感應式行動支付之營收分享機制 — 理論模型與市場研究

Abstract

根據全球行動通訊系統協會GSMA的統計，在未來的兩年使用手機的人數將增加到57億人，手機已成為人們生活中的必需品，無論是娛樂、聯絡、購物或是資訊獲取方面，手機都扮演著極為重要的角色。而在手機可提供的眾多服務之中，又以行動支付為近幾年最熱門的議題之一，已成為不可忽視的趨勢。本論文將專注在行動支付平台方跟卡片商之間的合約問題，討論要提供何種合約，及合約內確切數字的設定。 本研究將以賽局模型描述合約機制，提供行動支付平台方在不了解卡片商對店家抽成營收的情況下，提供兩個合約供卡片商選擇，每個合約均含有營收抽成比例以及固定費用，最後達到獲利最大化。最後我們得出：行動支付平台方應提供營收較多的卡片商不抽成，但收取等同營收的固定成本；提供營收較少的卡片商百分之百的抽成。 在估計模型內參數方面，我們使用發放問卷的方式進行資料搜集，並且以回歸分析估計卡片商對於抽成敏感度的估計，最後在以問卷結果內的基本消費資料估計若無抽成的總營收，將兩個估計的參數代入模型，求出確切的值。最後再加入行動支付平台方有限負債，即有限補貼，以及加入卡片商固定營運成本的考量，去評估對於契約抽成比例的影響。 本論文的主要貢獻在於行動支付平台方在向卡片商提出契約時，可以藉由營收較少的卡片商佔所有卡片商比例、卡片商對於抽成敏感度的認知以及卡片商固定營運成本以及行動支付平台方本身可以補貼的程度，在訂立抽成比例以及固定成本時有所依據。

According to the statistic of Groupe Speciale Mobile Association, there will be 5.7 billion people using cell phones in 2020. Mobile phones have become a necessity in people's lives. They play an extremely important role in entertainment, communication, shopping, and information acquisition. Among the various services, mobile payment is one of the most widely discussed in recent years and has become a trend that cannot be ignored. The research will focus on the design of the contract between the mobile payment platform (we name it wallet company throughout whole research) and the card companies, discussing which contract should be provided and the exact number on the contract. The study applied the game theory model to describe the contract in order to let wallet company provides two contracts to the card companies without understanding the revenue earned by the card company. Each contract contains the transaction fee rate and fixed costs. Both of the contracts provided would maximize the wallet company’s profit. We obtain the result by calculating the equilibrium of the model, and then we can conclude that the wallet company should provide card company which earns less with zero transaction fee rate and provide transaction fee rate to the ones with more revenue. After getting the equilibrium of the model, we start to consider the limit debt of the wallet company and fixed operating cost of the card company in order to access the impact of them on the transaction fee rate. We obtain the result that taking two more parameters into consideration would lower the upper bound of the transaction fee rate of the card company which earn less. Next, we estimate parameters in the model, we use questionnaires to collect data, and use regression analysis to estimate the card company's sensitivity of transaction fee ratio and we also estimate the maximum possible revenue under no revenue sharing with the questionnaire results; then we substitute two estimated parameters into the model and find the exact value. The contribution of this paper lies in the fact that the wallet company can use the proportion of the type card companies, the perception of card company toward sensibility of the transaction fee rate, the fixed operating costs of the card dealers and the debt limit of the wallet company in order to set the transaction fee rate and fixed fee and to maximize its profit.