A novel online reviews-based decision-making framework to manage rating and textual reviews

Rating and textual reviews are two of the most commonly used online reviews. However, most of existing studies utilize them separately to conduct decision analysis. Therefore, this paper proposes a novel Online Reviews-based Decision-Making (ORDM) framework that incorporates both kinds of reviews, w...

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Published inExpert systems with applications Vol. 259; p. 125367
Main Authors Pan, Xiao-Hong, He, Shi-Fan, García-Zamora, Diego, Wang, Ying-Ming, Martínez, Luis
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.01.2025
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Abstract Rating and textual reviews are two of the most commonly used online reviews. However, most of existing studies utilize them separately to conduct decision analysis. Therefore, this paper proposes a novel Online Reviews-based Decision-Making (ORDM) framework that incorporates both kinds of reviews, which can effectively model and manage the inherent uncertainty and fuzziness in hybrid reviews. To do so, we first define a method to model hybrid online reviews as interval values. Then, an automatic Consensus-Reaching Process (CRP) developed from a novel Minimum Cost Consensus (MCC) model for interval values, is applied to obtain an agreed collective opinion. Finally, a new interval Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is defined to compare and rank alternatives. A case study is then presented to illustrate the feasibility of this approach. Additionally, sensitivity analysis and discussions are further conducted to discuss the influence of parameters and the superiority of the proposed method. •Incorporate hybrid online reviews to assist in decision-making.•Define an information transformation method to handle hybrid online reviews.•Develop a minimum consensus cost model for handling interval information.•Propose an interval TOPSIS method based on total orders.
AbstractList Rating and textual reviews are two of the most commonly used online reviews. However, most of existing studies utilize them separately to conduct decision analysis. Therefore, this paper proposes a novel Online Reviews-based Decision-Making (ORDM) framework that incorporates both kinds of reviews, which can effectively model and manage the inherent uncertainty and fuzziness in hybrid reviews. To do so, we first define a method to model hybrid online reviews as interval values. Then, an automatic Consensus-Reaching Process (CRP) developed from a novel Minimum Cost Consensus (MCC) model for interval values, is applied to obtain an agreed collective opinion. Finally, a new interval Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is defined to compare and rank alternatives. A case study is then presented to illustrate the feasibility of this approach. Additionally, sensitivity analysis and discussions are further conducted to discuss the influence of parameters and the superiority of the proposed method. •Incorporate hybrid online reviews to assist in decision-making.•Define an information transformation method to handle hybrid online reviews.•Develop a minimum consensus cost model for handling interval information.•Propose an interval TOPSIS method based on total orders.
ArticleNumber 125367
Author Wang, Ying-Ming
Martínez, Luis
García-Zamora, Diego
Pan, Xiao-Hong
He, Shi-Fan
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Interval TOPSIS
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Interval minimum cost consensus
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Snippet Rating and textual reviews are two of the most commonly used online reviews. However, most of existing studies utilize them separately to conduct decision...
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SubjectTerms Hybrid online reviews
Interval minimum cost consensus
Interval TOPSIS
Online reviews-based decision-making
Title A novel online reviews-based decision-making framework to manage rating and textual reviews
URI https://dx.doi.org/10.1016/j.eswa.2024.125367
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