Search results

This study aims to investigate the mechanism of the misinformation spread based on the elaboration likelihood model and the effects of four factors – emotion, topic, authority and richness – on the depth, breadth and structural virality of misinformation spread.

The authors collected 2,514 misinformation microblogs and 142,006 reposts from Weibo, used deep learning methods to identify the emotions and topics of misinformation and extracted the structural characteristics of the spreading network using the network analysis method.

Results show that misinformation has a smaller spread size and breadth than true news but has a similar spread depth and structural virality. The differential influence of emotions on the structural characteristics of misinformation propagation was found: sadness can promote the breadth of misinformation spread, anger can promote depth and disgust can promote depth and structural virality. In addition, the international topic, the number of followers, images and videos can significantly and positively influence the misinformation's spread size, depth, breadth and structural virality.

The influencing factors of the structural characteristics of misinformation propagation are clarified, which is helpful for the detection and management of misinformation.

The purpose of this paper is to present an automatic approach for mesh sizing field generation of complicated  computer-aided design (CAD) models.

In this paper, the authors present an automatic approach for mesh sizing field generation. First, a source point extraction algorithm is applied to capture curvature and proximity features of CAD models. Second, according to the distribution of feature source points, an octree background mesh is constructed for storing element size value. Third, mesh size value on each node of background mesh is calculated by interpolating the local feature size of the nearby source points, and then, an initial mesh sizing field is obtained. Finally, a theoretically guaranteed smoothing algorithm is developed to restrict the gradient of the mesh sizing field.

To achieve high performance, the proposed approach has been implemented in multithreaded parallel using OpenMP. Numerical results demonstrate that the proposed approach is remarkably efficient to construct reasonable mesh sizing field for complicated CAD models and applicable for generating geometrically adaptive triangle/tetrahedral meshes. Moreover, since the mesh sizing field is defined on an octree background mesh, high-efficiency query of local size value could be achieved in the following mesh generation procedure.

How to determine a reasonable mesh size for complicated CAD models is often a bottleneck of mesh generation. For the complicated models with thousands or even ten thousands of geometric entities, it is time-consuming to construct an appropriate mesh sizing field for generating high-quality mesh. A parallel algorithm of mesh sizing field generation with low computational complexity is presented in this paper, and its usability and efficiency have been verified.

This study aims to investigate the performance of filament-based material extrusion additive manufacturing (MEX), combined with debinding and sintering, as a novel approach to manufacturing ceramic components.

A commercial ZrO₂ filament was selected and analysed by infra-red (IR) spectroscopy, rheology and thermo-gravimetry. The influence of the print parameters (layer thickness, flow rate multiplier, printing speed) and sintering cycle were investigated to define a suitable printing and sintering strategy. Biaxial flexure tests were applied on sintered discs realised with optimised printing strategies, and the results were analysed via Weibull statistics to evaluate the mechanical properties of printed components. The hardness and thermal conductivity of sintered components were also tested.

Layer thickness and flow rate multiplier of the printing process were proved to have significant effect on the density of as-printed parts. Optimised samples display a sintered density >99% of the theoretical density, 20% linear sintering shrinkage, a characteristic flexural strength of 871 MPa with a Weibull modulus of 4.9, a Vickers hardness of 12.90 ± 0.3 GPa and a thermal conductivity of 3.62 W/mK. Gyroids were printed for demonstration purposes.

To the best of the authors’ knowledge, this work is the first to apply biaxial flexure tests and Weibull statistics to additively manufactured MEX zirconia components, hence providing comparable results to other additive technologies. Moreover, fractography analysis builds the connection between printing defects and the fracture mechanism of bending. This study also provides guidelines for fabricating high-density zirconia components with MEX.

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.

Since stock return and volatility matters to investors, this study proposes to incorporate the textual sentiment of annual reports in stock price crash risk prediction.

