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Title: | 以機器學習探討直播主語言及非語言線索對購買意願的影響 The Impacts of Streamer's Verbal and Non-verbal Cues on Customer Purchase Intentions: A Machine Learning Approach |
Authors: | 陳亭妤 Chen, Ting-Yu |
Contributors: | 彭志宏 李怡慧 Peng, Chih-Hung Lee, Yi-Hui 陳亭妤 Chen, Ting-Yu |
Keywords: | 直播 語言行為理論 購買意圖 情感表達 機器學習 Live-streaming Speech act theory Purchase intention Emotional expression Machine learning |
Date: | 2024 |
Issue Date: | 2024-07-01 12:35:05 (UTC+8) |
Abstract: | 在直播環境中,主播的表現包括語言和非語言線索顯著地影響顧客的購買意圖,本研究基於語言行為理論,將語言分為五種類型(即斷言、表達、指令、承諾和宣告)。我們檢視了語言意圖類別對顧客購買意圖的影響,此外還引入了情感表達的概念作為調節變數。我們收集並分析台灣最大直播平台的153個影片,研究發現斷言和指令類型的語句對購買意圖有正面影響,而表達類型的語句則會削弱其意願,我們還發現較高的情感表達可以增強指令性語句的影響,但會削弱斷言性語言的效果。基於這些見解,我們建議主播應著重於詳細的產品描述和積極與觀眾互動,並在直播中謹慎流露其情緒表達,本研究為主播提供表演實用指南,進而增加顧客購買意圖。 In a live-streaming context, streamer performance—characterized by verbal and nonverbal cues—significantly influences customer purchase intentions. Drawing on speech act theory, this study categorizes speech phrases into five categories (i.e., assertive, expressive, directive, commissive, and declarative). We examine the impacts of speech intent categories on customer purchase intention. Furthermore, we introduce and examine the moderating effect of an emotional expression. We collect and analyze 153 videos from the largest streaming platform in Taiwan. We find that using more assertive and directive phrases is positively related to customer purchase intentions, while using more expressive phrases is negatively related to customer purchase intention. We also find that high emotional expression enhances the impact of directive speech but undermines assertive speech. Based on these findings, we suggest that streamers focus on detailed product descriptions and active audience engagement, and carefully express their emotions in the live-streaming area. This study provides practical guidelines for streamers to manage their performances and thereby enhance customer purchase intentions. |
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Description: | 碩士 國立政治大學 資訊管理學系 111356011 |
Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0111356011 |
Data Type: | thesis |
Appears in Collections: | [資訊管理學系] 學位論文
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