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Crowdsourcing refers to a new business model in which enterprises or individuals publish tasks or problems, attracting freelancers or contributors to participate in solving tasks, submitting bids and allowing task seekers to choose the final solution. How to attract more quantity and quality of contributors to submit their solutions through a crowdsourcing platform has become a vital question.

In this study, the authors use web crawling to obtain 43,265 effective tasks in EPWK website (www.epwk.com) to probe how to elevate the quantity and quality of contributors via task reward design. This study uses the hierarchical linear model to probe the research questions.

Results show that, with the increase of task reward, the quantity of contributors goes up first and then goes down (inverted U shape), whereas the quality of contributors goes down first and then goes up (U sharp). Moreover, the authors investigate the moderating effects of another task design attribute, task duration. This study finds that task duration weakens the effect of task reward on the quantity of contributors while strengthening the effects of task reward on the quality of contributors.

First, this study theoretically probes two key aspects of task performance, namely, the quantity and quality of contributors, which expand the scope of task performance evaluation. Second, this study reconciles previous concern about the relationship of task reward and performance, which is different from previous studies that have paid more attention to the single perspective of their relationship. Finally, the authors investigate the moderating effects of task duration, which further uncover the mechanism behind task reward and performance, that is, the quantity and quality of task contributors.

Artificial intelligence (AI) is experiencing growth and prosperity worldwide because of its convenience and other benefits. However, AI faces challenges related to consumer resistance. Thus, drawing on the user resistance theory, this study explores factors that influence consumers’ resistance to AI and suggests ways to mitigate this negative influence.

This study tested four hypotheses across four studies by conducting lab experiments. Study 1 used a questionnaire to verify the hypothesis that AI’s “substitute” image leads to consumer resistance to AI; Study 2 focused on the role of perceived threat as an underlying driver of resistance to AI. Studies 3–4 provided process evidence by the way of a measured moderator, testing whether AI with servant communication style and literal language style is resisted less.

This study showed that AI’s “substitute” image increased users' resistance to AI. This occurs because the substitute image increases consumers’ perceived threat. The study also found that using servant communication and literal language styles in the interaction between AI and consumers can mitigate the negative effects of AI-substituted images.

This study reveals the mechanism of action between AI image and consumers’ resistance and sheds light on how to choose appropriate image and expression styles for AI products, which is important for lowering consumer resistance to AI.

The continuous impact of the pandemic and the downturn of the global economy have brought new challenges to the tourism industry. In this context, effectively attracting consumers and improving user stickiness are the top priorities of tourism platform companies. This study explores the impact of ethical concerns raised by new issues under the multi-governance environment on user stickiness. Based on the trust theory, the authors provide solutions for tourism platforms.

This study adopted a quantitative approach, gathering survey data via an online platform. A total of 400 participants were investigated, and 356 valid questionnaires were returned, with a recovery rate of 89%. Questionnaires that did not meet the inclusion criteria were excluded, leaving 298 valid responses.

Studies have found that consumers' ethical concerns about platform companies are key factors affecting user stickiness, and among these, consumer trust plays a mediating role. They have found that corporate social responsibility (CSR) behaviours help alleviate ethical concerns and improve trust in enterprises. At the same time, enterprises should properly control the number of platform collaborators, and excessive platform cooperation negatively moderates the impact of consumer ethical concerns on competence-based trust.

This study complements the deficiency of previous research with regard to ethical concerns in a multi-governance environment. These findings indicate that subject diversity exacerbates the negative impact of ethical concerns on consumer trust; however, CSR alleviates the impact of ethical concerns on consumer trust.

In order to encourage customers to try experience virtual tourism, researchers and practitioners pay more attention on how to improve customers' perception of authenticity.

Using the theory of cross-sensory compensation, through 4 experiments, this study examines the impact of social interaction and cross-sensory strategies on the relationship between virtual reality (VR) and improving customers' perception of authenticity and customer experience.

Through experimental research, this paper finds that (1) VR immersion has a significant positive impact on perception of authenticity, which in turn acts on customers' virtual tourism experience. (2) In addition, social interaction strengthens the relationship between VR immersion and customers' perception of authenticity. (3) The cross-sensory compensation has a positive effect on VR immersion to enhance customers' perception of authenticity.

