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This paper aims to explore the critical factors which affect the quality of preschool education service so that targeted and effective measures to improve service quality can be put forward.

Evidential theory is applied to aggregate experts’ knowledge, and a fuzzy cognitive map (FCM) model of preschool education service quality is established to further carry out a simulation for inference, thus figuring out the critical factors to improve service quality.

The simulation results show that the main body of supervision and environment of governments and policies are two critical factors affecting the quality of preschool education service. More emphasis should be put on these two aspects, and corresponding measures can be put forward so as to ensure the quality of preschool education service.

This paper proposes a new model based on FCM and evidential theory to study the factors affecting preschool education service quality.

The purpose of this paper is to study the influence of calcium sulfate whiskers (CSWs) on the thermodynamic properties and shape memory properties of epoxy/cyanate ester shape memory composites.

To improve the mechanical properties of shape memory cyanate ester (CE)/epoxy polymer (EP) resin, high performance CSWs were used to reinforce the thermo-induced shape memory CE/EP composites and the shape memory CSW/CE/EP composites were prepared by molding. The effect of CSW on the mechanical properties and shape memory behavior of shape memory CE/EP composites was investigated.

After CSW filled the shape memory CE/EP composites, the bending strength of the composites is greatly improved. When the content of CSW is 5 Wt.%, the bending strength of the composite is 107 MPa and the bending strength is increased by 29 per cent compared with bulk CE/EP resin. The glass transition temperature and storage modulus of the composites were improved in CE/EP resin curing system. However, when the content of CSW is more than 10 Wt.%, clusters are easily formed between whiskers and the voids between whiskers and matrix increase, which will lead to the decrease of mechanical properties of composites. The results of shape memory test show that the shape memory recovery time of the composites decreases with the decrease of CSW content at the same temperature. In addition, the shape recovery ratio of the composites decreased slightly with the increase of the number of thermo-induced shape memory cycles.

A simple way for fabricating thermo-activated SMP composites has been developed by using CSW.

The outcome of this study will help to fabricate the SMP composites with high mechanical properties and the shape memory CSW/CE/EP composites are expected to be used in space deployable structures.

The purpose of this paper is to show that research on policy diffusion mechanism of Government Procurement of Public Services (GPPS) is beneficial to improve the efficiency of policy formulation and implementation.

In view of the four dimensions which are internal demand, external pressure, policy innovation environment and service characteristic, a system of factors affecting policy diffusion is established. On this basis, a Multilayer Fuzzy Cognitive Map (MFCM) model for policy diffusion of GPPS is constructed. Nonlinear Hebbian Learning algorithm and genetic algorithm are applied to optimize the two components of the MFCM model, which are relationship between nodes at the same layer and influence weights between nodes at different layers, respectively. Taking Nanjing municipal government purchasing elderly-care services in China as the empirical object, simulation of policy diffusion based on the MFCM model is carried out, aiming to obtain the key factors influencing policy diffusion and the dynamic diffusion mechanism of GPPS policy.

Research results show that, compared with monolayer Fuzzy Cognitive Map, the MFCM model converges faster. In addition, simulation results of policy diffusion indicate that economic development level of jurisdiction, superior pressure, administrative level and operability of services are key influencing factors which are under four dimensions correspondingly. And the dynamic influencing mechanism of key factors has also been learned.

This paper constructs the MFCM model, which is a new approach based on several monolayer FCMs, to study the policy diffusion mechanism.

The effect of board intellectual capital on non-profit organizational performance in non-western, less developed economies has been an important yet under-researched area. Given that the institutional and business relationships of a board account for the majority of board intellectual capital, the purpose of this paper is to fill the previously mentioned research gap by addressing how the interactions of the two relationships of board directors influence Chinese philanthropic foundation performance.

