국제학술발표논문집 (International conference on construction engineering and project management)

한국건설관리학회 (Korea Institute of Construction Engineering and Management)
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Advancing Defect Resolution in Construction: Integrating Text Mining and Semantic Analysis for Deeper Customer Experiences

  • Wonwoo Shin (Department of Civil Systems Engineering, College of Engineering, Ajou University) ;
  • SangHyeok Han (Department of Building, Civil and Environmental Engineering, Concordia University) ;
  • Sungkon Moon (Department of Civil Systems Engineering, College of Engineering, Ajou University)
  • 발행 : 2024.07.29
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초록

According to the South Korean Ministry of Land, Infrastructure, and Transport, instances of defect dispute resolutions, primarily between construction contractors and apartment occupants, have been occurring at an annual average of over 4,000 cases since 2014 to the present day. To address the persistent issue of disputes between contractors and occupants regarding construction defects, it is crucial to use customer sentiment analysis to improve customer rights and guide construction companies in their efforts. This study presents a methodology for effectively managing customer complaints and enhancing feedback analysis in the context of defect repair services. The study begins with collecting and preprocessing customer feedback data. Semantic network analysis is used to understand the causes of discomfort in customer feedback, revealing insights into the emotional sentiments expressed by customers and identifying causal relationships between emotions and themes. This research combines text mining, and semantic network analysis to analyze customer feedback for decision-making. By doing so, defect repair service providers can improve service quality, address customer concerns promptly, and understand the factors behind emotional responses in customer feedback. Through data-driven decision-making, these providers can enhance customer rights and identify areas for construction companies to improve service quality.

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과제정보

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (Grant Number: 2022R1F1A1074039)

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