臺灣博碩士論文加值系統

本研究的目的為使用Lotka-Volterra Model分析公開營收數據，探討台灣的物流產業與電商產業之間的互動情形。對比原始Lotka-Volterra Model，本研究透過Hodrick-Prescott Filter去除季節波動的影響，以趨勢信號進行營收預測以及產業競爭分析。預測方面，本研究方法的預測能力優於原始Lotka-Volterra Model，預測結果顯示未來物流產業與電商產業會呈現共存的均衡狀態，營收部分也還有許多成長空間。產業競爭分析方面，本研究的結果為物流產業與電商產業皆有良好的自體成長，其中各產業對於物流的需求提升，使得物流產業有較大的成長。但兩產業之中皆有內在競爭（對營收有負面影響），電商產業內在競爭較小於物流產業，可能原因是電商是新興產業因此尚有許多需求未被滿足，所以。兩產業之間存有互利共生的互動關係，透過有效的合作，物流產業與電商產業能夠帶動彼此的成長，促進兩產業共同發展。

The research applies the Lotka-Volterra model based on the revenue trend data to explore the interaction relationship between Taiwan's logistics industry and e-commerce industry. The revenue trend data is obtained by removing the seasonal fluctuation signal from raw revenue data. Experiment results reveal that the Lotka-Volterra model based on trend revenue data significantly outperforms that based on raw revenue data in terms of forecasting accuracy. Further experiments reveal the following findings. First, logistics industry and e-commerce industry both have a positive self-growth, which implies that the two industries are both promising industries. Second, the two industries both have internal competition, which impose a negative impact to their revenues. Third, the interaction relationship between the two industries is mutualism, which implies that the two industries help each other in revenue growth. The demand of e-commerce requires physical shipping, which in turn drives the demand of logistics. The higher the demand of logistics implies the additional installation of logistics capacity, which tends to reduce the shipping time and in turn drives the demand of e-commerce.

中文摘要 i
ABSTRACT ii
誌 謝 iii
目錄 iv
表目錄 vi
圖目錄 1
一、 緒論 2
1.1 研究背景與動機 2
1.2 研究問題 4
1.3 研究目的與方法 4
1.4 章節安排 5
二、 文獻回顧 6
2.1 LV-Model 6
2.2 單物種預測 7
2.3 零售產業預測文獻 7
2.4 LV-Model多物種預測 9
2.5 本論文特色 11
三、 研究方法 12
3.1 Basic LV-Model 12
3.2 Filtered LV-Model 13
3.2.1 Step 1: 濾波 14
3.2.2 Step 2: 趨勢信號預測 15
3.2.3 Step 3: 季節信號預測 17
3.2.4 Step 4: 各產業預測營收 17
3.3 預測準確度檢測 18
3.4 均衡分析 19
四、 實驗結果 22
4.1 原始數據 22
4.2 兩模型比較結果 24
4.2.1 參數估計值結果 24
4.2.2 預測準確度比較 26
4.2.3 小結 28
4.3 物種競爭關係分析(ai、bi、ci) 29
4.4 產業成長分析 32
4.4.1 均衡分析結果 32
4.4.2 物流產業-成長趨勢分析 34
4.4.3 電商產業-成長趨勢分析 35
五、 結論 37
5.1 研究貢獻 37
5.2 未來研究 38
參考文獻 40

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