Reserach On The Influence Of Context Sensitivity On Consumers’ Choice Of Artificial Intelligence Recommendation

As the level of technology evolves and innovates,artificial intelligence is constantly being iterated and updated,and companies are trying to use AI technology to provide advice to consumers.The rise of artificial intelligence means that consumers are increasingly faced with a novel choice:should they rely more on humans or artificial intelligence?In many areas consumers are reluctant to accept AI recommendations,showing an aversion to the phenomenon.However,when it comes to the need for us to provide sensitive information to make recommendations for us,being in a high-sensitivity scenario where AI makes us feel at ease and comfortable,we are instead more likely to choose AI to make recommendations for us.Most of the studies on consumers’ willingness to accept AI recommendations have been conducted from the perspective of different types of recommendation tasks,while most of the studies on sensitivity have focused on the dimension of information sensitivity without combining it with scenarios.In real decision-making,individual behavior is often influenced by external situational factors,and there is very little research in this area at home and abroad.Therefore,this paper will design experiments to investigate whether and how different situational sensitivities affect consumers’ perceptions of AI recommendations.Based on privacy computing theory,this paper introduces two mediating variables,private self-awareness and public self-awareness,from different situational sensitivities to profile consumers’ willingness to accept artificial intelligence recommendations.Meanwhile,this paper explores the boundary conditions of its influence and empirically analyzes the moderating role of consumers’ uniqueness needs and privacy concerns in it.Through pre-experiments and formal experiments,three important conclusions are drawn:first,when consumers are in a low-sensitivity scenario,private self-awareness increases,and then the willingness to accept human recommendations increases;when consumers are in a high-sensitivity scenario,public self-awareness increases,and then the willingness to accept artificial intelligence recommendations increases.Second,for consumers with high uniqueness needs(vs.low),uniqueness needs reduce consumers’ willingness to accept AI recommendations under situational sensitivity.Third,for consumers with high privacy concern(vs.low),privacy concern increases consumers’ willingness to accept AI recommendations under situational sensitivity.The results of this study provide new suggestions for practical interventions that marketers can use to increase consumers’ willingness to rely on AI over humans,and for companies to adapt recommendation types at the practice level for different populations in different sensitivity scenarios,providing AI to make recommendations for consumers in high situational sensitivity,enhancing consumer comfort throughout the service phase and helping modern companies find a balance between technology and people in their practices.