The research conclusion provides a direction for further discussion on how to improve customers' perception of authenticity and provides theoretical guidance and reference for the virtual tourism industry.

The purpose of this paper is to investigate the relationships between supply chain quality management (SCQM) and firm performance (including quality safety performance and sales performance) leveraging social co-regulation as a moderator.

Using survey data collected from 203 food manufacturers in China, a series of hierarchical linear modeling analyses were conducted to test hypotheses on the relationships between SCQM and firm performance.

The findings are threefold. First, all three dimensions of food SCQM practices, i.e., supplier quality management, internal quality management, and customer quality management, have significant positive effects on an enterprise's quality safety performance and sales performance. Second, SCQM practices can also increase sales performance indirectly through quality safety performance as a mediator. Third, while social co-regulation has no significant effect on the relationship between supplier quality management and quality safety performance, it has a significant moderating effect on the relationship between internal quality management and quality safety performance, customer quality management and quality safety performance.

This study not only integrates SCQM with social co-regulation but also explores the regulating effect of social co-regulation through empirical analysis, thereby providing a theoretical base for future research. However, this research is confined to China and so the results are not necessarily generalizable to other countries.

The findings inform managers of the importance in enhancing awareness of food quality and safety as well as in improving their sensitivity to salient quality demands of external stakeholders in order to achieve better SCQM practices. The findings can also inform policymakers of the significance in designing a systematic multi-agent cooperation mechanism for food SCQM as well as to build an effective information sharing mechanism for social co-regulation of food safety.

This study contributes to knowledge by empirically examining the relationships of SCQM practices with firm performance. It also expands the scope of SCQM research by incorporating social co-regulation in the study framework.

The microstructure and properties of Zn-Sn coating on sintered Nd-Fe-B magnets were investigated by the grain boundary diffusion process, to improve the corrosion resistance of magnet surface and explore the feasibility of realizing the lower-temperature grain boundary diffusion.

The Zn-Sn coating was deposited on sintered Nd-Fe-B magnets by magnetron sputtering, and then the Zn-Sn coated magnets were put into the vacuum tube furnace for grain boundary diffusion process. The morphology and structure of Zn-Sn coating as well as its mechanical properties and corrosion resistance were investigated.

Results showed that the particle size of vacuum diffusion-treated Zn-Sn coating increased and the particle agglomeration was weakened with increasing diffusion temperature, and the non-vacuum diffusion-treated Zn-Sn coating was oxidized to generate SnO₂ and ZnO compounds. The binding force of coating first increased and then decreased with increasing diffusion temperature, and the maximum binding force was obtained at 540 °C. The binding force and corrosion resistance of non-vacuum diffusion-treated Zn-Sn coating were higher than the vacuum diffusion-treated Zn-Sn coating at the same diffusion temperature.

The Zn-Sn coating after diffusion treatment can provide complete protection, and the coating elements diffusion can be carried out at the same temperature as the secondary aging of sintered Nd-Fe-B magnets. Simultaneously, further diffusion process optimization needs to be completed because the diffusion depth is very low and only about 10 µm, which does not meet the requirements of traditional grain boundary diffusion method.

The purpose of this study to analyze the plastic anisotropy of 6061 aluminum alloy with finite deformation using crystal plasticity finite element method.

A representative volume element (RVE) model was constructed by Voronoi tessellation. In this model, grain shapes, grain orientations and distribution of grains were involved. The mechanical response of the component under composite loading was tested using specify cruciform specimen. Moreover, different stress and strain states in the specific central region were analyzed to reveal the effects of complex loading.

We calculated the influence of misorientation of adjacent grains as well as the evolution of the micro structure’s plastic deformation on the macroscopic deformation of the structure. Geometry design for the cruciform specimen helps obtain a homogenous distribution of the stress and strain at the specimen center. In this process, the initial grain orientation is also an important factor, and the larger misorientations between special grains may cause greater stress concentration.

The influence of micro-scale factors on macro-scale plastic anisotropy of AA6061 is analyzed using RVE model and cruciform specimen, and they offer a reference for related research.

This paper aims to focus on the spatial docking task of unmanned vehicles under ground conditions. The docking task of military unmanned vehicle application scenarios has strict requirements. Therefore, how to design a docking robot mechanism to achieve accurate docking between vehicles has become a challenge.

