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The purpose of this paper is to investigate the feasibility of solving turbulent flows based on smoothed finite element method (S-FEM). Then, the differences between S-FEM and finite element method (FEM) in dealing with turbulent flows are compared.

The stabilization scheme, the streamline-upwind/Petrov-Galerkin stabilization is coupled with stabilized pressure gradient projection in the fractional step framework. The Reynolds-averaged Navier-Stokes equations with standard k-epsilon model are selected to solve turbulent flows based on S-FEM and FEM. Standard wall functions are applied to predict boundary layer profiles.

This paper explores a completely new application of S-FEM on turbulent flows. The adopted stabilization scheme presents a good performance on stabilizing the flows, especially for very high Reynolds numbers flows. An advantage of S-FEM is found in applying wall functions comparing with FEM. The differences between S-FEM and FEM have been investigated.

The research in this work is limited to the two-dimensional incompressible turbulent flow.

The verification and validation of a new combination are conducted by several numerical examples. The new combination could be used to deal with more complicated turbulent flows.

The applications of the new combination to study basic and complex turbulent flow are also presented, which demonstrates its potential to solve more turbulent flows in nature and engineering.

This work carries out a great extension of S-FEM in simulations of fluid dynamics. The new combination is verified to be very effective in handling turbulent flows. The performances of S-FEM and FEM on turbulent flows were analyzed by several numerical examples. Superior results were found compared with existing results and experiments. Meanwhile, S-FEM has an advantage of accuracy in predicting boundary layer profile.

The purpose of this paper is to investigate a novel stabilization scheme to handle convection and pressure oscillation in the process of solving incompressible laminar flows by finite element method (FEM).

The semi-implicit stabilization scheme, characteristic-based polynomial pressure projection (CBP3) consists of the Characteristic-Galerkin method and polynomial pressure projection. Theoretically, the proposed scheme works for any type of element using equal-order approximation for velocity and pressure. In this work, linear 3-node triangular and 4-node tetrahedral elements are the focus, which are the simplest but most difficult elements for pressure stabilizations.

The present paper proposes a new scheme, which can stabilize FEM solution for flows of both low and relatively high Reynolds numbers. And the influence of stabilization parameters of the CBP3 scheme has also been investigated.

The research in this work is limited to the laminar incompressible flow.

The verification and validation of the CBP3 scheme are conducted by several 2 D and 3 D numerical examples. The scheme could be used to deal with more practical fluid problems.

The application of scheme to study complex hemodynamics of patient-specific abdominal aortic aneurysm is also presented, which demonstrates its potential to solve bio-flows.

The paper simulated 2 D and 3 D numerical examples with superior results compared to existing results and experiments. The novel CBP3 scheme is verified to be very effective in handling convection and pressure oscillation.

Based on previous literature on big data analytics (BDA) and supply chain (SC) management, the purpose of this paper is to address the factors determining firms’ intention to adopt BDA in their daily operations. Specifically, this study classifies potential factors into four categories: technological, organizational, environmental factors, and SC characteristics.

Drawing on the innovation diffusion theory, a model consisted of direct technological and organizational factors as well as moderators was proposed. Subsequently, survey data was collected from 210 organizations. Then we used SPSS and SmartPLS to analyze the collected data.

The empirical results revealed that perceived benefits and top management support can significantly influence the adoption intention. And environmental factors, such as competitors’ adoption, government policy, and SC connectivity, can significantly moderate the direct relationships between driving factors and the adoption intention.

Given the fact that big data (BD) usage in logistics and SC management is still in the start-up stage, the interpretations toward BDA might vary from different perspectives, thus causing some ambiguity in understanding the meaning and potential BD has. In addition, we collected data through questionnaires completed by IT managers, whose viewpoint may not fully represent that of an organization.

This paper tests the organizational adoption intention of BDA and extends the literature streams of BD and SC management simultaneously.

This research helps top managers assess the benefits of BDA as well as how to adjust their business strategy along the changes of environment and SC maturity.

This paper contributes to the literature of organizational adoption intention of BDA and extends the literature streams of BD and SC management simultaneously.

This paper seeks to investigate the differences in the teachers’ professional development (TPD) by mentorship in workplace. The authors examined the role of mentorship in the PD of teachers and conducted a meta-analysis of pertinent empirical data.

Using data from over 2,900 individuals, 66 experiments and 12 countries, the authors presented a meta-analysis of the association between workplace mentorship and TPD.

The authors concluded that mentoring activities could boost the TPD to some extent. It contributes positively to the discipline of science and language, kindergarten, individual mentoring and curriculum research. In addition, the periodicity should not exceed 1 year.

