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題名:探討另類的國際貿易-僱用境外漁工的成本與效益
作者:王繼璽
作者(外文):WANG, CHI-HSI
校院名稱:中原大學
系所名稱:商學博士學位學程
指導教授:李正文
學位類別:博士
出版日期:2022
主題關鍵詞:境外雇用漁工國際漁業商業貿易遠洋漁船另類雇用型態失聯漁工Harris-Todaro模型經濟自變數多元迴歸分析風險分類two-tiered systemdistant water fleetsMigrant Fishermeninternational fishery tradeLost ImmigrantsHarris-Todaro modeleconomic variablesrisk groups
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本研究在探討於南方澳漁港的一種特殊的國際貿方式,以印尼籍為主的境外僱用漁工跨越了國境在台灣南方澳的部分遠洋漁船上,以自身的勞力換取報酬,而台灣籍船東或雇主則因為有了這群離鄉背景的漁工的付出,而獲得了各式各樣珍貴有價值的魚貨。再者,境外僱用漁工把薪資匯回其母國支持家庭生計且也增加了該國外匯收入。雖然境外僱用漁工在國際漁業商業貿易中扮演了重要角色,但不同於其他在台灣境內雇用並且有申請居留證(ARC)並比照本國籍勞工待遇的外籍移工,這群在南方澳工作但無台灣居留證與無勞健保,且不適用相關勞動法律的境外僱用漁工,以遠洋漁船另類雇用型態的方式,在經主管機關同意後,由雇主委託船務代理行以申辦臨時停留的方式進入方澳,原則上只能短期停留進行卸貨整補工作。然而少部分境外僱用漁工漏跳船變成失聯漁(移)工,在眾多可能原因之中,薪資(在本實驗為可支配所得)與期待報酬是其中很重要的一項。本研究借用Harris-Todaro Model of Migration移民理論模型的經濟因素來解釋漁工漏跳船行為,並與統計回歸分析做比較對照,在各結果的交叉比對之後,兩者似乎有相似的趨勢, 即當薪資(可支配所得)高於某特定值時,境外僱用漁工漏跳船人數即大幅下降。當Harris-Todaro Model of Migration移民理論模型可支持本研究第一步驟的OLS簡單線性回歸結果時,表示研究即可再進行下一步驟做經濟自變數多元回歸檢驗與建立風險預測模型。
可影響境外僱用漁工漏跳船的經濟變數因子有很多;例如雇主/船長的影響因素有: 進出港次數,每次停靠天數,出海航程距離, 每艘船的外籍漁工人數等等; 而境外僱用漁工本身的因數為年紀,經驗,及是否在台灣工作過等等。其中薪資(可支配所得)資訊應該是最難取得的,對於雇主與境外漁工來說,這個自變數對彼兩方的任何決定都有非常顯著的影響。而資料收集是個非常漫長與辛苦的過程,通常需先以非正式的方式開始,例如閒聊等等再慢慢帶入主題後,然後再對相關的受訪者例如船務代理行、報關行、雇主/船長、漁業相關組織、人力仲介、通譯人員、與印尼境外僱用漁工等等進行訪談,他們以不記名的方式提供了許多寶貴的資料,讓此研究順利進行。
當在各經濟因子的資料蒐集足夠之後,先對每一自變數與漏跳船漁工人數的關聯性做單一線性迴歸分析,在剔除配適度與顯著性不足的經濟因子後,再做多元線性回歸分析,但因為有共線性的因素存在,有些自變數會互相影響,所以這測試過程必須一直重複增減因子,直到最佳的迴歸公式出現。這多元迴歸模型是用來預測在各經濟因素在某特定排列組合下,可能的漏跳船漁工人數。
為了讓本研究的結果能產生實務貢獻,亦即對於那些還在船上工作但仍未漏跳船的境外漁工,降低他們在未來的漏跳船意願,且同時也能讓漁船生產力增加與提升船主與漁工收益。因為對於那些已經漏跳船的境外漁工來說,已發生就已發生了,覆水難收。所以本研究利用多元回歸分析的結果,另外再建立了一個漏跳船風險等級的分類,從嚴重到輕微風險共分4等級。第一級為漏跳船高風險的境外僱用漁工,需要立雇主/船長/仲介立刻的即關懷與輔導。而第4級為最輕微風險,只需一般性的照顧。即期待以適當的風險分類降低境外漁工漏跳船率。
雖然經濟因素對於境外漁工的漏跳船扮演著重要角色,但其他像是法規,社會,心理,管理模式等層面也皆有顯著性的影響。而本研究僅做單純的各經濟因素間關聯性分析,不做任何法規及社會面的評論與道德價值的判斷。本研究結果在實務與理論上皆不適宜被類推或引用到非單純經濟分析。因本研究的變數中包含了許多漁工本身的質與量因素,例如本研究所使用的可支配所得就已先扣除了境外僱用漁工私人的基本生活費用(豐儉由人),而非單純工資因素。故若不適當的引用本研究數據或斷章取義會扭曲該分析過程,從而做出不正確或帶偏見的判斷。
最後,因為本研究的各自變數與依變數其實是一直在恆常性的變動中,不同時期的人事時地物,會對研究產生不同的結果,故未來會持續尋求之前資料提供者的合作,繼續改良回歸方程式與增減相關經濟因子,以期持續降低境外漁工的漏跳船風險。
The two-tiered system is currently adopted in Taiwanese fishery industry, and the distance water fleets (DWF) are allowed to recruit those overseas hired migrant fishermen (Migrant Fishermen) who are separated from the regular foreign workers. Those Migrant Fishermen play very important roles to economic contribution at Nanfangao fishing port in Taiwan, and among those migrant fishermen the majorities are Indonesians who are the targeted groups in this research. Those Migrant Fishermen are part of international fishery business due to the labor movement and wage remittance across the national borders. Their remittance is vital financial support to those Migrant Fishermen’s families and to the foreign exchange deposit of their home countries. However, some of Migrant Fishermen who become the undocumented migrant workers or the lost contact immigrants (Lost Immigrants) generate social and public issues in their host communities. Hopefully, this Ph.D. research may deliver some possible solutions to reduce the rate of those issues.
