研究生: |
許嘉芸 Hsu, Chia-Yun |
---|---|
論文名稱: |
運用質化及量化方法於建構行動支付使用者人物誌 Creating Mobile Payment Users Personas: Qualitative and Quantitative Approaches |
指導教授: |
許裴舫
HSU, PEI-FANG |
口試委員: |
王俊程
WANG, JYUN-CHENG 王貞雅 WANG, CHEN-YA |
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: | 2019 |
畢業學年度: | 107 |
語文別: | 英文 |
論文頁數: | 62 |
中文關鍵詞: | 人物誌 、人物誌塑造 、使用者研究 、行動支付 |
外文關鍵詞: | persona, persona development, user research, mobile payment |
相關次數: | 點閱:2 下載:0 |
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人物誌(Persona)在使用者研究領域當中廣泛被運用,過去企業利用質化的方式來製作人物誌,藉此了解使用者的需求及目的,然而透過觀察及訪談方式所製作出的人物誌常被批評為過於主觀且欠缺量化證據佐證。
為了彌補上述質化人物誌的缺點,本研究提出結合質化及量化的新方法來建構人物誌,並且將其應用在台灣行動支付使用者上,從中去了解其特性並透過量化的方式去驗證。首先,本研究根據訪談結果建立三個質化人物誌,並且依照訪談結果設計問卷從中了解行動支付使用者及非使用者。另外則利用因素分析去濃縮量化人物誌的特徵數目,接著採用集群分析來決定量化人物誌的數量以及單因子變異數分析法去辨別集群間是否存在著差異,並依照量化分析結果建構出三個量化人物誌。
最終本研究檢驗質化人物誌及量化人物誌是否存在差異,我們發現質化與量化方式所呈現出的人物誌是有落差的,而這般的差異便是我們挖掘洞見之所在。同時本研究發現各個量化人物誌擁有屬於其獨特的特徵,讓我們更容易將其歸類在某一個量化人物誌底下。另外本研究也採用獨立樣本t檢定去檢測行動支付使用者及非使用者,兩者在生活脈絡上是否有差異,藉此可利用此結果來挖掘行動支付的潛在使用者。
本研究克服當先製作人物誌方法上的缺點,並且建立了更具代表性且更有效率的行動支付使用者人物誌
It has been known that persona method is used widely in user research. Using qualitative approach in persona development is the most traditional method which helps the industry to focus on user needs and goals. However, the qualitative persona through user observations and interviews has met some criticism such as: it is subjective and lacks quantitative evidence to make stakeholders buy-in.
In order to compensate for the disadvantages of qualitative persona, this study proposes a new approach which combines qualitative and quantitative methods to build and validate personas and applied it in Taiwan mobile payment industry to understand the characteristic of mobile payment users. First, we conducted interviews which were transformed into a questionnaire and built 3 quantitative personas according to the result of quantitative data analysis. During the process, we adopted factor analysis to reduce the qualitative data and cluster analysis to form 3 clusters based on mobile payment users’ similarities. Eventually, we applied one-way ANOVA analysis to test the differences among the clusters.
We examined qualitative and quantitative personas and treat the differences as significant insights in discovering the characteristics of mobile payment users. Besides, we find that each quantitative persona has its unique features which make it more distinctive. In addition, we performed t-test to understand the difference between mobile payment users and non mobile payment users.
We could use the result to find potential adopters of mobile payment.
This study has overcome some of the weakness of current methods for the identification and creation of reliable personas and made the persona building process less subjective, more efficient.
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