基於推薦機制之平台擴張策略分析;Analysis of Platform Expansion Strategy Based on Referral Mechanism

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Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/98397

Title:	基於推薦機制之平台擴張策略分析;Analysis of Platform Expansion Strategy Based on Referral Mechanism
Authors:	王聖智;WANG, SHENG-CHIH
Contributors:	資訊管理學系
Keywords:	霍特林模型;推薦機制;廣告投放;Hotelling′s model;Referral Mechanism;advertising
Date:	2025-07-30
Issue Date:	2025-10-17 12:43:59 (UTC+8)
Publisher:	國立中央大學
Abstract:	本研究探討平台如何在競爭激烈的市場中透過廣告和推薦策略迅速增加使用者數量並最大化利潤。成功的關鍵在於快速擴展用戶基數，因此，本研究嘗試透過建立不同模型，深入分析各種廣告與推薦機制的效益。基本模型中，平台通過初期廣告吸引新用戶，再透過推薦機制擴大用戶基數。結果顯示，最佳的廣告觸及率與推薦人數組合可有效促進平台增長，但隨著推薦成本增加，整體收益會因此降低。進階1-1模型分析了在兩個時期內投放相同廣告量的策略，發現此策略雖能持續吸引新用戶，但因推薦成本及廣告效應遞減，收益受限。進階1-2模型則展現較高策略靈活性，根據市場變化調整廣告投放量，應對市場反應及時調整策略，特別是在品質差距小時，會在初期投入較多資源吸引新用戶；品質差距大時，則逐步減少廣告量，轉而依賴用戶推薦促進增長。付費版模型通過向用戶收取一次性升級費用來獲取收益，此策略在高推薦成本下展現出相較於推薦機制的優勢。總結而言，適當的廣告投放策略對平台初期發展至關重要，而靈活的推薦機制則能有效促進用戶增長，進階1-2模型的策略靈活性尤為突出，能根據市場變化及時調整以最大化收益。本研究的發現為制定行銷策略提供理論依據，幫助平台在競爭市場中突破重圍。;This study investigates how platforms can rapidly increase user numbers and maximize profits through advertising and referral strategies in highly competitive markets. The key to success lies in quickly expanding the user base, so this research builds various models to deeply analyze the effectiveness of different advertising and referral mechanisms. In the basic model, the platform attracts new users through initial advertising, then expands the user base through a referral mechanism. The results show that the optimal combination of advertising reach and referral numbers can effectively promote platform growth, but as referral costs increase, overall profits decrease. The Advanced 1-1 model analyzes a strategy of deploying the same amount of advertising in two phases, finding that although this strategy continues to attract new users, profits are limited due to the diminishing effects of advertising and increasing referral costs. The Advanced 1-2 model demonstrates greater strategic flexibility, adjusting advertising volumes based on market changes and timely adjusting strategies in response to market feedback. Particularly, when there is a small quality gap, it invests more resources initially to attract new users; when there is a significant quality gap, it gradually reduces advertising volumes and relies more on user referrals for growth. The paid version model gains revenue by charging users a one-time upgrade fee, showing advantages over the referral mechanism in scenarios with high referral costs. In conclusion, appropriate advertising strategies are crucial for the initial development of platforms, while flexible referral mechanisms can effectively promote user growth. The strategic flexibility of the Advanced 1-2 model is particularly notable, able to adjust to market changes in time to maximize profits. The findings of this study provide a theoretical basis for formulating marketing strategies, helping platforms break through in competitive markets.
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