越洋航商在兩岸三地擇港因素與港口競爭力之評估

Abstract

近年以來，東亞迄北美地區的貨櫃流量為全球最高，貨櫃航商在此間的船隊運能投入亦持續增長。台灣海峽兩岸三地之上海、高雄、鹽田與香港四大港口，同為目前貨櫃航商配置越洋主航線之重要樞紐港口，其在貨源分佈與航線配置上具有重疊性，競爭情勢甚為顯著。 本文主要內容共分為三大部分，第一部分首先由貨櫃航商之觀點，對於影響航商在兩岸三地間，選擇樞紐港口的重要因素，進行探究，並分析這些影響因素與樞紐港口可提供誘因之間的因果關係。經綜合相關文獻並參酌航商在兩岸三地四大港口營運上的特殊性，進行問卷設計調查，並以因素分析方法，篩選出影響航商之港口選擇以及吸引航商誘因的各項因素。繼而應用結構方程模式(SEM)，探討這些重要影響因素(港口內部條件與外部環境、航商之營運策略配合因素)與樞紐港口營運誘因(如增加營收、節省成本等)之關係。結果顯示：貨櫃航商在樞紐港口之營運策略配合因素，對於航商整體營運成本之節省，具有正向之影響。且該因素與樞紐港口外部環境間，具有顯著之相關性。此外，樞紐港口外部環境愈佳，愈有助於貨櫃航商擴大其市場範圍與增加營收。 為了分析與評估四大樞紐港口的競爭優勢與整體競爭力，本文第二部分則綜合上述三大類影響因素，進行第二次問卷設計與調查，再以灰關聯分析法(GRA)評估四大港口的各項競爭優勢，並分別採用階層分析法(AHP)、熵值法(Entropy)及折衷權重法(Compromised Weighting Method)求取各類因素的權重值，進行港口整體競爭力的評比。結果發現：樞紐港口內部條件以鹽田港具有最佳優勢，外部環境與航商營運策略的配合因素，則以上海港最佳。整體競爭力的評比結果，亦均以上海港最佳。 此外，為了解營運實務上，各類不同的營運考量因素對於港口競爭力的影響，於第三部分首先應用灰色理論之GM(1,1)方法對各大樞紐港口進行三種情境之總櫃量預測，再應用灰關聯分析得出不同因素的權重值。以保守之預測結果為例：未來五年內之總櫃量成長以上海港最高，鹽田港將會超越香港，而高雄港之總櫃量將會達到1千萬TEU以上，與我國交通部之預測值極為接近。由於櫃量多寡係港口之貨源因素所呈現的現象，亦為航商擇港之重要考量因素。因此，本文以過去迄未來之櫃量增長率平均值，代表港口外部環境之貨源因素時，亦得出該一指標對於影響樞紐港口競爭力的權重值最高的結果，而港口內部條件之基礎設施指標，權重值較弱。顯示樞紐港口原本就需擁有設施完善的內部條件，才能符合貨櫃航商配置越洋航線之最基本要求。 綜論之，影響樞紐港口競爭力最重要的因素，或航商選擇樞紐港口最重視的因素，以港口外部環境居首，其次依序為營運策略配合因素及港口內部條件。本文並綜合研究結果，研提有助於提升我國高雄港整體競爭力的建議，以供參考。

In recent years, the global ocean container transportation markets between East Asia and North America have maintained the highest market shares, and almost all major container carriers have continuously increased their fleet capacities in this district. Currently, many container carriers select Shanghai, Kaohsiung, Yantian and Hongkong as hub ports to deploy trunk routes. Due to the overlap in cargo-sources and route-deployment, competitions do obviously exist among those ports. This dissertation includes three parts. Firstly, from the viewpoints of container carriers, to investigate major factors affecting hub ports selection, as well as to explore the causal relationships among these factors and the operational incentives to the carriers across Taiwan-strait. A questionnaire survey was conducted on the basis of extensive literature review, and the characteristics of shipping operation in those hub ports. Factors analysis was then used to identify major influential factors of port selection and operational incentives to the liners. Moreover, a Structural Equations Modeling (SEM) approach was used to examine the relationships among influential factors of port selection; including internal and external factors of port, and operational strategy of container carriers, and the operational incentives, such as expanding the market, increasing revenue, cost-saving of liners, etc.. Results indicate that operational strategy of container carriers has direct impacts on cost-saving of liners and is positively correlated with the external factors of hub-port. In addition, external factors have positive impacts on expanding market and increasing revenue of container carriers. In the second part, a second questionnaire survey was designed and conducted based on the three categories of major influential factors identified above to analyze and evaluate relative competitive advantages and port competitiveness among those hub ports. Grey Relational Analysis (GRA) was used to evaluate the relative port competitive advantages based on those factors. Moreover, Analytic Hierarchy Process (AHP), Entropy and Compromised Weighting Method were utilized to obtain the weights of the three major factors for evaluating and comparing the competitiveness among those hub ports. Results show that in terms of internal factors, Yantian possess the best competitive advantage, whereas Shanghai possess best competitive advantages on both external factors and operational strategy of container carriers, which is also ranked as the port with the highest competitiveness. Furthermore, in order to explore the impact of influence factors on hub port competitiveness from the operational viewpoints of carriers, the third part of this dissertation adopts the GM(1,1) of Grey Theory to predict future throughput of the four hub ports under three different scenarios, and the GRA method to estimate weights of influential factors on port competitiveness. The results of conservative scenarios reveal that the growth of container cargos in 2010 would be the highest in Shanghai, and Yantain would handle more container cargos than Hongkong. In the meantime, there would be about 10 million TEU in Kaohsiung which approximated to the figure the Ministry of Communications in Taiwan anticipated. The container volume of ports is an indicator of cargo-source in the hinterland, and an attracting factor for container carriers on port-selection and route-deployment. So, the average growth rate of past and future volume is taken as an indicator of cargo-source. Results indicate that cargo-source is the most influential factor with the highest weight while the infrastructure of port internal factors is less significant on hub-port competitiveness with the lowest weight for container carriers. It shows that good internal factors are the basic required conditions for the selection of hub-ports. In conclusion, the external factors of hub ports are the most significant influential elements on port competitiveness and carriers’ selection, followed by operational strategies and internal factors. Finally, suggestions are proposed and discussed for the enhancement of the competitiveness in Kaohsiung.