• 한국콘텐츠학회논문지
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• 제13권10호
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• pp.533-546
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• 2013

본 연구는 온라인상에 남겨진 호텔이용후기에 대해 질적내용분석을 실시하여, 호텔이용자들이 지각한 고객가치의 차원에 대해 살펴보았다. 한국관광공사의 우수 호텔 브랜드인 베니키아 호텔가운데 의도적 표집방법에 의해 행정구역을 기준으로 하여 온라인 후기가 남겨진 10개소를 선정, 연구를 진행했다. 그 결과, 베니키아 호텔이용자들이 지각한 주된 고객가치로는 기능적 가치, 정서적 가치, 가격대비 가치, 인식적 가치, 조건적 가치가 있음을 확인했고 사회적 가치인식은 전혀 발현되지 않았다. 기능적 가치는 호텔이 응당 갖추어야할 기본적인 기능에 대한 평가였고 정서적 가치는 주로 이에 맞물려 생성되었다. 가격대비 가치는 고객이 지불한 비용대비 전체적인 경험의 질에 따른 가치인식이었다. 기존의 호텔고객가치 연구와는 달리, 본 연구는 식당 음식품질의 중요성, 호텔 주변 환경의 매력성도 호텔이용자의 경험에 관여하는 주요 요소임을 확인할 수 있었고, 질적내용분석방법을 통해 실제 고객들의 호텔이용경험에 대한 그 내면을 살필 수 있음을 알 수 있었다.

• 한국정보시스템학회지:정보시스템연구
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• 제25권3호
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• pp.217-245
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• 2016

Purpose With the increasing number of foreign travelers visiting Korea, it is a heavy question to evaluate service quality of typical domestic hotel companies. Our research aims to evaluate service quality of domestic hotels in Korea from the perspective of foreign travelers in order to provide the quality improvements that call attention for the hotel management. Design/Methodology/Approach In this paper, topics of sentiment followed Lodging Quality Index(LQI) dimensions classifying lodging service quality appropriately. Also, we employed word2vec algorithm which calculates similarity and affinity among the vocabularies accurately. To calculate sentiment of each dimension, we adopted scores from SentiWordNet. Findings From the result, we found the number of foreign travelers particularly satisfied with cleanliness, politeness, and problem solving skills. In contrast, it has also been found out that both promptness of services and efficiency of communication do not fulfill the requirements of travelers.

• 디지털산업정보학회논문지
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• 제17권4호
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• pp.209-229
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• 2021

Recently, the tourism industry faced a crisis due to COVID-19. Smart tourism that combines information and communication technology (ICT) is rapidly growing to overcome the crisis in the tourism industry. In order to revitalize the tourism industry after COVID-19, such as non-face-to-face and non-contact, smart tourism incorporating information and communication technology (ICT) is actively encouraged and promoted. The purpose of this study is to empirically verify how perceived pleasure, perceived awakening, and perceived domination, which are three important variables of emotional response theory, affect the intention to continue use through perceived usefulness, expectation, and satisfaction. The survey was conducted for two weeks from November 1 to 15, 2020. A total of 175 surveys were collected during the period and used for analysis. As a result of the study, first, perceived pleasure did not significantly affect perceived usefulness, expectation, satisfaction, and intention to continue use. Second, perceived awakening had a significant effect on expectations, but did not significantly affect perceived usefulness, satisfaction, and continued use intention. Third, perceived domination had a significant effect on perceived usefulness, expectation, and continued use intention. However, it did not significantly affect satisfaction. Fourth, perceived usefulness did not significantly affect satisfaction. Fifth, expectations had a significant effect on perceived usefulness and satisfaction. Sixth, satisfaction had a significant effect on the intention to continue use. Through this, companies and developers that provide online review content for aviation and hotels should know what part of the content is actually focused on and provide it to customers. In addition, content should be provided in consideration of the emotional aspects that aviation and hotel online review users feel while watching videos.

