatively analyzes the impact of different dimensions of the digital economy on innovation output and the impact of the digital economy on different dimensions of innovation output.

It is found that the digital economy is conducive to boosting innovation output considering innovation continuity. Specifically, the driving impact of core industries and enterprise application of digital economy on innovation output is more prominent, but the driving impact of infrastructure and personal application on innovation output is not fully played. Meanwhile, the driving impact of the digital economy on the innovation output quality is more significant than that digital economy on the innovation output quantity.

This study employs a DPDM for the first time to investigate the specific impact of the digital economy on innovation output, and contributes to the existing literature on the digital economy and digital economy-driven innovation. The findings offer a comprehensive explanation for the impact of the digital economy on innovation output, which has reference value for the formulation of innovation policies driven by digital economy, thereby providing impetus for the sustained and stable development of China's economy.

This study aims to examine how fairness concerns and power structure in dyadic green supply chains impact retail price, supply chain profits and greening level decisions.

This study develops game-theoretic models considering fairness concerns and asymmetric power structures under an iso-elastic demand setting. The research paper employs the Stackelberg game approach, taking into consideration the fairness concern of the channel leader.

The findings indicate that under fairness, there is an increase in both wholesale and retail prices, as well as greening expenditures. Notably, when comparing the two models (manufacturer Stackelberg and retailer Stackelberg), double marginalization is more pronounced in the retailer Stackelberg setup than in the manufacturer Stackelberg setup. In a traditional supply chain with iso-elastic demand, the follower typically extracts higher profit compared to the leader; however, our results show that, under fairness conditions, the leader achieves higher profit than the follower. Additionally, our study suggests that supply chain coordination is unattainable in a fairness setup. This paper provides insights for managers on the optimal supply chain structure and the level of fairness to maximize profit.

This paper investigates the impact of a leader's fairness on the optimal decisions within a green supply chain, an area that has received limited attention previously. Additionally, the study investigates how fairness concerns manifest in distinct power dynamics, specifically, in the contexts of manufacturer Stackelberg and retailer Stackelberg.