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추천 알고리듬의 세렌디피티 경험을 통한 항공권 구매: 개인화의 조절 효과

Airline Ticket Purchase through the Serendipity Experience of Recommendation Algorithm: Moderating Effect of Personalization

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한국항공경영학회 (Aviation Management Society Of Korea)|2023.06|한국항공경영학회지 (Journal of the Aviation Management Society of Korea)|제21권 제3호|pp. 3-26|DOI 10.30529/amsok.2023.21.3.001

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참고문헌

키워드

Artificial Intelligence인공 지능개인화Personalization추천 시스템Recommender System세렌디피티 경험항공권 구매추천 만족Serendipity ExperienceAirline TicketRecommend Satisfaction
주제분류경영학

초록

인공지능의 발전과 비대면 서비스의 확대로 온라인 항공권 추천 서비스를 이용하는 소비자는 증가하고 있다. 온라인 추천 시스템은 소비자의 과거 구매나 검색 기록을 분석하여 개인화된 추천 제안을 제공하는 자동화된 알고리듬이다. 대부분의 소비자들은 최저 가격과 최적 조건의 항공권을 구매하는 것을 목표로 추천 서비스를 이용한다. 그러나 추천 서비스를 이용하는 과정에서 경험하는 뜻밖의 행운, 즉 세렌디피티 경험에 관한 연구는 매우 부족한 실정이다. 세렌디피티는 의도하거나 찾고 있지 않은 것을 우연히 발견하였을 때 발생하는 긍정적이고 예상치 못한 발견이며, 기업이나 브랜드에 대한 소비자의 긍정적인 태도를 강화한다. 본 연구에서는 항공권 추천 서비스 이용자들을 대상으로 세렌디피티 경험의 특성을 연구하고, 세렌디피티 경험이 추천 만족과 구매 의도에 미치는 관계를 실증하고자 한다. 또한 개인화 변수의 조절적 효과를 탐색함으로써, 추천 시스템에서 고객 데이터의 중요성을 확인하고 개인화 마케팅의 방향을 제시하였다. 연구 모델의 실증 분석을 위하여 온라인 설문지 사이트를 구축하고 총 154부의 설문을 수집하였다. 사용된 척도의 신뢰성과 타당성은 요인분석과 신뢰성 분석을 실시하였고, 가설 검증은 PLS 분석을 활용하였다. 분석 결과에 따르면 의사결정 용이성, 호기심, 진기성, 관심 상기성이 세렌디피티 경험에 유의한 영향을 미쳤으며, 거래조건 특별성은 예상과 다르게 세렌디피티 경험에 유의한 영향을 주지 않았다. 세렌디피티 경험은 추천 만족과 구매 의도에 모두 유의한 영향을 주었다. 또한 세렌디피티 경험과 추천 만족, 구매 의도 변수간의 관계는 개인화 변수에 의하여 효과적으로 조절되는 것으로 확인되었다. 본 연구 결과는 항공사와 연구자들이 항공권 추천 서비스를 이해하고, 세렌디피티라는 새로운 고객 경험을 이해하는데 새로운 시사점을 제공하고 있으며, 이 과정에서 개인화의 중요성을 확인하는 성과를 거두었다.

Abstract

The increasing development of artificial intelligence and the expansion of online services have led to a growing number of consumers using online recommendation services. Online recommendation systems are automated algorithms that provide personalized recommendation proposals by analyzing consumers’ past purchasing or search history. Most consumers use recommendation services to purchase the lowest priced and most optimal flight conditions. However, research on serendipity experiences is minimal. Serendipity experiences is defined as finding valuable things not sought for unexpectedly and can enhance consumers’ positive attitudes toward companies or brands. This study aims to investigate the characteristics of serendipity experiences among users of flight recommendation services and empirically demonstrate the relationship between serendipity experiences and recommendation satisfaction and purchase intention. Furthermore, by exploring the moderating effect of personalization variables, this study confirms the importance of customer data in recommendation systems and provides direction for personalized marketing. To conduct the empirical analysis of the research model, an online survey site was established, and a total of 154 surveys were collected. The reliability and validity of the scales used were verified through factor analysis and reliability analysis, and the hypothesis was tested using PLS analysis. According to the analysis results, decision comport, curiosity, novelty, and evoked interest significantly influenced serendipity experiences, while deal exclusivity did not significantly influence serendipity experiences. In addition, serendipity experiences significantly influenced both recommendation satisfaction and purchase intention. Moreover, it was confirmed that the personalization variable effectively moderated the relationship between serendipity experiences and recommendation satisfaction and purchase intention variables. The results of this study provide new insights for airlines and researchers to understand flight recommendation services and a new customer experience of serendipity and confirm the importance of personalization in this process.

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