Some Selected Problems of Modern Soft Computing

Cường, Bùi Công; Sơn, Lê Hoàng

doi:10.15625/vap.2015.000203

Cited by 2 publications

(1 citation statement)

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“…Two popular distance measures are defined in Cuong and Son (2015); Son 2016) as follows Let, Ã = x,µ Ã(x), η Ã(x), υ Ã(x) and B = x, µ B(x), η B(x), υ B(x) are two PFS ∀x ∈ U where x = {x 1 , x 2 , x 3 , . .…”

Section: Distance Calculationmentioning

confidence: 99%

A modified EDAS model for comparison of mobile wallet service providers in India

Biswas

Pamučar

2023

Financ Innov

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The present paper has two-fold purposes. First, the current work provides an integrated theoretical framework to compare popular mobile wallet service providers based on users' views in the Indian context. To this end, we propose a new grey correlation-based Picture Fuzzy-Evaluation based on Distance from Average Solution (GCPF-EDAS) framework for the comparative analysis. We integrate the fundamental framework of the Technology Acceptance Model and Unified theory of acceptance and use of technology vis-à-vis service quality dimensions for criteria selection. For comparative ranking, we conduct our analysis under uncertain environments using picture fuzzy numbers. We find that user-friendliness, a wide variety of use, and familiarity and awareness about the products help reduce the uncertainty factors and obtain positive impressions from the users. It is seen that PhonePe (A3), Google Pay (A2), Amazon Pay (A4) and PayTM (A1) hold top positions. For validation of the result, we first compare the ranking provided by our proposed model with that derived by using picture fuzzy score based extensions of EDAS and another widely used algorithm such as The Technique for Order of Preference by Similarity to Ideal Solution. We observe a significant consistency. We then carry out rank reversal test for GCPF-EDAS model. We notice that our proposed GCPF-EDAS model does not suffers from rank reversal phenomenon. To examine the stability in the result for further validation, we carry out the sensitivity analysis by varying the differentiating coefficient and exchanging the criteria weights. We find that our proposed method provides stable result for the present case study and performs better as ranking order does not get changed significantly with the changes in the given conditions.

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Section: Distance Calculationmentioning

confidence: 99%