Scholarlink

The objective of this study is to develop or enhance a Kansei engineering-based service improvement methodology previously employed in related research. By integrating Kansei Engineering, text mining, service blueprinting, SERVQUAL, the Kano model, and Quality Function Deployment (QFD), this study proposes a comprehensive approach tailored to service optimization for autonomous ride-hailing platforms.Text mining is employed to extract Kansei-related vocabulary from online customer reviews. The service blueprint is utilized to identify key service attributes, while SERVQUAL is applied to assess the current service quality. The Kano model is used to classify these service attributes into Kano categories, and QFD is adopted to translate customer needs into technical characteristics and operational specifications. The proposed approach is validated through a case study of Robo Taxi, a leading autonomous ride-hailing service platform in China. Beyond autonomous ride-hailing platforms, the methodology is also applicable to broader service industries.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A Service Improvement Approach for Autonomous Taxi Based on Kansei Engineering and the Kano Model: A Case Study of Robo Taxi

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Meiyu Zhou,
  • Hai Liu,
  • Jing Peng

摘要

The objective of this study is to develop or enhance a Kansei engineering-based service improvement methodology previously employed in related research. By integrating Kansei Engineering, text mining, service blueprinting, SERVQUAL, the Kano model, and Quality Function Deployment (QFD), this study proposes a comprehensive approach tailored to service optimization for autonomous ride-hailing platforms.Text mining is employed to extract Kansei-related vocabulary from online customer reviews. The service blueprint is utilized to identify key service attributes, while SERVQUAL is applied to assess the current service quality. The Kano model is used to classify these service attributes into Kano categories, and QFD is adopted to translate customer needs into technical characteristics and operational specifications. The proposed approach is validated through a case study of Robo Taxi, a leading autonomous ride-hailing service platform in China. Beyond autonomous ride-hailing platforms, the methodology is also applicable to broader service industries.