IVOD_ID |
160014 |
IVOD_URL |
https://ivod.ly.gov.tw/Play/Clip/1M/160014 |
日期 |
2025-04-09 |
會議資料.會議代碼 |
委員會-11-3-19-7 |
會議資料.會議代碼:str |
第11屆第3會期經濟委員會第7次全體委員會議 |
會議資料.屆 |
11 |
會議資料.會期 |
3 |
會議資料.會次 |
7 |
會議資料.種類 |
委員會 |
會議資料.委員會代碼[0] |
19 |
會議資料.委員會代碼:str[0] |
經濟委員會 |
會議資料.標題 |
第11屆第3會期經濟委員會第7次全體委員會議 |
影片種類 |
Clip |
開始時間 |
2025-04-09T13:22:16+08:00 |
結束時間 |
2025-04-09T13:28:51+08:00 |
影片長度 |
00:06:35 |
支援功能[0] |
ai-transcript |
video_url |
https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/984603a5a250cdce8fbc53fe30abffb4a0ce932bdb5123485ac7c33fa4103456b0ca6921d57b82b45ea18f28b6918d91.mp4/playlist.m3u8 |
委員名稱 |
葉元之 |
委員發言時間 |
13:22:16 - 13:28:51 |
會議時間 |
2025-04-09T09:00:00+08:00 |
會議名稱 |
立法院第11屆第3會期經濟委員會第7次全體委員會議(事由:邀請經濟部部長及國家發展委員會主任委員就「國際經貿情勢變化,提出協助國內傳統產業及中小企業因應之對策」進行報告,並備質詢。) |
transcript.pyannote[0].speaker |
SPEAKER_00 |
transcript.pyannote[0].start |
11.64096875 |
transcript.pyannote[0].end |
11.92784375 |
transcript.pyannote[1].speaker |
SPEAKER_00 |
transcript.pyannote[1].start |
12.07971875 |
transcript.pyannote[1].end |
12.58596875 |
transcript.pyannote[2].speaker |
SPEAKER_00 |
transcript.pyannote[2].start |
13.39596875 |
transcript.pyannote[2].end |
14.72909375 |
transcript.pyannote[3].speaker |
SPEAKER_00 |
transcript.pyannote[3].start |
15.20159375 |
transcript.pyannote[3].end |
15.72471875 |
transcript.pyannote[4].speaker |
SPEAKER_00 |
transcript.pyannote[4].start |
22.96409375 |
transcript.pyannote[4].end |
27.40221875 |
transcript.pyannote[5].speaker |
SPEAKER_00 |
transcript.pyannote[5].start |
27.97596875 |
transcript.pyannote[5].end |
30.22034375 |
transcript.pyannote[6].speaker |
SPEAKER_00 |
transcript.pyannote[6].start |
30.82784375 |
transcript.pyannote[6].end |
32.51534375 |
transcript.pyannote[7].speaker |
SPEAKER_00 |
transcript.pyannote[7].start |
32.70096875 |
transcript.pyannote[7].end |
35.43471875 |
transcript.pyannote[8].speaker |
SPEAKER_00 |
transcript.pyannote[8].start |
35.99159375 |
transcript.pyannote[8].end |
38.21909375 |
transcript.pyannote[9].speaker |
SPEAKER_01 |
transcript.pyannote[9].start |
36.12659375 |
transcript.pyannote[9].end |
36.68346875 |
transcript.pyannote[10].speaker |
SPEAKER_01 |
transcript.pyannote[10].start |
38.60721875 |
transcript.pyannote[10].end |
42.62346875 |
transcript.pyannote[11].speaker |
SPEAKER_00 |
transcript.pyannote[11].start |
42.62346875 |
transcript.pyannote[11].end |
42.70784375 |
transcript.pyannote[12].speaker |
SPEAKER_01 |
transcript.pyannote[12].start |
42.70784375 |
transcript.pyannote[12].end |
52.36034375 |
transcript.pyannote[13].speaker |
SPEAKER_00 |
transcript.pyannote[13].start |
46.23471875 |
transcript.pyannote[13].end |
46.67346875 |
transcript.pyannote[14].speaker |
SPEAKER_00 |
transcript.pyannote[14].start |
51.76971875 |
transcript.pyannote[14].end |
55.31346875 |
transcript.pyannote[15].speaker |
SPEAKER_00 |
transcript.pyannote[15].start |
55.81971875 |
transcript.pyannote[15].end |
