인공지능 추천서비스에 의한 자율성 침해가 소비행복과 구전의도에 미치는 영향과 개인화와 제품유형의 조절효과

The Effects of Autonomy Infringement by Artificial Intelligence Recommendation Services on Consumption Happiness and Word-of-Mouth Intention and the Moderating Effects of Personalization and Product Types

Purpose - The purpose of this study is to verify the effects of autonomy infringement by AI recommendation services on consumption happiness and word of mouth intention. In addition, this research investigates the moderating roles of product types and personalization. Product types are classified into search goods and experience goods, and personalization is classified into high, medium, and low. Design/Methodology/Approach - This study tests the six hypotheses through experimental designs using scenarios. The experimental scenario situation is set as mobile shopping. Based on the previous research, a laptop is used for search goods and cosmetics is used for experience goods. Recommending travel services is selected for manipulating personalization. 155 people participate in the experiment. Scenarios are produced as 2 (autonomy infringement high, low) x 2 (search goods, experience goods) and 2(autonomy infringement high, low) X 3(personalization high, medium, low). For hypotheses testing, t-test and ANOVA are used. Findings - The results of this study show that autonomy infringement by AI recommendation services negatively affects consumption happiness and word of mouth intention. And the negative effects are greater in the experience goods than in the search goods. However, personalization does not significantly reduce the negative effects of autonomy infringement on consumer happiness and word of mouth intention. Research Implications - When marketing managers introduce automation technologies such as artificial intelligence into their marketing activities, they should consider that the technologies could undermine consumers’ autonomy, hampering consumers’ quality of life and voluntary loyalty behavior. Since the negative effects of autonomy infringement could appear differently depending on the product type and situation, a sophisticated approach is required when providing recommendation services to customers.