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This paper aims to study the following two questions. Do earnings announcements stimulate investors to participate in online discussions? Does online investment forum participation affect the market’s reaction to earnings news?

The authors collect all the online posts, which were related to the internet service companies and posted in a Chinese financial forum, guba.eastmoney.com (Guba), during the period between June 30, 2008 and December 31, 2015. Multiple linear regression analysis is used to test the questions.

The study finds that the earnings announcements induce online discussion. In addition, before the earnings announcement, online posting activity does not affect earnings response coefficient but can weaken the positive association between the magnitude of the upcoming earnings surprise and abnormal trading volume. In contrast, after the earnings announcement, online forum participation can facilitate the incorporation of earnings surprise into the price.

This study contributes to the literature studying the impact of social media on market reaction to earnings news by providing evidence that the price discovery process can be affected by the online investment forum. Several policy implications are also provided.

The purpose of this paper is to investigate the impacts of the 2008 Chinese stimulus program on earnings management.

Using a sample period from 2004 to 2011 (per-stimulus period: 2004-2007 and post-stimulus period: 2008-2011), the authors compare the change in earnings management between the firms that received the stimulus funds and those that did not receive the stimulus funds.

The authors find that from the pre- to post-stimulus period, the recipient firms experienced a greater increase in downward accrual management and a greater decrease in real management than the non-recipient firms did. This result is primarily driven by the non-state-owned enterprises and firms using non-Big-Four auditors.

The results suggest that the earnings management level is ultimately determined by the underlying economic and political factors influencing managers’ and auditors’ incentives (Cohen, 2008; Ball et al., 2003). Meanwhile, some mechanisms, such as high-quality audit (Eshleman and Guo, 2014) and state ownership (Wang and Yung, 2011) can also play a role in determining the level of earnings management.

This paper aims to investigate the relationships between several macro‐economic indicators and real estate investment in China.

This study proposes the “investment preference theory” to explain that bank deposits, stock investment and real estate investment are three important investment vehicles to Chinese households.

The authors find that interest rate, an important monetary aggregate indicator – M2 – and the size of new equity offering are negatively related to real estate investment, which may imply that Chinese investors would prefer to channel their funds to stock market and high‐interest‐rate‐bearing bank deposits to keep a good balance between risk and high return on investment while higher interest rate also increases the cost of borrowing for the property buyers.

This is one of the first studies which investigated the connections behind Chinese consumers' real estate investment and empirically tested the choices among bank deposit, stock and property investment. This study hopefully deepens the understanding towards the consumer investment behaviors in housing investment decisions.

The purpose of this paper is to investigate the effect of operating cycle on the differential persistence of accruals and cash flow, and the market reaction to the different components of earnings across firms with various operating cycles.

By examining the US public firms' earnings and the capital market reaction to different components of earnings, from 1964 to 1993, it is found that the longer the operating cycle, the lesser will be the persistent of accruals.

This result is consistent with Sloan's theory that the differential persistence of accruals is attributable to estimation errors in accruals. Moreover, the market efficiency test shows that the mispricing of accruals is greater for firms with longer operating cycle, indicating that investors fixate on earnings, while ignoring the persistence of accruals among firms with different earnings quality.

This paper adds to the growing literature that has begun to examine the factors affecting accrual persistence and accrual mispricing by indicating that the length of operating cycle can play a role. In addition, it provides fresh evidence that the market fixates on earnings, thus emphasizing the importance of contextual analysis of financial statement. Finally, it corroborates Sloan and Xie that estimation errors in accruals drive the lower persistence of accruals.

The purpose of this paper is to explore how networks of boards of directors affect relative performance evaluation (RPE) in chief executive officer (CEO) compensation.

In this study, the authors propose that an interlocking network is an important inter-corporate setting, which has a bearing on whether boards decide to use RPE in CEO compensation. They adopt four typical graph measures to depict the centrality/position of each board in the interlock network: degree, betweenness, eigenvector and closeness, and study their impacts on RPE use.

The authors find that firms that have more connected board members and whose board members are connected to better connected firms are more likely to reward their CEOs contingent on their peers’ performance, indicating that information transmission along the board interlock network facilitates the adoption of RPE. This result is robust to alternative measures for board interlock networks and various types of CEO compensation. It highlights the role of interlocking directorates in disseminating information and practice of RPE use along board network.

The authors use social network analysis to measure the relationships and flows between the connected nodes and study the impact on executive compensation design.

The purpose of this paper is to understand the impact of tenure on earnings management.

Analytical model; multivariate regression analysis.

The paper predicts that managers are conservative in managing earnings when they first start to take top managerial positions, and then become aggressive in the next few years. Once they reach the maximum level of earnings management, they will become conservative again and report earnings less aggressively. This inverted U-shaped relationship between tenure and earnings management is confirmed by the data from the Chinese stock market.