73.11659375 |
transcript.pyannote[16].speaker |
SPEAKER_01 |
transcript.pyannote[16].start |
63.24471875 |
transcript.pyannote[16].end |
63.41346875 |
transcript.pyannote[17].speaker |
SPEAKER_01 |
transcript.pyannote[17].start |
63.66659375 |
transcript.pyannote[17].end |
63.78471875 |
transcript.pyannote[18].speaker |
SPEAKER_01 |
transcript.pyannote[18].start |
68.47596875 |
transcript.pyannote[18].end |
70.43346875 |
transcript.pyannote[19].speaker |
SPEAKER_00 |
transcript.pyannote[19].start |
73.58909375 |
transcript.pyannote[19].end |
80.76096875 |
transcript.pyannote[20].speaker |
SPEAKER_00 |
transcript.pyannote[20].start |
80.82846875 |
transcript.pyannote[20].end |
92.91096875 |
transcript.pyannote[21].speaker |
SPEAKER_01 |
transcript.pyannote[21].start |
91.57784375 |
transcript.pyannote[21].end |
100.03221875 |
transcript.pyannote[22].speaker |
SPEAKER_00 |
transcript.pyannote[22].start |
100.03221875 |
transcript.pyannote[22].end |
108.77346875 |
transcript.pyannote[23].speaker |
SPEAKER_01 |
transcript.pyannote[23].start |
101.80409375 |
transcript.pyannote[23].end |
101.85471875 |
transcript.pyannote[24].speaker |
SPEAKER_01 |
transcript.pyannote[24].start |
101.95596875 |
transcript.pyannote[24].end |
102.07409375 |
transcript.pyannote[25].speaker |
SPEAKER_00 |
transcript.pyannote[25].start |
109.17846875 |
transcript.pyannote[25].end |
110.89971875 |
transcript.pyannote[26].speaker |
SPEAKER_00 |
transcript.pyannote[26].start |
111.37221875 |
transcript.pyannote[26].end |
112.04721875 |
transcript.pyannote[27].speaker |
SPEAKER_00 |
transcript.pyannote[27].start |
112.16534375 |
transcript.pyannote[27].end |
114.86534375 |
transcript.pyannote[28].speaker |
SPEAKER_00 |
transcript.pyannote[28].start |
115.57409375 |
transcript.pyannote[28].end |
126.59346875 |
transcript.pyannote[29].speaker |
SPEAKER_01 |
transcript.pyannote[29].start |
123.15096875 |
transcript.pyannote[29].end |
123.31971875 |
transcript.pyannote[30].speaker |
SPEAKER_00 |
transcript.pyannote[30].start |
126.91409375 |
transcript.pyannote[30].end |
132.11159375 |
transcript.pyannote[31].speaker |
SPEAKER_00 |
transcript.pyannote[31].start |
132.48284375 |
transcript.pyannote[31].end |
134.32221875 |
transcript.pyannote[32].speaker |
SPEAKER_00 |
transcript.pyannote[32].start |
134.71034375 |
transcript.pyannote[32].end |
144.59909375 |
transcript.pyannote[33].speaker |
SPEAKER_00 |
transcript.pyannote[33].start |
144.75096875 |
transcript.pyannote[33].end |
150.75846875 |
transcript.pyannote[34].speaker |
SPEAKER_00 |
transcript.pyannote[34].start |
151.21409375 |
transcript.pyannote[34].end |
160.05659375 |
transcript.pyannote[35].speaker |
SPEAKER_01 |
transcript.pyannote[35].start |
157.08659375 |
transcript.pyannote[35].end |
157.57596875 |
transcript.pyannote[36].speaker |
SPEAKER_01 |
transcript.pyannote[36].start |
158.13284375 |
transcript.pyannote[36].end |
158.36909375 |
