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With the proliferation of ideas submitted by users in firm-built online user innovation communities, community managers are faced with the problem of user idea overload. The purpose of this paper is to explore the influencing factors on the idea adoption to identify high quality ideas, and then propose a method to quickly filter high value ideas.

The authors collected more than 110,000 data submitted by Xiaomi community users and analyzed the factors affecting idea adoption using a multinomial logistic regression model. In addition, the authors also used BP neural network to predict the idea adoption process.

The empirical results show that idea semantics, number of likes, number of comments, number of related posts, the existence of pictures and self-presentation have positive impact on idea adoption, while idea length and idea timeliness had negative impact on idea adoption. In addition, this paper calculates the idea evaluation value through the idea adoption process predicted by neural network and the mean value of idea term frequency inverse document frequency (TF-IDF).

This empirical study expands the theoretical perspective of idea adoption research by using dual-process theory and enriches the research methods in the field of idea adoption research through the multinomial logistic regression method. Based on our findings, firms can quickly identify valuable ideas and effectively alleviate the information overload problem of online user innovation communities.

Enterprises build online product community to expect users to contribute: opinion sharing (content contribution) and product consumption (product contribution). Previous literature rarely focused on both. The purpose of this paper is to explain user contribution mechanism by identifying content contribution and product contribution.

This research chose Xiaomi-hosted online product community (bbs.xiaomi.cn) and Huawei-hosted online product community (club.huawei.com) where users can freely share ideas and buy products at the same time. Data were crawled from 109,665 community users to construct dependent variable measurement, and 611 questionnaires were used to verify research hypotheses.

The results indicate that both cognitive needs and personal integration needs have a significant positive impact on browse behavior; social integration needs and hedonic needs have a significant positive impact on content contribution behavior. Browse behavior not only directly affects but also indirectly influences product contribution through content contribution behavior.

Findings of this research provide community managers with useful insights into the relationship between content contribution and product contribution.

This study explains the formation mechanism of user product contribution and reveals the relationship between user content contribution and product contribution in online product community. This paper provides a different way of theorizing user contributions by incorporating uses and gratifications theory into the “Motivation-Behavior-Result” framework.

MITRE and the National Security Agency cooperatively developed and maintained a D3FEND knowledge graph (KG). It provides concepts as an entity from the cybersecurity countermeasure domain, such as dynamic, emulated and file analysis. Those entities are linked by applying relationships such as analyze, may_contains and encrypt. A fundamental challenge for collaborative designers is to encode knowledge and efficiently interrelate the cyber-domain facts generated daily. However, the designers manually update the graph contents with new or missing facts to enrich the knowledge. This paper aims to propose an automated approach to predict the missing facts using the link prediction task, leveraging embedding as representation learning.

D3FEND is available in the resource description framework (RDF) format. In the preprocessing step, the facts in RDF format converted to subject–predicate–object triplet format contain 5,967 entities and 98 relationship types. Progressive distance-based, bilinear and convolutional embedding models are applied to learn the embeddings of entities and relations. This study presents a link prediction task to infer missing facts using learned embeddings.

Experimental results show that the translational model performs well on high-rank results, whereas the bilinear model is superior in capturing the latent semantics of complex relationship types. However, the convolutional model outperforms 44% of the true facts and achieves a 3% improvement in results compared to other models.

Despite the success of embedding models to enrich D3FEND using link prediction under the supervised learning setup, it has some limitations, such as not capturing diversity and hierarchies of relations. The average node degree of D3FEND KG is 16.85, with 12% of entities having a node degree less than 2, especially there are many entities or relations with few or no observed links. This results in sparsity and data imbalance, which affect the model performance even after increasing the embedding vector size. Moreover, KG embedding models consider existing entities and relations and may not incorporate external or contextual information such as textual descriptions, temporal dynamics or domain knowledge, which can enhance the link prediction performance.

Link prediction in the D3FEND KG can benefit cybersecurity countermeasure strategies in several ways, such as it can help to identify gaps or weaknesses in the existing defensive methods and suggest possible ways to improve or augment them; it can help to compare and contrast different defensive methods and understand their trade-offs and synergies; it can help to discover novel or emerging defensive methods by inferring new relations from existing data or external sources; and it can help to generate recommendations or guidance for selecting or deploying appropriate defensive methods based on the characteristics and objectives of the system or network.

The representation learning approach helps to reduce incompleteness using a link prediction that infers possible missing facts by using the existing entities and relations of D3FEND.

