요즘은 과거와 달리 인터넷에 기반을 둔 온라인이 발달하여 정보를 얻는 방법도 획기적으로 변하게 됨에 따라 소비자들은 이미 경험해 본 고객들이 게재한 온라인 리뷰에 의지하여 의사 결정하는 경향이 커졌다. 온라인 구전은 점점 활발해지고 관련 연구도 많아졌으나, 온라인 리뷰의 평점과 리뷰의 수에 대한 정확한 연구 결과는 부족한 실정이다. 우리는 흔히 관련 정보가 없는 레스토랑에 대해서는 블로그 등 온라인 리뷰를 많이 참고하곤 한다. 그런데, 고가 레스토랑과 저가 레스토랑을 선택하기 위한 의사결정 과정은 다를지도 모른다. 다시 말해 이용하고자 하는 레스토랑의 가격수준에 따라 온라인 리뷰 정보가 레스토랑의 방문의도에 미치는 영향이 다르게 나타날 수도 있을 것이다. 따라서 본 연구는 소비자가 레스토랑을 방문하고자 할 때 방문하고자 하는 레스토랑이 고가인지 저가인지에 따라서 리뷰의 정보인 평점, 리뷰의 양이 미치는 영향이 다르다는 것을 입증하고자 한다. 본 연구 결과를 요약하면 첫째, 리뷰평점과 방문의도 간의 영향 관계를 살펴본 결과, 리뷰평점이 높아질수록 방문의도도 높아진다고 본 연구 결과 나타났다. 이는 대부분의 레스토랑 방문자들이 방문하기 전에 리뷰평점에 대해서 확인 후 방문한다는 것을 나타내는 것으로써 리뷰평점의 중요성이 강조된다. 둘째, 리뷰수와 방문의도 간의 영향 관계를 살펴본 결과, 저가 레스토랑의 경우에만 리뷰수가 높아질수록 방문의도도 높아진다는 연구 결과가 나타났다. 저가 레스토랑의 경우에는 대중성 요인이 크게 작용하는 것으로 볼 수 있고 리뷰 평점과 더불어 리뷰수의 역시 중요하다는 점을 나타내는 결과이다. 셋째, 레스토랑의 가격 수준에 따라 리뷰 평점과 리뷰의 양이 방문의도에 미치는 영향에 차이가 있는 것으로 나타났다. 저가의 레스토랑에서는 리뷰의 양이 높고 평점이 높은 경우 방문의도가 특히 높게 나타났다. 이러한 결과를 보면 저가 레스토랑의 경우는 리뷰의 평점관리뿐만 아니라 리뷰의 양을 높이는 것이 매우 중요하다는 것을 보여준다.

Consumers who want to buy products or services tend to rely on online reviews during the decision-making process, such as convincing purchases based on online reviews posted by customers who have already experienced them. It also plays a role in reducing risk. Prior to the development of the Internet, it was common to hear about the experiences or feelings of users who first used products and services by face-to-face WOM. Recently, 92% of online consumers accept the content of a review and make purchase decisions based on it. In terms of purchasing behavior of restaurant consumers, more than 60% of restaurant consumers decide to eat their own meals by recommending and recommending others. In recent years, with the increasing popularity of the Internet and the rapid development of mobile, online consumers have been using online reviews before purchasing. Online reviews have the advantage of being able to obtain a wide variety of new information easily, quickly and almost free of charge from the consumer's point of view, and from an enterprise's point of view, they can take advantage of new online marketing tools. In response to this social trend, this study attempted to analyze the effect of review rating and review number as a factor influencing review users' intention to visit restaurants. ANCOVA analysis was conducted to test the hypotheses. Covariates were controlled because age, income, and education were demographic variables that could affect high and low cost restaurant visits. First, the hypothesis 1 was found to be statistically significant both in the high-priced restaurant (F value = 8.448, p = .004) and low cost restaurant (F value = 6.100, p = .015) where “review rate affects the intention to visit”. Hypothesis 1 was therefore adopted (see Table 3). On the other hand, the positive relationship between the volume of reviews and the intention to visit in hypothesis 2 was not statistically significant in the expensive restaurant (F value =.253, p = .616). On the other hand, in the low-cost restaurant, the volume of reviews influenced the visit intention (F value = 8.01, p = .005). In other words, in the high-priced restaurant, only the review rate had an effect on the visit intention, while in the low-cost restaurant, both the rate and the volume of the review had the main effect. As a result of the interaction term effect of hypothesis 3, in the case of the high-priced restaurant, the interaction term of the rating of the review and the volume of the review was not statistically significant (F value = .465, p <.05). On the other hand, in the low-cost restaurant, the interaction term between the rating and the volume of reviews was statistically significant (F value = 5.88, p <.05) (see <Figure 1>). Therefore, hypothesis 3 was adopted. The results of this study are summarized as follows. First, as a result of examining the relationship between review score and visit intention, the result of this study showed that the higher the review score, the higher the visit intention. This indicates that most restaurant visitors check and review the review score before visiting, thereby emphasizing the importance of the review score. Second, as a result of examining the relationship between the number of reviews and the intention to visit, the research results showed that the higher the number of reviews, the higher the intention of visits in low-cost restaurants. In the case of low-cost restaurants, the popularity factor can be considered to be a big factor, and the result shows that the number of reviews is important as well as the review rating. Third, according to the price level of the restaurant, there was a difference in the effect of the review rating and the amount of reviews on the visit intention. In low-cost restaurants, visit intentions were particularly high when the volume of reviews and high ratings were high. These results show that in the case of low-cost restaurants, it is very important not only to manage the rating of the reviews but also to increase the volume of the reviews. Regarding the academic implications, the empirical analysis confirms that ratings and reviews of online reviews have a direct impact on consumers' intention to visit restaurants. In particular, until now, online review-related studies have been conducted separately by ratings and number of reviews, and have never been measured by simultaneously reviewing ratings and reviews. Second, the effect of the interaction between review score and review number according to the level of restaurant was verified. If the price level of a restaurant is high, it can be significant that the review rating plays a more important role than the number of reviews. Practical implications are as follows: First, companies need continuous monitoring based on the results of the ratings and volume of online reviews. In other words, companies need to conduct strategic marketing activities to keep potential ratings and the number of reviews appropriate for potential consumers. Regardless of the restaurant's price level, the rating of the review is very important, and the activity to increase the rating should be continued. For example, whether a negative review has increased due to a problem with the service or food, or whether the quality of the product is not a problem. Second, based on the fact that the response of consumers to online reviews varies depending on the level of the restaurant, it is necessary to clearly identify the consumer's perception of whether the restaurant has a high price level or a low price level and establish a strategy accordingly. For example, if you are an expensive restaurant, you will need to pay more attention to the rating of the review, and you will need to pay particular attention to the quality of the review and the management of the rating rather than the volume of the review. If you are a low-cost restaurant, you should pay more attention to the volume of reviews. Consumers looking for a low-cost restaurant usually make the decision with more emphasis on the large and small number of reviews. Therefore, inexpensive restaurants should continue to be incentives or promotions for many users to leave reviews.

Online Review, Review rate, Review volume, Visit Intention, Low Cost Restaurant