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https://nccur.lib.nccu.edu.tw/handle/140.119/152083
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| Title: | 探討免費增值商業模式下影響用戶參與度之因素 - 以證券投資交易 App 為例
Examining the Factors Influencing User Engagement in Freemium Business Model: A Case of Stock Trading App |
| Authors: | 邱筱涵
Chiu, Hsiao-Han |
| Contributors: | 何乾瑋
Ho, Chien-Wei
邱筱涵
Chiu, Hsiao-Han |
| Keywords: | 證券投資投資應用程式
免費增值商業模式
用戶參與度
用戶留存
羅吉斯迴歸模型
XGBoost
Stock Trading Mobile Application
Freemium
User Engagement
User Retention
XGBoost
Logistic Regression Model |
| Date: | 2024 |
| Issue Date: | 2024-07-01 12:43:23 (UTC+8) |
| Abstract: | 隨著行動應用程式的迅速發展與普及，用戶對 APP 的依賴和使用時數持續增加，並衍生出多樣化的商業模式，其中免費增值模式尤為絕大多數企業所採用。然而，文獻指出，大多數用戶在下載 APP 後的 90 天內即停止使用。因此，如何提升用戶留存成為企業面臨的挑戰。多篇研究顯示，用戶參與度是影響用戶留存的關鍵因子，故本研究以證券投資交易 APP 為研究案例，探討在免費增值商業模式下，影響用戶參與度的重要因素。
目前既有之相關研究，多是採用問卷研究及次級資料的方式來蒐集相關用戶 APP 使用行為資料。然而，這樣的研究方式局限於用戶意願、態度或下載行為的量測，無法實際衡量用戶於下載後的實際使用行為。故本研究擷取過往文獻中提及的四大構面作為研究框架，進而從個案研究公司資料庫中選取組成研究構面的 APP 使用行為相關變數，並利用機器學習的 XGBoost 演算法，進行重要性排序，篩選出具影響力的變數。最後，使用羅吉斯迴歸模型進行預測分析。
研究結果顯示，無所不在性、交易效率與互動性等構面，對用戶的留存具有正向的顯著影響。然而，知覺個性化則不符合研究假設，對用戶留存產生負向影響。本研究結果期待能夠拓展 APP 免費增值商業模式相關研究的開展，進一步推動該領域研究框架的完善，並即時提供企業在證券投資交易 APP 後續產品開發和精準行銷的實務建議。
With the rapid development and widespread adoption of mobile applications, user dependency and the amount of time spent on apps have continually increased. Several different business models were thus derived, with the freemium business model being predominantly adopted by most companies. However, existing literature indicates that most users left within 90 days of downloading the App. Thus, enhancing user retention is a significant challenge. While multiple studies have shown that user engagement is a key determinant of user retention, this study explores the critical factors that affect user engagement under the freemium business model.
Most extant research relies on survey research and secondary data to collect information on user app usage behavior, which is limited to measuring user intentions, attitudes, or download behaviors and fails to assess actual usage behavior post-download. Consequently, this study draws on previous literature and selects four constructs as the research framework to extract relevant app usage behavior variables from the case company's database. The XGBoost technique in machine learning and logistic regression were used for further analysis.
This study found that ubiquity, transaction efficiency, and interactivity significantly increase user retention, whereas perceived personalization negatively affects user retention. These results are expected to expand research on the freemium business model, refine the research framework in this field, and provide companies with timely and precise marketing recommendations for future stock trading app development. |
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| Description: | 碩士
國立政治大學
國際經營與貿易學系
111351031 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0111351031 |
| Data Type: | thesis |
| Appears in Collections: | [國際經營與貿易學系 ] 學位論文
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