2021
DOI: 10.1016/j.inffus.2020.11.010
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Online-review analysis based large-scale group decision-making for determining passenger demands and evaluating passenger satisfaction: Case study of high-speed rail system in China

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Cited by 171 publications
(71 citation statements)
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“…In the future, the proposed concepts may be extended using other fuzzy variants to solve MCGDM problems with unknown weight information. It may also be motivated to use the proposed TOPSIS‐based method in other fields for solving real‐life decision‐making problems, such as the high‐speed rail system, 14,57 construction method selection, 45 strategic management, 34 supplier selection, 36 and so forth.…”
Section: Discussionmentioning
confidence: 99%
“…In the future, the proposed concepts may be extended using other fuzzy variants to solve MCGDM problems with unknown weight information. It may also be motivated to use the proposed TOPSIS‐based method in other fields for solving real‐life decision‐making problems, such as the high‐speed rail system, 14,57 construction method selection, 45 strategic management, 34 supplier selection, 36 and so forth.…”
Section: Discussionmentioning
confidence: 99%
“…(5-7) overcomes the shortcomings of the above-mentioned distance Eqs. (1)(2)(3)(4), satisfies the definition of distance, and fully considers the differences in their membership degrees, as well as the differences in length and probability. For Example 2, using the new Hamming distance to calculate, we can get: d nh (h(p), h 1 (p)) = 0.05, d nh (h(p), h 2 (p)) = 0.06.…”
Section: Proof (1)nonnegativementioning
confidence: 99%
“…Multi-attribute decision-making (MADM) problems are becoming more and more common in human social activities. For example, it could be applied to site selection assessment [1], hotel selection [2], passenger demand and service quality of High-speed rail [3,4], sustainable supplier selection [5], and so on. Decision makers (DMs) solve MADM problems based on their own values, preferences and knowledge system.…”
Section: Introductionmentioning
confidence: 99%
“…In practice, consumers often make their purchasing decisions on the basis of online product information, such as reviews, ratings and comments 77 . This is often exploited by online retailers that design product recommendation systems with the purpose of helping customers easily identify products that meet their tastes and needs.…”
Section: Hybrid Multiattribute Online Product Recommendation For Consumer Decision Makingmentioning
confidence: 99%