探索不同免費增值策略對於付費意願之影響｜國立清華大學博碩士論文庫

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研究生：	謝秉均 Hsieh, Ping-Chun
論文名稱：	探索不同免費增值策略對於付費意願之影響 Exploring how different freemium strategies affect users’ willingness to pay?
指導教授：	許裴舫 Hsu, Pei-Fang.
口試委員:	王貞雅 Wang, Chen-Ya. 李傳楷 Lee, Chuan-Kai.
學位類別：	碩士 Master
系所名稱：	科技管理學院 - 服務科學研究所 Institute of Service Science
論文出版年：	2017
畢業學年度：	105
語文別：	英文
論文頁數：	49
中文關鍵詞：	免費增值、串流影音電視、人為購買欲望、生活型態區隔
外文關鍵詞：	Freemium, Streaming TV, Artificial Buying Desire, Lifestyle Segmentation
相關次數：	點閱：2 下載：0
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Abstract (Chinese)
本研究旨在了解在使用串流影音電視時，不同的免費增值策略如何影響用戶之人為購買慾望與實際購買行為。同時，我們更基於受測者之使用行為進行群聚分析，將台灣之串流影音用戶分群。免費增值策略已廣泛被應用於網路服務和軟體產業。採用免費增值策略的廠商能在極短的時間內，獲取大量的用戶。然而伴隨免費增值策略而來的低轉換率，免費增值策略因此受到了許多質疑。同時，過去免費增值之相關研究，也未針對不同免費增值策略進行比較。本研究透過田野實驗之方式，使用真實之串流影音平台。將免費增值策略分為內容限制(content limited: many or less free content)及時間限制(time limited)，並隨機將受測者分配到五組實驗中。實驗結束後，除了回答人為購買慾望之相關問題外，受測者可選擇新台幣六十元或付費版之串流影音帳號（新台幣六十元等值）作為他們的獎勵，受測者如果選擇付費帳號，我們則視其購買串流影音帳號。基於人為購買慾望的概念，我們發現不同的免費增值策略會產生不同之人為購買慾望，且時間限制能夠創造更多的人為購買慾望，且越高的人為購買慾望，實際購買之比例越高。同時，透過群聚分析，我們將台灣串流影音用戶分為戲劇狂熱、資訊敏捷及社交活躍用戶，且戲劇狂熱用戶有最高的人為購買慾望。最後，相較於華語內容愛好者來說，外語內容愛好者更有可能在免費增值策略下付費。因此，本研究建議採取免費增值策略之廠商，應將時間限制納入其免費增值策略中，且針對戲劇狂熱用戶和外語內容愛好者之使用行為設計行銷策略。

Nowadays, freemium strategies are widely used in online services and software industry. Those who adapt freemium strategies can have large number of users in such a short time. However, due to their low conversion rate, freemium strategies are always challenged. In the meantime, little do we know about how efficient these freemium strategies are. This study aims to understand how different freemium strategies affect users’ desire and their actual paying behaviors when using streaming TV platforms. Furthermore, we examine Taiwanese streaming TV users’ behaviors and their desire and conduct clustering analysis to segment Taiwanese streaming TV users. Freemium strategies: Content limited (many free content / less free content) and Time limited are selected in our field experiment. Participants were randomly assigned to our scenarios. After the experiment, they are asked about the desire and they can choose $NT 60 or a paid premium streaming TV account (equal to $NT 60) as their reward. The latter represents that participant buy the account. Based on the concept of artificial buying desire, we propose different freemium strategies may result in different desire. Secondly, we then explore the relationship between artificial buying desire and actual paying behaviors. Finally, we segment Taiwanese streaming TV users using lifestyle theory and understand their desire and behaviors. The results show that using different freemium strategies can result in different desire and time limited results in the highest desire. Also, the higher your artificial buying desire is, the higher probability will you buy the premium account. Lastly, there are three types of streaming TV users in Taiwan. They are Drama frenzy users, Agile information users and Actively social users. Drama frenzy users have the highest desire among them. Besides, comparing to Chinese content lovers, foreign content lovers are more likely to pay. The findings suggest that vendors should take time limited as one of their freemium strategies and focus on drama frenzy users and foreign content lovers’ behaviors to design their marketing strategies.

