| Summary: | 博士 === 國立中央大學 === 企業管理研究所 === 92 === This study applies Activity-Based Costing (ABC) to examine operating costs in the airline industry. This study illustrates how to calculate accurate costs, including the operating costs for individual airplanes and flights, as well as the costs per available seat kilometers, and per available ton kilometers. This study also tries to identify the main activity items and activity drivers of each airplane and flight for an airline. If airline management could accurately calculate costs, then they would gain an advantage in price control and competitiveness.
Through ABC cost assignment, airline management can accurately obtain input cost information for different routes based on individual flight cost multiplied by flight numbers or by the sum of various flight costs for different routes. During the past two decades, data envelopment analysis (DEA) has been demonstrated to be a robust and valuable methodology for performance evaluation. This study uses an example to demonstrate how to measure overall profits lost (opportunity cost) from inefficient routes by combining ABC and DEA methods. This model can enable airline management to identify inefficient routes and quick decisions. The advantage of this model lies in providing relevant, reliable and timely information for decision-makers.
In recent years, ABC has become a popular cost and operations management technique to improve the accuracy of product or service costs for firms to stay competition. The product-mix decision is one of the important ABC applications. However, most studies in the ABC literature were generally focused on the effect of ABC analysis on the product-mix decision or product costs without explicitly considering price elasticity of demand and capacity expansions. This study develops a new ABC product-mix decision model it uses mathematical programming approach to explore the optimal production volume and the effect analysis for adding new products into the present product-mix. Additionally, this model can find the optimal product-mix, maximizing profit considering the price elasticity of demand and capacity expansions as well as unit-level, batch-level, product-level, and facility-level activity constraints. Simultaneously, this model can help managers to identify excess resources and re-deploy them in order to increase the optimization of resource usage.
|
|---|
