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A blockchain-based evaluation approach to analyse customer satisfaction using AI techniques.

Kousik Barik1, Sanjay Misra2,3, Ajoy Kumar Ray4

  • 1Department of Computer Science, University of Alcala, Spain.

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|June 9, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a novel blockchain-based framework to predict online consumer satisfaction. The advanced Multi-Dimensional Naive Bayes-K Nearest Neighbor and Multi-Objective Logistic Particle Swarm Optimization Algorithm model significantly enhances prediction accuracy and efficiency.

Keywords:
Blockchain technologyCustomer satisfactionMulti-dimensional naive bayes K-Nearest neighbor (MDNB-KNN)Multi-objective logistic particle swarm optimization algorithm (MOL-PSOA)Regression analysis

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Area of Science:

  • Computer Science
  • Information Systems
  • E-commerce Technology

Background:

  • Online shopping is rapidly evolving due to technological advancements and changing consumer demands.
  • Predicting customer satisfaction is crucial for e-commerce organizations to improve service quality and decision-making.
  • Trust and privacy platforms are integral to modern online retail environments.

Purpose of the Study:

  • To develop a robust framework for predicting online consumer satisfaction.
  • To enhance decision-making processes for e-commerce businesses regarding service and quality.
  • To integrate blockchain technology for a trustworthy prediction model.

Main Methods:

  • A blockchain-based framework was proposed, integrating the Multi-Dimensional Naive Bayes-K Nearest Neighbor (MDNB-KNN) algorithm.
  • The Multi-Objective Logistic Particle Swarm Optimization Algorithm (MOL-PSOA) was employed for optimization.
  • A regression model was utilized to quantify the impact of production factors on customer satisfaction.

Main Results:

  • The proposed model achieved high levels of measurement: 98% for customer satisfaction, 95% for accuracy, 95% for precision, and 95% for recall.
  • The model demonstrated a significant reduction in necessary time, achieving 60% efficiency compared to existing methods.
  • The framework provided superior performance metrics over current studies.

Conclusions:

  • The developed blockchain-based framework effectively predicts online consumer satisfaction with high accuracy and efficiency.
  • Trustworthy platforms are essential for understanding customer purchasing decisions in e-commerce.
  • The study contributes to both conceptual and practical advancements in e-commerce customer satisfaction measurement.