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The purpose of this paper is to examine the long-run survival of earnings fixated traders.

This paper builds a theoretical model of a competitive securities market where both rational traders and earnings fixated traders receive an informational signal about the asset payoff before any trade occurs. Since earnings fixated traders underestimate the mean and variance of the risky asset payoff, earnings fixated traders is shown to make less expected profits than rational traders.

If traders’ types replicate according to the relative profitability of their trading strategies, then earnings fixated traders will disappear in the long run. The results of this paper provide analytical support to Tinic’s (1990) intuition about the eventual disappearance of earnings fixated traders.

In the literature, the underestimation of risk is popularly viewed as the cause of irrational traders being better able to exploit the misvaluations (created by noise traders) than rational traders. Hence, it favors the survival of irrational traders over rational traders. However, this paper disapproves this intuition in the informational environment of the competitive securities market.

The market environment plays a crucial role in determining the long-run survival of irrational traders.

This paper is the first to present a theoretical result showing that in this informational environment of the competitive securities market, the underestimation of risk by irrational traders does not give them advantage over rational traders in exploiting the misvaluations (created by noise traders) as it does in Callen and Luo (2011) and Hirshleifer and Luo (2001).

Whilst professional learning communities (PLCs) have been widely explored at the school level, they have received less attention at the departmental level. The study takes the variance between departments and the role of departmental teacher leaders into consideration, and the relationships amongst departmental-level PLC dimensions, two types of teacher leadership (TL) and individual teacher self-efficacy are investigated.

The sample consisted of 907 teachers from 81 departments in Chinese schools. The associations between the studied variables were explored through a multi-level analysis approach.

The results show that two specific characteristics of departmental PLCs, namely reflective dialogue (RD) and collective responsibility (CR), exhibit a positive correlation with individual teacher self-efficacy. Additionally, the findings indicate that teacher transformational leadership significantly predicts teacher self-efficacy, whereas teacher instructional leadership (IL) does not emerge as a significant predictor. These findings may be attributed to the contextual factors of Chinese teachers' collective work and the practice of teacher leaders.

This research contributes to the existing literature by addressing the variance between departments and uncovering the impacts of departmental PLC dimensions on individual teachers. Furthermore, two TL styles at the departmental level are differentiated, and their distinct influences on teacher self-efficacy are further analysed.

This paper aims to investigate the economic consequence of the tax reductive strategy on stock price. The authors’ theory, empirically reinforced, suggests managerial tax aggressiveness endangers the corporation through a heightened risk in stock price crashing. Information opacity worsens the situation by reinforcing the relationship. Policymakers should emphasize two aspects: market openness and tighter institutional monitoring. The evidence shown in this paper demonstrates that these two weaken the tax aggressiveness impact on risk of a crashing stock price.

The sample in this paper consists of 9,702 observations from listed firms from 2008 to 2013 in China. The tax rate is manually collected and all the other original data used in this study are sourced from Wind and China Capital Market and Accounting Research databases. Both logistic regression and ordinary least squares regression methods are used to test the hypothesis in this paper.

One key insight is in tax aggressiveness to be strongly correlated with a greater risk of future stock price crashing. The authors also found information opacity to exert a positive moderating effect. That is, the higher the information opacity, the stronger and more positive the correlation between tax aggression and stock price crash risk. However, the market process and an institutional investor have opposite, negative impacts. An open market environment reduces their correlativeness. Similarly, stronger institutional vigilance leads to an attenuation of such a co-relationship.

The findings of this paper have wide policy implications for management and control by authorities of listed corporations. Aggressiveness in management of corporate taxes accentuates the risks borne by stockholders. If so, internally within the corporation, such aggression shown by management, if not proscribed, could be subject to scrutiny, possibly by an independent committee. Externally, this may be countered by the authority in emphasizing three key factors: openness in information sharing, the market environment and tighter institutional monitoring.

This study provides a consequential theory of aggressive management of tax, rigorously analyzed and strongly, empirically supported. Overall, aggressiveness in tax management is related with assumption of higher risks in the crashing of stock price. The relationship is enhanced through information opacity, but reduced via market environment and institutional monitoring.

