| 研究生: |
奈娜法 Chamnisampan, Netnapha |
|---|---|
| 論文名稱: |
在平台提供者競爭下權衡隱私保護與應用程式兼容性 Balancing Privacy Protection and Application Compatibility in a Competition of Platform Providers |
| 指導教授: |
吳政翰
Wu, Cheng-Han |
| 學位類別: |
博士 Doctor |
| 系所名稱: |
管理學院 - 工業與資訊管理學系 Department of Industrial and Information Management |
| 論文出版年: | 2024 |
| 畢業學年度: | 112 |
| 語文別: | 英文 |
| 論文頁數: | 178 |
| 中文關鍵詞: | 消費者隱私 、平台共爭 、應用程式兼容性 、數據洩漏 、隱私悖論 |
| 外文關鍵詞: | consumer privacy, platform co-opetition, application compatibility, data leakage, privacy paradox |
| 相關次數: | 點閱:110 下載:0 |
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這研究深入探討了消費者隱私保護努力與兩個競爭平台之間的競合動態,特別 是透過應用程式的兼容性。雖然這樣的兼容性可以增強互操作性,♘可能會妥協消 費者安全並引發隱私顧慮。檢視了這些平台提供者的策略和操作決策。分析包含四 個主要策略:不兼容(策略 I)、雙向兼容(策略 T )、單向優越兼容(策略 OS) 和單向劣等兼容(策略 OI)。此外,我們採用同時和序列決策模型來全面捕捉這些平台的細膩選擇。 我們的發現指出,在同時決策模型中,作為優越者的平台 1 一致在策略 T 下投入最多努力於消費者隱私保護。另一方面,平台 2 將最大的隱私努力集中在策略 I 上,不論潛在用戶因數據洩露風險所面臨的損失,向策略 T 的努力最少。這表明平台 1 擴大市場存在和增加應用程式使用可能需要在隱私上作出妥協。凸顯了在隱私悖論中,平衡市場擴張的需求與保護消費者隱私的必要性。 在較低至中等的數據洩露風險折扣下,兩個平台都偏好策略 OI。然而,隨著風險折扣增加, 轉向策略 T ,開拓更大的市場。 在序列決策模型中,平台 1 領先消費者隱私保護努力和應用價格,優先考慮在策略 T 中面對數據洩露風險的潛在損失的隱私。平台 2 最初在數據洩露的潛在損失較小時,將最大的努力放在策略 I 上,♘隨著數據洩露的潛在損失加劇,則轉向策略 OI。 值得注意的是,兩個平台在較低的數據洩露風險折扣下都顯示出對策略 OS 的偏好。然而,隨著風險折扣增加,轉向策略 T ,尋求雙贏的結果。 最後,兩種決策模型都顯示兩個平台在策略 T 下設定了最高的應用價格,表明通過廣泛、整合的用戶基礎的貨幣化實現最大價值提取。這項研究還探 討了網路效應如何影響平台提供者保護消費者隱私的努力,並分析平台提供者賺取 相同和不同廣告收入的場景。這些洞察提供了寶貴的指導,幫助數位平台在面對嚴 重隱私顧。
This study delves into the complex interplay between consumer privacy protection efforts and the co-opetition dynamics of two competing platforms, particularly through application compatibility. While such compatibility can enhance interoperability, it may compromise consumer safety and raise privacy concerns. In response, we examine these platform providers’ strategic and operational decisions. The analysis encompasses four primary strategies: incompatibility (Strategy I), two-way compatibility (Strategy T ), one-way superior compatibility (Strategy OS), and one-way inferior compatibility (Strategy OI). In addition, we employ simultaneous and sequential decision-making models to capture these platforms’ nuanced choices comprehensively. Our findings indicate that in the simultaneous decision model, Platform 1, being superior, consistently invests the most effort in consumer privacy protection under Strategy T. On the other hand, Platform 2 focuses her highest privacy ef- forts on Strategy I, with the least effort directed towards Strategy T, regardless of potential user losses from data leakage risks. This suggests that Platform 2’s strategy to expand her market presence and increase app usage may require a compromise on privacy. It highlights the complex task of navigating the privacy paradox, balancing the need for market expansion against the imperative of protecting consumer privacy. At lower to moderate data leakage risk discounts for integrated services, both platforms favor Strategy OI. Yet, as the risk discount escalates, they transition to Strategy T, aiming to tap into a larger market. In the sequential decision model, Platform 1 takes the lead by setting his consumer privacy protection effort and application price first, prioritizing privacy in Strategy T across the potential loss users face from the risk of data leakage. Platform 2 responds by initially putting her greatest effort into Strategy I when the potential losses from data leakage are minimal but shifts to Strategy OI as the potential losses from data leakage intensify. Notably, both platforms prefer Strategy OS under lower data leakage risk discounts for integrated services. However, as the risk discount increases, they shift to Strategy T, pursuing a win-win outcome. Lastly, both decision models show that both platforms set the highest application prices under Strategy T, indicating maximum value extraction through monetization of an extensive, integrated user base. This study also explores how network effects influence platform providers’ efforts to protect consumer privacy and analyzes scenarios in which platform providers earn identical and differing advertising revenues. These insights offer valuable guidance for digital platforms navigating the complexities of serious privacy concerns, facilitating better outcomes in the digital platforms.
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