碩士 / 國立高雄應用科技大學 / 工業工程與管理系碩士班 / 103 / Marine transportation is one of the important driving forces for a country's international trading and economic development. Strong countries around the world are growing their marine transportation industry to enhance their economic. Thanks to the improvement of the container shipping system and the transportation system, the marine transportation nowadays has become more convenient. Since the shipping route service, shipping quality and operating cost are more similar between enterprises, the competition in this industry has become tougher. Therefore, companies need to have operating improvements to achieve competitive advantage.
Our research uses Data Envelopment Analysis (DEA) method along with Grey Forecasting Model to study the operating performance of marine transportation companies. We use the world's top 10 marine transportation companies as our research target and collected data from their financial statements. We use the operating expenses, operating cost and equity as the input variables, while using the operating revenues and operating income as the output variables. First, we use the data from 2010 through 2013 to forecast the input and output variables of 2014 to 2016 by applying the FRGM(1,1) model. Then, we combined the forecast results and the data from 2010 through 2013 to conduct the Malmquist productivity index model to measure the operating efficiency. Through these processes, we will further discuss the operating changes of the whole industry of the marine transportation.
From the results of our research, we find out that the economic growth slowed sharply by the period 2010 through 2013, as a results the cargo quantity growth was disturbed. Moreover, data showed that the 10 companies' competitiveness and productivity were dropped simultaneously. We use FRGM(1,1) to calculate the predictive value because the average variable value results are more precise then the results of Grey Forecasting Model GM(1,1). We applied the Malmquist productivity index model with the predictive value, and found out that the MPI value of transportation companies should be 1.1627 within the period 2014 trough 2015 which shows an upward tendency. Meanwhile, the MPI value is 0.9948 within the period 2015 through 2016, which shows a slightly downward tendency. In brief, the MPI value of the next three years is 1.0787 which shows that the productivity index will improve gradually.
The performance results which conduct from the DEA model are considered to be the relative performances, managers can use the data as a reference to make business strategy if the analyze results showed out to be relatively efficient. The method of which this study presents can be also applied to different industries. With this approach, both new and existing companies can gain their own benefits. The newer companies can refer to others' data before they plan for the future, whereas the existing enterprises can make decision easier and more precise.
| Identifer | oai:union.ndltd.org:TW/103KUAS0041017 |
| Date | January 2015 |
| Creators | Chang, Ren-Hao, 張任豪 |
| Contributors | Wang, Chia-Nan, 王嘉男 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 94 |
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