In this paper, first, the docking mechanism system is described, and the inverse kinematics model of the docking robot based on Stewart is established. Second, the genetic algorithm-based optimization method for multiobjective parameters of parallel mechanisms including workspace volume and mechanism flexibility is proposed to solve the problem of multiparameter optimization of parallel mechanism and realize the docking of unmanned vehicle space flexibility. The optimization results verify that the structural parameters meet the design requirements. Besides, the static and dynamic finite element analysis are carried out to verify the structural strength and dynamic performance of the docking robot according to the stiffness, strength, dead load and dynamic performance of the docking robot. Finally, taking the docking robot as the experimental platform, experiments are carried out under different working conditions, and the experimental results verify that the docking robot can achieve accurate docking tasks.

Experiments on the docking robot that the proposed design and optimization method has a good effect on structural strength and control accuracy. The experimental results verify that the docking robot mechanism can achieve accurate docking tasks, which is expected to provide technical guidance and reference for unmanned vehicles docking technology.

This research can provide technical guidance and reference for spatial docking task of unmanned vehicles under the ground conditions. It can also provide ideas for space docking missions, such as space simulator docking.

Hexahedral meshing is one of the most important steps in performing an accurate simulation using the finite element analysis (FEA). However, the current hexahedral meshing method in the industry is a nonautomatic and inefficient method, i.e. manually decomposing the model into suitable blocks and obtaining the hexahedral mesh from these blocks by mapping or sweeping algorithms. The purpose of this paper is to propose an almost automatic decomposition algorithm based on the 3D frame field and model features to replace the traditional time-consuming and laborious manual decomposition method.

The proposed algorithm is based on the 3D frame field and features, where features are used to construct feature-cutting surfaces and the 3D frame field is used to construct singular-cutting surfaces. The feature-cutting surfaces constructed from concave features first reduce the complexity of the model and decompose it into some coarse blocks. Then, an improved 3D frame field algorithm is performed on these coarse blocks to extract the singular structure and construct singular-cutting surfaces to further decompose the coarse blocks. In most modeling examples, the proposed algorithm uses both types of cutting surfaces to decompose models fully automatically. In a few examples with special requirements for hexahedral meshes, the algorithm requires manual input of some user-defined cutting surfaces and constructs different singular-cutting surfaces to ensure the effectiveness of the decomposition.

Benefiting from the feature decomposition and the 3D frame field algorithm, the output blocks of the proposed algorithm have no inner singular structure and are suitable for the mapping or sweeping algorithm. The introduction of internal constraints makes 3D frame field generation more robust in this paper, and it can automatically correct some invalid 3–5 singular structures. In a few examples with special requirements, the proposed algorithm successfully generates valid blocks even though the singular structure of the model is modified by user-defined cutting surfaces.

The proposed algorithm takes the advantage of feature decomposition and the 3D frame field to generate suitable blocks for a mapping or sweeping algorithm, which saves a lot of simulation time and requires less experience. The user-defined cutting surfaces enable the creation of special hexahedral meshes, which was difficult with previous algorithms. An improved 3D frame field generation method is proposed to correct some invalid singular structures and improve the robustness of the previous methods.

Drawing on the premise that the media play a vital corporate governance role, this paper aims to investigate the association between media coverage and financial report restatements.

Based on a sample of Chinese listed companies over the period 2011–2015, the authors use ordinary least squares regression as well as a number of additional tests. To mitigate the endogeneity issue, the authors use a two-stage Heckman test and a propensity score matching model.

The authors document a negative and significant association between media coverage and restatements, suggesting that firms with high media coverage engage less in financial restatements. The authors further explore the moderating effects of internal control quality and state ownership on the association between media coverage and restatements. Regression results reveal that the governance role of the media is more pronounced for state-owned enterprises than for private firms. However, no significant difference in the disciplining effect of media coverage is found for firms with high, versus low, internal control quality.

The role of the media in corporate governance and financial reporting quality has been well documented. In emerging economies, such a role has been overlooked. As a result, the purpose of this study is to fill that void. Furthermore, prior research ignores the impacts of state ownership and the internal control environment on the media's governance role.