The results of the meta-analysis are restricted to short-term mentorship activities, and the sample size is modest. Building upon the findings from the literature review and meta-analysis, the authors delineated a research agenda for prospective investigations. This includes an imperative for further exploration into the nexus between mentoring and the PD of educators.

Based on the available literature and meta-analysis findings, the authors developed a framework for the “Experts in the classroom” TPD pattern.

This is the first meta-analysis evaluating the association between mentorship and TPD.

The purpose of this paper is to use samples from Chinese-listed companies to investigate the effects of interest rate deregulation and earnings transparency on company’s capital structure in China over the period of 2003–2015. In particular, the authors study the link between state-owned enterprises (SOEs), economic growth targets and marketization in China’s unique institutional context.

Based on the methodology of quantitative analysis, the authors use baseline and cluster analysis for all samples with full set of controls, for robustness tests of alternative proxy of interest rate control by using a cluster analysis at the firm level, regarding endogeneity tests conducted fixed effect model with adding instrument variables (IV), two-period factors regression method via IV and system generalized method of moments for dynamic analysis.

The results show that earnings transparency increases firm leverage and the additional tests suggest that such an effect takes place via a mechanism by reducing the cost of debt finance. However, information transparency could moderate the effects of interest rate deregulation on corporate capital structure. In addition, it finds that SOEs are less sensitive toward the changes of interest rates in China because lending to SOEs is policy-oriented and lacks of market evaluation of business risk. Government control is conducive to enhancing the transparency of the whole industry; however, market-oriented reform is conducive to enhancing the transparency of the company’s own information.

The paper makes contribution to the relationship between earnings disclosure quality and capital structure in the Chinese unique institutional context, such as taking the progressive interest rate reform, SOES, different economic growth target and different marketization level in each province of China. The authors suggest that investors will pay more attention to the company’s own unique information transparency in the provinces with a high degree of marketization. As a potential direction for future research, the authors will investigate how the earnings transparency has impact on capital structure, and how such impact would depend on the transparency of specific business, the cap of foreign shareholding and the convenience of investment.

This research would be the target of banking market reform in order to bring a fair financing environment for all businesses in China. It implies that current experiment of interest rate liberalization in China is not as efficient as it could be in allocating funds across all businesses. State banks, SOEs and local governments are still the biggest players on both the demand and supply sides of the Chinese credit markets.

The social implication of this paper lies in the fact that first, it provides additional evidence on the effect of market-oriented reforms through how the information transparency interacts with the financial decisions making of corporations. Second, it offers policy implication to banking market deregulation in China.

The paper makes contribution to the relationship between earnings disclosure quality and capital structure in the Chinese unique institutional context. This research tests the existing literature, such as Francis et al. (2004) and Zhang and Lu (2007), and suggests that informationally transparent firms have a higher debt ratio and lower effective interest costs on bank loans. In addition, this paper further explores the role played by interest rate deregulation in corporate finance, and in turn market fund allocation. This paper sheds new light on information transparency and explores the relationship between earnings disclosure quality and debt financing behaviors of Chinese publicly listed companies over the period of 2003–2015.

With specific big-data mining worked on 61,522 firm announcements, we discovered a diverse Employee Share Ownership Plan (ESOP) model in China, called “Core-Staff-Based ESOPs.” Distinct from standard broad-based or executive-based ESOPs, these specific targeted-broad-based ESOPs require the qualification for participants, involving the participation of senior executives, directors at the middle level and any other employees that make particular contributions to firms. We take on the challenge to analyze ESOP mechanism, firm characteristics and performance in the view of organizational ecology and resource-based choice-making, and explore which factors have influenced the ESOP development in China.

We utilize a combination of approaches including qualitative and quantitative methods, and construct the main database of 117,767 firm-quarter data.

Firstly, based upon our institutional research, we find no coercive mechanisms that force all the Chinese listed firms to implement ESOPs since 2005. Secondly, our binary logistic regressions identify ESOP firms’ specific properties significantly distinct from non-ESOP firms, and draw profiles for these ESOP firms. Thirdly, our panel regression test results sustain the rational of ESOP mechanism, demonstrating that ESOPs enable Chinese firms to improve performance both in profits and their industry positions. Finally, with further quantitative tests, we find out this ESOP design’s limitations and the heterogenous effects due to China’s environments.

The discovery of Core-staff-based ESOPs contributes a diversity to the standard framework of ESOPs, enhances our understanding of China’s ESOP development, and provides new evidence for ESOP performance.