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The Korean Society for Journalism & Communication (KSJCS)
[ Article ]
Korean Journal of Journalism & Communication - Vol. 68, No. 6, pp.178-216
ISSN: 2586-7369 (Online)
Print publication date 31 Dec 2024
Received 02 Aug 2024 Revised 12 Nov 2024 Accepted 18 Nov 2024
DOI: https://doi.org/10.20879/kjjcs.2024.68.6.005

AI 스피커의 메시지 상호작용성이 지속사용의도에 미치는 영향 : 자기효능감, 복합기능성, 기대충족의 구조모델

장한진** ; 노기영***
**한림대학교 건강과뉴미디어 연구센터 연구교수 hjcloud@hallym.ac.kr
***한림대학교 미디어스쿨 교수 gnoh@hallym.ac.kr
Impact of Message Interactivity on the Continued Usage Intention of AI Speakers : A Structural Model of Self-Efficacy, Multifunctionality, and Expectation Fulfillment
Han-Jin Jang** ; Ghee-Young Noh***
**Research Professor, Center for Health and New Media Research, Hallym University hjcloud@hallym.ac.kr
***Professor, Media School, Hallym University gnoh@hallym.ac.kr

초록

이 연구는 통합 기술 수용 및 사용 이론(UTAUT)을 확장하여 AI 스피커의 핵심 특성인 메시지 상호작용성이 사용자 수용과 지속적인 사용 의도에 미치는 영향을 분석합니다. 메시지 상호작용성은 대화를 통해 학습하고 적응하여 개인화된 피드백을 제공하는 AI 스피커의 능력으로 정의됩니다. 이 기능은 자기 효능감과 다기능성의 매개 역할을 통해 사용자 경험을 향상시켜 지속적인 사용 의도에 긍정적인 영향을 미치며, 이는 사용자-시스템 상호작용 중 인지 부하를 줄이는 데 기여합니다. 또한 메시지 상호작용성은 사용자의 기대를 충족시킴으로써 기술 사용 의도를 강화하는 데 중요한 역할을 합니다. 기대-확증 이론에 따르면, 초기 기대치를 충족하면 시스템 성능에 대한 긍정적인 확신이 생겨 만족도가 높아집니다. 이러한 만족은 다시 사용자의 지속적인 사용 의도와 직결됩니다. 또한 자기 효능감과 다기능성은 기대 충족의 매개 효과를 통해 지속적인 사용 의도에 영향을 미치며, 이는 기술 수용 모델(TAM)에서 설명하는 주요 선행 요인인 지각된 사용용이성과 지각된 유용성을 통해 지속적인 사용 의도에 큰 영향을 미칩니다. 이러한 변수를 효과적으로 활용하고 개선하는 것은 기술의 채택과 사회적 수용을 촉진하는 데 매우 중요합니다.

이 연구는 학문적, 실무적으로 중요한 의미를 지니고 있습니다. 학문적으로는 메시지 상호작용성이 자기효능감, 다기능성, 기대충족을 통해 지속적인 사용의도에 영향을 미치는 과정을 체계적으로 규명함으로써 기존 기술 수용 모델을 확장하고 심화시키는 데 기여했습니다. 실제로 이번 연구 결과는 AI 스피커 개발자와 사용자 경험 디자이너에게 메시지 상호 작용의 중요성을 강조합니다. 이 연구는 사용자의 자기 효능감과 기대 충족을 향상시킬 필요성을 강조함으로써 사용자 만족도와 참여를 향상시키는 기능과 인터페이스를 설계하는 데 실질적인 방향을 제시합니다. 그러나 AI 스피커 수용에 영향을 미칠 수 있는 사회적 영향력, 즐거움, 자발성과 같은 추가적인 요인도 고려해야 합니다. 이 연구는 설문조사 데이터를 기반으로 하기 때문에 대화형 경험과 자기 효능감 간의 인과 관계를 명확하게 입증할 수 있는 실험적 증거가 부족합니다. 향후 연구를 통해 이러한 한계를 해결한다면 외부 요인이 AI 스피커 채택에 있어 사용자의 인식과 행동에 미치는 영향에 대한 이해가 더욱 깊어질 수 있습니다. 향후 연구에서는 통제된 실험 환경이 아닌 실제 사용자 경험을 반영함으로써 실제 상황에서 상호작용과 자기 효능감의 관계를 탐구하여 보다 현실적인 인사이트를 제공할 수 있습니다.

