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A generalized distribution with wide range of skewness and elongation will be suitable for the data mining and compatible for the misspecification of the distribution. Hence, the purpose of this paper is to present a distribution-based approach for estimating degradation reliability considering these conditions.

Tukey’s g-and-h distribution with the quantile expression is introduced to fit the degradation paths of the population over time. The Newton–Raphson algorithm is used to approximately evaluate the reliability. Simulation verification for parameter estimation with particle swarm optimization (PSO) is carried out. The effectiveness and validity of the proposed approach for degradation reliability is verified by the two-stage verification and the comparison with others’ work.

Simulation studies have proved the effectiveness of PSO in the parameter estimation. Two degradation datasets of GaAs laser devices and crack growth are performed by the proposed approach. The results show that it can well match the initial failure time and be more compatible than the normal distribution and the Weibull distribution.

Tukey’s g-and-h distribution is first proposed to investigate the influence of the tail and the skewness on the degradation reliability. In addition, the parameters of the Tukey’s g-and-h distribution is estimated by PSO with root-mean-square error as the object function.

The purpose of this paper is to provide additive manufacturing-based solutions for preparation of elastomeric foam with broaden compressive stress plateau.

Mechanic models are developed for obtaining designs of foam cell units with enhanced elastic buckling. An experimental approach is taken to fabricate the foams based on direct ink writing technique. Experimental and simulation data are collected to assist understanding of our proposals and solutions.

A simple tetragonal structured elastomeric foam is proposed and fabricated by direct ink writing, in which its cell unit is theoretically designed by repeating every four filament layers. The foam exhibits a broader stress plateau, because of the pronounced elastic buckling under compressive loading as predicted by the authors’ mechanic modeling. A two-stage stress plateaus as observed in the foam, being attributed to the dual elastic buckling of the cell units along two lateral directions of the XY plane during compression.

Future work should incorporate more microscopic parameters to tune the elastomeric foam for mechanic performance testing on linear elastic deformation and densification of polymer matrix.

Additive manufacturing offers an alternative to fabricate elastomeric foam with controlled cell unit design and therefore mechanics. Our results comment on its broad space for development such superior cushioning or damping material in the fields of vibration and energy absorption.

This work has contributed to new knowledge on preparation of high performance elastomeric foam by providing a better understanding on its cell structure, being printed using direct ink writing machines.

Customers' continuous value creation (e.g. voice) is an important research issue for the success of brand virtual community (BVC) and new product development, while it is rarely studied from a firm perspective. The purpose of the present study is to investigate how firm attributes exert influences on continuous voice intention in brand virtual communities.

The data were collected through a survey in mobile brand virtual communities in China, and 291 valid responses for data analysis were included to test the research model by using partial least squares (PLSs).

The results show that intrinsic motivation to voice is positively associated with continuous voice intention. Furthermore, the impact of brand identification on intrinsic motivation is found to be fully mediated by community identification. Customer orientation has a positive effect on perceived openness, and both customer orientation and perceived openness positively affect customers' brand identification and community identification.

Although prior studies have examined some variables relevant to voice behavior, few studies have recognized the influence of firm attributes toward the BVC on sustained voice intention. To fill this research gap, the authors propose a research model to shed light on the role of firm attributes by classifying them into brand- vs community-based firm attributes, which affect intrinsic motivation through two types of social identification, namely brand identification and community identification.

The purpose of this study is to develop a framework for the perceived intelligence of VAs and explore the mechanisms of different dimensions of the perceived intelligence of VAs on users’ exploration intention (UEI) and how these antecedents can collectively result in the highest level of UEI.

An online survey on Amazon Mechanical Turk is employed. The model is tested utilizing the structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) approach from the collected data of VA users (N = 244).

According to the SEM outcomes, perceptual, cognitive, emotional and social intelligence have different mechanisms on UEI. Findings from the fsQCA reinforce the SEM results and provide the configurations that enhanced UEI.

This study extends the conceptual framework of perceived intelligence and enriches the literature on anthropomorphism and users’ exploration. These findings also provide insightful suggestions for practitioners regarding the design of VA products.

Prior researches on the adoption of mobile health services (MHS) concentrate on the subjective cognitive appraisals resulting in technology adoption, while ignoring how to shape those cognitive appraisals by the objective message design strategies which are easier to operate in practice. Based on protection motivation theory (PMT), the current research aims to explore the antecedents of cognitive appraisals by focusing on message design strategies of fear appeal and coping appeal.

A two-stage scenario-based survey of 204 participants was conducted to collect data. The authors chose SPSS and covariance-based structural equation modeling (CB-SEM) approach with the software LISREL 8.8 to test our model.

The results show that the relationship between fear appeal and fear arousal is inverted U-shaped such that the degree of fear arousal is the greatest when the fear appeal is at a moderate level. Perceived usefulness for the message with negative framing is higher than that with positive framing. Furthermore, fear appeal and coping appeal have a significant interaction on the adoption of MHS at different stages.

The sample data of this study come from a special health service of a special group in China, which limits the universality of our research results for other groups or health care services. Therefore, future researchers can validate the model in other research scenarios and sample populations.

This study shows how fear appeal and coping appeal work together to influence individuals' adoption intention. The authors’ findings expand the theoretical depth of PMT and fear theory, enriching the theoretical connotation of framing effect in mobile health technology adoption context, which add new insights to design more persuasive messages through fear appeal and coping appeal for researchers and MHS providers in mobile health communication or propaganda.

