The Impact of Advice Source and Attribution Type of Errors on the Willingness to Punish Agent Platforms
With the development of computer technology,the agency platforms are increasingly using AI as advisors to provide advice to consumers.However,like human advisors,AI may also make errors during service.In consumption,investment,and medical scenarios,a 2 × 3 between-subjects design was used to explore the impact of the advice source and attribution type on consumers'willingness to punish the agency platform after experiencing incorrect advice.The results showed that the effect of advice source on the willingness to punish the agent platform was not significant;attribution type significantly affected the willingness to punish,which manifested as an increase in punish willingness when attributing errors to the platform's intention.The impact of error intention attribution of platforms on the punitive willingness was mediated by anger.
advice sourceattribution typeangerpunitive willingness to punishAI
NETL
NSTL
万方数据
