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This study aims to introduce the hybrid finite element (FE) – meshfree method and multiscale variational principle into the traditional mixed FE formulation, leading to a stable mixed formulation for incompressible linear elasticity which circumvents the need to satisfy inf-sup condition.

Using the hybrid FE–meshfree method, the displacement and pressure are interpolated conveniently with the same order so that a continuous pressure field can be obtained with low-order elements. The multiscale variational principle is then introduced into the Galerkin form to obtain stable and convergent results.

The present method is capable of overcoming volume locking and does not exhibit unphysical oscillations near the incompressible limit. Moreover, there are no extra unknowns introduced in the present method because the fine-scale unknowns are eliminated using the static condensation technique, and there is no need to evaluate any user-defined stability parameter as the classical stabilization methods do. The shape functions constructed in the present model possess continuous derivatives at nodes, which gives a continuous and more precise stress field with no need of an additional smooth process. The shape functions in the present model also possess the Kronecker delta property, so that it is convenient to impose essential boundary conditions.

The proposed model can be implemented easily. Its convergence rates and accuracy in displacement, energy and pressure are even comparable to those of second-order mixed elements.

The purpose is to provide decision support for tourists recommending scenic spots and corresponding suggestions for the management of scenic spots.

Based on the Baidu index data generated, this paper analyzes the temporal and spatial characteristics of network attention of 5A scenic spots in Sichuan Province. The online comment data are used to build the assessment model of scenic spots based on network attention, and the comment information of tourists is mined and analyzed through statistical analysis. At the same time, the key attributes of scenic spots from the perspective of network attention are evaluated and analyzed by using the probabilistic linguistic term set. Finally, this paper further constructs a recommendation model based on the key attribute set of scenic spots.

This paper uses different types of tourism network information, integrates multi-types of data and methods, fully excavates the value information of tourism network information, constructs the research framework of “scenic spot assessment + scenic spot recommendation” from the perspective of network attention, analyzes the network attention characteristics of scenic spots, evaluates the performance of scenic spots, and implements scenic spot recommendation.

This paper integrates multi-source data and multidisciplinary theoretical methods to form a scenic spot research framework of “assessment + recommendation” from the perspective of network attention.

This study investigates the way in which acquisition-related human factors affect knowledge transfer in the context of Chinese cross-border M&A for strategic assets. The authors find that the process of knowledge transfer is reciprocal for revenue and cost synergies, including explicit and tacit knowledge. The establishment of joint ventures (JV) in China after the takeover boosts product-oriented knowledge transfer from overseas-acquired firms in mature markets to Chinese acquirers. The promotion of overseas synergies stimulates complementary knowledge transfer flow, which is reversely transferred from Chinese acquirers to overseas-acquired subsidiaries such as low-saving sourcing and new market applications. This study identifies three acquisition-related human factors that impact overseas knowledge senders for knowledge transfer. These human factors are implemented by Chinese strategic investors as new shareholders during the loosen integration phase. The first facilitator is all-round communication programs with top management involvement, aiming to build up constructive communication channels to boost knowledge transfer. The second facilitator is competence-based trust, which stimulates cooperation and application based on similar professional competence between Chinese acquirers and their overseas-acquired subsidiaries. The impeder is a high turnover of key skilled workers at Chinese acquirers to undermine the effectiveness of knowledge transfer.

Drawing upon the creativity interaction theory and expectation-identity perspective, the purpose of this paper is to construct a chain mediation model of the influence of workplace status on individual creativity from the perspective of expectation identity and to explore the moderating effect of prosocial motivation in this model.

This study reached 529 employees from 35 enterprises as the investigation objects and used structural equation model and hierarchical regression for data analysis. Data on workplace status, prosocial motivation, creativity expectations and creativity role identity were collected at Time Point T1, and individual creativity was collected at time point T2 (one month later).

The results reveal that: workplace status has a significantly positive effect on creativity; creativity performance expectations and creativity role identity have partial mediating effect in the relationship between workplace status and creativity, respectively; creativity performance expectations and creativity role identity play a chain double mediation role in the relationship between workplace status and creativity; and prosocial motivation moderates the relationship between workplace status and creativity and further moderates the chain double mediation effect of creativity performance expectations and creativity role identity.

In existing studies, conclusions about the relationship between workplace status and individual creativity could be divided into three viewpoints: positive, negative and U-shaped. These inconsistent findings on the relationship between workplace status and creativity imply that the relationship is complex and not fully elucidated. This may be attributed to the fact that workplace status is influenced by cultural factors and research objects. This study reinterprets the relationship between workplace status and individual creativity through the lens of creativity interaction theory and demonstrates the significance of employee workplace status in the Chinese context.

This paper aims to study the corrosion inhibition behavior of imidazopyridine and its three derivatives on brass.

The authors performed weight loss experiments, electrochemical experiments including the polarization curve and electrochemical impedance spectrum, corrosion morphology observation using scanning electron microscope (SEM) and atomic force microscope (AFM) and surface composition analysis via X-ray photoelectron spectroscopy (XPS) to analyze the corrosion inhibition behavior of imidazopyridine and its three derivatives on brass by using quantum chemical calculation (Gaussian 09), molecular dynamics simulation (M-S) and Langmuir adsorption isotherm.

According to the results, imidazole-pyridine and its derivatives were found to be modest or moderately mixed corrosion inhibitors; moreover, they were spontaneously adsorbed on the metal surface in a single-layer, mixed adsorption mode.

The corrosion inhibition properties of pyrazolo-[1,2-a]pyridine and its derivatives on brass in sulfuric acid solution were analyzed through weight loss and electrochemical experiments. Moreover, SEM and AFM were simultaneously used to observe the corrosion appearance. Furthermore, XPS was used to analyze the surface. Then, Gaussian 09 and M-S were combined along with the Langmuir adsorption isotherm to investigate the corrosion inhibition mechanism of imidazole-[1,2-a]pyridine and its derivatives.