Table of Content
Table of Content    I
List of Table    II
List of Figure    IV
Abstract (Chinese)    V
Abstract    VI
1    Introduction    1
2    Literature Review    4
2.1    Streaming TV / Over the Top Media (OTT Media)    4
2.2    Freemium    5
3    Theoretical Foundation, Hypotheses and Research Model    11
3.1    Artificial Buying Desire    11
3.2    Lifestyle Theory and Segmentation    13
3.3    Research Model    15
4    Methodology    16
4.1    Pre-study and Interview    16
4.2    Experiment Design    17
4.2.1    Experimental environment and groups    17
4.2.2    Participants    18
4.3    Experiment Tasks and Procedures    19
4.4    Lifestyle Variables    20
5    Data Analysis and Results    23
5.1    Descriptive Statistic    23
5.2    Different Freemium Strategies    24
5.3    Artificial Buying Desire and Actual Buying Behaviors    26
5.4    Moderating Effect of Price Acceptance level    28
5.5    Lifestyle Segmentation and Artificial Buying Desire    30
6    Discussion, Conclusions and Implications    36
Study Limitations and Opportunity for Further Research    37
7    Reference    38
8    Appendix – Survey (for Aiqiyi free plan participants)    42


List of Table
Table 2.1 Freemium Types …………………………………………………………. 6
Table 3.1 A.I.O. dimensions ………………………………………………………. 15
Table 4.1 A comparison of content and types among platforms …………………. 16
Table 4.2 A rank of free content among platforms ………………………………. 16
Table 4.3 Experimental Groups …………………………………………………... 18
Table 4.4 Demographics of participants …………………………………………. 19
Table 4.5 Lifestyle variables ……………………………………………………… 21
Table 5.1 Purposes to watch streaming TV ………………………………………. 23
Table 5.2 Favorite origin of content ……………………………………………... 23
Table 5.3 Favorite types of content ……………………………………………… 23
Table 5.4 Factors that affect user’s willingness to pay …………………………… 24
Table 5.5 Experimental groups …………………………………………………… 24
Table 5.6 ANOVA test results among three strategies ……………………………. 25
Table 5.7 Post Hoc tests results among three freemium strategies ………………. 25
Table 5.8 Percentage of actual paying behavior among different desire …………. 26
Table 5.9 Chi-square results of desire and actual paying behaviors ……………… 27
Table 5.10 Percentage of actual paying behavior among different strategies………..27
Table 5.11 Chi-square results of freemium strategies and actual paying rate ……. 28
Table 5.12 Percentage of high/ low price acceptance participants ……………….. 29
Table 5.13 Logistic regression results of low price acceptance participants …….. 29
Table 5.14 Logistic regression results of high price acceptance participants ……. 29
Table 5.15 KMO tests of factor analysis ………………………………………… 30
Table 5.16 Factor analysis results ………………………………………………… 31
Table 5.17 Participants in each cluster ……………………………………………… 32
Table 5.18 ANOVA tests of three clusters ………………………………………….. 32
Table 5.19 Factor score of three clusters …………………………………………… 33
Table 5.20 ANOVA tests results among three clusters’ desire ……………………. 34
Table 5.21 Post Hoc tests results among three clusters’ desire …………………… 34
Table 5.22 percentage of content lovers and paying behaviors ……………………35
Table 5.23 Chi-square results of content lovers and paying behaviors ……………35









List of Figure
Figure 3.1 Research Model ………………………………………………………… 15
Figure 5.1 Scree plot of factor analysis ……………………………………………. 30
Figure 5.2 Hierarchical clustering results …………………………………………. 32

                                

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