Following Creswell's (2014) explanatory sequential mixed-methodology, a qualitative study (Study 1) was first conducted to pre-test the assumptions, and then a quantitative study (Study 2) was carried out based on a secondary database of 1,405 Chinese philanthropic foundations to further examine the hypotheses. Several regression models were built for analyzing the results.

Study 1 confirmed that Chinese philanthropic foundations gained greater revenues and hosted more public welfare activities by leveraging the reinforcing or complementary effects of board directors' intellectual capital to improve organizational performance. Study 2 further examined the hypotheses that the interactions of intellectual capital increased the total revenue and public welfare expenditure of the foundations; however, significant positive relationships were only identified in foundations at the local level, and no significant associations were found in those at the national level.

The research indicates that the intellectual capital of board directors may influence the performance of their philanthropic foundations. Thus, Chinese philanthropic foundations should be more aware of the importance of this influence when determining which candidates will join the board.

The study makes significant contributions to the existing knowledge of the development of non-governmental organizations; it incorporates the resource dependence theory and agency theory into understanding how the intricate interactions between the institutional and business relationships of board directors affect foundation performance and how the jurisdiction affiliations act as a boundary condition for such relationships in a non-western setting such as China.

Researchers continue to address the concept of self-disclosure because it is foundational for helping social networking sites (SNS) function and thrive. Nevertheless, the authors' literature review indicates that uncertainty remains around the underlying mechanisms and factors involved in the self-disclosure process. The purpose of this research is to better understand the self-disclosure process from the lens of dual-process theory (DPT). The authors consider both the controlled factors (i.e. self-presentation and reciprocity) and an automatic factor (i.e. social influence to use an SNS) involved in self-disclosure and broaden The authors proposed a model to include the interactive facets of enjoyment.

The proposed model was empirically validated by conducting a survey among users of WeChat Moments in China.

As hypothesized, this research confirms that enjoyment and automatic processing (i.e. social influence to use an SNS) are complementary in the SNS self-disclosure process and enjoyment negatively moderates the positive relationship between controlled factor (i.e. self-presentation) and self-disclosure.

Theoretically, this study offers a new perspective on explaining SNS self-disclosure by adopting DPT. Specifically, this study contributes to the extant SNS research by applying DPT to examine how the controlled factors and the automatic factor shape self-disclosure processes and how enjoyment influences vary across these processes – enriching knowledge about SNS self-disclosure behaviors. Practically, the authors provide important design guidelines to practitioners concerning devising mechanisms to foster more automatic-enjoyable value-added functions to improve SNS users' participation and engagement.

This study aims to explore the complex relationship between leadership and organizational knowledge sharing by investigating the moderating role of exchange ideology on the relation between transformational leadership in attributed charisma and knowledge sharing and the influence of attributed charisma and knowledge sharing on task performance. The influence of leadership in organizational knowledge sharing process has been gradually highlighted.

Based on the review of relevant literature and survey, a structural equation model considering four factors in the model together is now constructed and provides four hypotheses which can be verified. Self-completed questionnaires were collected from 163 students in the context of a graduate class in China.

The findings illustrate the relationship between leadership theory and knowledge sharing from a perspective of social exchange theory. In particular, results show that both transformational leadership and knowledge sharing have positive impacts to task performance and for individuals with low exchange ideology the positive influence from attributed charisma to knowledge sharing is stronger.

This research introduces exchange ideology as a moderator and explains the complex relationship between transformational leadership and knowledge sharing with sufficient proof. Transformational leadership in attributed charisma is more effective to those individuals with low exchange ideology in facilitating their knowledge effort. This paper can be theoretically and practically helpful to researchers and enterprise leaders in organizational knowledge management.

This study aims to explore the underlying mechanisms that support the resilience of the Chinese hospitality industry during and after the COVID-19 epidemic.

Content analysis was applied to 133 manually collected text articles about COVID-19 responses and strategies.