• 한국IT서비스학회지
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• 제16권4호
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• pp.161-176
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• 2017

Recently, most of the users can easily get access to a variety of information sources about companies, products, and services through online channels. Therefore, the online user evaluations are becoming the most powerful tool to generate word of mouth. The user's evaluation is provided in two forms, quantitative rating and review text. The rating is then divided into an overall rating and a detailed rating according to various evaluation criteria. However, since it is a burden for the reviewer to complete all required ratings for each evaluation criteria, so most of the sites requested only mandatory inputs for overall rating and optional inputs for other evaluation criteria. In fact, many users input only the ratings for some of the evaluation criteria and the percentage of missed ratings for each criteria is about 40%. As these missed ratings are the missing values in each criteria, the simple average calculation by ignoring the average 40% of the missed ratings can sufficiently distort the actual phenomenon. Therefore, in this study, we propose a methodology to predict the rating for the missed values of each criteria by analyzing user's evaluation information included the overall rating and text review for each criteria. The experiments were conducted on 207,968 evaluations collected from the actual hotel evaluation site. As a result, it was confirmed that the prediction accuracy of the detailed criteria ratings by the proposed methodology was much higher than the existing average-based method.

• 한국조리학회지
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• 제22권6호
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• pp.61-70
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• 2016

The purpose of this study is to identify the effects of a company's response strategies (response type, communication style, and response sincerity) on customer's brand attitude and purchase intentions. A fictional Facebook fan page containing 6 separate scenarios was developed based on actual customer reviews and company responses observed on Facebook restaurant fan pages. Participants were recruited from Amazon's Mechanical Turk (MTurk). A total of 202 responses were obtained; 185 responses were analyzed after deleting insufficient responses. The results of MANOVA found that an accommodative response leads customers to have a more favorable attitude towards a brand and have stronger purchasing intentions. In addition, customers who perceive the company's response to a negative review as sincere are more likely to have a positive brand attitude and purchasing intentions, as compared to those who perceive it as either insincere or neutral.

• 통합자연과학논문집
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• 제14권2호
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• pp.35-40
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• 2021

In this paper, we proposed a multi-subject-level sentiment analysis model for user reviews using the Latent Dirichlet Allocation (LDA) method targeting user-generated content (UGC). Data were collected from users' online reviews of hotels in major tourist cities in the world, and 30 hotel-related topics were extracted using the entire user reviews through the LDA technique. Six major hotel-related themes (Cleanliness, Location, Rooms, Service, Sleep Quality, and Value) were selected from the extracted themes, and emotions were evaluated for sentences corresponding to six themes in each user review in the proposed sentiment analysis model. Sentiment was analyzed using a dictionary. In addition, the performance of the proposed sentiment analysis model was evaluated by comparing the emotional values for each subject in the user reviews and the detailed scores evaluated by the user directly for each hotel attribute. As a result of analyzing the values of accuracy and recall of the proposed sentiment analysis model, it was analyzed that the efficiency was high.

• 지능정보연구
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• 제28권2호
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• pp.171-189
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• 2022

온라인 리뷰는 소비자의 구매 의사결정 과정에서 중요한 역할을 담당하고 있으므로 소비자에게 유용하고 신뢰성이 있는 리뷰를 제공하는 것이 중요하다. 기존의 온라인 리뷰 유용성 예측 관련 연구는 주로 온라인 리뷰의 텍스트와 평점 정보 간의 일관성을 바탕으로 리뷰 유용성을 예측하였다. 그러나 기존 연구는 평점 정보를 스칼라로 표현했기 때문에 표현 수용력이 제한적이거나 평점 정보와 리뷰 텍스트 정보와의 상호작용을 제한적으로 학습하는 한계가 존재한다. 본 연구에서는 기존 연구의 한계점을 보완하기 위해 리뷰 텍스트와 평점 정보 간의 상호작용을 효과적으로 학습할 수 있는 CNN-RHP(CNN based Review Helpfulness Prediction) 모델을 제안하였다. 먼저, 리뷰 텍스트의 의미론적 특성을 추출하기 위해 multi-channel CNN을 적용하였다. 다음으로, 평점 정보는 텍스트 특성과 동일한 차원을 나타내는 독립된 고차원 임베딩 특성 벡터로 변환하였다. 최종적으로 요소별(Element-wise) 연산을 통해 리뷰 텍스트와 평점 정보 간의 일관성을 학습하였다. 본 연구에서는 제안된 CNN-RHP 모델의 성능을 평가하기 위해 Amazom.com에서 수집된 온라인 소비자 리뷰를 사용하였다. 실험 결과, 본 연구에서 제안한 CNN-RHP 모델이 기존 연구에서 제안된 여러 모델과 비교했을 때 우수한 예측 성능을 나타내는 것을 확인하였다. 본 연구의 결과는 온라인 전자상거래 플랫폼에서 소비자들에게 리뷰 유용성 예측 서비스를 제공할 때 유의미한 시사점을 제공할 수 있다.

