Product Selection Considering Multiple Consumers’ Expectations and Online Reviews: A Method Based on Intuitionistic Fuzzy Soft Sets and TODIM

Cao, Pingping; Zheng, Jin; Li, Mingyang

doi:10.3390/math11173767

Cited by 5 publications

(1 citation statement)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The literature introduces some of the most renowned MADM methods, including PROMETHEE, TODIM, VIKOR, and TOPSIS, which are designed to tackle ranking problems effectively [52][53][54][55]. Qin et al [56] initially extracted product attributes, weight values, and emotional tendencies from online reviews.…”

Section: Review the Ranking Methods Of Multi-attribute Decision-makingmentioning

confidence: 99%

Text Mining and Multi-Attribute Decision-Making-Based Course Improvement in Massive Open Online Courses

Yang,

Liu,

Luo

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

As the leading platform of online education, MOOCs provide learners with rich course resources, but course designers are still faced with the challenge of how to accurately improve the quality of courses. Current research mainly focuses on learners’ emotional feedback on different course attributes, neglecting non-emotional content as well as the costs required to improve these attributes. This limitation makes it difficult for course designers to fully grasp the real needs of learners and to accurately locate the key issues in the course. To overcome the above challenges, this study proposes an MOOC improvement method based on text mining and multi-attribute decision-making. Firstly, we utilize word vectors and clustering techniques to extract course attributes that learners focus on from their comments. Secondly, with the help of some deep learning methods based on BERT, we conduct a sentiment analysis on these comments to reveal learners’ emotional tendencies and non-emotional content towards course attributes. Finally, we adopt the multi-attribute decision-making method TOPSIS to comprehensively consider the emotional score, attention, non-emotional content, and improvement costs of the attributes, providing course designers with a priority ranking for attribute improvement. We applied this method to two typical MOOC programming courses—C language and Java language. The experimental findings demonstrate that our approach effectively identifies course attributes from reviews, assesses learners’ satisfaction, attention, and cost of improvement, and ultimately generates a prioritized list of course attributes for improvement. This study provides a new approach for improving the quality of online courses and contributes to the sustainable development of online course quality.

show abstract

Section: Review the Ranking Methods Of Multi-attribute Decision-makingmentioning

confidence: 99%

Text Mining and Multi-Attribute Decision-Making-Based Course Improvement in Massive Open Online Courses

Yang,

Liu,

Luo

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

show abstract

An integrated complex T-spherical fuzzy set and soft set model for quantum computing and energy resource planning

Jan,

Gwak,

Pamucar

et al. 2024

Information Sciences

View full text Add to dashboard Cite

A Decision‐Making Approach Incorporating TODIM Method and Sine Entropy in q‐Rung Picture Fuzzy Set Setting

Aydoğan,

Olgun,

Smarandache

et al. 2024

Journal of Applied Mathematics

View full text Add to dashboard Cite

In this study, we propose a new approach based on fuzzy TODIM (Portuguese acronym for interactive and multicriteria decision-making) for decision-making problems in uncertain environments. Our method incorporates group utility and individual regret, which are often ignored in traditional multicriteria decision-making (MCDM) methods. To enhance the analysis and application of fuzzy sets in decision-making processes, we introduce novel entropy and distance measures for q-rung picture fuzzy sets. These measures include an entropy measure based on the sine function and a distance measure derived from the Jensen-Shannon divergence. In our methodology, incorporating the sine function into the entropy measure stands out as a distinctive decision, grounded in a profound understanding of the inherent characteristics of fuzzy sets. Utilizing the sine function proves especially advantageous when handling fuzzy sets that exhibit cyclical variations or fluctuations in their membership degrees. We effectively weight the criteria for an improved evaluation by using this new entropy measure. The introduced distance measure finds application in the TODIM approach, allowing the execution of TODIM method steps within a fuzzy environment until the determination of one alternative’s dominance over another—an advancement beyond traditional approaches. We apply our enhanced fuzzy TODIM method to a real-life construction project management problem from the literature and compare the results with those in the literature and obtained from other MCDM methods. Our proposed measures are robust, as demonstrated by the sensitivity analysis that varied the weights of group utility and individual regret, with the results visualized in a 3D sensitivity plot. The findings demonstrate the superiority of our method in providing a more comprehensive evaluation of alternatives, making it a useful tool for decision-makers facing complex and uncertain decision-making problems.

show abstract

Product Selection Considering Multiple Consumers’ Expectations and Online Reviews: A Method Based on Intuitionistic Fuzzy Soft Sets and TODIM

Cited by 5 publications

References 55 publications

Text Mining and Multi-Attribute Decision-Making-Based Course Improvement in Massive Open Online Courses

Text Mining and Multi-Attribute Decision-Making-Based Course Improvement in Massive Open Online Courses

An integrated complex T-spherical fuzzy set and soft set model for quantum computing and energy resource planning

A Decision‐Making Approach Incorporating TODIM Method and Sine Entropy in q‐Rung Picture Fuzzy Set Setting

Contact Info

Product

Resources

About