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This study aimed to investigate the collective effects of bending load and hygrothermal aging on glass fibre-reinforced plastics (GFRP) due to the fact that stress and water absorption is inevitable during GFRP applications.

The water boiling method was used to study the moisture absorption, desorption behaviour and evaluate the performance of GFRP laminates under loading in this article. The moisture diffusion of laminates is characterized in three aging conditions (25°C, 45°C and 65°C water), along with three levels of bending load coefficients (0, 0.3 and 0.6). The moisture diffusion coefficients are determined through the curve fitting method of the experimental data of the initial process, based on the Fickian diffusion model. Moreover, the laminates’ performance is further discussed after adequate environmental aging and loading.

It was found that moisture absorption is promoted by the presence of bending load and boiling during this study. The absorption diffusion coefficient and moisture equilibrium content of the specimens increased with an increasing loading ratio and temperature. The bending strength of the laminate varied according to a contrary trend. Furthermore, the desorbed moisture content is found to be much higher after higher levels of bending load because it is harder to desorb the moisture in the interfaces and micro cracks.

Collective effects of bending load and hygrothermal aging promote the absorption and result in accelerating property degradation of GFRP. It is significant to focus on these effects on the failure of GFRP.

A novel unit was designed to simulate the various loading acted on containers in this work.

The purpose of this paper is to propose a dynamic multi-attribute decision-making method based on the prospect theory for dealing with the dynamic multi-attribute decision-making problem with three-parameter interval grey number.

First, the kernel and comparison rule of three-parameter interval grey numbers are defined, which are the basis of collecting and sorting grey numbers. Next, the prospect value function is determined in view of the decision-making information with different time points as the reference points. Then, an optimal model for solving the attribute weight and time weight is constructed based on the grey entropy principle.

The paper provides a dynamic grey interrelation decision method based on the prospect theory with three-parameter interval grey number, and the example analysis shows that the method proposed in this paper has validity and rationality.

If we have a better understanding of the weights of different reference points, it is possible to receive a more reasonable expression for the comprehensive prospect utility value function.

The paper provides a grey interrelation decision method based on the prospect theory, which can help the decision maker deal with the dynamic multi-attribute decision-making problems under the uncertain environment.

The paper proposes the kernel and ranking method of three-parameter interval grey number, and uses different time points as the reference points to define the prospect value function. Furthermore, this paper structures a dynamic grey interrelation decision method with three-parameter interval grey number based on the prospect theory.

The purpose of this study is to propose an unbiased generalized grey relational closeness evaluation model to improve the accuracy of regional agricultural drought vulnerability decision-making results, as well as to provide theoretical support for reducing agricultural drought risk and losses.

The index weight is calculated using a rough set and deviation minimization criterion, and the relational degree between the research object and the double reference sequence is thoroughly investigated using the generalized grey relational closeness degree. Because different index rankings can correspond to different closeness degrees, the Monte Carlo method was used to calculate an unbiased estimate of the generalized grey relational closeness degree, which was used as a decision basis.

Agricultural drought vulnerability in Henan Province in 2019 was clearly spatially differentiated. The vulnerability to agricultural drought in the southern and eastern regions was generally higher than that in other regions. The evaluation results of this model are highly stable and reliable compared to those of the traditional generalized grey relational evaluation model.

This study proposes an evaluation model based on an unbiased generalized grey relational closeness degree, which is important to supplement the grey relational analysis method system and plays a positive role in promoting the quantitative evaluation of regional agricultural drought vulnerability.

The Monte Carlo method is used to calculate the unbiased estimation of the generalized grey relational closeness degree, which solves the problem of the replacement dependence of the traditional generalized grey relational degree and the one-sidedness of the evaluation results, and provides a new research idea for the evaluation of regional agricultural drought vulnerability under cross-sectional informatics.

The purpose of this paper is to verify the effectiveness of the proposed transient mixed lubrication and wear coupling model [mixed lubrication and wear (MLW) coupling model] under water lubricated conditions by comparing with the experimental results.

Water lubricated bearings are the key parts of the transmission system of an underwater vehicle and some surface ships. In this study, the friction and wear behaviors of rubber, nylon and polyether ether ketone (PEEK) samples with stainless steel underwater lubrication were compared by using ring-block contact structure on multifunctional friction and wear test bench-5000 friction and wear tester.

The results show that the transient wear depth and wear amount of PEEK, nylon and rubber samples under water lubrication are in good agreement with the calculated results of the theoretical model, which verifies the rationality and scientific nature of the MLW coupling model. Thus, the numerical model is applicable for the wear prediction of the journal bearing under water-lubricated conditions. Furthermore, numerical and experimental results reveal that the anti-wear performance among three water-lubricated materials can be ranked by: PEEK > nylon > rubber.

It is expected that this study can provide more information for experimental and numerical research of water-lubricated bearings under water-lubricated conditions.

This study aims to develop a new method to treat the numerical singularity at the critical nodes of two skew coordinates, and optimize the leakage of micro herringbone grooved journal bearings (MHGJBs) with this method.

A side leakage numerical algorithm is proposed by using the skew meshes with a virtual node (SMVN) method to evaluate the effects of groove angle, bank/groove ratio, groove depth and groove number on load capacity, friction and side leakage of MHGJB.

The SMVN method is effective in treating the numerical singularity at the critical nodes of two skew coordinates. Besides, a group of optimized parameters of micro herringbone groove is obtained which can not only minimize the side leakage but also improve the load capacity and friction force.