• 산경연구논집
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• 제10권7호
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• pp.83-89
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• 2019

Purpose - It is a very important issue for the Korean tourism industry to increase tourism revenue by attracting foreign tourists. Although Japanese tourists have been an important part of the Korean tourism industry for a long time, the level of tourist satisfaction including accommodation has been at the worst compared to other foreign visitors, which strongly requires concrete solutions. Therefore, this study focuses on improving the satisfaction level of Japanese visitors in the use of accommodation, and find out the influence of the managerial response. Research design, data, and methodology - In this study, customer review and managerial response of hotels in Seoul were collected from "Rakuten Travel" which is the most representative online travel agency in Japan. As a result of collecting data from 2016 to 2018, 6,190 customer reviews and 1,241 managerial responses from 120 hotels were used for analysis. In addition, information on the properties of 120 hotels, such as the number of rooms, classification, types of hotel facilities, types of room facilities, accessibility and prices, were collected. To test the hypotheses, moderated multiple regression analysis was conducted with SPSS 22.0. Results - It was found that only 25 sites, 20.8% of the total 120 sites, were implementing managerial response and average response rate was 66.42% among them. As a result of examining the main effects of the hotel attributes on the ratings, accessibility and price are confirmed as effective variables. We also found that the response rate has a significant moderate effect in both the accessibility and price. In other words, there was a significant difference in the influence of accessibility and price on the ratings depending on the response rate. Also, it was confirmed that the response rate is not a pure moderator variable but a quasi moderator variable. Overall, the evidences partially supported the hypothesis. Conclusion - It was possible to provide important suggestions to the hotel managers who were concerned about managing tourist satisfaction with accessibility problems. It was found that the accessibility problem could be overcome by increasing the response rate. It was also confirmed that high ratings can be more effectively achieved for high priced hotels by increasing the response rate.

• 한국IT서비스학회지
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• 제20권5호
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• pp.159-176
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• 2021

In this study, we performed a comparative analysis of the sentiment value for the tourists in USA, China, and Korea on the COVID19 pandemic era to explore and find out the features of the tourists by using online reviews. We collected a total of 243,826 online hotel reviews for metropolitan city and vacation spot in the three countries to compare the features between the business and the vacation trips. We collected the online reviews into the tow groups from Jan. 1, 2019 to Nov. 31, 2019 for before COVID19 pandemic and from Apr. 1, 2020 to Deb 28, 2021 for during COVID19. Online reviews were categorized into 6 dimensions using LDA model. Sentiment analysis were presented for 6 dimensions by utilizing a lexicon base. We proposed an approach to analyzing the importance of each attribute by applying 6-dimensional sentiment values to conjoint analysis. Our empirical analysis showed that the proposed approach could explore and find out the changed features of travelers during the COVID19 pandemic.

• 한국정보시스템학회지:정보시스템연구
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• 제27권1호
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• pp.89-110
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• 2018

Purpose There is much information in customer reviews, but finding key information in many texts is not easy. Business decision makers need a model to solve this problem. In this study we propose a multi-topic sentiment analysis approach using Latent Dirichlet Allocation (LDA) for user-generated contents (UGC). Design/methodology/approach In this paper, we collected a total of 104,039 hotel reviews in seven of the world's top tourist destinations from TripAdvisor (www.tripadvisor.com) and extracted 30 topics related to the hotel from all customer reviews using the LDA model. Six major dimensions (value, cleanliness, rooms, service, location, and sleep quality) were selected from the 30 extracted topics. To analyze data, we employed R language. Findings This study contributes to propose a lexicon-based sentiment analysis approach for the keywords-embedded sentences related to the six dimensions within a review. The performance of the proposed model was evaluated by comparing the sentiment analysis results of each topic with the real attribute ratings provided by the platform. The results show its outperformance, with a high ratio of accuracy and recall. Through our proposed model, it is expected to analyze the customers' sentiments over different topics for those reviews with an absence of the detailed attribute ratings.