Specific sentences gathered from management discussions and their subsequent analyses are tokenized and transformed into numeric vectors using textual mining techniques, and then the Naïve Bayes method is applied to score the sentiment, which is used as an input variable for crash risk prediction. The results are compared between a collection of predictive models, including linear regression (LR) and machine learning techniques.

The experimental results find that those predictive models that incorporate textual sentiment significantly outperform the baseline models with only accounting and market variables included. These conclusions hold when crash risk is proxied by either the negative skewness of the return distribution or down-to-up volatility (DUVOL).

It should be noted that the authors' study focuses on examining the predictive power of textual sentiment in crash risk prediction, while other dimensions of textual features such as readability and thematic contents are not considered. More analysis is needed to explore the predictive power of textual features from various dimensions, with the most recent sample data included in future studies.

The authors' study provides implications for the information value of textual data in financial analysis and risk management. It suggests that the soft information contained within annual reports may prove informative in crash risk prediction, and the incorporation of textual sentiment provides an incremental improvement in overall predictive performance.

Scholars of persuasion have long made a distinction between appeals to logic, emotion and authority- logos, ethos and pathos- but ideas developed to account for live face-to-face conversation processes must also be tested in new media. We aimed to test the effectiveness of these three strategies in one-to-one chats through different communication media.

With a 3 × 3 × 2 between-subject factorial design, we tested these three strategies in one-to-one chats (female–female or male–male pairs) through three communication media: face-to-face, Skype video or Skype text. The persuasion scenario was adapted from prior studies in which students were presented with the idea of requiring a comprehensive exam as part of their degree. The participants were all undergraduate students of a major university in USA.

Our results showed trivial differences between female–female and male–male conditions. The logos appeal worked best overall in persuading the participants to change their reported attitudes. Additionally, the explanations provided by the participants for their own opinions were most like the persuasion scripts in the logos condition compared to the other two appeal conditions. Separately, participants indicated some disapproval of the pathos appeal in the text-based chat condition, although this did not seem to make a difference in terms of actual attitude change.

One major limitation of our study is that our subjects are college students and therefore are not representative of Internet users in general. Future research should test these three types of persuasion strategies on people of diverse backgrounds. For example, while logos seems to be most effective strategy in persuading college students (at least in our study), pathos or ethos may be more effective when one attempts to persuade people of different backgrounds.

Although it is enough for a statistical test, our sample size is still relatively small due to constraints on time, personnel and funding. We also recognize that it is challenging both conceptually and empirically to compare the effectiveness of three persuasion strategies separately.

Our findings suggest it is helpful to use fact-checking tools to combat disinformation in cases where users may not have sufficient domain knowledge or may not realize the need to identify or examine the given information. Additionally, it may require more effort to negate the impact of the disinformation spread than correcting the information, as some users may not only believe false information but also may start to reason in ways similar to those presented in the disinformation messages.

Past studies on online persuasion have limitedly examined whether and how communication media and persuasion strategies interact in one-to-one persuasion sessions. Our experiment makes an attempt to close this gap by examining the persuasion process and outcome in three different communication media and with three different persuasion strategies.

In this paper, the authors study the entry and outsourcing strategies of manufacturer while considering the brand spillover effect resulting from outsourcing. The supply chain comprises two manufacturers: one being the entrant with a strong brand, and the other as the incumbent with a weak brand. The entrant decides whether and how to enter the market.

Stackelberg game is applied to study the optimal strategies for the manufacturers. This paper conducts a comparative analysis on four situations, yielding conclusions and managerial insights.

The results show that, for the entrant, there is no need to worry about the brand spillover effect in the outsourcing process, which is very interesting and counterintuitive. To get further, the authors find the reason: The spillover effect causes the entrant’s equilibrium retail price to grow faster than the wholesale price. They also prove that a stronger brand effect empowers the entrant to challenge industry barriers, while the impact of the brand spillover effect is the opposite. For the incumbent who acts as the weak party in this issue, it is demonstrated that the optimal choice is to continue selling when facing the encroachment and outsourcing call from the entrant.

