探討用戶生成內容於餐飲業網路行銷之應用
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2019
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Abstract
近年來，因為社群網路 (Social Networking Sites, SNS) 的活躍及普及，個人發布於SNS中的訊息變得越來越具有影響力。於Web 2.0的背景之下，網路使用者注重於建構共享、創作和交流的SNS環境，因而產生用戶生成內容 (User-generated content, UGC)，消費者不僅會藉由SNS分享、交換意見，也會提供相關產品的體驗經驗，並且透過網路獲取資訊。在資訊社會中，圖片於訊息整體的影響力也變得更加重要，能夠有效的吸引觀眾的注意力。目前尚未有文獻針對個人發布於SNS中的訊息呈現模式進行最佳效率之分析，本研究將SNS平台Instagram貼文之文字長度、可讀性、實體環境相片及餐點相片數量做為投入項；按讚數量及留言數量作為產出項，以資料包絡分析法 (Data Envelopment Analysis, DEA) 計算效率值，求出最佳效率的貼文呈現模型。本研究共收集894則介於2017年1月1日至12月31日發布的Instagram訊息，使用DEA投入導向模型分析，研究結果顯示，當Instagram中的UGC訊息使用7個字，控制其中難詞數量，維持文字可讀性數值於3.51，以及使用1張實體環境照片搭配2張餐點照片，能夠達到整體最佳效率值，持續引起觀眾對於這一則訊息的興趣 (感知愉悅性) 及討論 (感知實用性)。本研究之結果可以提供餐飲業者進行網路行銷之參考。
Due to social networking sites (SNS) becoming more popular in recent years, the messages that individuals published on social media had become more influential on the others’ behaviors. Most Internet users generated a shared, creative and communicated society. Opinions exchanging and personal experiences sharing generated from consumer via the social network called User-generated content (UGC). In the digital era, the influence of visual message had become more important than the past. UGC has become an effective way to attract other viewers. There has no study analyzing the best efficiency model of message presentation in visual-based social media. This study collected the UGCs including length of posts written in Chinese, the text readability, and numbers of photos for physical environment and food& beverage as input, number of likes and comments as output from Instagram, one of the most popular SNS. This paper uses the Data Envelopment Analysis (DEA) to evaluate the efficiency values of the observed UGCs in order to obtain the efficient message model. In total, 894 Instagram messages posted during 2017 January 1 to December 31 were collected and analyzed with DEA input-oriented model in this paper. The results showed that when UGC on Instagram is composed of 7 words, the text readabilityin 3.51 as well as one physical environment photos and two food& beverage photos, UGC can achieve the best efficiency value and increase viewers' perceived response to this message gerenally. The results of this study can provide a reference for catering operators to improve online marketing.
Due to social networking sites (SNS) becoming more popular in recent years, the messages that individuals published on social media had become more influential on the others’ behaviors. Most Internet users generated a shared, creative and communicated society. Opinions exchanging and personal experiences sharing generated from consumer via the social network called User-generated content (UGC). In the digital era, the influence of visual message had become more important than the past. UGC has become an effective way to attract other viewers. There has no study analyzing the best efficiency model of message presentation in visual-based social media. This study collected the UGCs including length of posts written in Chinese, the text readability, and numbers of photos for physical environment and food& beverage as input, number of likes and comments as output from Instagram, one of the most popular SNS. This paper uses the Data Envelopment Analysis (DEA) to evaluate the efficiency values of the observed UGCs in order to obtain the efficient message model. In total, 894 Instagram messages posted during 2017 January 1 to December 31 were collected and analyzed with DEA input-oriented model in this paper. The results showed that when UGC on Instagram is composed of 7 words, the text readabilityin 3.51 as well as one physical environment photos and two food& beverage photos, UGC can achieve the best efficiency value and increase viewers' perceived response to this message gerenally. The results of this study can provide a reference for catering operators to improve online marketing.
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Keywords
社群網路, 用戶生成內容, Instagram, 資料包絡分析法, SNS, UGC, Instagram, DEA