The overload of user-generated content in online mental health community makes the focus and resonance tendencies of the participating groups less clear. Thus, the purpose of this paper is to build an early identification mechanism for users' high attention content to promote early intervention and effective dissemination of professional medical guidance.

We decouple the identification mechanism from two processes: early feature combing and algorithmic model construction. Firstly, based on the differentiated needs and concerns of the participant groups, the multiple features of “information content + source users” are refined. Secondly, a multi-level fusion model is constructed for features processing. Specifically, Bidirectional Encoder Representation from Transformers (BERT)-Bi-directional Long-Short Term Memory (BiLSTM)-Linear are used to refine the semantic features, while Graph Attention Networks (GAT) is used to capture the entity attributes and relation features. Finally, the Convolutional Neural Network (CNN) is used to optimize the multi-level fusion features.

The results show that the ACC of the multi-level fusion model is 84.42%, F1 is 79.43% and R is 76.71%. Compared with other baseline models and single feature elements, the ACC and F1 values are improved to different degrees.

The originality of this paper lies in analyzing multiple features based on early stages and constructing a new multi-level fusion model for processing. Further, the study is valuable for the orientation of psychological patients' needs and early guidance of professional medical care.

The purpose of this paper is to clarify the effect of material hardening model and lump-pass method on the thermal-elastic-plastic (TEP) finite element (FE) simulation of residual stress induced by multi-pass welding of materials with cyclic plasticity.

Nickel-base alloy and stainless steel, which are used in J-type weld for manufacturing the nuclear reactor pressure head, can easily harden during multi-pass welding. The J-weld welding experiment is carried out and the temperature cycle and residual stress are measured to validate the TEP simulation. Thermal-mechanical sequence coupling method is employed to get the welding residual stress. The lumped-pass model and pass-by-pass FE model are built and two materials hardening models, kinematic hardening model and mixed hardening model, are adopted during the simulations. The effects of material hardening models and lumped-pass method on the residual stress in J-weld are distinguished.

Based on the kinematic hardening model, the stresses simulated with the lumped-pass FE model are almost consistent with those obtained by the pass-by-pass FE model; while with the mixed hardening material model, the lumped-pass method has great effect on the simulated stress.

A computation with mixed isotropic-kinematic material seems not to be the appropriate solution when using the lumped-pass method to save the computation time.

In the simulation of multi-pass welding residual stress involved in materials with cyclic plasticity, the material hardening model should be carefully considered. The kinematic hardening model with lump-pass FE model can be used to get better simulation results with less computation time. The results give a direction for welding residual stress simulation for the large structure such as the reactor pressure vessel.

The purpose of this paper is to examine the effects of the government intervention and bank competition on small and medium enterprise (SME) external debt financing in Chinese capital market.

This study uses ordinary least squares with standard errors clustered at the firm level. In addition, the authors use the dynamic system generalized method of moments to address the possible endogeneity issue in the regressions.

Using a sample of 908 firms from 2000 to 2010, the authors found that SMEs are more likely to access bank loans only in regions with higher level of government intervention than median government intervention. Further, the result shows that the government is motivated to help SMEs to obtain more external debt in regions where the level of bank competition is lower than the median bank competition index. Last, the authors found evidence that firms with politically connected CEOs are likely to access bank loans.

This paper highlights that government intervention enables the SMEs to secure more bank loans. Second, the authors’ results imply that the government is motivated to help SMEs to obtain more external debt in regions with low level of bank competition.

This study contributes to the current literature by revealing that government intervention is the driving force alleviating SMEs’ constraints in accessing external financing. Second, this study finds the evidence to supports the argument that government has a strong motive to help SMEs to secure long-term credits for political purpose (Fan et al., 2012), when the level of bank competition is low (Berger and Udell, 2006).

The purpose of this paper is to develop a spectral element modeling to predict electromechanical admittance in the surface-bonded piezoelectric wafer and beam structure considering temperature effects.

For modeling the beam, the axial and transverse vibrations of the beam have been considered, and temperature-dependent mechanical and electromechanical properties of piezoelectric wafer active sensor and aluminum have been analyzed. The influences of temperature effects on electromechanical admittance are investigated.

The results show that a frequency left shift and a decrease in amplitude of admittance in any natural frequencies with increasing temperature have been observed. The mechanism of these changes is discussed.

