The purpose of my research is to contribute to the field of forecasting from a methodological perspective as well as to the field of crude oil as an application area to test the performance of my methodological contributions and assess their merits. In sum, two main methodological contributions are presented. The first contribution consists of proposing a mathematical programming based approach, commonly referred to as Data Envelopment Analysis (DEA), as a multidimensional framework for relative performance evaluation of competing forecasting models or methods. As opposed to other performance measurement and evaluation frameworks, DEA allows one to identify the weaknesses of each model, as compared to the best one(s), and suggests ways to improve their overall performance. DEA is a generic framework and as such its implementation for a specific relative performance evaluation exercise requires a number of decisions to be made such as the choice of the units to be assessed, the choice of the relevant inputs and outputs to be used, and the choice of the appropriate models. In order to present and discuss how one might adapt this framework to measure and evaluate the relative performance of competing forecasting models, we first survey and classify the literature on performance criteria and their measures – including statistical tests – commonly used in evaluating and selecting forecasting models or methods. In sum, our classification will serve as a basis for the operationalisation of DEA. Finally, we test DEA performance in evaluating and selecting models to forecast crude oil prices. The second contribution consists of proposing a Multi-Criteria Decision Analysis (MCDA) based approach as a multidimensional framework for relative performance evaluation of the competing forecasting models or methods. In order to present and discuss how one might adapt such framework, we first revisit MCDA methodology, propose a revised methodological framework that consists of a sequential decision making process with feedback adjustment mechanisms, and provide guidelines as to how to operationalise it. Finally, we adapt such a methodological framework to address the problem of performance evaluation of competing forecasting models. For illustration purposes, we have chosen the forecasting of crude oil prices as an application area.

網路開放商業化以來，各式各樣的商機在網際網路上浮現，大小商家紛在網路上設立據點，或從事廣告、宣傳公司形象，或展示產品內容與產品功能，有的更進一步的設計能與消費者在網路上直接交易，我們概括性的稱之為電子商務。在電子商務的背後，各網站必須要有資料庫作支撐，才能有好的效率和服務。本研究以網際網路資料庫為探討主體，績效為探討目的。並主要以績效評估(Benchmark)理論為貫穿整個研究的基礎理論，一步步地建立適合網際網路資料庫及運算作績效評估的模型。並於模型完成後，予以程式化實作，並以所得數據作測試。 / A lot of business opportunity springs after commercial activities are officially allowed on Internet. The power and the potential of this market is represented by lots of web sites being set up. "Electronic Commerce" is coming to the whole world. However, it is the database supporting business web sites running that counts. Based upon the theory of benchmarking, we want to find out ways that we can know the performance of web database. After the model is set up and the workload is ready, an implementation is being made.