2014-11-132024-05-18https://scholars.lib.ntu.edu.tw/handle/123456789/698086摘要：非耐久財廠商，如航空公司、球票經紀商、演唱會承辦公司、時尚產品零售商等，必須在有限時間內售出存貨。拜科技進步所賜，更改商品價格、追蹤存貨，與瞭解消費者行為的成本日漸下滑。因此，愈來愈多此類廠商運用動態定價策略(Dynamic Pricing)，依據存貨量與剩餘銷售時間訂定商品價格。許多經理人十分肯定這種收益管理策略的價值。前美國航空公司執行長，曾形容這種策略是「自1979年空運政策鬆綁後，交通管理上最重要的技術突破。」經濟學上，動態定價的理論基礎發展相當完整，尤其是單一賣家的模型。然而，能作為定價依據的實證計量模型尚付之闕如。特別是包含以下三種要素的模型：(a) 異質產品，(b) 激烈市場競爭，與 (c) 一賣家所定價格可能影響其他賣家未來定價。這三個要素普遍存在於上述非耐久財市場。在此研究案，本人計畫針對此三要素建構實證計量模型， 並利用此模型分析賣家實際定價，是否約為最佳價格。此研究案的資料來源為網路球票次級市場（StubHub網站）。在此網站中，球票經紀商面對許多來自個人賣家的競爭，這些賣家通常持有季票，利用StubHub網站出售無法參加的某幾場比賽門票。此資料擁有許多特點，例如涵蓋交易時間點、座位特徵、每次交易座位量，以及賣家代號等，有助於在動態環境中估計消費需求。 <br> Abstract: Sellers of perishable goods, such as airlines, ticket brokers, concert organizers and retailers of fashion and seasonal items, have to sell inventory within a fixed time horizon. These firms increasingly use dynamic pricing (DP) strategies, where they change prices as a function of both inventory and the time remaining, as technology makes it cheaper to change prices, track inventory and model consumer behavior. Managers often identify these types of revenue management strategies as being very valuable. The former CEO of American Airlines has been widely quoted as describing them as “the single most important technical development in transportation management since we entered the era of airline deregulation in 1979.” The theoretical basis of DP strategies is now well-established, principally in cases where there is a single seller. However, there are few empirically-tractable models that can be used to guide managers’ pricing decisions, especially in settings where (a) products are differentiated, (b) there is significant competition from other sellers, and (c) it is possible that the price that the manager sets will affect the prices that competitors set in the future. These features are present in all of the examples of perishable goods markets given above. In this project, I plan to introduce an empirical model that can be used for this purpose and use the model to analyze whether the pricing strategy that a seller currently uses is approximately optimal. My empirical setting is an online secondary ticket market (StubHub) for sports event tickets. In this market the broker faces competition from a large number of smaller sellers, many of whom are season ticket holders who do not want to attend a particular game. There are several advantages of the unique data that make it possible to model the dynamic pricing behavior of the sellers. In the data, I observe the timing of transactions, characteristics of seats sold, number of seats sold in a transaction, seller ID, etc. These would help to estimate demand in a dynamic framework.動態定價非耐久財Dynamic pricingperishable good