Fabric has complicated anisotropic mechanical behavior because of the woven pattern and complex physical properties. However, most current fabric simulation models are not satisfied because the models are usually geometrical models with stiffness parameters.

In this paper, the authors present a modeling technique to simulate fabric with Riemann manifold. The proposed nonlinear model is formed with ridge wave-curved surface based on the Riemann zero curvature, and the authors develop a solution to conserve the surface area. It decomposes the m × n matrix constituting the fabric into several batches and processes the fabric dots in batches. In this model, the distance between any two adjacent particles of the fabric's is assumed to be equal, and the area of the curved surface is always constant, and the inclination and decay of the ridge wave-curved surface are also considered.

As the result, the simulated shape is lifelike. In time cost performance, the model improves the efficiency of the fabric styling and meets the requirements of real-time simulation.

The proposed nonlinear model is formed with ridge wave-curved surface based on the Riemann zero curvature, and the authors develop a solution to conserve the surface area.

While education policymakers in Asian polities find it difficult to resist the English language which has attained a new status in “late capitalism”, prevailing policy-level perceptions also suggest that a ruthless adoption of English may undermine national languages, identities and cultures. Despite the heightened commercialisation of English as a global language this policy dilemma raises some critical questions. For example, how can individual entrepreneurs also acting as “language policy actors” effectively promote for-profit English teaching ventures without being accused of compromising national interests, identities and traditions? This article makes a modest attempt towards addressing these questions by conducting a critical analysis of Li Yang’s English teaching venture called “Crazy English” in China and its underlying discourses.

From a sample of English teaching resources available on its official website, this paper identifies and discusses four major discourses on the relationship between English and individual entrepreneurship in English on the one hand and Chinese and China’s national values and interests on the other.

This paper argues that collectively these discourses represent a model of “edu-business” in English language teaching that reconciles the dichotomies between nationalism and post-nationalism, individualism and collectivism and public and private interests in a neoliberal world.

With the onset of globalisation and its impact on all aspects of life including the economy, education and communication, there have been on-going debates on the emerging tensions between the nation-state and the forces of trans/post-nationalism, the latter being underpinned by neo-liberalism. These tensions have also been observed in the fields of English and English language education. While research has examined how macro-level policymakers respond to globalisation through their English language policies, there has been limited work on how individual language policy actors engaged in the commercialisation of English reconcile the apparently irreconcilable forces of nationalism and post-nationalism. The contribution of the present article lies in illustrating a case that seeks to reconcile these forces through discourses and discursive strategies.

Drawing on the fairness theory, this paper aims to propose a conceptual framework that investigates how co-creation in the failed service delivery (coproduction intensity) and co-creation in the service recovery affect customers’ evaluation of the firm’s competence, justice and ethicalness, and ultimately their willingness to co-create in the future.

Tax services were chosen as the research context. A consumer panel consisting of individuals who live in the USA and have used tax preparation services within the past year was recruited. The first study explores what happens to customers’ ethical perceptions during a failed co-created service encounter. A secondary study investigates what happens to customers’ ethical perceptions in the event that the failed co-created service is recovered.

The findings show that customers’ perceptions of the firm’s abilities and ethics are impeded by coproduction intensity but favorably influenced by co-creation of recovery.

A sense of ethicalness and fairness is violated when co-created service failure occurs, but fortunately, practitioners can count on engaging customers in the service recovery process as co-creators of the solution to positively alter perceived ethicalness and fairness.

Failed co-created services represent an under-researched area in the marketing literature. Current investigations of co-created service failures have largely approached the notion of fairness from a perceived justice perspective without referencing ethical judgments. However, fairness is grounded in basic ethical assumptions of normative treatment. This research is among the first to highlight the importance of perceived ethicalness in the context of co-created service failure and recovery.

The drive shaft and the distribution shaft of a traditional radial piston pump are in a cantilever state. To solve this problem, this paper aims to present a radial piston pump with through shaft driving and valve plate distribution.

The working principle of the pump is discussed in detail. In this radial piston pump, valve plate distribution parts are designed to distribute oil to the piston chambers, and the distribution shaft is replaced. A bearing is installed between the stator and rotator to reduce the friction. The transmission shaft is supported by two bearings to ensure smooth operation. The support force of the transmission shaft is optimized. In addition, the flow pulsation principle is presented. To accomplish the change, the displacement of the radial piston pump, the proportional control system is designed.

After completing the machining and assembly of the pump, an experimental study was carried out. The results show that the output flow of the pump is basically the same as the theoretical flow.

