The Analysis of Two-Way E-Commerce Credit Evaluation Model Based on the C2C Mode

Li, Zhezhou; Dai, Rui; Feng, Xuan; Xiong, Yan

doi:10.4018/jgim.305238

Cited by 5 publications

(1 citation statement)

References 40 publications

(31 reference statements)

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“…The Service Performance (SERVPERF) model challenged the SERVQUAL model, believing that when customers continuously receive services, each service received is a process of difference correction of perception and expectation ( Li et al, 2022b ). Using the SERVQUAL model to measure the difference may result in double calculations of customer expectations.…”

Section: Related Workmentioning

confidence: 99%

Multi-angle perception and convolutional neural network for service quality evaluation of cross-border e-commerce logistics enterprise

Zhao,

Yin,

Xie

2024

PeerJ Computer Science

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The development of cross-border e-commerce logistics services has injected new vitality into the development of international trade, and therefore has become a new hot spot in theoretical research. In order to ensure the healthy development of cross-border e-commerce, it is urgent to build a set of scientific and effective evaluation mechanisms to scientifically evaluate the logistics service quality of cross-border e-commerce. Multi-angle perceptual convolutional neural network is a framework for service scene identification of cross-border e-commerce logistics enterprises based on deep convolutional neural network and multi-angle perceptual width learning. In this article, both shallow features and deep features were input into the deep perception model (DPM) to obtain a set of distinguishable features with causal structure, which was used to completely describe the high-level semantic information of cross-border e-commerce logistics enterprise services. Among them, DPM mainly adopts the fusion strategy of shallow feature and deep feature. Meanwhile, the feature representation is input into the width learning pattern recognition system for training and classification, so as to evaluate the service quality of cross-border e-commerce logistics enterprises. The multi-angle perceptual convolutional neural network can effectively solve the problems of high similarity between service classes of cross-border e-commerce logistics enterprises and large differences within the class, and achieve better generalization performance and algorithm complexity than support vector machine, random forest and convolutional neural network.

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Section: Related Workmentioning

confidence: 99%

Multi-angle perception and convolutional neural network for service quality evaluation of cross-border e-commerce logistics enterprise

Zhao,

Yin,

Xie

2024

PeerJ Computer Science

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The data transaction reputation evaluation model based on evaluation entity

Zhao,

Cao,

Gao

2024

J Supercomput

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Enhanced group decision-making through an intelligent algorithmic approach for multiple-attribute credit evaluation with 2-tuple linguistic neutrosophic sets

Mao

2024

KES

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With the development of the internet economy, e-commerce has rapidly risen, and a large number of small and micro e-commerce enterprises have emerged. However, these enterprises have low financial information transparency, small scale, and high development uncertainty. Therefore, combining the characteristics of the internet economy, it is of great significance to dynamically evaluate credit risk. This not only helps to enhance the quality and rationality of credit risk evaluation results, but also helps to improve financing efficiency and reduce financing risks. The credit evaluation for small and micro enterprises is a multiple-attribute group decision-making (MAGDM). Recently, the TODIM (an acronym in Portuguese of interactive and multicriteria decision making) and TOPSIS method has been inaugurated to cope with MAGDM issues. The 2-tuple linguistic neutrosophic sets (2TLNSs) are inaugurated as an effective tool for characterizing uncertain information during the credit evaluation for small and micro enterprises. In this paper, the 2-tuple linguistic neutrosophic TODIM-TOPSIS (2TLNN-TODIM-TOPSIS) method is inaugurated to solve the MAGDM under 2TLNSs. Finally, a numerical case study for credit evaluation for small and micro enterprises is inaugurated to confirm the proposed method. The prime contribution of this paper are outlined: (1) The information entropy based on score function and accuracy function are built on the 2TLNSs to obtain weight information; (2) an integrated the 2-tuple linguistic neutrosophic TODIM-TOPSIS (2TLNN-TODIM-TOPSIS) method is established to cope with MAGDM; (3) An illustrative example for credit evaluation for small and micro enterprises has accomplished to illustrate the 2TLNN-TODIM-TOPSIS; (4) some comparative analysis are employed to verify the 2TLNN-TODIM-TOPSIS method.

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The Analysis of Two-Way E-Commerce Credit Evaluation Model Based on the C2C Mode

Cited by 5 publications

References 40 publications

Multi-angle perception and convolutional neural network for service quality evaluation of cross-border e-commerce logistics enterprise

Multi-angle perception and convolutional neural network for service quality evaluation of cross-border e-commerce logistics enterprise

The data transaction reputation evaluation model based on evaluation entity

Enhanced group decision-making through an intelligent algorithmic approach for multiple-attribute credit evaluation with 2-tuple linguistic neutrosophic sets

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