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챗봇의 특성이 지속사용의도에 미치는 영향에 관한 연구: 후기수용모델을 중심으로

A Study on the Effects of Chatbot Characteristics on Continuous Usage Intention: Focusing on the Post-Acceptance Model

안현철|정영권
한국컴퓨터정보학회 (The Korean Society Of Computer And Information)|2023.06|한국컴퓨터정보학회논문지 (Journal of The Korea Society of Computer and Information)|제28권 제6호|pp. 169-179|DOI https://doi.org/10.9708/jksci.2023.28.06.169

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참고문헌

키워드

자율성챗봇Chatbot개인화Autonomy의인화PersonalizationAnthropomorphism후기수용모델Post-Acceptance Model
주제분류컴퓨터학

초록

본 논문에서는 후기수용모델(PAM)을 기반으로 챗봇의 지속적 사용의도를 설명하는 모델을 설계하고, 선행요인으로 의인화, 개인화, 자율성을 제안하였다. 제안 모델을 검증하기 위해 챗봇 사용 경험이 있는 441명을 대상으로 설문을 수집하고, PLS 구조방정식 모델을 사용하여 실증적으로 분석하였다. 설문에서 챗봇의 의인화, 개인화, 자율성의 수준을 높고 낮은 예시를 그림으로 제공하여 그 효과를 조사했으며 실질적인 챗봇 서비스의 사용이 스스로 가능한 20대부터 70대의 연령대를 실험 대상으로 선정하였다. 구조방정식 모델링 수행 시 부트스트랩핑 기법을 사용하여 모델의 적합도 및 신뢰구간을 계산하였다. 분석 결과 의인화와 개인화가 지각된 유용성과 확신에 유의한 영향을 미치는것으로 나타났다. 자율성은 지각된 유용성에 직접적인 영향을 미치지는 않았지만, 확신에 강한 영향을 미쳐 간접적으로 지각된 유용성에 영향을 미치는 것으로 나타났다. 이 연구 결과는 챗봇 서비스제공자가 고객의 지속적인 챗봇 사용 의도를 증대시키는 전략을 개발하는데 기여할 수 있을 것이다.

Abstract

In this paper, we propose a model to explain the intention to continue using chatbots based on the Post-Acceptance Model(PAM). We suggest anthropomorphism, personalization, and autonomy as antecedents. To validate the proposed model, we collected 441 responses from a survey and analyzed them using PLS. The survey included examples in the form of images depicting high and low levels of anthropomorphism, personalization, and autonomy in chatbots, aiming to investigate their effects. The study selected participants aged 20 to 70, covering a range of practical chatbot service users. The collected data were empirically analyzed using the PLS(Partial Least Squares) structural equation modeling(SEM) approach. The bootstrap resampling technique was employed during the SEM analysis to calculate model fit indices and confidence intervals. The results show that anthropomorphism and personalization significantly impact perceived usefulness and confidence. Autonomy did not directly affect perceived usefulness, but it strongly affected confirmation, which indirectly influenced perceived usefulness. These findings can help chatbot service providers develop strategies to increase customers' intention to continue using chatbots.

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