台資銀行在中國大陸發展競合之動態分析

Abstract

本研究首次以Lotka-Volterra模型探討台灣銀行業赴大陸市場的發展策略，比較官股和非官股銀行赴大陸投資之間的動態競合關係。官股銀行定義為曾經100％為台灣政府持股的銀行，而其他銀行在本論文則定義為非官股銀行。本研究運用台灣銀行赴大陸投資的設立分行的每月營收與每月淨利驗證官股和非官股銀行之間是否為純粹競爭或獵食者與獵物的關係，接著，本研究預測官股和非官股銀行的大陸分行未來關係傾向是否存在著均衡關係，最後，本研究進行精確度分析，比較本研究所提出的Lotka-Volterra模型與Bass模型何者較能精確預測台資銀行赴中國大陸投資。 本研究結果發現官股銀行和非官股銀行在中國大陸市場存在片利共生的競合關係，兩者之間呈現官股銀行對非官股銀行有利、非官股銀行對官股銀行沒有影響的情形。兩岸金融業的往來與法規的限制有相當密切的關聯，業務經營範圍與兩岸監管機構的談判進度息息相關，官股銀行對相關訊息的掌握度較高。因此導致官股銀行成為類似Myerson (1991)先行者的角色，幫助非官股銀行在大陸發展的現象，而非官股銀行對官股銀行的發展無明顯的影響。在模型預測能力上，Lotka-Volterra模型在官股和非官股銀行大陸分行的資料樣本上，實際值曲線與估計值曲線都較Bass模型有更好的預測表現，和更佳的配適效果。其背後原因是由於Bass模型僅就個別銀行做擴散成長預估分析，Lotka- Volterra模型除了考量個別銀行的擴散成長預估分析之外，更考慮了不同銀行之間的競爭合作關係，因此準確度較高。Lotka-Volterra模型較佳的預測和配適能力代表此模型可用來解釋官股銀行與非官股銀行大陸分行的競合關係。本研究建構出一個有效、準確的模型分析和預測方法，提供我國銀行業者前進大陸和政府制定相關金融規範時的參考。

This study is the first time to use the Lotka-Volterra competition model to analyze the business strategic of Taiwanese bank in China market. Compare the dynamic competitive model between government-owned-banks and non-government-owned-banks’ investment in China. Use monthly revenue and net income from the branch of Taiwanese Banks in China to verify the relation between government-owned-banks and non-owned-banks is Pure competition or Predator-prey. This study predicts the existence of equilibrium relation between government-owned-banks and non-government-owned-banks’ branch in China. And analyze the accuracy of Lotka-Volterra model and Bass model in this study to understand which one can accurately predict the investment of Taiwanese banks in mainland China. The result of this study found that the relation between government-owned-bank and non-government-owned-bank is Commensalism in China market. Government-owned-banks benefits non-government-owned-banks and non-government-owned-banks has no effect on the government-owned-banks circumstances. The financial industry for Taiwan and China are closely related to the restrictions of law. The business scope depends on the progress of negotiations between financial regulatory authorities. Government-owned-banks are more familiar with this information. Thus leading to help non-government-owned-banks’ business in China as pioneer (first mover) (Myerson, R., 1991) and non-government bank has no significant influence on the growth of government bank. On the predictive ability of the model, Lotka-Volterra model shows the better performance than Bass model to predict the business, effectiveness and better fit on the data samples. The reason behind this is that Lotka-Volterra model considers the competitive and cooperative relations between different banks, but Bass model does not. Lotka-Volterra model’s better predictive ability can explain the dynamic competitive model between government-owned bank and non-government-owned bank’s branch in China. This study constructed efficient methods for our government when developing the related financial norms and provided a reference to Taiwanese banks when get into the mainland China's banking industry.