Differing from previous studies, the authors notice the brand spillover effect caused by outsourcing when studying company’s entry strategy. They further divide the brand effect into two parts, one of which does not exhibit a spillover.

The purpose of this paper is to examine the alternative accounts produced by Green Earth Volunteers (GEV), a Chinese environmental non-governmental organisation, over a 10-year period in the context of their campaign to create visibilities about hydroelectric dam projects along the Chang Jiang.

Drawing on conceptions of the human–nature relationship, including those evident in ancient Chinese philosophy and mythology, and the Chinese way of viewing and resolving conflict, this paper offers an interpretive analysis of the alternative accounts of GEV in terms of their form and content.

In terms of their content, the alternative accounts reflect elements of interrelated thinking, being underpinned by a recognition of the relationship between humans and nature, which is evident in Confucianism, Taoism and ancient Chinese mythology. The strategies adopted by GEV are a non-confrontational but feasible way to promote their ecological beliefs in the Chinese context.

The study suggests that social and environmental accounting (SEA) in developing countries is steeped in local cultural and philosophical traditions that need to be considered and incorporated into the design of alternative accounts.

The study contributes to the very limited literature that offers qualitative analyses of SEA in developing countries.

This study aims to excavate the external and internal driving factors of enterprise digital innovation and further condense the function mechanisms and response actions of the innovation process as well as the final innovation outcomes to propose the theoretical framework of enterprise digital innovation with the logic thread of “innovation motivation–innovation process–innovation result”.

Based on the digital background and integrating previous case studies on enterprise digital innovation, this study uses qualitative meta-analysis to explore the motivations of enterprise digital innovation, the function mechanisms and response actions of innovation process as well as the innovation outcomes.

This study finds that digitally transformed enterprises driven by external environmental factors and internal organizational factors follow the logic of adaptive and open innovation, and finally accomplish the digital innovation results of products, services, processes, business models, technology and social responsibility through the response actions of adaptation and interaction mechanisms.

In the digital economy era, digital innovation has become the key strategic choice for enterprise transformation, upgrading and innovation. Why and how enterprises realize digital innovation with the help of emerging digital technology remain to be explored. This study has important theoretical significance and practical value for the digital innovation and transformation of enterprises under the digital background.

This paper aims to examine and compare the associations between financial capability and financial anxiety (FA) before and during the coronavirus disease 2019 (COVID-19) pandemic. Specifically, financial capability is measured by three indicators: financial knowledge, financial behavior and financial confidence. This study also examines and compares the association among different income groups before and during the pandemic.

Data are from 2018 to 2021 National Financial Capability Study (NFCS). Structural equation modeling (SEM) is employed to examine the direct and indirect associations between financial capability factors and FA. Furthermore, this paper also conducts multi-group SEM for three income groups to examine the heterogeneous effects of household income.

Both before and during the pandemic, financial knowledge is directly positively and financial behavior is directly negatively associated with FA. In addition, both financial knowledge and financial behavior are positively associated with financial confidence, which in turn is negatively associated with FA. However, when taking the indirect effects into consideration, the total effects of financial capability factors on FA are all negative. Furthermore, the pandemic has intensified the negative association between financial behavior and FA rather than financial knowledge or financial confidence. Multi-group SEM shows that the positive direct effects of financial knowledge are only significant in the low-income group, while the negative direct effects of financial behavior are only significant in the low- and middle-income groups before the pandemic. However, direct effects of financial knowledge and financial behavior are significant in all income groups during the pandemic.

First, this study specifies a construct, financial confidence, to proxy perceived financial capability. Second, it examines the mediating role of financial confidence in the association between the other two financial capability factors (financial knowledge and financial behaviors) and FA. Third, it also compares the associations between financial capability factors and FA before and during the COVID-19 pandemic.