城際型交通資訊服務系統商業模式建立之研究

A Study on Establishing the Business Model of Traffic Information Service System of the Intercity Type

李誌嘉(Jhih-Jia Li)

指導教授 ： 陳敦基

淡江大學/管理學院/運輸管理學系碩士班/碩士(2007年)

https://doi.org/10.6846/TKU.2007.00222

摘要

近年來，隨著資訊與通訊科技日新月異，進而促進發展出智慧型運輸系統(Intelligent Transportation System, ITS)，各國皆以智慧型運輸系統(ITS)解決交通運輸問題，其中，先進用路人資訊服務(Advanced Traveler Information Services, ATIS)其目的為提供用路人即時的交通資訊及路線導引，協助用路人做有效的旅運決策。本研究以政府促進民間參與智慧型運輸建設之前提，分析政府、民間業者參與城際型交通資訊服務系統營運所形成之商業模式及財務模式。本研究透過調查問卷，利用敘述性偏好情境設計取得旅運者對於交通資訊服務系統提供之偏好程度及旅運特性，進而預測未來市場收益。
在系統成本方面，本研究之規劃建置範圍包含國道高速公路路網、一般快速道路及主要省道，於建置範圍之路段架設車輛偵測器(Vehicle Detector)蒐集交通流量與速率資訊；重要路口架設閉路電視監視器(Closed Circuit Television)蒐集交通流量影像資料並進行監測。建置上述設備為初期投資之固定成本，約為37.95億元，基年維運成本為2.56億元/每年。
在系統收益方面，本研究利用個體運具選擇模式(Disaggregate Modal Choice Model)分析旅運者使用交通資訊之選擇行為，有使用交通資訊習慣分為使用行動通訊 (Mobile Telecommunication)設備及使用非行動通訊設備，另亦考慮無使用交通資訊習慣之旅運者。本研究利用敘述性偏好資料分別建立多項與巢式羅吉特模式，並以最大概似法進行模式校估，結果發現多項羅吉特模式具較佳解釋能力，故本業收益估算即以多項羅吉特模式計算之。本業收益為交通資訊服務系統中心提供基本型及加值型交通資訊之服務費率收益，交通資訊服務平台租金收益，亦為本業收益之一。交通資訊服務本業之基年收益為1.55億元，至目標年之分年收益為12.18億元/每年，而交通資訊服務平台租金為0.25億元/每年。在達財務自償的前提下，不同費率方案(繳月租費配合較低方率、免月租費配合較高費率及繳月租費可抵用使用次數)，其所需業外收益約在0.33~2.26億元/每年之間，而其成本回收年期約為33年。在不考慮業外收益的前提下，分別依據成本回收年期設定不同特許年期時，發現其財務自償率則介16.13％~121.46％之間。

關鍵字

交通資訊服務 ； 商業模式 ； 財務模式 ； 個體運具選擇模式 ； 自償率

並列摘要

In the recent years with the progress of Information and communication science and technology, the Intelligent Transportation System (ITS) has been applied to solve the transportation problem by the various countries. Wherein the Advanced Traveler Information Services (ATIS) is built to provide the real time traffic information and the guidance of route, and also assist the road user to make the decision of travel efficiently. This study aims to development the business model and the financial model that are used to analysis the government and the private operator participating the deployment and operation of the traffic information service system. Besides the questionnaire of the stated preference survey is utilized to collect the degree of preference and the characteristic of travel for the traffic information service, in order to predict the market reverence in the future.
In the cost of the system, the study plans the range of deployment which includes the national freeway network, the expressway and the major province highway. The vehicle detector is deployed to collect the data of traffic volume and speed in the each segment of road, and the closed circuit television is employed to collect the data of volume and image under surveillance. In all of the above facilities, the total deployment cost is about 3.75 billions dollars, and the maintenance cost is about or is about 256 millions dollars for every year.
In the revenue of the system, the study applied Disaggregate Modal Choice Model to analyze the traveler’ choice behavior on the usage of the traffic information, wherein the user types include the traveler used to use the traffic information via the mobile and non-mobile approaches, and the traveler not used to do. The stated preference data is used to develop the multinomial and the nested Logit models in the study. The calibration of models which employed the maximum likelihood ratio method, shows the multinomial Logit model posses the better result of explanation, then it is used to estimate the original business(OB) revenue, which is from the rates of the basic service and the added value service. Besides the rent revenue of traffic information platform is also the major revenue for the system. In the basic year the OB revenue of traffic information service is about 155 millions dollars, and until the objective year the revenue is about 1.22 billions dollars, and the rent revenue of platform is about 25 millions dollars in each year. For the self-liquidating the demanded revenue of non-OB is among 33 millions dollars to 226 millions dollars for the various alternative of rate, and the pay-back periods is about 33 years. Under the franchise year that designed as the pay-back periods, and without the consideration of non-OB, this study find that the ratio of self-liquidating is between 16.13％ to 121.46％.

並列關鍵字

Traffic Information Service ； Business Model ； Financial Model ； Disaggregate Modal Choice Model ； the Self-Liquidating Ratio

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