網路廣告平台之競爭模型

Abstract

數位廣告在近幾年迅速成長，網路廣告平台可以透過平台所蒐集的資料分析顧客的喜好，將廣告以更精準的方式傳送給特定的顧客，廣告投放效益取決於平台的廣告投放準確度與社群化程度，當社群化程度越高，使用者互動越頻繁，彼此的聯繫越高，廣告的口碑效應越高，廣告投放效益越大。因此，在本篇論文中，我們提出一競爭模型以探討平台的社群化程度、廣告投放準確度與平台上的使用者人數對網路廣告平台的影響。其中，當準確度分析成本小時，網路廣告平台的社群化程度越高以及人數差異越大，則會使得具有社群化優勢的廣告平台的利潤降低；而準確度分析成本大時，此廣告平台的利潤會隨著社群化程度和人數差異提高而增加。當兩家競爭程度降低，則處於劣勢的廣告平台的利潤則會提高，而具有優勢的平台則會因為準確度分析成本的大小而有不同的走向。廣告平台利潤的高低取決於兩個平台的社群化優勢與人口優勢的權衡結果，權衡之後，當準確度分析成本小時，較有優勢的平台的利潤較低，而當準確度分析成本大時，較有優勢的平台的利潤較高，本研究成果可幫助網路廣告平台根據市況擬定有效的競爭策略。

Digital advertising has grown rapidly in recent years, where online advertising platforms may deliver ads to target customers more precisely than traditional advertising providers since they know customers better by mining customers’ preferences from the data collected on their platforms. The ad effectiveness on an online advertising platform may be influenced by its targeting accuracy and degree of socialization. The higher degree of socialization, the stronger social interaction and tie among users on the platform, which may lead to the larger word-of-mouth effect. Therefore, in this thesis, we propose a model to study how online advertising platforms are affected by the degree of socialization, targeting cost, and amount of users on each platform. When the targeting cost is low, the profit of platform with advantage in socialization decreases with the degree of socialization and difference between the amounts of users of both platforms. When targeting cost is high, the profit of platform with advantage in socialization increases with the degree of socialization and difference between the amounts of users of both platforms. The profit of platform with disadvantage in socialization increases when the competition is getting weaker; however, the profit of platform with advantage in socialization increases first and decreases when the targeting cost is low, and decreases then increases when the targeting cost is high. In addition, which platform is more profitable is decided by trading off the advantage in socialization of one platform and the advantage in amount of users on the other. The platform with more advantage after the trade-off is less profitable when the targeting cost is low; however, it is more profitable when the targeting cost is high. Therefore, our proposed model may help online advertising platforms trade off the advantage in socialization of one platform and the advantage in amount of users, and formulate effective strategies.