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컨조인트 분석을 이용한 온라인 제품 평가점수의 해부: 환대산업의 선택속성을 중심으로
- Alternative Title
- Essays on Deconstructing Online Product Reviews’ Numerical Rating
- Author(s)
- Rhee, Hosung Timothy
- Advisor
- 강주영
- Department
- 일반대학원 경영정보학과
- Publisher
- The Graduate School, Ajou University
- Publication Year
- 2016-08
- Language
- eng
- Keyword
- online product reviews; hotels attributes; restaurant attributes; attribute importance value; part-worth values; conjoint analysis
- Alternative Abstract
- Internet technology has introduced an online business platform where the collaboration among product/service providers, third-party website providers, and consumers leads to a new value creation for society. One of the important aspects of this platform is the relationship between user generated contents (UGSs) in the form of online product reviews (OPRs) and e-WOM (electronic word-of-mouth). This dissertation explores the dynamics of the comparative importance of critical attributes of hospitality industry (specifically, hotels and restaurants) by deconstructing the numerical rating of OPRs. The application of conjoint analysis to the Tripadvisor.com data enables the interpretation of six hotel attributes (i.e., value, service, rooms, sleep quality, location, and cleanliness) and four restaurant attributes (i.e., value, service, food, and atmosphere) in two particular ways: attribute importance value and attribute part-worth value (PWV). This explorative case study consists of three independent essays that investigate a myriad of granular information regarding travelers’ assessment on the attributes. Travelers are divided into domestic and foreign residents, and also into distinctive trip purpose groups (i.e., business, families, couples, solo, and friends). In addition to examining the effects of hotel’s star rating (4-star versus 2-star) and overall rating (high-rated versus low-rated) on travelers' demand, the impact of each attribute’s PWV on the total part-worth value (TPWV) is analyzed. Furthermore, how the type of restaurant information, by itself or combined with the travelers' residency information, influences travelers' behavior is scrutinized. From the pool of numerous meaningful findings from the study, some of the emerged facts are as follows: (1) Whether staying at hotels or dining at restaurants, travelers consider the value and the ‘industry-specific attribute (i.e., rooms for hotels and food for restaurants)’ as the most important attributes. (2) A group of families or friends staying at hotels place a higher degree of importance on value than a group with other purposes (i.e., business, couples, and solo). (3) Whereas domestic travelers indicate a greater degree of importance on rooms than foreign travelers, foreign travelers convey a greater degree of importance on location than domestic travelers. (4) The 2-star hotels amass a greater degree of importance on location from travelers than the 4-star hotels. (5) The management of high-rated hotels should closely monitor the service attribute, but not cleanliness and location attributes. (6) If two kinds of travelers were to eat at restaurants, foreign travelers’ emphasis on food and atmosphere is greater than domestic travelers'. (7) If indoor restaurants keep the price low, foreign travelers’ emphasis on value and service is greater than domestic travelers’ while domestic travelers’ emphasis on food and atmosphere is greater than its counterpart. The management of hospitality industry may unearth ‘hidden’ information that could be transformed into the knowledge of ‘jewels’ by integrating OPR data with conjoint analysis. This novel method can assist the management to strategically prioritize important attributes in the middle of changing circumstances. Moreover, an efficient resource deployment may be achieved by knowing the trade-off implications among different attributes, and their impact on the overall rating. Lastly, the decomposition of data into multi-dimensions of sub-levels may pave a way to developing a new theory that is suitable for big data interpretation.
- Fulltext
- Appears in Collections:
- Graduate School of Ajou University > Department of Management Information Systems > 4. Theses(Ph.D)
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