• Information Systems Review
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• v.23 no.3
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• pp.127-158
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• 2021

Many online travel agencies (OTAs) provide average ratings and time-relevant information or the most recently posted reviews regarding hotels to satisfy customers. To identify these two factors' relative influence on behavioral decision-making processes, we conducted two studies: (1) an experimental research design to explore the relative influence of the two on online review consumption and (2) an empirical approach to examine their relative impact on online review generation. The results show that when review posters observe an inconsistency between average ratings and recent reviews, they tend to deviate from the recent reviews regardless of the overall direction (reactance behavior). Meanwhile, review consumers tend to conform to the opinions presented in recent reviews (herding behavior). Additionally, in both cases, the effects are amplified in case of a negative aberration. Based on the findings, this study provides theoretical and practical implications regarding the relative influences of average rating and recently posted reviews and their different impacts on online review consumption and generation.

• Proceedings of the Korea Database Society Conference
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• 2008.05a
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• pp.235-252
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• 2008

전통적인 상거래 영역에 정보기술을 접목한 전자상거래는 그 규모와 성장면에서 계속적으로 증가하고 있다. 특히 기업과 소비자간 전자상거래를 의미하는 B2C는 그 종류와 규모면에서 계속 성장하고 있다. 본 연구에서는 기업과 소비간의 거래에 있어서 제품 구매에 중요한 영향을 미치는 온라인 리뷰의 정보제공능력에 대해 연구하고자 한다. 온라인리뷰가 제공하는 정보의 양이 증가할수록 이는 처리해야 하는 판매자와 구매자에게는 부담이 된다. 기존의 온라인 리뷰에 대한 연구는 사용자의 구매 경험을 전달하는 방법에 주력하여 온라인 리뷰의 형태와 전달효과 등에 대한 연구가 부족하였다. 따라서 본 연구에서는 효과적으로 정보를 전달하기 위해 필요한 온라인 리뷰의 형태와 정보 전달 등에 대해 연구하고자 한다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.181-188
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• 2018

In this paper, we propose an analysis scheme of customer spending pattern using text mining. In proposed consumption pattern analysis scheme, first we analyze user's rating similarity using Pearson correlation, second we analyze user's review similarity using TF-IDF cosine similarity, third we analyze the consistency of the rating and review using Sendiwordnet. And we select the nearest neighbors using rating similarity and review similarity, and provide the recommended list that is proper with consumption pattern. The precision of recommended list are 0.79 for the Pearson correlation, 0.73 for the TF-IDF, and 0.82 for the proposed consumption pattern. That is, the proposed consumption pattern analysis scheme can more accurately analyze consumption pattern because it uses both quantitative rating and qualitative reviews of consumers.

• Distribution Business Review
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• v.1
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• pp.77-85
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• 2001

• Information Systems Review
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• v.16 no.3
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• pp.113-134
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• 2014

Since a movie is an experience goods, purchase can be decided upon preliminary information and evaluation. There are ongoing researches on what impact online reviews might have on movie revenues. Whereas research in the past was focused on the effect of online reviews. The influence of online reviews appears to be significant in products like a movie because it is difficult to evaluate the feature prior to "consuming" the product. Since an online review is regarded to be objective, consumers find it more trustworthy. Contrary to prior research focused on movie review ratings and volume, we focus moves on movie features related specific reviews. This research proposes a predictive model for movie revenue generation. We decided 15 criteria to classify movie features collected from online reviews through the online review mining and made up feature keyword list each criterion. In addition, we performed data preprocessing and dimensional reduction for data mining through factor analysis. We suggest the movie revenue predictive model is tested using discriminant analysis. Following the discriminant analysis, we found that online review factors can be used to predict movie popularity and revenue stream. We also expect using this predictive model, marketers and strategic decision makers can allocate their resources in more parsimonious fashion.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.153-173
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• 2022

