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The current study examines the relationship between financialization, managers’ incentives, and the enterprise’s innovation. Based on the principal-agent and incentive theories, this study proposes a research model with two management incentives as moderating variables between financialization and the enterprise’s innovation. First, we analyze the direct relationship between financialization and the enterprise’s innovation. Second, we examine the moderating effect of managers’ equity incentive and compensation incentives on the relationship between entity financialization and the enterprise’s innovation in high-tech/non-high-tech enterprises and state-owned and non-state-owned enterprises. This study covers the most recent updated data from both A-share listed companies in the Shenzhen and Shanghai stock exchange in China from 2009 to 2019. This study’s finding indicates a significant negative impact of entity financialization and the enterprise’s innovation. It means that the entity financial has a significant “crowding-out” effect on the enterprise’s innovation. This study also confirms that management incentives cannot effectively suppress a “crowding-out” impact of entity financialization on firm innovation because of the principal-agent severe problem in financialization. Finally, considering the heterogeneities of property rights and degrees of dependence on the enterprise’s innovation, a “crowding-out” effect of entity financialization on the enterprise’s innovation is more significant in high-tech and state-owned enterprises. Managers’ equity incentive significantly affects the enterprise’s innovation in high-tech enterprises, while the managers’ compensation incentive affects the enterprise’s innovation in state-owned enterprises. Our study could help the enterprise to improve the company manager’s incentive and provide the optimal assets allocation to improve the enterprise’s innovation ability. Lastly, this study provides significant policies and recommendations for the public sector high-tech enterprise and private sector high-tech enterprises. Moreover, policies and recommendations are fruitful for the public sector non-high-tech enterprise and private sector non-high-tech enterprise.

Soft manipulators can perform continuous operations due to their inherent compliance and dexterity, thus enabling safe interactions and smooth movements in confined environments. However, high compliance usually means low load capacity. It is important for a soft manipulator to possess proper flexibility while maintaining an acceptable stiffness to widen its applications. This paper has hence devoted efforts to a kind of variable stiffness mechanism for a soft manipulator actuated by pneumatic artificial muscles (PAMs). Due to the combination of contractile and extensor PAMs, the manipulator is able to vary its stiffness independently from the configuration. The stiffness characteristics of the soft manipulator are quantitatively analyzed by bending shape prediction under different loading and inflation conditions, and the prediction is built upon a nonlinear statics model coupled with PAM nonlinearity and the Cosserat theory. In addition, experimental measurements are conducted to further validate the expected performance of the manipulator design. The experimental and verified theoretical analysis results indicate that the manipulator shape and stiffness are greatly affected by the pressure variation of PAMs, realizing a large bending space with a high output force. The variable stiffness design obviously increases the manipulator's ability to resist additional interference at the same position. INDEX TERMS Soft manipulator, PAM, bending shape prediction, variable stiffness, the Cosserat theory. LINA HAO received the Ph.D. degree in control theory and control engineering from Northeastern University, China, in 2001. From 2005 to 2006, she worked as a Visiting Researcher with Michigan State University, USA. She is currently a Professor with the School of Mechanical Engineering and Automation, Northeastern University. Her main research interests include design and control of micro-nano robotic systems, bionic drivers of artificial muscles, and smart sensors and actuators. She is a Fellow of the IEEE Robotics and Automation Society and the International Society of Bionic Engineering.

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