A virtual node method was proposed, which can significantly improve the calculation accuracy in the side leakage model.

The purpose of this paper is to examine the effect of servant leadership on followers’ subjective career success and the mediating role of career skills. The moderating effect of followers’ proactive personality is also investigated.

This paper collected two-wave matched data from 283 employees of an IT company. The authors use hierarchical regression and bootstrapping to test the hypotheses.

Servant leadership has a positive effect on career satisfaction and perceived employability through career skills. In addition, proactive personality moderates the association between servant leadership and career skills, such that the relationship is stronger when proactive personality is high. Proactive personality also moderates the indirect effect of servant leadership on career satisfaction and perceived employability.

The findings suggest that organizations should select and train leaders to practice servant leadership to enhance employee subjective career success.

This is the first study to investigate the mechanism and boundary conditions of the association between servant leadership and employee subjective career success.

This paper provides the strategic direction and coordination mechanism selection for the intelligent transformation of manufacturing enterprises.

A theoretical framework is developed through grounded theory and case analysis.

Collaboration value is the building block of the intelligent product ecosystem. The ecosystem is upgraded via a path of product coordination, platform coordination and network coordination.

This paper provides a framework for enterprises to build an intelligent product ecosystem.

The proposed intelligent product ecosystem framework is new to the literature and lays down a fruitful avenue for future research.

This study aims to explore the opposite effects of single-category versus multi-category products information diversity on consumer decision making. Further, the authors investigate the moderating role of three categories of visitors – direct, hesitant and hedonic – in the relationship between product information diversity and consumer decision making.

The research utilizes a sample of 1,101,062 product click streams from 4,200 consumers. Visitors are clustered using the k-means algorithm. The diversity of information recommendations for single and multi-category products is characterized using granularity and dispersion, respectively. Empirical analysis is conducted to examine their influence on the two-stage decision-making process of heterogeneous online visitors.

The study reveals that the impact of recommended information diversity on consumer decision making differs significantly between single-category and multiple-category products. Specifically, information diversity in single-category products enhances consumers' click and purchase intention, while information diversity in multiple-category products reduces consumers' click and purchase intention. Moreover, based on the analysis of online visiting heterogeneity, hesitant, direct and hedonic features enhance the positive impact of granularity on consumer decision making; while direct features exacerbate the negative impact of dispersion on consumer decision making.

First, the article provides support for studies related to information cocoon. Second, the research contributes evidence to support the information overload theory. Third, the research enriches the field of precision marketing theory.

Instrumental and emotional information influence paradoxically on people’s decision-making, and similar influences are more evident in e-commerce scenarios where physical information is limited. This study aims to construct a systematic explanatory framework for the influence of multidimensional recommendation information diversity (RID) on users' click and purchase decisions based on the social support theory (SST).

This study analyses 453,176 data from 67,079 users of a Chinese e-commerce platform, applying lasso algorithmic techniques and cross-fit partialling-out (XPO) regression for empirical analysis.

The study finds that instrumental support information diversity (ISID) and emotional support information diversity (ESID) play divergent roles, and that the effects of both on user decision-making are inconsistent with mode-flip and marginal change. Differences in users' information craving and information overload processing mechanisms for instrumental and emotional information, leading to an inverted U-shaped effect of ISID on consumption decisions, while ESID has a U-shaped effect. Additionally, supplier certification eliminates the marginal change in ESID, and products with a high information standardisation degree eliminate the marginal change in ISID.

Research results reveal the opposing roles of the two types of RID and the application boundaries of their roles, providing empirical evidence for academic research.

Against the backdrop of the global reshaping of supply chains, supply chain ecosystems have emerged as a critical force in ensuring the high-quality development of enterprises and fostering stable economic growth. However, a systematic theoretical understanding of how to construct these supply chain ecosystems remains nascent. This study aims to explore the mechanism of the process of building supply chain ecosystems between digital innovation platform enterprises and digital trading platform enterprises from the perspective of dynamic capabilities.

An explanatory case study is conducted based on a theoretical framework grounded on dynamic capabilities view. Two preeminent digital platform enterprises in China (Haier and JD.com) are studied. The authors primarily conducted this research by collecting a large volume of these Chinese public materials.

First, the construction processes of supply chain ecosystems in both digital platform enterprises can be delineated into three stages: embryonic, development and maturity. Second, digital innovation platform enterprises’ construction process is primarily influenced by factors such as production and operational collaboration, consumer demand and research and development. This influence is exerted through interactions on digital platforms and within sub-ecosystems. Meanwhile, digital trading platform enterprises’ construction process is influenced by factors such as infrastructure development, consumer demand and financial support, driving dynamic capability formation through multi-party cooperation and ecological interactions based on conceptual identity.

In the establishment of supply chain ecosystems, digital platform enterprises should prioritize the cultivation of opportunity expansion, resource integration and symbiotic relationship capabilities. Furthermore, this study shows that digital platform enterprises need to actively adjust their interactive relationships with cooperating enterprises based on changes in the market, industry, policies and their own developmental stages.

This study addresses prior deficiencies in understanding the comprehensive construction of supply chain ecosystems and provides significant insights to enhance the theoretical foundation of supply chain ecosystem studies. Additionally, this paper uncovers the dynamic capability development behaviors and contextual features inherent in the construction process of supply chain ecosystems by digital platform enterprises.