This study analyzes yelp's online restaurant reviews written in 2019 and explores the factors influencing the decision of the usefulness for online reviews in the restaurant consumption decision process. Specifically, factors expected to affect review usefulness are classified according to the Elaboration Likelihood model. Also, it is assumed that the price range of the restaurant would have a moderating role. For the analysis, datasets provided by yelp.com in February 2020 are used. Among the datasets, online reviews of businesses located in Nevada in the US and belonging to the Food and Restaurant categories are targeted. As a result of the negative binomial regression analysis, it is confirmed that the central cues including review depth and readability and the peripheral cues including review consistency, reviewer popularity, and reviewer exposure positively affect the review usefulness. It is also confirmed that the influences of antecedents that affect the review restaurant prices moderate the effect of the central and peripheral cues on the review usefulness. It also provides implications for the need for price-differentiated review management strategies by review platforms and restaurant businesses.

• KDI북한경제리뷰
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• v.23 no.9
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• pp.67-80
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• 2021

북한은 최근 당중앙위원회 제8기 제3차 정치국 확대 회의에서 주민들에게 필요한 소비품의 생산을 늘리기 위해 경공업 공장들에 원자재들을 우선 보장하는 규율을 확립하고, 소비품 생산과 공급을 계획적으로 실속 있게 조직하여야 한다는 것에 대하여 언급하였다. 이것은 코로나19로 모든 무역활동이 중지된 상황에서 필수품의 생산을 늘려 이에 대한 내수시장을 일정 정도 확보하려는 의도로 해석된다. 본고에서는 원자재 구매, 생산과 판매 등 은행을 통한 북한의 기업관리에서 수요자와 공급자 간에 실질적으로 적용되는 다양한 결제방법을 계좌(돈자리) 개설, 제출 단위와 적용 근거, 해당 서류들을 따라가며 고찰함으로써 북한기업의 실질적 운영에 대한 구체적인 이해를 돕고자 한다. 자료로는 관련 도서와 문헌, 북한 관련법, 간행물 등을 참고하였다.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.75-86
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• 2020

Hotel review data can extract various information that includes purchasing factors that lead to consumption, advantages, and disadvantages for hotels. In particular, the sentiment keyword of the review data helps consumers understand the pros and cons of hotels. However, it is not efficient for consumers to read a large number of reviews. Therefore, it is necessary to offer a summary review to customers. In this study, we suggest providing summary information on sentiment keywords association as well as a network of hotels based on sentiment keywords. Based on a sentiment keyword dictionary, the extracted sentiment keywords associations construct the hotel network through topological data analysis based mapper. This hotel network allows a consumer to find some hotels associated with specific sentiment keywords as well as recommends the same related hotels. This summary information provides users with a summarized emotional assessment of hotels and helps hotel marketing teams understand consumers' perceptions of their hotel.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.4
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• pp.153-160
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• 2021

With the advent of the "age of video" due to the simplification of video content production and the convenience of broadcasting channel operation, review videos on various products are drawing attention. We proposes RASIA, an integrated reliability analysis system based on verbal and nonverbal sentiment analysis of review videos. RASIA extracts and quantifies each emotional value obtained through language sentiment analysis and facial analysis of the reviewer in the video. Subsequently, we conduct an integrated reliability analysis of standardized verbal and nonverbal sentimental values. RASIA provide an new objective indicator to evaluate the reliability of the review video.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.111-122
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• 2021

This study analyzed user reviews of Dongbaekjeon and Incheoneum app, which are representative local currencies in Korea, to identify the positive/negative factors of local currency users, and established a marketing strategy based on this. App user reviews were classified into positive and negative based on the star rating, and word cloud, topic modeling, and social network analysis were performed, respectively. As a result, in the negative reviews of Dongbaekjeon and Incheoneum, dissatisfaction with app use and card issuance appeared in common. In positive reviews, keywords such as 'local economy' and 'small business owners' along with satisfaction with 'cashback' appeared. It means that local currency users perceived that their consumption support local economy, and they felt satisfaction in using local currency. Based on the satisfaction/dissatisfaction factors identified as a result of the analysis of this study, we identified what needs to be improved and to be strengthened, and appropriate marketing strategies were established. The text mining method used in this study and research results can provide meaningful information about local currencies to public officials and marketers in charge of local currencies.