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The purpose of this study is to investigate the deformation characteristics and failure modes of the right bank slope of Xiluodu Hydropower Station after excavation.

Micro-seismic monitoring technology is applied to obtain the microfracture information and study the internal damage evolution law of the slope rock mass. A numerical model for discontinuous deformation analysis (DDA) is established to analyse the deformation characteristics and failure mode of the slope. Micro-seismic monitoring and DDA can verify and supplement each other's results in the investigation of slope failure.

The results show that the slope has a downhill displacement along the weathered zone under natural conditions; the maximum resultant displacement at the monitoring point is 380 mm. The micro-seismic events are concentrated in an area located 30–100 m horizontally away from the slope surface and at an elevation of 390–470 m. The distribution of these micro-seismic events is consistent with the location of the unloading and weathered zones; it is the same as the DDA simulation result.

The study is anticipated to be used as reference for the stability analysis of rock slopes. By combining the continuous (micro-seismic monitoring technology) and discontinuous (DDA) methods, the entire process starting from the gradual accumulation of internal rock micro-damage to the macroscopic discontinuous deformation and failure of the slope can be investigated.

Due to the increasing risk and uncertainty of construction projects, contractual flexibility has been considered as an effective tool to cope with emergences and to promote cooperation between owners and contractors. However, in practice, owners often failed to build an efficient cooperative relationship via contracts, resulting in a lacking of appropriate justice. Furthermore, due to a lack of available empirical research, the influence of contractual flexibility on the cooperative behavior of contractors requires further investigation. The purpose of this paper is to fill this gap by conducting empirical research from the perspective of justice perception.

A theoretical model was developed and a series of hypotheses were proposed. Then, partial least squares structural equation modeling analyses were conducted on a sample of 188 respondents.

The results show that contractual content and executing flexibility both have a positive influence on the cooperative behavior of a contractor, which was partially mediated by distribution, procedural, and interactional justice perceptions. Moreover, content flexibility has a significant impact on all three types of justice perception, and the execution of flexibility has more impact on interactional justice compared to other justice perceptions.

The findings contribute to an improved understanding of how contractual flexibility affects the cooperative behavior of contractors, indicating that the owner could develop a fair exchange relationship through flexible contracting and motivation of the other party.

This study aims to explore the relationship between financing constraints and the innovation performance of Internet enterprises in the cross-border innovation cooperation network. The study also analyzes the moderating effect of the location of the cross-border innovation cooperation network.

The authors selected patent data, related transaction data and other data of A-share listed companies on Shanghai and Shenzhen stock exchanges from 2014 to 2019. The generalized moment estimation method of instrumental variables (IV-GMM) method was used to analyze the relationship between financing constraints and the innovation performance of Internet firms and the moderating effect of the cross-border innovation cooperation network location. The threshold value of the moderating effect of the network structure hole was calculated with the threshold model.

The empirical results show a significant inverted U-shaped relationship between financing constraints and the innovation performance in the cross-border innovation cooperation network of Internet enterprises. Network centrality positively moderates this relationship. There is a threshold for the adjustment effect of network-structural holes, and the adjustment intensity of structural holes changes before and after the threshold.

This study provides a new perspective for Internet firms in innovation cooperation networks to alleviate the negative impact of financing constraints on innovation performance. The inverted U-shaped relationship between financing constraints and the innovation performance of Internet enterprises is in two stages. The moderating range of network centrality and the structural hole besides the threshold of the moderating effect of a structural hole are detailed.

For the developing countries involving in the Belt and Road Initiative (BRI) with China as the main source of foreign development investment (FDI) and development as the top priority, it appears to attract more and more attention on how to make the best use of China’s outward foreign development investment. However, the contradictory evidence in the previous studies of FDI spillover effect and the remarkable time-lag feature of spillovers motivate us to analyze the mechanism of FDI spillover effect. The paper aims to discuss this issue.

The mechanism of FDI spillovers and the unavoidable lag effect in this process are empirically analyzed. Based on the panel data from the Belt and Road developing countries (BRDCs) and China’s direct investments (CDIs) from 2003 to 2017, the authors establish a panel vector autoregressive model, employing impulse response function and variance decomposition analysis, together with Granger causality test.

