INCENTIVE EFFECT AND EMOTION REGULATION OF INFORMATION TECHNOLOGY ON INNOVATION BEHAVIOR
Authors: Zhao Xincheng , Liu Qian , Xu Dongpeng , Yang Yile 
Published: July 2022

Abstract

Background
This paper attempts to explain the impact mechanism of information technology on enterprise innovation ability, in order to put forward policy suggestions to optimize information resources and improve enterprise innovation ability. It has become an important strategic choice for China to connect with the world under the background of independent information construction. Information technology has become an important contribution to China's economic development. Information technology provides convenient conditions for the optimal allocation of various innovation elements in enterprise innovation activities. At the same time, the application of information technology also plays an important role in improving the efficiency of innovation activities and emotion regulation.

Research Objects and Methods
Based on the subjective survey data of Chinese enterprises by the world bank, taking the intensity of enterprise innovation output as the dependent variable and the degree of enterprise informatization as the core independent variable. The relevant influencing factors mainly include network economy, financing constraints and technology imitation. In order to alleviate the possible endogenous problems, this paper uses ivtobit model combined with the concept of maximum likelihood method for empirical research. In order to verify the impact of technological innovation on emotion, this study used relevant scales to investigate. (1) Positive emotion scale. The Panas emotion scale developed by Wason et al. Is widely used to measure emotion. The scale includes two dimensions: positive emotion and negative emotion. The sample is from full-time postgraduates and undergraduates in a university in Shanghai. 210 students (1 graduate class and 4 undergraduate classes) were randomly divided into 46 teams with an average size of 4.57. The age of the subjects ranged from 19 to 25 years old, with an average of 21.45 years old. Women accounted for 76.1% of the total sample, and men accounted for 23.9%. All subjects are required to complete a campus recruitment project in the form of a team simulating the employer in about two months. This project is designed according to the curriculum requirements of talent evaluation. Before the formal implementation of the project, the subjects were randomly divided into groups. The implementation cycle of the whole project is 9-11 weeks (two classes per week, a total of 90 minutes), including three main links: project preparation, project implementation and project summary. Among them, the preparation link is 2-3 weeks, mainly to complete the formulation of the overall recruitment plan and determine the recruitment target post, set post evaluation model, design evaluation technical scheme, prepare test questions and evaluation form, etc. The implementation link is 3-4 weeks, mainly completing the tasks of publishing recruitment information, collecting and screening resumes, notifying interviews, organizing interviews, and scoring by examiners. The summary link is 3-4 weeks, which mainly completes the tasks of discussing and summarizing the evaluation results of candidates, issuing evaluation reports, project reports, and submitting final reports. In the whole process of project implementation, in addition to completing the corresponding project tasks in class, the project team also needs to make sufficient preparations and conduct more interaction and discussion after class

Results
The regression results showed that the enterprise informatization coefficient was positive. This shows that there is a positive correlation between enterprise application of information technology and innovation. This means that the higher the application level of information technology in enterprises, the more innovation output. Chinese enterprises should increase it (Information Technology) investment, use information technology to optimize the allocation of enterprise innovation elements and enhance enterprise innovation ability. Some factors are closely related to innovation behavior. There is a significant positive correlation between e-commerce and enterprise innovation. Companies engaged in e-commerce activities have higher innovation probability than companies not engaged in e-commerce activities. In other words, the existence of network commerce has a significant incentive effect on enterprise innovation. The financing barrier coefficient is negative, which is significant at the level of 1%. Enterprise financing channels hinder innovation. Whether the company has convenient financing channels has a significant impact on innovation. For the impact of technology imitation, the regression coefficient is negative and significant at the level of 1%. It can be seen that technology imitation has a negative impact on enterprise innovation. Because informal enterprises can “fake” quickly and mechanically in a short time, it has a certain negative impact on the enthusiasm of independent innovation activities of formal enterprises. At the same time, in terms of emotion regulation ability, in order to test the structural validity of the main variables in the study, model comparison is carried out first. Using mplus6.11 software, confirmatory factor analysis was carried out on the model of 12 dimensions (5 personality dimensions, 4 emotional intelligence dimensions, trust perception within the team, task performance and organizational citizenship behavior, a total of 48 items), the model of 8 dimensions (5 personality dimensions combined) and the model of 9 dimensions (4 emotional intelligence dimensions combined) at the item level. The analysis results show that the main fitting index values of the 12 dimensional model are: X2 (1014) = 1584.10, X2 / DF = 1.56, RMSEA = 0,05, CFI = 0.89, which is better than the 8-dimensional model (x2 (1052) = 2383.22, X2 / DF = 2.27, RMSEA = 0.08, CFI = 0.74) and 9-dimensional model (x2 (1044) = 2620.93, 2 / DF = 2.51, RMSEA = 0. 09, CFI=0.70). Secondly, the factor load of each item of the optimal model is investigated. According to the analysis results of Mplus 6.11, the factor load is 0.23-0.94 (the smallest factor load is 0.23, and the factor load of the other 47 items is greater than 0.40), which is significant at the level of 0,01. The above results show that the measurement variables in this study have good structural validity. The reliability of each measurement tool basically meets the requirements of psychometrics. From the reliability and validity test results, the data collected by the measurement tools in this study have strong reliability.

Conclusion
With the continuous improvement of global informatization level, the country should pay more attention to informatization construction. Chinese enterprises should take the initiative to improve the level of informatization, promote the optimal allocation of innovation elements and improve their innovation ability. This study has important reference significance for understanding the incentive and influencing factors of enterprise innovation behavior under the information wave.

Acknowledgements
Supported by the projects grant from Guangdong Philosophy and Social Science Planning Project (Grant No. GD18XYJ20), Research Platforms and Projects of Colleges and Universities in Guangdong (Grant No.2020WTSCX312, 2020GXJK252). Guangzhou Science and Technology Planning Project (202102080280).