The friction between the slipping shoes and the stator is greatly reduced due to the function of rolling bearings. The higher stability of the driveshaft is obtained for the reason of double-sided support. The radial piston pump has a novel structural design in reducing the friction between the shoes and the stator and improving the stability of the transmission shaft.

Effectuation, which articulates the process of entrepreneurial action based on nonpredictive control logic, is receiving extensive scholarly attention. What drives the effectual entrepreneurship is featured with high complexity. However, existing studies ignored the complex driving forces underlying entrepreneurial decision-making. Building on a configurational perspective, the purpose of this study was to examine the combinative effects of environmental uncertainty and entrepreneurs’ means on effectual entrepreneurship.

Drawing on 54 entrepreneurs who are launching new ventures in China, this study adopts a fuzzy-set Qualitative Comparative Analysis (fsQCA) to investigate two sets of antecedent conditions and how they form different combinations for a highly effectual entrepreneurship.

Our findings disclose four highly effectual entrepreneurship paths involving novice–specialist effectual entrepreneurship in a highly uncertain environment, socialite–specialist effectual entrepreneurship in a highly uncertain environment, pure-specialist effectual entrepreneurship and resourceful effectual entrepreneurship, and one path of barefoot noneffectual entrepreneurship in a highly uncertain environment, which reveals the complex nature of environmental uncertainty and entrepreneurs’ means in driving entrepreneurs to adopt effectuation.

Our study makes the following contributions. First, by taking a configurational perspective, we are able to obtain an elaborate view of the combined effects of environmental uncertainty and entrepreneurs’ means on effectual entrepreneurship. Second, we expand prior thinking on the relationship between environmental uncertainty and effectuation. Third, our study offers a more delicate understanding of entrepreneurs’ means in driving effectuation by splitting means into three separate factors.

This study aims to investigate the effect of social media use on healthcare workers’ psychological safety and task performance and the moderating role of perceived respect from patients during public health crises.

To test the proposed moderated mediation model, a survey was conducted in 12 Chinese medical institutions. A total of 637 valid questionnaires were collected for data analysis.

The results revealed that psychological safety mediated the relationships between task-related social media (TSM) use and social-related social media (SSM) use and task performance. In addition, perceived respect from patients moderated the relationship between TSM use and psychological safety, as well as the indirect relationship between TSM use and task performance through psychological safety.

This study sheds new light on understanding how different types of social media use influence task performance in the context of public health crises. Furthermore, this study considers the interactions of healthcare workers with colleagues and patients and examines the potential synergistic effects of these interactions on healthcare workers’ psychological state and task performance.

Governments around the world have used social distancing methods to slow the spread of COVID-19. Some people, however, have ignored repeated warnings about the need to maintain social distance. The purpose of this study was to segment individuals based on their perceptions of social distancing with respect to shared constructs, such as attitudes and demographic profiles. The findings can assist social marketing efforts to target specific groups for health campaigns.

This study used a priori methods, meaning that the type and number of segments were determined in advance. Amazon’s Mturk was used to collect data from an online sample of US residents (n = 759) in May 2020, in the midst of the COVID-19 pandemic.

Individuals’ perceptions of social distancing were segmented as follows: Segment 1 = majority social distancing followers; Segment 2 = social distancing inbetweeners; and Segment 3 = minority social distancing rebels. Interestingly, some of these segments were strongly affiliated with political parties. In addition, the results show attitudes toward social distancing appear to be influenced by individuals’ beliefs regarding their susceptibility to coronavirus and the potential severity of the symptoms or disease’s impact on their lives.

This study makes several theoretical and practical contributions to the literature on these issues. In particular, it involved the application of the health belief model to the context of attitudes toward social distancing, which were found to be influenced by individuals’ beliefs regarding whether they are susceptible to coronavirus infection and whether the symptoms or disease could have a significant effect on their lives.

The results of this study will assist public health researchers, social marketers and policymakers in efforts to improve the effectiveness of health campaigns. Public health campaigns in the USA need to be bi-partisan. The finding that the social distancing rebels were mostly Republicans is consistent with an earlier report that those who identify with this party were less convinced than those who identified with the Democratic party regarding the efficacy of maintaining social distancing measures and more concerned about the adverse effects of these measures on the economy.

Only a few studies have segmented populations based on their perceptions of social distancing. This study was designed to understand the distinguishing features of such segments to enhance health messaging and content and convince those reluctant to engage in social distancing to view the issue from the perspective of marketing and medical practitioners.