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A Novel Recommendation System for Dental Services Based on Online Word-of-Mouth

A Novel Recommendation System for Dental Services Based on Online Word-of-Mouth

Wen-Chin Hsu, Li-Chuan Chen
Copyright: © 2017 |Volume: 30 |Issue: 1 |Pages: 18
ISSN: 1040-1628|EISSN: 1533-7979|EISBN13: 9781522510956|DOI: 10.4018/IRMJ.2017010103
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MLA

Hsu, Wen-Chin, and Li-Chuan Chen. "A Novel Recommendation System for Dental Services Based on Online Word-of-Mouth." IRMJ vol.30, no.1 2017: pp.30-47. http://doi.org/10.4018/IRMJ.2017010103

APA

Hsu, W. & Chen, L. (2017). A Novel Recommendation System for Dental Services Based on Online Word-of-Mouth. Information Resources Management Journal (IRMJ), 30(1), 30-47. http://doi.org/10.4018/IRMJ.2017010103

Chicago

Hsu, Wen-Chin, and Li-Chuan Chen. "A Novel Recommendation System for Dental Services Based on Online Word-of-Mouth," Information Resources Management Journal (IRMJ) 30, no.1: 30-47. http://doi.org/10.4018/IRMJ.2017010103

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Abstract

Electronic word of mouth (eWoM) is one of the most valuable resources available to consumers in the search for products and services. This paper presents a novel recommendation system in which eWoM citations compiled using search engines are filtered according to the preferences and requirements of users. The proposed mechanism uses descriptive term creation to formalize the language used in searches, which is then classified according to the Rational Decision Making model to facilitate the analysis of eWoM. The proposed system was evaluated by applying it to the search for dental services in Chungli, Taiwan. Experiment results show that the proposed system reduces the time and effort required to sift through search results. Participants reported that the proposed system excels in quality and effectiveness and had a positive effect on their satisfaction and behavioral intentions. From a managerial perspective, the proposed system provides a valuable tool with which to improve service quality by identifying areas in which previous users have provided negative commentary via eWoM.

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