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Drawing on the literature regarding the social network and stock investment, this paper aims to focus on the use of the social network on stock ownership decisions at individual levels. This paper also attempts to shed light on potential mediators of the relationship between the social network and stock ownership.

To determine the relationship between stock ownership and using the social network, logistic regression was used. In order to isolate the effect of using hs on stock ownership, a decomposing method was adopted.

The findings provide evidence of the positive contribution of the use of social networks in stock ownership. Personal characteristics, such as household net worth, homeownership, education level and risk tolerance, may play a vital role in influencing individuals' decisions regarding stock investment. In addition, this study contributes to our understanding of income's mediating role in stock investment decisions.

First, the authors contribute theoretically by drawing from the assumptions of social networking contagion theory, social influence theory, and social capital theory. Second, we explored potential mediators of the relationship between the social network and stock ownership. Third, this study complements the literature in incorporating the social network in business, financial professionals to be exact.

The purpose of this study is to clarify the effects of transformational leadership (TL) on radical and incremental innovation through the mediating roles of knowledge sharing (KS) behaviors. This study also attempts to bring deeper insight of the correlation among the latent factors by examining how knowledge-centered culture (KCC) moderates the effects of TL on KS behaviors and innovation capability.

This study conducts a questionnaire survey and Structural Equation Modeling to test the proposal research model based on a sample of 321 participants in 85 service and manufacturing firms.

The results revealed that KS behaviors significantly mediate the relationship between TL and two types of innovation. Specifically, knowledge collecting has more significant effect on incremental innovation compared with influence of knowledge donating. By contrast, knowledge donating has a greater effect on radical innovation compared with effect of knowledge collecting. The paper also highlights the important role of KCC in enhancing the effects of TL on KS activities and innovation capabilities.

The study has highlighted the important role of KCC as it positively moderates the influences of TL on KS and innovation capability.

The study provides evidence that TL style is the main driving force of KS processes. Managers should prioritize practicing this leadership style to improve employees' KS behaviors and firm's innovation capability.

The study significantly fills the gaps in the literature that emphasizes how KS behaviors induce different impacts on specific aspects of innovation capability. By exploring the moderator of KCC, the paper significantly contributes to advancing the understanding of how transformational leaders foster employees' KS behaviors for improving radical and incremental innovation.

As a world leader in the textiles and clothing trade, Hong Kong has played an important role in world denim products trade. To obtain a sound understanding of the current status and position of Hong Kong in the world denim trade, the authors carried out a comprehensive statistical survey of the Hong Kong denim industry. This paper reports detailed analyses on the production, sales and trade of denim products in Hong Kong. The analysis on trade covers imports, domestic exports and re‐exports of denim fabric and apparel products.

The aim of this paper is to provide a statistical review of the Chinese denim industry, which covers the following topics: Chinese production and production capacity of denim yarns, fabrics and apparels; Chinese domestic consumption of denim yarns, fabrics and apparels; Chinese denim export to the USA, EEC and Hong Kong; and finally the geographic distribution of the Chinese denim industry — yarn production, fabric production and apparel production.

Based on the error analysis, the authors proposed a new kind of high accuracy boundary element method (BEM) (HABEM), and for the large-scale problems, the fast algorithm, such as adaptive cross approximation (ACA) with generalized minimal residual (GMRES) is introduced to develop the high performance BEM (HPBEM). It is found that for slender beams, the stress analysis using iterative solver GMRES will difficult to converge. For the analysis of slender beams and thin structures, to enhance the efficiency of GMRES solver becomes a key problem in the development of the HPBEM. The purpose of this paper is study on the preconditioning method to solve this convergence problem, and it is started from the 2D BE analysis of slender beams.

The conventional sparse approximate inverse (SAI) based on adjacent nodes is modified to that based on adjacent nodes along the boundary line. In addition, the authors proposed a dual node variable merging (DNVM) preprocessing for slender thin-plate beams. As benchmark problems, the pure bending of thin-plate beam and the local stress analysis (LSA) of real thin-plate cantilever beam are applied to verify the effect of these two preconditioning method.

For the LSA of real thin-plate cantilever beams, as GMRES (m) without preconditioning applied, it is difficult to converge provided the length to height ratio greater than 50. Even with the preconditioner SAI or DNVM, it is also difficult to obtain the converged results. For the slender real beams, the iteration of GMRES (m) with SAI or DNVM stopped at wrong deformation state, and the computation failed. By changing zero initial solution to the analytical displacement solution of conventional beam theory, GMRES (m) with SAI or DNVM will not be stopped at wrong deformation state, but the stress error is still difficult to converge. However, by GMRES (m) combined with both SAI and DNVM preconditioning, the computation efficiency enhanced significantly.

This paper presents two preconditioners: DNVM and a modified SAI based on adjacent nodes along the boundary line of slender thin-plate beam. In the LSA, by using GMRES (m) combined with both DNVM and SAI, the computation efficiency enhanced significantly. It provides a reference for the further development of the 3D HPBEM in the LSA of real beam, plate and shell structures.

This study examines the relationship between investors' familiarity bias, including the home bias and endowment bias, and their financial situations, expectations and personal characteristics.

