| The competition of Chinese financial enterprises is fierce.Financial enterprises must develop new products to match the changing needs of markets,and most financial enterprises will set up cross functional teams including market,technology,finance and other functional employees.Therefore,one of the key factors to improve the effect of financial product development is to effectively integrate and manage employees,so as to reduce the probability of immoral behavior of team members.Meanwhile,the COVID-19 makes the online collaboration platform develop blowout.Many online collaboration platforms can provide more advanced algorithmic technology to monitor people’s online collaboration process.However,the impact mechanism of this algorithm-enabled shared monitoring on the behavior of members of financial product development team is still uncertain.This study adopted the self-regulated learning theory and the learning strategy to explore the impact mechanism of algorithm-enabled shared monitoring on team members’ deviant behavior.This study carried out the laboratory experimental research method,that is,through the laboratory experiment to simulate the online cooperation process of the financial product development team,and collected the data according to the different stages of the laboratory experiment.The results show that in the online collaborative environment,both learning strategies can reduce deviant behavior by improving the participation of collaborative learning.At the same time,algorithm-enabled shared monitoring has a U-shaped regulatory effect on deviant behavior,that is,appropriate monitoring can promote the cooperation effect of team members and reduce deviant behavior,but more in-depth monitoring will lead to the exclusion of team members,and promote deviant behavior.This study has a deeper understanding of the behavior mechanism of financial product development team in both theoretical and practical significance. |
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