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A Study on Visitor Engagement of the Audio Guide and Curating-bot at Museum of Modern and Contemporary Art

  • Bo-A Rhee (College of Art & Technology, Chung-Ang University) ;
  • Ye-Eun Seo (Department of Art and Technology, Chung-Ang University) ;
  • Yeon-U Ro (Department of Art and Technology, Chung-Ang University) ;
  • Gyu-Hyun Kim (The graduate School of Advanced Imaging Science, Immersive Media/Animation Contents, Chung-Ang University)
  • Received : 2024.09.02
  • Accepted : 2024.10.02
  • Published : 2024.10.31

Abstract

In this paper, we propose a comparative evaluation framework for digital services in the Museum of Modern and Contemporary Art, focusing on user experience analysis of both mobile apps and curating-bots. Our method assesses the efficiency, support, and innovative attributes of these services, particularly regarding their Pragmatic Quality (PQ) and Hedonic Stimulation (HS). The proposed framework combines empirical user engagement data via survey with hypothesis testing to determine the influences of digital services such as the mobile app and curating-bot on visitor satisfaction and immersion. The research team demonstrates the suitability of the Technology Acceptance Model (TAM) and the Quality-Value-Loyalty (QVL) Chain in evaluating digital services in the art museum context and the impact of these services on the visitor experiences.

본 연구는 국립현대미술관 디지털 서비스의 사용자 경험을 비교 평가하는 구조적 틀을 제안했다. 모바일 앱과 큐레이팅 봇의 효율성, 지원 기능, 혁신적 속성 등을 평가하며, 특히 실용적 품질(PQ)과 쾌락적 자극(HS)에 중점을 두었다. 본 연구는 설문조사를 통해 수집된 관람객의 디지털 서비스에 대한 이용 경험 데이터, 그리고 이 데이터를 기반으로 한 가설 검증을 통해 모바일 앱과 큐레이팅 봇 등 두 가지의 디지털 서비스가 전시만족도와 몰입도에 미치는 영향을 분석했다. 연구팀은 본 연구를 통해 미술관 디지털 서비스 평가에 대한 기술수용모델(TAM)과 박물관의 품질-가치-충성도(QVL) 연계 모델의 적합성과 상술한 서비스의 관람 경험에 대한 영향력을 입증했다.

Keywords

Acknowledgement

This research was conducted as part of the 2023 Cultural Technology R&D Project supported by the Ministry of Culture, Sports and Tourism and the Korea Creative Content Agency (Project title: Development of 3D Precision Information Acquisition and Authoring Technology for Ultra-High Precision Cultural Heritage Restoration of Microstructures, Project number: RS-2023-00227749, Contribution rate: 100%).

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