Results suggest a dynamic interactive causality mechanism. First, CDI promotes the economic growth of BRDCs through technical efficiency, human capital and institutional transition with combined lags of five, nine and eight years. Second, improvements in the technical efficiency and institutional quality promote economic growth by facilitating the human capital with integrated delays of six and eight years. Third, China’s investment directly affects the economic growth of BRDCs, with a time lag of six years. The average time lag is about eight years.

Based on the analysis on the mechanism and time lag of FDI spillovers, the authors have shown that many previous articles using one-year lagged FDI to examine the spillover effect have systematic biases, which contributes to the research on the FDI spillover mechanism. It provides new views for host countries on how to make more effective use of FDI, especially for BRDCs using CDIs.

This paper aims to mainly investigate the role of trust, which is an important informal system, in executive compensation incentives.

Using the data of Chinese A-share private enterprises from 2003 to 2014, the paper estimates the effect that trust has on executive compensation incentives.

Results indicate that trust can significantly enhance the effectiveness of executive compensation incentives. Furthermore, the better the regional trust environment in which companies are located, the more pronounced the effect is. In particular, the effect of trust on executive compensation incentives is only significant when the formal legal system is immature. As companies continue to grow and develop and the formal system becomes perfect, the role of trust weakens. The formal system, including the corporate governance mechanism and perfect legislation, then becomes the key to promoting executive compensation incentives.

This paper provides evidence of the significance of both informal and formal systems. It not only emphasises the important role that the informal system has played in “the mystery of China’s economic growth” but also supports the “ruling the country by law” strategy for the sustainable development of China’s economy.

This paper reveals the relationship between the formal and informal systems, which provides a new perspective on and empirical evidence for the determinants of executive compensation incentives, and it also finds an explanation for the rapid growth of China’s economic development.

Building information modeling (BIM) is recognized as a major innovation in the architecture, engineering, and construction (AEC) industry. Understanding the factors that influence the AEC’s adoption of BIM will benefit the research and practice of BIM. The paper aims to discuss these issues.

This study provides empirical evidence for the accumulated knowledge of BIM adoption by examining the context of Chinese construction industry. Based on the technology-organization-environment (TOE) framework in the innovation diffusion literature, the authors develop a research model that integrates the critical success factors related to the technology of BIM, the construction company and the environment in Chinese construction industry. The authors collected two different data sets from engineering consulting firms and construction firms in China, and conducted rigorous analyses using a sophisticated statistical approach.

The authors found that the relative advantage of BIM was a major factor that enabled BIM adoption, while the complexity of BIM was an inhibiter. In addition, management support was also a significant antecedent of BIM adoption. However, organizational readiness was significant for engineering consulting firms but not for construction firms. Surprisingly, the authors did not find consistent significant impacts of any environmental factors. Last, younger firms were more likely to adopt BIM.

One of the first to apply the TOE framework to integrate three groups of factors that may explain BIM adoption in China. Such a comprehensive framework provides a much broader perspective of BIM adoption to evaluate the impacts of different antecedent factors. The authors conducted an empirical study based on survey data collected from two different types of companies, i.e., engineering consulting firms and construction firms, representing the two parties in the principal-agent relationship of a construction project. One of the first to apply a sophisticated statistical approach, i.e., partial least squares, to analyze the data in the BIM literature.

Coal is a critical global energy source, and fluctuations in its price significantly impact related enterprises' profitability. This study aims to develop a robust model for predicting the coal price index to enhance coal purchase strategies for coal-consuming enterprises and provide crucial information for global carbon emission reduction.

The proposed coal price forecasting system combines data decomposition, semi-supervised feature engineering, ensemble learning and deep learning. It addresses the challenge of merging low-resolution and high-resolution data by adaptively combining both types of data and filling in missing gaps through interpolation for internal missing data and self-supervision for initiate/terminal missing data. The system employs self-supervised learning to complete the filling of complex missing data.

The ensemble model, which combines long short-term memory, XGBoost and support vector regression, demonstrated the best prediction performance among the tested models. It exhibited superior accuracy and stability across multiple indices in two datasets, namely the Bohai-Rim steam-coal price index and coal daily settlement price.

The proposed coal price forecasting system stands out as it integrates data decomposition, semi-supervised feature engineering, ensemble learning and deep learning. Moreover, the system pioneers the use of self-supervised learning for filling in complex missing data, contributing to its originality and effectiveness.