본 연구는 개인화 광고의 개인 정보 활용 정도에 따라 이용자의 혜택 및 위험 요인 인식이 광고의 수용의도에 미치는 영향을 검증하였다. 이를 위해 개인 정보 활용 정도에 따라 개인화 광고의 수준을 고 · 중 · 저 세 가지 수준으로 조작한 후, 20-30대를 대상으로 집단 간 실험을 진행하였다. 개인화 광고에 대한 이용자 인식은 프라이버시 계산 모형을 토대로, 혜택(정보성, 신뢰성, 오락성)과 위험 요인(프라이버시 우려, 침입성)으로 구분하였다. 연구 결과, 개인화 광고의 수준이 높아질수록 실험 참가자들은 광고의 혜택 요인인 정보성과 신뢰성, 오락성을 높게 인식하였다. 개인화 광고의 위험 요인 중 프라이버시 우려는 흥미롭게도 개인화가 가장 적게 된 광고를 접한 집단(저 집단)에서 가장 높게, 중간 집단(중 집단)에서 가장 낮게 인식하는 것으로 나타났다. 개인화 광고의 혜택 및 위험 요인이 수용의도에 미치는 영향을 알아본 결과, 개인화 광고가 적절한 제품 정보를 제공하고, 신뢰할 수 있고, 오락적이라고 느낄수록 광고에 대한 수용의도가 높게 나타났다. 프라이버시 우려는 수용의도에 유의미한 영향을 미치지 않은 반면, 침입성은 수용의도에 부정적인 영향을 미쳤다. 이는 프라이버시에 대한 우려보다 개인화 광고로 인해 자신의 온라인 활동을 방해 받았다고 느끼는 것이 수용의도에 더 큰 영향을 미친다는 것을 의미한다. 본 연구는 개인화 광고의 개인 정보 활용 정도에 따라 광고에 대한 이용자의 인식과 수용의도가 달라짐을 프라이버시 계산 모형을 바탕으로 분석하였다는 점에서 학술적 의의가 있다. 나아가 프라이버시 계산 모형에서 자주 다뤄지지 않았던 변인들의 관계를 규명하였다는 점에서, 실무적 시사점을 제공할 수 있을 것으로 기대된다.
This study examined the impact of the personalization level of personalized advertising on users’ perceived benefits, risk factors and acceptance intentions. Online experiments were conducted on people in their 20s and 30s. Specifically, personalized advertisements were manipulated at three levels based on the degrees of personal information, and between-subjects designed experiment was conducted accordingly. User’s awareness of personalized advertising was divided into benefits (informativeness, trust, entertainment) and risk factors (privacy concerns, intrusion) by applying the privacy calculus model. Users who encountered personalized advertisements were divided into three groups according to the level of personalization, and then analyzed the users’ perceptions in each group of how they felt about the advertisements. The result of the analysis revealed that among the benefit factors of personalized advertising, informativeness, trust, and entertainment were higher as the level of personalization increased. Interestingly, privacy concern, one of the risk factors for personalized advertising, turned out to be higher in the following sequence of personalization-levels : mid-level group, high-level group, and low-level group. This means that privacy concern is the highest in the group with a low level of personalization, and the lowest in the group with an intermediate level of personalization. These results give us some implications. First of all, the usage of Instagram search history leads to targeted advertisements for me. In the end, the more my search records accumulate, the more likely I will be exposed to personalized advertisements aimed at me, which means that it can lead to invasion of my privacy. In addition, users who have encountered medium-level personalized advertisements using search, gender, and age data can positively recognize this advertisement. In other words, it means that people exposed to mid-level personalized advertisements may have a positive perception that personalized advertisements have obtained the new information they need, rather than feeling that they violate my personal information. As a result of examining the effect of the benefits and risk factors of personalized advertisements on the advertisement acceptance intention, the higher the acceptance intention for advertisements as personalized advertisements provide appropriate product information, and feel reliable and entertaining. On the other hand, privacy concerns did not significantly affect advertising acceptance intention, while intrusion negatively affected acceptance intention. This means that feeling that one’s online activities have been hindered by personalized advertising has a greater impact on acceptance intention than concerns about privacy. Based on the privacy calculation model, this study academically proved that the user’s perception and acceptance intention of personalized advertisements varies depending on the degree of personal information use. The practical implication of this study is that the relationship between variables that have rarely been dealt with in the privacy calculation model was investigated.