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

【Author】 Barik, Kousik; Misra, Sanjay; Ray, Ajoy Kumar; Shukla, Ankur

【Source】HELIYON

【影响因子】3.776

【Abstract】Due to technological advancements and consumer demands, online shopping creates new features and adapts to new standards. A robust customer satisfaction prediction model concerning trust and privacy platforms can encourage an organization to make better decisions about its service and quality. This study presented an approach to predict consumer satisfaction using the blockchain-based framework combining the Multi-Dimensional Naive Bayes-K Nearest Neighbor (MDNB-KNN) and the Multi-Objective Logistic Particle Swarm Optimization Algorithm (MOLPSOA). A regression model is employed to quantify the impact of various production factors on customer satisfaction. The proposed method yields better levels of measurement for customer satisfaction (98%), accuracy (95%), necessary time (60%), precision (95%), and recall (95%) compared to existing studies. Measuring consumer satisfaction with a trustworthy platform facilitates to development of the conceptual and practical distinctions influencing customers' purchasing decisions.

【Keywords】Blockchain technology; Customer satisfaction; Multi -dimensional naive bayes K -Nearest; neighbor (MDNB-KNN); Multi -objective logistic particle swarm; optimization algorithm (MOL-PSOA); Regression analysis

【发表时间】2023 JUN

【收录时间】2023-07-26

【文献类型】实证数据

【主题类别】

区块链应用-实体经济-客户关系管理