It is based on China stock market data. Generalization of the research results to other countries is limited.

With the knowledge of when earnings management is more likely to occur, regulators can set up policies targeting firms and managers with certain characteristics, instead of requiring observances from all firms and managers. This limited scope can greatly reduce the costs of preventing and identifying earnings management, while effectively maintaining the quality of earnings in the meantime.

This paper examines the earnings management behavior related to CEO tenure. It is hoped that the research results can improve the overall understanding of earnings management, then social wealth spent on preventing and identifying it could be reduced.

It is an original work.

The purpose of this paper is report the importance of research publications for the tenure promotion and for faculty in accounting, finance, and information system (IS) areas, developing valid criteria for the assessment of quality in related journals is necessary.

Existing rankings are usually based on a survey among faculty members, while ignoring the chairs' critical role in tenure evaluation. This paper uses department chairs' responses to a survey asking to assess relative journal quality, and hence provides quantitative standards to measure research productivity. The rankings are primarily obtained by the familiarity‐rank position index method. Different sets of rankings for the decision‐makers in universities, with various requirements for research are provide.

It is found that the rankings in accounting and finance areas are consistent with the prior research, but the rankings in the IS have changed significantly. This difference to the rapid growth in the field of IS is attributed. The robustness check also corroborates the ranking lists.

In addition, this paper reports not only a comprehensive ranking list including most journals in accounting, finance, and IS areas, but also separate rankings in each field.

Building information modelling (BIM), lean construction (LC) and prefabricated housing construction (PHC) have individually aroused great attention from academia and industry. However, the integration of LC and BIM in PHC projects has not been sufficiently explored. This study aims to assess the current status of the implementation of BIM and LC in China’s PHC sector given, firstly, that China is a developing country characterised by the world’s largest population and a huge housing market, and secondly, that although China’s PHC is strongly supported by the government, the adoption of BIM and LC in PHC varies.

A mixed approach (questionnaire survey and interviews) is adopted in this study. A total of 127 valid questionnaires were collected. This is followed by interviewing 12 interviewees who are key stakeholders in PHC and hold managerial positions.

The findings of the questionnaire survey show that BIM is more prevalent than LC in PHC projects in China. In addition, the adoption of LC exhibits more maturity in stages associated with production and manufacturing, and logistics and transportation, whereas BIM has seen wider adoption in design and construction. The interviews validated the factors that influence the implementation of BIM and LC in PHC projects in China.

The study uses a strengths, weaknesses, opportunities and threats analysis framework to clarify the opportunities, threats, strengths and weaknesses of BIM and LC in China’s PHC and proposes strategies.

This study aims to develop a quadrotor with a robust control system against weight variations. A Proportional-Integral-Derivative (PID) controller based on Particle Swarm Optimization and Differential Evaluation to tune the parameters of PID has been implemented with real-time simulations of the quadrotor.

The optimization algorithms are combined with the PID control mechanism of the quadrotor to increase the performance of the trajectory tracking for a quadrotor. The dynamical model of the quadrotor is derived by using Newton-Euler equations.

In this study, the most efficient control parameters of the quadrotor are selected using evolutionary optimization algorithms in real-time simulations. The control parameters of PID directly affect the controller’s performance that position error and stability improved by tuning the parameters. Therefore, the optimization algorithms can be used to improve the trajectory tracking performance of the quadrotor.

The online optimization result showed that evolutionary algorithms improve the performance of the trajectory tracking of the quadrotor.

This study states the design of an optimized controller compared with manually tuned controller methods. Fitness functions are defined as a custom fitness function (overshoot, rise-time, settling-time and steady-state error), mean-square-error, root-mean-square-error and sum-square-error. In addition, all the simulations are performed based on a realistic simulation environment. Furthermore, the optimization process of the parameters is implemented in real-time that the proposed controller searches better parameters with real-time simulations and finds the optimal parameter online.

The purpose of this study is to make a prediction of China's energy consumption structure from the perspective of compositional data and construct a novel grey model for forecasting compositional data.

Due to the existing grey prediction model based on compositional data cannot effectively excavate the evolution law of correlation dimension sequence of compositional data. Thus, the adaptive discrete grey prediction model with innovation term based on compositional data is proposed to forecast the integral structure of China's energy consumption. The prediction results from the new model are then compared with three existing approaches and the comparison results indicate that the proposed model generally outperforms existing methods. A further prediction of China's energy consumption structure is conducted into a future horizon from 2021 to 2035 by using the model.

China's energy structure will change significantly in the medium and long term and China's energy consumption structure can reach the long-term goal. Besides, the proposed model can better mine and predict the development trend of single time series after the transformation of compositional data.

The paper considers the dynamic change of grey action quantity, the characteristics of compositional data and the impact of new information about the system itself on the current system development trend and proposes a novel adaptive discrete grey prediction model with innovation term based on compositional data, which fills the gap in previous studies.