The numerical results may be considered helpful for structural health monitoring using electromechanical impedance technique.

This paper aims to solve the issue of target positioning in auto stiffener bonder (ASB) systems for flexible printed circuits.

The proposed approach uses Phong’s bidirectional reflectance distribution function (BRDF) model to simulate the reflection of light off a target in ASB systems to predict the current pose of the target based on image brightness, update the template, decrease the initial errors in the template and narrow down the search range.

The experimental results indicate that the proposed approach can predict the inclination angle of the target with precision, presenting angle prediction errors of less than three degrees. Furthermore, with larger inclined angles, the overall matching errors were less than 1.5 pixels. Comparisons with the unmodified matching algorithm revealed that the proposed approach resulted in 65 per cent less calculation time for the algorithm and 14 per cent higher overall work efficiency in the ASB system.

The edge-based perspective shape matching algorithm was modified using the Phong BRDF model and enhanced algorithm efficiency with the target pose prediction method while ensuring the precision and robustness of the system. The proposed approach has high potential value and can be expanded to recognition systems for objects with varying inclination angles and highly reflective surfaces.

The purpose of this paper is to examine the effects of bank ownership structure and ownership concentration on credit risk.

Using panel data on a sample of 88 Chinese commercial banks, with 826 observations over a period of 2003–2018, this study has applied system generalised method of moments regression to examine the impact of bank ownership structure and ownership concentration on credit risk. This study has used two measures of credit risk, which are non-performing loan ratio (NPLR) and loan loss provision ratio (LLPR).

The results show that ownership type (both government and private ownership) exerts a positive and significant impact on credit risk. Measuring ownership concentration using Herfindahl–Hirchmann Index, the results indicate that concentration of ownership in the hands of government has a negative and significant effect on credit risk, whereas private ownership concentration positively impacts credit risk. Overall, the findings suggest that concentration of ownership in government hands reduces risk; however, private ownership concentration exacerbates credit risks. The results are invariant to both measures of credit risk, before and after the financial crisis.

The findings provide useful insight to guide policy decisions in Chinese banks’ lending policies and bank ownership.

Using two ex post measures of credit risk, NPLR and LLPR, and one ownership concentration measure, HHI, this study deepens our understanding on the effectiveness of Chinese banks’ corporate governance reforms on managing credit risks.

Over the last ten years (2010–2019), the amount of nonperforming loans (NPLs) has been more than tripled in the banking industry of Bangladesh. Thus, this paper explores the behavioral dimensions, which contribute to the NPLs.

By analyzing social, cultural, psychological, political, economic, internal control mechanism and law enforcement contexts of Bangladesh, this study identifies nepotism (NE), moral hazard (MH ), inadequate collateral (IC), poor credit assessment (CA), lack of proper monitoring (LPM), repayment flexibility (RF), business risk (BR) and lending interest rate (LIR) as the catalysts of raising NPLs. Next, a structured questionnaire survey has been performed in Bangladesh among bank officials who closely work in credit risk management, credit supervision, corporate finance and loan recovery department. Finally, partial least squares (PLS) path modeling, a variance-based technique of structural equation modeling, is used in this study as a statistical tool to analyze the data.

This study finds that moral hazard problem, lack of proper monitoring, inadequate collateral and nepotism have significant positive impact on the raising of NPLs. Unfortunately, this study does not find any statistical significance of poor credit assessment, business risk and repayment flexibility on the NPLs in Bangladesh. Finally, this study reveals that lending interest rate has significant positive impact on the NPLs. Hence, this study concludes that domestic lending interest rate is not lower enough, and so this double-digit interest rate affects negatively to loan repayment.

This study concludes that moral hazard problem of borrower, lack of board independence, lack of proper monitoring, form and extent of collateral, management lobbying, indecorous personal guarantee by management, dependent-independent directors and nepotism are extensively contributing for occurring NPLs in Bangladesh. These noninstitutionalized stimulators should adequately be scrutinized by regulatory bodies, policy makers and banks. Besides, LIR needs to be decreased in a convenient level for mitigating NPLs.

This study is the empirical evidence of behavioral dimensions related with the growth of NPLs in Bangladesh by taking direct response from knowledgeable bankers.