以科技接受模式探討LINE APP內功能型聊天機器人的使用意願

ASIA unversity > 資訊學院 > 資訊傳播學系 > 博碩士論文 > Item 310904400/114439

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题名:	以科技接受模式探討LINE APP內功能型聊天機器人的使用意願 Exploring the Willingness to Use a Functional Chatbot in the LINE APP with the Technology Acceptance Model
作者:	葉貝盈 YE, BEI-YING
贡献者:	資訊傳播學系
关键词:	LINE APP;聊天機器人;科技接受模式;使用意願 Technology Acceptance Model;LINE APP;Chatbot;Willingness to Use
日期:	2020
上传时间:	2022-12-19 02:50:23 (UTC+0)
出版者:	亞洲大學
摘要:	根據Global Information, Inc.的聊天機器人全球市場預測調查報告書，顯示目前聊天機器人瘋迷全球，加上在台灣滲透率高達九成的通訊軟體LINE開放了Messaging API的功能，讓有能力的開發商可以透過聊天機器人，將自己的服務24小時不間斷地以對話的方式與使用者進行交流。因此本研究認為未來聊天機器人將深入日常生活，故以針對使用者接受新資訊科技行為所設計的科技接受模式（Technology Acceptance Model, TAM）為理論模型，加上四項外部變數「便利性」、「互動性」、「即時性」及「未來趨勢」，探討使用者在「知覺態度」上選擇LINE APP內的功能型聊天機器人作為查詢管道或紀錄資料的原因。本研究使用線上網路問卷調查方式，以使用過LINE APP功能型機器人的使用者為研究對象，一共回收247份有效樣本，以SPSS統計軟體進行量化分析。分析結果顯示，本論文選擇之外部變數、知覺有用性、知覺易用性及行為態度皆會正面影響使用者。若越能滿足使用者取得資訊或更有效率完成使用目的，就越能提升對聊天機器人的使用意願。以此分析供後續聊天機器人研究學者及服務商進行參考。 According to the Global Market Forecast Survey Report of Chatbots from Global Information, Inc., it shows that chatbots are very popular around the world now. In addition, the Instant Messaging App LINE, which has the usage rate of up to 90% in Taiwan, has opened the function of the Messaging API; this leads to that capable developers can use chatbots to communicate with their users in the form of dialog 24 hours a day. In this thesis, we believe that in the future, chatbots will penetrate into our daily life. Therefore, this study uses the Technology Acceptance Model (TAM) as the research framework and considers four external variables (convenience, interaction, immediateness and future trends) to study the reasons why users choose functional chatbots in the LINE APP as query channels or record data on the perceptual attitude. In this study, the research objects are the users who have used the LINE APP functional chatbot. The online questionnaire was used to collect data and 247 valid samples were collected. With these samples, the SPSS statistical software was used for quantitative analysis. The research results show that external variables, perceived ease of use, perceived usefulness, and behavioral attitudes all positively affect users. The more satisfyingly users obtain information or more efficiently complete the purpose of use, the more willingly they use chatbots. As a result, this analysis can provide a reference for researchers and service providers of chatbots.
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