Forecasting CNY exchange rate accurately is a challenging task due to its complex coupling nature, which includes market-level coupling from interactions with multiple financial markets, macro-level coupling from interactions with economic fundamentals and deep coupling from interactions of the two aforementioned kinds of couplings. This study develops a new deep coupled Long Short-Term Memory (LSTM) approach, namely DC-LSTM, to capture the complex couplings for USD/CNY exchange rate forecasting. In this approach, a deep structure consisting of stacked LSTMs is built to model the complex couplings. The experimental results with 10 years data indicate that the proposed approach significantly outperforms seven other benchmarks. The DC-LSTM is verified to be a useful tool to make wise investment decisions through a profitability discussion. The purpose in this paper is to clarify the importance of coupling learning for exchange rate forecasting, and the usefulness of deep coupled model to capture the couplings.

With the rise of corporate social responsibility (CSR) and the great changes of the organization scale of the modern enterprise, it is difficult to maintain an ideal development only by maximizing the equity of shareholders. The co-governance of stakeholders can meet the interests of all stakeholders, which is the embodiment of corporate social responsibility in corporate governance. The creation and sharing of enterprise values are the foundation of the coexistence of stakeholders. A rational allocation of the limited enterprise values among stakeholders plays a crucial role in balancing their relationship and realizing the sustainable development of the enterprise. Based on the application of corporate social responsibility in stakeholder governance, this paper constructs a stakeholder symbiosis evolution model with the help of symbiosis theory. By solving the differential equation, the symbiotic evolution path of stakeholders is analyzed. The dynamic mechanism of stakeholder Symbiosis evolution is analyzed by using the system analysis method and evolution theory. The dynamic mechanism of the population evolution of stakeholders is represented in an original graphical manner to describe the symbiotic evolution process of stakeholders. Lastly, we use the numerical simulation method to simulate different symbiosis models which are reflected by different symbiosis coefficients. It is concluded that the symmetric mutual benefit symbiosis model is the most effective model to reflect corporate social responsibility.

In the context of global sustainable development, the relationship between environmental, social responsibility, and governance (ESG) performance and multi-stakeholder value creation has been widely discussed. However, there is a complex causal relationship between ESG performance and value creation, many firm characteristics are involved, and there is no systematic study on them. In this study, we aim to explore the relationship between ESG performance and value creation, the joint role of firms’ internal and external characteristics in this relationship, and how the three components of ESG performance act on value creation through their various configurations. To identify complex causal relationships among variables, this study introduces rough sets method to describe these configuration relationships by generating rules. We use China’s 300 CSI-listed companies on the Shanghai and Shenzhen Stock Exchanges from 2015 to 2020 as research samples and find that firms with good ESG performance are more likely to have high-efficiency value creation; moreover, this relationship exists only among firms with specific characteristics. Additionally, different combinations of ESG components may have a differential impact on value creation, and we identify four configurations that generate high-efficiency value creation. This study contributes to guiding companies to strengthen their ESG practices and rationally allocate resources.

This study aims to illustrate how intellectual capital (IC) dimensions can improve corporate performance, and explore ideal IC combination methods in diversified firm situations to distribute IC dimensions effectively with limited resources. A universal theoretical framework based on Balanced Scorecard (BSC) theory is proposed to illustrate the way in which IC dimensions can enhance corporate performance from the perspective of stakeholders. Then, the rough set method is introduced to empirically explore ideal IC combination methods in diversified situations using 539 valid samples from China’s information technology industry. The theoretical analysis shows that IC dimensions work as a combination rather than as isolated parts to affect corporate performance, and different levels of corporate performance can be achieved by different IC combination methods under diverse firm factors. Ideal IC combination method is obtained through empirical study. Relational capital is the most important IC dimension, whereas leverage is the most important influence factor. This study extends IC management theory by profoundly illustrating the internal logical between IC dimensions and corporate performance through the theoretical framework. Additionally, this study introduces the rough set method to IC empirical research to explore ideal IC combination methods. Findings will deepen insight of practitioners about the essence of IC dimension combinations to corporate performance, and how they can apply the IC combination results to effectively distribute IC resources in diversified firm situations. The theoretical and practical research of this study extends both the third and fourth stages of IC research.