이러한 한계에도 불구하고 이 연구는 메시지 상호작용성의 주요 특징을 파악하고 AI 스피커의 수용과 지속적인 사용 의도에 영향을 미치는 과정과 요인을 확인했습니다. 이러한 연구 결과는 AI 스피커의 수용과 사용자 경험을 향상시키기 위한 전략을 제시하는 동시에 새로운 AI 기반 기술 및 미디어의 수용과 확산에 대한 의미 있는 시사점을 제공합니다. 향후 AI 스피커에 대한 연구는 기술적 분석을 넘어 인간과 기술의 상호작용, 사회적 변화, 윤리적 고려 사항 등을 포괄하는 종합적인 접근 방식을 채택해야 합니다. 이러한 연구는 인간 중심의 기술 개발에 기여할 수 있습니다.

Abstract

This study analyzes the impact of message interactivity, a core characteristic of AI speakers, on user acceptance and continued usage intention by extending the Unified Theory of Acceptance and Use of Technology (UTAUT). Message interactivity is defined as the AI speaker’s ability to learn and adapt through conversations, providing personalized feedback. This capability positively influences continued usage intention by enhancing user experiences through the mediating roles of self-efficacy and multi-functionality, which contribute to reducing cognitive load during user-system interactions. Furthermore, message interactivity plays a significant role in reinforcing technology usage intention by fulfilling user expectations. Consistent with expectation-confirmation theory, meeting initial expectations leads to a positive affirmation of system performance, resulting in heightened satisfaction. This satisfaction, in turn, directly connects to users’ continued usage intention. Self-efficacy and multi-functionality also impact continued usage intention through the mediating effect of expectation fulfillment, which significantly influences continued usage intention via perceived ease of use and perceived usefulness—key antecedents outlined in the Technology Acceptance Model (TAM). Effectively utilizing and enhancing these variables is critical for promoting the adoption and social acceptance of technology.

The study holds both academic and practical significance. Academically, it systematically elucidates the process by which message interactivity affects continued usage intention through self-efficacy, multi-functionality, and expectation fulfillment, thereby contributing to the extension and deepening of existing technology acceptance models. Practically, the findings emphasize the importance of message interactivity for AI speaker developers and user experience designers. By highlighting the need to enhance users’ self-efficacy and expectation fulfillment, the study provides practical directions for designing functions and interfaces that improve user satisfaction and engagement. However, additional factors such as social influence, enjoyment, and voluntariness, which may also affect AI speaker acceptance, need to be considered. Since this research is based on survey data, it lacks experimental evidence to clearly establish causal relationships between interactive experiences and self-efficacy. Addressing these limitations through future research could deepen understanding of how external factors influence user perceptions and behaviors in AI speaker adoption. By reflecting real-world user experiences rather than controlled experimental settings, future studies can explore the relationship between interactivity and self-efficacy in practical contexts, providing more realistic insights.

Despite these limitations, the study identifies the key characteristics of message interactivity and verifies the processes and factors influencing AI speaker acceptance and continued usage intention. These findings offer strategies to enhance AI speaker adoption and user experience while providing meaningful implications for the acceptance and diffusion of emerging AI-based technologies and media. Future research on AI speakers should adopt a comprehensive approach that goes beyond technical analyses, encompassing human-technology interaction, social changes, and ethical considerations. Such research can contribute to the human-centric development of technology.

Keywords:

AI speaker, message-interactivity, self-efficacy, multi-functionality, expectancy-fulfillment

키워드:

인공지능스피커, 메시지 상호작용성, 자기효능감, 복합기능성, 기대충족

Acknowledgments

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea(이 논문 또는 저서는 2022년 대한민국 교육부와 한국연구재단의 지원을 받아 수행된 연구임)[NRF-2022S1A5C2A03091539].

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