transcript.pyannote[37].speaker |
SPEAKER_01 |
transcript.pyannote[37].start |
159.76971875 |
transcript.pyannote[37].end |
183.73221875 |
transcript.pyannote[38].speaker |
SPEAKER_00 |
transcript.pyannote[38].start |
173.10096875 |
transcript.pyannote[38].end |
174.68721875 |
transcript.pyannote[39].speaker |
SPEAKER_00 |
transcript.pyannote[39].start |
176.45909375 |
transcript.pyannote[39].end |
176.57721875 |
transcript.pyannote[40].speaker |
SPEAKER_01 |
transcript.pyannote[40].start |
184.39034375 |
transcript.pyannote[40].end |
189.03096875 |
transcript.pyannote[41].speaker |
SPEAKER_00 |
transcript.pyannote[41].start |
189.03096875 |
transcript.pyannote[41].end |
196.06784375 |
transcript.pyannote[42].speaker |
SPEAKER_00 |
transcript.pyannote[42].start |
196.50659375 |
transcript.pyannote[42].end |
210.68159375 |
transcript.pyannote[43].speaker |
SPEAKER_01 |
transcript.pyannote[43].start |
196.67534375 |
transcript.pyannote[43].end |
196.96221875 |
transcript.pyannote[44].speaker |
SPEAKER_01 |
transcript.pyannote[44].start |
197.33346875 |
transcript.pyannote[44].end |
198.41346875 |
transcript.pyannote[45].speaker |
SPEAKER_01 |
transcript.pyannote[45].start |
203.23971875 |
transcript.pyannote[45].end |
203.40846875 |
transcript.pyannote[46].speaker |
SPEAKER_01 |
transcript.pyannote[46].start |
210.49596875 |
transcript.pyannote[46].end |
226.03784375 |
transcript.pyannote[47].speaker |
SPEAKER_00 |
transcript.pyannote[47].start |
211.50846875 |
transcript.pyannote[47].end |
214.32659375 |
transcript.pyannote[48].speaker |
SPEAKER_00 |
transcript.pyannote[48].start |
223.60784375 |
transcript.pyannote[48].end |
224.58659375 |
transcript.pyannote[49].speaker |
SPEAKER_00 |
transcript.pyannote[49].start |
226.03784375 |
transcript.pyannote[49].end |
230.20596875 |
transcript.pyannote[50].speaker |
SPEAKER_00 |
transcript.pyannote[50].start |
230.69534375 |
transcript.pyannote[50].end |
237.73221875 |
transcript.pyannote[51].speaker |
SPEAKER_01 |
transcript.pyannote[51].start |
234.07034375 |
transcript.pyannote[51].end |
238.25534375 |
transcript.pyannote[52].speaker |
SPEAKER_01 |
transcript.pyannote[52].start |
238.37346875 |
transcript.pyannote[52].end |
238.40721875 |
transcript.pyannote[53].speaker |
SPEAKER_00 |
transcript.pyannote[53].start |
238.40721875 |
transcript.pyannote[53].end |
246.15284375 |
transcript.pyannote[54].speaker |
SPEAKER_01 |
transcript.pyannote[54].start |
238.44096875 |
transcript.pyannote[54].end |
238.98096875 |
transcript.pyannote[55].speaker |
SPEAKER_01 |
transcript.pyannote[55].start |
239.47034375 |
transcript.pyannote[55].end |
240.02721875 |
transcript.pyannote[56].speaker |
SPEAKER_01 |
transcript.pyannote[56].start |
246.15284375 |
transcript.pyannote[56].end |
251.82284375 |
transcript.pyannote[57].speaker |
SPEAKER_00 |
transcript.pyannote[57].start |
246.67596875 |
transcript.pyannote[57].end |
255.67034375 |
transcript.pyannote[58].speaker |
