本研究旨在探討製造業廠商區位之選擇，利用卜瓦松迴歸模型為研究之計量分析工具。以民國86至90年間各鄉鎮市（除苗栗縣外）之製造業新增廠商家數為研究之應變數，自變數則是以民國85年為研究時間點，包括產業環境、勞力因素、地區可及性與其他等四大類，共11個自變數。研究發現，當一鄉鎮市至交流道愈近、工業用地地價稅愈低、工業用地面積愈大、政府歲出愈多、設有編定工業區、產業結構愈多元、至區域市場愈近、製造業聚集程度愈高、製造業薪資愈低，愈能吸引製造業廠商投資設廠。

 本研究亦將製造業分為都市勞力型、都市技術型、地方資源型、與基礎資源型等四大類型，來探討其區位影響因素與各區位因素對不同類型製造業之影響程度。利用模型校估結果具影響力之區位因素與隨機效用極大化機率模型來對各鄉鎮市之製造業投資機率進行預測，發現以台南市最具有吸引製造業廠商新增投資之優勢，其次為新莊市，而投資機率最高之第一級區的26個鄉鎮市，與實際之新增廠商家數最多的前26名鄉鎮市中，有22個鄉鎮市相符合，表示模型之投資機率預測結果與事實頗為相符，代表模型選出之區位因素確實可能影響製造業廠商設廠之區位選擇。

　The present research investigates the location choices of manufacturing plants that began operations between 1997 and 2001. Empirical results, estimated from Poisson regression model, indicate that when a township is closer to the freeway interchange and regional market area, has lower industrial land tax and a larger pool of industrial estate, with more various industrial structures and manufacturing concentration etc., then it will have more new plants.

　The present research also classifies the manufacturing industry into four categories: urban labor, urban technology, local resources, and basic resources manufacturing industries and investigates the location factors as well as their effects on each manufacturing industry. By using the significant location factors and the random utility maximization probability model to predict the investment probabilities, Tainan city gets the largest investment probability, and Sinjhung city gets the second largest one. The prediction almost matches the reality, suggesting that the study picks up the right explanatory variables that influence the location choices of new plant births.

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