인공지능 알고리즘에 의한 추천이 소비자의 그린워싱 제품 수용의도에 미치는 영향 = The Effects of AI Algorithmic Recommendations on Consumer’s Intentions to Accept Greenwashing Products

국문 초록 (Abstract)

최근 환경문제가 심각해지면서 지구온난화의 심각성이 커지는 가운데, 소비자들의 친환경 제품에 대한 관심이 꾸준히 이어지고 있다. 그러나 일부 기업들은 친환경 마케팅의 효과를 높이기 위해 ‘그린워싱’ 전략을 사용함에 따라 소비자들은 진정한 친환경 제품을 식별하는 데 어려움을 경험하고 있으며, 이로 인해 외부 정보에 더 크게 의존하는 경향을 보이고 있다. 디지털 전환이 이루어짐에 따라 정보 탐색 수단으로 AI 기반 추천 시스템이 보편화되고 있음에도 불구하고, 친환경 제품 구매 의사 결정에서 인공지능 알고리즘과 같은 추천 주체의 유형이 소비자의 제품수용 의도에 미치는 영향을 실증적으로 검증한 연구는 아직 부족한 실정이다. 따라서 본 연구에서는 2(제품 유형: 친환경 제품 vs. 그린워싱 제품) x 2(추천 주체: 실제 전문가 vs. AI 알고리즘) 집단 간 실험설계를 통해 제품유형에 따라 추천 주체가 소비자의 제품 수용 의도와 제품 비윤리성 인식에 미치는 영향을 측정하였다. 실증 분석결과에 따르면, 그린워싱 제품의 경우 인공지능 알고리즘이 추천해 주었을 때 보다 실제 전문가가 추천해 주었을때 제품에 대한 수용 의도가 더 높게 나타났다. 반면 친환경 제품의 경우 추천 주체에 따른 제품 수용 의도의 차이는 나타나지 않았다. 또한, 제품 유형과 추천 주체의 상호작용이 제품 수용 의도에 미치는 영향은 소비자가 인지하는 제품의 비윤리성에 의해 완전 매개됨을 확인하였다.

다국어 초록 (Multilingual Abstract)

As environmental issues become more serious, highlighting the severity of global warming and the growing importance of ESG management, consumers’ interests in eco-friendly products is steadily growing. As such, individuals have begun to directly perceive the severity of environmental issues in their daily lives, and this shift significantly influences corporate activities. In particular, over the past two decades, eco-friendly marketing has seen substantial global growth, with a corresponding increase in awareness and interest across various countries. Major global companies are actively adopting eco-friendly trends, and the global green economy is projected to generate approximately $10 trillion in business value and create up to 400 million jobs by 2030. In the domestic market, the size of the eco-friendly market also saw a nearly 20-fold increase, growing from 1.5 trillion KRW in 2001 to 30 trillion KRW in 2020. However, as some companies use ‘greenwashing’ strategies to enhance their eco-friendly marketing effects, consumers find it difficult to identify genuine eco-friendly products and, as a result, indicate a greater tendency to rely on external recommendations. Although AI-based recommendation systems have become widespread as information search tools, there is a lack of empirical studies verifying whether artificial intelligence algorithms can fully replace human expert recommendations in making purchase decisions of eco-friendly products, and how the type of recommendation sources affects consumers’ product acceptance intentions.
Therefore, this study conducts a 2 (product type: eco-friendly product vs. greenwashing product) × 2 (recommendation source: human expert vs. AI algorithm) between-subjects experimental design. Scenarios and stimuli for a body wash product were presented according to each experimental condition, and consumer responses regarding product acceptance intention and perception of product unethicality were measured.
According to the empirical analysis results, for a greenwashing product, the product acceptance intention was higher when the product recommended by a human expert than by an AI algorithm. Conversely, for an eco-friendly product, there was no difference in product acceptance intention based on the recommendation source between an AI algorithm and a human expert. Furthermore, it was confirmed that the interaction effect of product type and recommendation source on product acceptance intention was fully mediated by a consumers’ perception of product unethicality. These results demonstrate that a consumer places greater trust in recommendations from a human expert than in those from an AI algorithm when requiring ethical judgment to discern genuine green attributes from greenwashed attributes of the product. However, the influence of the recommendation source is not a significant element in processing information of an eco-friendly product.