SPEAKER_00 |
transcript.pyannote[58].start |
256.19346875 |
transcript.pyannote[58].end |
259.46721875 |
transcript.pyannote[59].speaker |
SPEAKER_00 |
transcript.pyannote[59].start |
259.78784375 |
transcript.pyannote[59].end |
264.85034375 |
transcript.pyannote[60].speaker |
SPEAKER_01 |
transcript.pyannote[60].start |
263.98971875 |
transcript.pyannote[60].end |
268.47846875 |
transcript.pyannote[61].speaker |
SPEAKER_01 |
transcript.pyannote[61].start |
268.66409375 |
transcript.pyannote[61].end |
276.84846875 |
transcript.pyannote[62].speaker |
SPEAKER_01 |
transcript.pyannote[62].start |
277.08471875 |
transcript.pyannote[62].end |
285.38721875 |
transcript.pyannote[63].speaker |
SPEAKER_01 |
transcript.pyannote[63].start |
285.65721875 |
transcript.pyannote[63].end |
292.42409375 |
transcript.pyannote[64].speaker |
SPEAKER_00 |
transcript.pyannote[64].start |
291.61409375 |
transcript.pyannote[64].end |
292.05284375 |
transcript.pyannote[65].speaker |
SPEAKER_01 |
transcript.pyannote[65].start |
292.82909375 |
transcript.pyannote[65].end |
294.02721875 |
transcript.pyannote[66].speaker |
SPEAKER_00 |
transcript.pyannote[66].start |
294.02721875 |
transcript.pyannote[66].end |
294.04409375 |
transcript.pyannote[67].speaker |
SPEAKER_01 |
transcript.pyannote[67].start |
294.04409375 |
transcript.pyannote[67].end |
294.09471875 |
transcript.pyannote[68].speaker |
SPEAKER_00 |
transcript.pyannote[68].start |
294.09471875 |
transcript.pyannote[68].end |
295.52909375 |
transcript.pyannote[69].speaker |
SPEAKER_01 |
transcript.pyannote[69].start |
295.52909375 |
transcript.pyannote[69].end |
295.56284375 |
transcript.pyannote[70].speaker |
SPEAKER_01 |
transcript.pyannote[70].start |
295.73159375 |
transcript.pyannote[70].end |
306.83534375 |
transcript.pyannote[71].speaker |
SPEAKER_01 |
transcript.pyannote[71].start |
307.39221875 |
transcript.pyannote[71].end |
314.14221875 |
transcript.pyannote[72].speaker |
SPEAKER_01 |
transcript.pyannote[72].start |
314.32784375 |
transcript.pyannote[72].end |
331.21971875 |
transcript.pyannote[73].speaker |
SPEAKER_01 |
transcript.pyannote[73].start |
331.48971875 |
transcript.pyannote[73].end |
331.52346875 |
transcript.pyannote[74].speaker |
SPEAKER_00 |
transcript.pyannote[74].start |
331.52346875 |
transcript.pyannote[74].end |
333.41346875 |
transcript.pyannote[75].speaker |
SPEAKER_00 |
transcript.pyannote[75].start |
333.97034375 |
transcript.pyannote[75].end |
338.67846875 |
transcript.pyannote[76].speaker |
SPEAKER_00 |
transcript.pyannote[76].start |
339.16784375 |
transcript.pyannote[76].end |
340.24784375 |
transcript.pyannote[77].speaker |
SPEAKER_00 |
transcript.pyannote[77].start |
340.88909375 |
transcript.pyannote[77].end |
344.60159375 |
transcript.pyannote[78].speaker |
SPEAKER_00 |
transcript.pyannote[78].start |
345.05721875 |
transcript.pyannote[78].end |
348.31409375 |
transcript.pyannote[79].speaker |
SPEAKER_00 |