Social media provides a convenient way to popularise first aid knowledge amongst the general public. So far, little is known about the factors influencing individuals’ adoption of first aid knowledge on social media. Drawing on the information adoption model (IAM), this study investigates the joint effects of cognitive factors (e.g. perceived information usefulness (PIU)), affective factors (e.g. arousal (AR)) and social factors (e.g. descriptive norms (DN)) on first aid knowledge adoption (KA) and examines their antecedent cues from the perspective of information characteristics.

The data were collected from 375 social media users, and the structural equation model was adopted to analyse the results.

The results indicate that PIU, AR and DN all have positive direct effects on first aid KA. Additionally, the study highlights the positive synergistic effect of AR and PIU. Furthermore, the study suggests that AR is determined by message vividness (MV) and emotional tone (ET), whilst DN are determined by peer endorsement (PEE) and expert endorsement (EXE).

Our research is groundbreaking as it delves into the adoption of first aid knowledge through social media, thus pushing the boundaries of existing information adoption literature. Additionally, our study enhances the IAM by incorporating emotional and social elements and provides valuable insights for promoting the spread of first aid knowledge via social media.

Prior studies fail to reach a consensus on the effects of extrinsic motivation (EM) on knowledge contribution in virtual communities. To fill this research gap, this research proposes two mechanisms of EM – direct effect versus indirect effect via intrinsic motivation (IM) – and introduces prosocial motivation (PSM) as the moderator to define the valence of these two mechanisms.

This research adopts structural equation modeling to validate hypotheses based on 448 responses from XiaoMi online community users.

The results of the moderated mediation analysis show that the direct effect, indirect effect via IM and total effect of EM on knowledge contribution are contingent on the level of PSM. Specifically, as the level of PSM increases, the direct, indirect and total effects of EM on knowledge contribution and the effects of EM on IM change from positive to insignificant and then to negative. Although IM constantly plays an important role across levels of PSM, its effect is stronger when the degree of PSM is high.

This paper advances knowledge of an integrated framework of EM by simultaneously describing its direct and indirect effects, describing its positive and negative effects and untangling the boundary conditions under which each effect of EM applies.

Social media rumor combating is a global concern in academia and industry. Existing studies lack a clear definition and overall conceptual framework of users' rumor-combating behaviors. Therefore, this study attempts to empirically derive a typology of rumor-combating behaviors of social media users.

A three-phase typology development approach is adopted, including content analysis, multidimensional scaling (MDS), interpreting and labeling. Qualitative and quantitative data collection and analysis methods are employed.

The elicited 40 rumor-combating behaviors vary along two dimensions: high versus low difficulty of realization, and low versus high cognitive load. Based on the two dimensions, the 40 behaviors are further divided into four categories: rumor-questioning behavior, rumor-debunking behavior, proactive-appealing behavior, and literacy enhancement behavior.

This typology will serve as reference for social media platforms and governments to further explore the interventions to encourage social media users to counter rumor spreading based on various situations and different characteristics of rumor-combating behaviors.

This study provides a typology of rumor-combating behaviors from a novel perspective of user participation. The typology delves into the conceptual connotations and basic forms of rumor combating, allowing for a comprehensive understanding of the complete spectrum of users' rumor-combating behaviors. Furthermore, the typology identifies the similarities and the differences between various rumor-combating behaviors, thus providing implications and directions for future research on rumor-combating behaviors.

Although microblogs have become an important information source, the credibility of their postings is still a critical concern due to the open and unregulated nature. To understand the antecedents of microblog information credibility, the purpose of this paper is to investigate the dual-role of cognitive heuristics (i.e. the additivity and bias roles) and the effect of gender differences.

This study collected data via an online field survey of active microblog users, and a total of 204 valid responses was received.

This study demonstrates the dual-role of source credibility and vividness, the additivity role of microblog platform credibility, and the bias role of social endorsement. Furthermore, this study also found out gender difference that the additivity role of cognitive heuristics was stronger for men while bias role was stronger for women.

This research enriches the microblog literature by examining the cognitive heuristic determinants as key predictors of microblog information credibility, and contributes to the information credibility literature by identifying and analyzing the dual-role effect of cognitive heuristics and corresponding gender differences.

This study can help organizations better manage their reputation, especially during the reputation crises, and also serves as a reminder to microblog platform operators of the importance of their microblog platform credibility.

This study can help organizations better manage their reputation, especially during the reputation crises, and serves as a reminder to the microblog platform operators of the importance of their microblog platform credibility.

This study investigates the dual-role effect of cognitive heuristics (i.e. the additivity role and bias role) and corresponding gender differences that are less touched on before, and thus provides a more nuanced understanding of the more complex effects of cognitive heuristics.

Periodic inspection and maintenance are essential for effective pavement preservation. Cracks not only affect the appearance of the road and reduce the levelness, but also shorten the life of road. However, traditional road crack detection methods based on manual investigations and image processing are costly, inefficiency and unreliable. The research aims to replace the traditional road crack detection method and further improve the detection effect.

In this paper, a crack detection method based on matrix network fusing corner-based detection and segmentation network is proposed to effectively identify cracks. The method combines ResNet 152 with matrix network as the backbone network to achieve feature reuse of the crack. The crack region is identified by corners, and segmentation network is constructed to extract the crack. Finally, parameters such as the length and width of the cracks were calculated from the geometric characteristics of the cracks and the relative errors with the actual values were 4.23 and 6.98% respectively.

To improve the accuracy of crack detection, the model was optimized with the Adam algorithm and mixed with two publicly available datasets for model training and testing and compared with various methods. The results show that the detection performance of our method is better than many excellent algorithms, and the anti-interference ability is strong.

This paper proposed a new type of road crack detection method. The detection effect is better than a variety of detection algorithms and has strong anti-interference ability, which can completely replace traditional crack detection methods and meet engineering needs.