Research On The Effect Of Task Description Strategies In Crowdsourcing Contests

As the application of crowdsourcing contests in the context of innovation continues to increase,the size of the group is particularly important for innovation resource managers.How to gather and manage a large-scale group of intellectual resources,and how to gain a comparative advantage in the contests for limited intellectual resources with competition task employers in the same field,is a challenging strategic issue for crowdsourcing contest employers.In the online crowdsourcing contests platform,the employee only relies on limited information disclosure when selecting tasks,and bears a high risk of uncertainty.Task description is an important source of information.UGC‘s content generation methods and the differences in language style and rhetoric between individuals lead to large differences in text content,which can effectively help crowdsourcing tasks stand out from similar tasks in the same field.Existing studies have discussed the formal characteristics of task descriptions such as length,format,and normativeness,but there are still research gaps for the impact of task description strategies.Based on the research perspective of textual persuasion,this thesis uses the word frequency statistics method of text analysis to explore the impact of different persuasive styles of crowdsourcing contests task description strategies on the size of the participants.On this basis,combined with the situational factors of the characteristics of the crowdsourcing contests task and the employers,three moderators have been introduced to expand the application boundary of the research conclusion.Collected 60,504 pieces of real competition data through the method of web crawling,and used the negative binomial regression model to conduct hypothesis testing,proving that "appeal to logic" is the most effective persuasion method for creative crowdsourcing tasks.There are different optimal persuasion strategies corresponding to the situation of the task and the characteristics of the employer.This thesis expands the research literature in the field of crowdsourcing contests to a certain extent and provides some valuable management implications for crowdsourcing employers.