A two-step learning model (emergency reaction, precautions and prevention stages) was identified in the study. In the emergency reaction step, the primary strategies were related to customers, employees, suppliers and facility/food. In the precautions and prevention step, the strategies were related to customers, employees, suppliers and society/public relations. Multiple stakeholders are discussed in the two circles over a continual process in the learning, reacting and adapting stages.

A gap in the literature is filled by this study, providing a learning model and synthesizing various strategies applied in the hotel sector for multiple stakeholders.

The brand logo, as a fundamental element of marketing communications, serves as a crucial visual representation of a brand. In the current era of mobile Internet, logo flatness has become a new trend in practice. However, there remains a scarcity of research that explores the effects of logo flatness on consumer perceptions and brand attitudes.

Across four studies, using both observational analyses of real brands and experimental manipulations of fictitious brands, the authors examined the impact of logo flatness on consumer perceptions and brand attitudes.

Results show that logo flatness promotes the perception of modernity due to the simplicity it presents. Consumers will evaluate the brand more positively when their perception of the logo association is congruent with the brand image. Notably, traditional brands using skeuomorphic logos and modern brands employing flat logos can effectively enhance consumers' brand attitudes.

The findings of this study have significant implications for businesses seeking to enhance consumers' brand attitude and foster brand renewal through the strategic selection and design of logos that align with their brand image.

This study provides a theoretical and empirical test of the influence of logo flatness on consumers' perception of brand image, thereby enriching the existing research on brand management.

Safety management plays an important part in coal mine construction. Due to complex data, the implementation of the construction safety knowledge scattered in standards poses a challenge. This paper aims to develop a knowledge extraction model to automatically and efficiently extract domain knowledge from unstructured texts.

Bidirectional encoder representations from transformers (BERT)-bidirectional long short-term memory (BiLSTM)-conditional random field (CRF) method based on a pre-training language model was applied to carry out knowledge entity recognition in the field of coal mine construction safety in this paper. Firstly, 80 safety standards for coal mine construction were collected, sorted out and marked as a descriptive corpus. Then, the BERT pre-training language model was used to obtain dynamic word vectors. Finally, the BiLSTM-CRF model concluded the entity’s optimal tag sequence.

Accordingly, 11,933 entities and 2,051 relationships in the standard specifications texts of this paper were identified and a language model suitable for coal mine construction safety management was proposed. The experiments showed that F1 values were all above 60% in nine types of entities such as security management. F1 value of this model was more than 60% for entity extraction. The model identified and extracted entities more accurately than conventional methods.

This work completed the domain knowledge query and built a Q&A platform via entities and relationships identified by the standard specifications suitable for coal mines. This paper proposed a systematic framework for texts in coal mine construction safety to improve efficiency and accuracy of domain-specific entity extraction. In addition, the pretraining language model was also introduced into the coal mine construction safety to realize dynamic entity recognition, which provides technical support and theoretical reference for the optimization of safety management platforms.

Excavating valuable outlier information of gray privacy products, the purpose of this study takes the online reviews of women’s underwear as an example, explores the outlier characteristics of online commentary data, and analyzes the online consumer behavior of consumers’ gray privacy products.

This research adopts the social network analysis method to analyze online reviews. Based on the online reviews collected from women’s underwear flagship store Victoria’s Secret at Tmall, this study performs word segmentation and word frequency analysis. Using the fuzzy query method, the research builds the corresponding co-word matrix and conducts co-occurrence analysis to summarize the factors affecting consumers’ purchase behavior of female underwear.

Establishing a formal framework of gray privacy products, this paper confirms the commonalities among consumers with respect to their perceptions of gray privacy products, shows that consumers have high privacy concerns about the disclosure or secondary use of personal private information when shopping gray privacy products, and demonstrates the big difference between online reviews of gray privacy products and their consumer descriptions.

The research lays a solid foundation for future research in gray privacy products. The factors identified in this study provide a practical reference for the continuous improvement of gray privacy products and services.