In the era of information overload, the density of tourism information and the increasingly sophisticated information needs of consumers have created information confusion for tourists and scenic-area managers. The study aims to help scenic-area managers determine the strengths and weaknesses in the development process of scenic areas and to solve the practical problem of tourists' difficulty in quickly and accurately obtaining the destination image of a scenic area and finding a scenic area that meets their needs.

The study uses a variety of machine learning methods, namely, the latent Dirichlet allocation (LDA) theme extraction model, term frequency-inverse document frequency (TF-IDF) weighting method and sentiment analysis. This work also incorporates probabilistic hesitant fuzzy algorithm (PHFA) in multi-attribute decision-making to form an enhanced tourism destination image mining and analysis model based on visitor expression information. The model is intended to help managers and visitors identify the strengths and weaknesses in the development of scenic areas. Jiuzhaigou is used as an example for empirical analysis.

In the study, a complete model for the mining analysis of tourism destination image was constructed, and 24,222 online reviews on Jiuzhaigou, China were analyzed in text. The results revealed a total of 10 attributes and 100 attribute elements. From the identified attributes, three negative attributes were identified, namely, crowdedness, tourism cost and accommodation environment. The study provides suggestions for tourists to select attractions and offers recommendations and improvement measures for Jiuzhaigou in terms of crowd control and post-disaster reconstruction.

Previous research in this area has used small sample data for qualitative analysis. Thus, the current study fills this gap in the literature by proposing a machine learning method that incorporates PHFA through the combination of the ideas of management and multi-attribute decision theory. In addition, the study considers visitors' emotions and thematic preferences from the perspective of their expressed information, based on which the tourism destination image is analyzed. Optimization strategies are provided to help managers of scenic spots in their decision-making.

Based on climate issues and carbon emissions, this study aims to promote low-carbon consumption and compel consumers to actively shift to energy-saving appliances. In this big data era, online reviews in social and electronic commerce (e-commerce) websites contain valuable product information, which can facilitate firm business strategies and consumer comparison shopping. This study is designed to advance existing research on energy-saving refrigerators by incorporating machine learning models in the analysis of online reviews to provide valuable suggestions to e-commerce platform managers and manufacturers to effectively understand the psychological cognition of consumers.

This study proposes an online e-commerce review mining and management strategy model based on “data acquisition and cleaning, data mining and analysis and strategy formation” through multiple machine learning methods, namely, Bayes networks, support vector machine (SVM), latent Dirichlet allocation (LDA) and importance–performance analysis (IPA), to help managers.

Based on a case study of one of the largest e-commerce platforms in China, this study linguistically analyzes 29,216 online reviews of energy-saving refrigerators. Results indicate that the energy-saving refrigerator features that consumers are generally satisfied with are, in sequential order, logistics, function, price, outlook, after-sales service, brand, quality and space. This study also identifies ten topics with 100 keywords by analyzing 18 different refrigerator models. Finally, based on the IPA, this study allocates different priorities to the features and provides suggestions from the perspective of consumers, the government and manufacturers.

In terms of limitations, future research may focus on the following points. First, the topics identified in this study derive from specific points in time and reviews; thus, the topics may change with the text data. A machine learning-based online review analysis platform could be developed in the future to dynamically improve consumer satisfaction. Moreover, given that consumers' needs may change over time, e-commerce platform types and consumer characteristics, such as user profiles, can be incorporated into the model to effectively analyze trends in consumers' perceived dimensions.

This study fills the gap in previous research in this field, which uses small-sample data for qualitative analysis, while integrating management ideas and proposes an online e-commerce review mining and management strategy model based on machine learning methods. Moreover, this study considers how consumers' emotional and thematic preferences for products affect their purchase decision-making from the perspective of their psychological perception and linguistically analyzes online reviews of energy-saving refrigerators using the proposed mining model. Through the improved IPA model, this study provides optimizing strategies to help e-commerce platform managers and manufacturers.

Drawing on ego depletion theory, this study aims to provide insights into the effect of work-family conflict on the high-speed railway (HSR) drivers’ safety performance by examining the mediating role of ego depletion and the moderating roles of work-family centrality and supervisor safety support.

In total, 243 HSR drivers from 7 railway bureaus in China were surveyed. Structural equation modeling was used to test the hypotheses.

Both work-to-family conflict and family-to-work conflict have direct and positive effects on HSR drivers’ ego depletion and indirect effects on both safety compliance and safety participation via ego depletion. Moreover, both the direct effect of work-family conflict on ego depletion and its indirect effect on safety performance are moderated by work-family centrality. Supervisor safety support plays a buffering role in the relationship between ego depletion and safety performance.

This study examined the relationship between work-family conflict and safety performance based on the perspective of ego depletion theory. The findings testify to the importance of reducing work-family conflict among HSR drivers pursuant to maximizing safety.

As demographic changes impact the workplace, governments, organizations, and workers are looking for ways to sustain optimal working lives at higher ages. Workplace flexibility has been introduced as a potential way workers can have more satisfying working lives until their retirement ages. This chapter presents a critical review of the literature on workplace flexibility across the lifespan. It discusses how flexibility has been conceptualized across different disciplines, and postulates a definition that captures the joint roles of employer and employee in negotiating workplace flexibility that contributes to both employee and organization benefits. Moreover, it reviews how flexibility has been theorized and investigated in relation to older workers. The chapter ends with a future research agenda for advancing understanding of how workplace flexibility may enhance working experiences of older workers, and in particular focuses on the critical investigation of uses of flexibility in relation to older workers.