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Sanchez-Montanes, ManuelAuthor

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March 20, 2025
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A Multi-Criteria Decision Support Model for Restaurant Selection Based on Users' Demand Level: The Case of Dianping.com

Publicated to: Information Processing & Management. 61 (3): 103650- - 2024-05-01 61(3), DOI: 10.1016/j.ipm.2024.103650

Authors:

Shu, Ziwei; Carrasco, Ramon Alberto; Sanchez-Montanes, Manuel; Garcia-Miguel, Javier Portela
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Affiliations

Univ Autonoma Madrid, Escuela Politecn Super, Dept Comp Sci, Madrid 28049, Spain - Author
Univ Complutense Madrid, Fac Stat, Dept Mkt, Madrid 28040, Spain - Author
Univ Complutense Madrid, Fac Stat, Dept Stat & Data Sci, Madrid 28040, Spain - Author
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Abstract

The Internet, by offering a variety of information sources such as online reviews, aids people in selecting restaurants. However, it also prolongs their decision-making process due to the need to integrate information across multiple criteria. Existing decision support models for choosing satisfactory restaurants overlook users' varying demand levels for each aspect of the restaurant, making the process less efficient. This paper aims to develop a multi-criteria decision support model for users to efficiently and accurately rank and select restaurants based on their demand level for various restaurant aspects. The 2-tuple linguistic ordered weighted averaging (2LOWA) aggregation operator is applied for the first time to aggregate user ratings, generating linguistic ratings that mirror the diverse levels of user demand for restaurant service, food, and environment. The importance weights (IW) method is introduced to calculate linguistic weights, thereby obtaining customized 2T-SFE composite scores under various user demand scenarios. The proposed model's applicability is demonstrated using a dataset comprising over 3.7 million reviews sourced from Dianping.com. The results show multiple personalized restaurant rankings with more linguistically understandable composite scores, enabling users to efficiently choose a suitable restaurant based on their preferences and requirements. Moreover, a list of restaurants satisfying most users with different demand levels can be generated by assessing their frequency of appearance in the top 10 restaurants across over 340 scenarios established by the proposed model. This contributes to offering more reliable and comprehensive restaurant recommendations and rankings, ultimately increasing customer satisfaction in the selection process.
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Keywords

2-tuple linguistic modelAggregationInformationMulti-criteria decision-makinMulti-criteria decision-makingOnline reviewsOperatorOrdered weighted averaging aggregationOrdered weighted averaging aggregation operatorOwa operatorsPerformancePersonalized restaurant rankingQualityRecommendationServicWord-of-mouth

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal INFORMATION PROCESSING & MANAGEMENT due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2024 there are still no calculated indicators, but in 2023, it was in position 9/166, thus managing to position itself as a Q1 (Primer Cuartil), in the category Information Science & Library Science. Notably, the journal is positioned above the 90th percentile.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-05:

  • WoS: 16
  • Scopus: 6
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-05:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 33 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

    It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

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    Awards linked to the item

    The authors would like to acknowledge the financial support received from the Universidad Complutense de Madrid and Banco Santander (Project CT58/21-CT59/21) , the FEDER funds provided in the National Spanish project (PID2019-103880RB-I00) , and grants PID2021-127946OB-I00, PID2021-122347NB-I00, and PID2022-139297OB-I00 (funded by MCIN/AEI/10.13039/501100011033 and by "ERDF A way of making Europe") . Furthermore, co-author Ramon Alberto Carrasco wishes to express gratitude for the financial support received from The Japan Society for the Promotion of Science (JSPS) Grant-in-Aid for Scientific Research (C) "Cross-cultural study on AI ethics from a perspective of business" (23K01545) .
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