In this research, Harris-Todaro Model of Migration theory is adopted and modified to study how the wage (disposable income in the research) affects the rate of Lost Immigrants. Then, the Harris-Todaro study data is compared with the OLS regression analysis. As a result, both seem with similar outcomes that the rate of lost immigrant reduces significantly once the wages of Migrant Fishermen is beyond a certain amount. Next, other related economic variables will be collected to build multivariate regression model for more precise forecast. Based on the forecast result, it might be possible to establish a risk evaluation model for segmenting every individual Migrant Fisherman. Depending on their risky level, those Migrant Fishermen are categorized into four risk groups from level one to level four. The level one is the lowest risk group, and the level four is the highest risk group. Therefore, the employers/captains can pay more attention with hearty care to those higher risky Migrant Fishermen, and in return the rate of Lost Immigrants might have opportunity to reduce.
The economic variables are investigated from two aspects. The one aspect is variables related to employer/captain factors such as how often the fishing ships anchor at Nanfangao, how long the boats stay at port, how far the ships sail, and how many migrant fishermen on vessels and so on. The other aspect is variables belonging to migrant fisherman factors like ages, experience and so on. Among those variables, probably the wage (the disposable income which has been deducted from all fees and necessary personal expenses, various from person to person) is the most important factor, yet it is probably the most difficult data to collect. In order to get accurate investigation of those economic variables, the survey has been anonymously conducted to many stakeholders who are such as shipping agents/brokers, employers/captains, some related fishery organizations, migrant fishermen etc.
Although the economic variables play a very important role to the rate between Migrant Fishermen and Lost Immigrants, yet other social, regulate, moral, and psychological aspects etc. are also significantly dominates the change of the rate. However, those uneconomic factors are not input in the research. This study is keeping purely in economic correlation between variable without any prejudice or judgment from other uneconomic factors. So to speak, the findings in this research cannot and should not be applied or quoted to all other uneconomic reference. Otherwise, it may twist the results with unwanted bias and tendentious variables, and also shake the mutual-trust foundation with related stakeholders in this research.
The variables in this Ph.D. research are on constant change. The results might be various when the data is collected from different people, time, place etc. In the future, it may be necessary to remove old variables and add new ones to the formula in this research. This might be further reducing the rate of Lost Immigrants by continuously improving the model

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