Using the 2019 Survey of Consumer Finances, the authors utilize an ordinary least squares regression to identify the presence of endowment bias and home bias in individual investors' direct stock holdings and use a Heckman selection model to examine determinants of the extent of endowment bias and home bias.

This study finds that investors with higher income and more education, men, non-white investors and people with greater risk tolerance are actually at a greater risk of endowment bias. This study also identifies a profile of investors that are more likely to have a home bias: with less financial sophistication, lower net worth, older, female, more risk-averse, with a positive expectation about the domestic economy and a relatively shorter investment horizon.

This paper is among the first to use US investors' directly reported stock holdings to examine the individual characteristics that are correlated with greater familiarity bias, providing financial professionals with information about how to allocate their limited time in providing education to a variety of clients.

The purpose of this paper is to obtain the single-tooth stiffness, single-tooth time-varying meshing stiffness and comprehensive meshing stiffness of the internal and external face gears and to analyze the influence of the modulus, pressure angle and tooth width of each face gear on the single-tooth stiffness of the gear in nutation face gear transmission.

From the point of view of material mechanics, the gear teeth of nutation face gear are simplified as spacial variable cross-section beams. The shear deformation of gear teeth, the bending deformation of tooth root and the additional elastic deformation caused by the base deformation are gotten by simplified trapezoidal section method, thus the stiffness of nutation face gear teeth can be obtained. The comparison with finite element method results verifies the rationality of simplified trapezoidal section method for calculating the tooth stiffness of nutation face gear.

The variation of stiffness of internal and external face gears along the meshing line and tooth height in nutation face gear transmission is studied, and the variation laws of single tooth stiffness, single-tooth-pair mesh stiffness and single tooth time-varying meshing stiffness of nutation face gear teeth are obtained.

Nutation face gear transmission is a new type of transmission. The stiffness of face gear teeth is analyzed, and the variation rules of single tooth stiffness, single-tooth-pair mesh stiffness and single tooth time-varying meshing stiffness of nutation face gear teeth are obtained, which not only enriches the research of nutation face gear transmission but also has important guiding significance for the application of nutation face gear in engineering practice.

This research explored how COVID-19 affects Shenzhen high school students' reading behavior and preference and their parents' attitudes toward reading during the lockdown.

This research adopted a qualitative approach to conduct one-on-one semi-structured interviews with parents of a boarding high school in Shenzhen, China. Thirteen parents were recruited through a purposeful sampling method, and NVivo12 software was used to analyze the results with a theme-based approach guided by the 5E instructional model.

The results revealed the effectiveness and problems of high school students' use of electronic resources and discovered changes in the reading behavior of high school students and their parents' attitudes during COVID-19.

There are few studies specifically on the reading behavior of boarding students from a parental view, especially in Asia. This research can fill the gaps in related research during COVID-19.

Introduction: When people need to take decisions, being economic decisions or otherwise, their decisions tend to rely on information the brain has already processed, and this includes the resources that the person has already invested. This is called sunk cost bias in the behavioural economics literature. On the other hand, mental practices could lead to the mental accounting bias, where people allocate a different value to a fixed amount of money, depending on circumstances.

Purpose: In this chapter, both biases mental accounting and sunk cost are investigated for the tourism industry in Turkey.

Methodology: The topic is researched through scenario-based questions and the Chi-square Automatic Interaction Detector (CHAID) method is applied.

Findings: As a result, it could be reported that people, regardless of gender, fall into sunk cost and mental accounting biases in decisions relating to their vacations. Mental accounting biases can be primarily explained using the scenario questions posed rather than gender, education, and income while sunk cost bias is explained by status, ‘being s university student’ and ‘income level’.

Practical implications: Rapid price changes in the tourism industry can disturb consumers who are mental accounting and sunk cost biased. So, they can change their holiday preferences or be dissatisfied with it and give negative feedback.

The popularity of massive open online courses (MOOCs) has attracted worldwide research interest. This study aims to identify and summarize the research foci (e.g. themes, methods, contexts, etc.) and discuss the new directions and trends of MOOC research in the context of Mainland China.

A systematic review of the published MOOC research papers in Mainland China was conducted with the following inclusion criteria: (1) papers written in English; (2) context focused on Mainland China; and (3) empirical studies. Three main issues were explored with the selected 70 papers: (1) research methods (data collection and analysis); (2) the research foci; and (3) research objects.

The results found that the major MOOC research in China was quantitative, mostly using one method to collect data. Most studies collected data through the databases of MOOC platforms and survey techniques, which was consistent with the widely used descriptive statistics for data analysis. Learner-focused themes were investigated the most, aligning with the result that learners were the most popular research objects.

The findings suggest that using new technology tools, such as the Big Data approach for learning analytics, may transform traditional MOOC research into new practices. Transdisciplinary research concepts may also provide an alternative evolving model for constructing collaboratively dynamic research frameworks under the changing technologies and paradigms. Meanwhile, educational research traditions, such as qualitative methods, contribute to scaffolding MOOC research for more pragmatic applications.

Most systematic reviews on MOOCs focus on general or regional contexts other than Mainland China, and scant MOOC review is based on published English papers about Mainland China.