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In the face of an increasingly complex competitive environment, a company's ability to innovate is the key to a gaining sustainable competitive advantage. As the cornerstone of an organization's survival and development, employee innovative behavior is key to enhancing an organization's innovative capability. Based on a conservation of resources, this study investigates the mechanism of the role of superior–subordinate guanxi on employees' innovative behavior from both emotional and cognitive perspectives. Through the analysis of 305 full-time employees' research data, the results show that superior–subordinate guanxi can promote employees' innovative behavior by stimulating their work passion and reducing their dependence on superiors. Our research provides certain theoretical guidance and policy recommendations for enterprises to improve the innovation ability of employees by revealing the internal mechanism of superior–subordinate guanxi affecting the innovation behavior of employees. [ABSTRACT FROM AUTHOR]

The prediction of traffic flow is of great significance in the traffic field. However, because of the high uncertainty and complexity of traffic data, it is challenging that doing traffic flow prediction. Most of the existing methods have achieved good results in traffic flow prediction, but are not accurate enough to capture the dynamic temporal and spatial relationship of data by using the structural information of traffic flow. In this study, we propose a traffic flow prediction method with temporal attention mechanism and spatial attention mechanism based on neural architecture search (TS-NAS). Firstly, based on temporal and spatial attention mechanisms, we design a new attention mechanism. Secondly, we define a novel model to learn temporal flow and space flow in traffic network. Finally, the proposed method uses different modules about time, space and convolution and neural architecture search to be used for optimizing the model. We use two datasets to test the method. Experimental results show that the performance of the method is better than that of the existing method. [ABSTRACT FROM AUTHOR]

By collecting and analyzing sample from 384 employees in China, this study explored relationship between responsible leadership and organization citizenship behavior for the environment (OCBE) with structural equation model (SEM). The results are as follows: (1) responsible leadership is positively related to organization citizenship behavior for the environment. (2) responsible leadership has positive effects on both autonomous and external environmental motivation. (3) autonomous and external environmental motivation have a multiple-mediate role in the relationship between responsible leadership and organization citizenship behavior for the environment. Finally, this paper discusses the management implications of the research results and the future research direction. [ABSTRACT FROM AUTHOR]