汽車價格調整對其銷量變動之探討

The Influence Analysis of Gasoline Price Adjustment on Gasoline Sales Changes

林淑娟(Shu-Chuan Lin)

浮動油價調整機制 ； 時間數列介入函數 ； 自營站 ； 加盟站 ； The Floating Oil Price Adjustment Mechanism ； Time Series Intervention Analysis ； CPC's Owned Gas Station ； Fanchise Gas Station

石油季刊

54卷2期（2018 / 06 / 01）

81 - 87

繁體中文

本文係探討台灣地區在實施浮動油價調整機制下，宣布調價日與實施當日，消費者（加盟業者）對調價的反應。主要係利用時間數列介入函數，分別探討2004/01/01～2017/12/31/期間，計14年，中油公司直營站與加盟站，各計5,114筆日資料的銷量（訂貨量）受汽油價格調價的影響。實證結果發現，自營站調漲前一天平均銷售量大幅增加53.3%，顯示消費者對油價上漲相當敏感；調漲當天則因為消費者於調價日前一天已加滿油，故銷售量降低13.8%。調降前一天銷售量微幅降低0.5%（不顯著），而調降當天銷售量上升15.9%。加盟站調漲前一天平均訂貨量大幅增加100.1%，調漲當天訂貨量降低69.6%。調降前一天訂貨量微幅也降低63.6%，而調降當天因銷量達一定程度故須補貨，訂貨量上升107.2%。本文探討標的為中油公司自營站汽油銷量與加盟站向中油公司訂貨量的每日總量，不分站別與汽油種類，日後若能結合加油站庫存，並善用大數據相關概念，針對每站與不同種類的汽油進行分析，除可掌握每座加油站的輸儲調度情況外，也可提升油罐車運輸效能，並降低不必要的斷油與營運風險。

This article explores the reaction of consumers (franchisees) to gasoline price adjustments under the implementation of the floating oil price adjustment mechanism in Taiwan. Using the time series intervention analysis, we discuss the affected sales volume (order quantity) of 5,114 daily data of the Chinese Petroleum Corporation's(CPC's) owned gas station and affiliate station for the 14-year period from January 1, 2004 to December 31, 2017. The empirical results show that the average increase in gasoline sales volume of the CPC's self-operated station before the day of price up was 53.3%, indicating that consumers are quite sensitive to the rise in gasoline prices. On the day of the price up, the sales volume decreased by 13.8% due to consumers had already filled up the gasoline on the day before the price adjustment. On the day before the price cut, the sales volume decreased slightly by 0.5% (not significant), while the sales volume increase 15.9% on the day of the price cut. The average order volume of the fanchise gas station increased by 100.1% on the day before the price up, and decreased by 69.6% on the day of the price up. The order volume decreased by 63.6% on the day before the price cut. On the day of the price cut, the sale volume reached a certain level, so the order volume increased by 107.2%. This article discusses the daily gasoline sales volume of the CPC's owned gas station and the order quantity of the fanchise gas station to CPC, regardless the gasoline station location and gasoline type. If we can combine the gasoline station inventory and the concept of big data and analyze each gasoline station and each type of gasoline, we can predominate the storage and dispatch status of each gasoline station, and can also improve the transportation efficiency of tank trucks and reduce unnecessary oil interrupt and operational risks.

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