transcript.pyannote[79].start |
348.75284375 |
transcript.pyannote[79].end |
351.38534375 |
transcript.pyannote[80].speaker |
SPEAKER_00 |
transcript.pyannote[80].start |
351.62159375 |
transcript.pyannote[80].end |
353.12346875 |
transcript.pyannote[81].speaker |
SPEAKER_01 |
transcript.pyannote[81].start |
351.77346875 |
transcript.pyannote[81].end |
352.53284375 |
transcript.pyannote[82].speaker |
SPEAKER_01 |
transcript.pyannote[82].start |
352.92096875 |
transcript.pyannote[82].end |
353.10659375 |
transcript.pyannote[83].speaker |
SPEAKER_01 |
transcript.pyannote[83].start |
353.12346875 |
transcript.pyannote[83].end |
355.03034375 |
transcript.pyannote[84].speaker |
SPEAKER_00 |
transcript.pyannote[84].start |
355.03034375 |
transcript.pyannote[84].end |
355.13159375 |
transcript.pyannote[85].speaker |
SPEAKER_01 |
transcript.pyannote[85].start |
355.13159375 |
transcript.pyannote[85].end |
355.23284375 |
transcript.pyannote[86].speaker |
SPEAKER_01 |
transcript.pyannote[86].start |
355.46909375 |
transcript.pyannote[86].end |
355.48596875 |
transcript.pyannote[87].speaker |
SPEAKER_00 |
transcript.pyannote[87].start |
355.48596875 |
transcript.pyannote[87].end |
357.00471875 |
transcript.pyannote[88].speaker |
SPEAKER_00 |
transcript.pyannote[88].start |
357.56159375 |
transcript.pyannote[88].end |
357.96659375 |
transcript.pyannote[89].speaker |
SPEAKER_01 |
transcript.pyannote[89].start |
357.96659375 |
transcript.pyannote[89].end |
361.71284375 |
transcript.pyannote[90].speaker |
SPEAKER_00 |
transcript.pyannote[90].start |
359.48534375 |
transcript.pyannote[90].end |
361.74659375 |
transcript.pyannote[91].speaker |
SPEAKER_01 |
transcript.pyannote[91].start |
361.74659375 |
transcript.pyannote[91].end |
363.56909375 |
transcript.pyannote[92].speaker |
SPEAKER_00 |
transcript.pyannote[92].start |
362.53971875 |
transcript.pyannote[92].end |
364.96971875 |
transcript.pyannote[93].speaker |
SPEAKER_01 |
transcript.pyannote[93].start |
364.96971875 |
transcript.pyannote[93].end |
367.63596875 |
transcript.pyannote[94].speaker |
SPEAKER_00 |
transcript.pyannote[94].start |
365.18909375 |
transcript.pyannote[94].end |
365.96534375 |
transcript.pyannote[95].speaker |
SPEAKER_01 |
transcript.pyannote[95].start |
367.80471875 |
transcript.pyannote[95].end |
371.17971875 |
transcript.pyannote[96].speaker |
SPEAKER_00 |
transcript.pyannote[96].start |
367.82159375 |
transcript.pyannote[96].end |
368.44596875 |
transcript.pyannote[97].speaker |
SPEAKER_01 |
transcript.pyannote[97].start |
371.36534375 |
transcript.pyannote[97].end |
377.74409375 |
transcript.pyannote[98].speaker |
SPEAKER_00 |
transcript.pyannote[98].start |
377.74409375 |
transcript.pyannote[98].end |
381.69284375 |
transcript.pyannote[99].speaker |
SPEAKER_00 |
transcript.pyannote[99].start |
381.99659375 |
transcript.pyannote[99].end |
388.30784375 |
transcript.pyannote[100].speaker |
SPEAKER_01 |
transcript.pyannote[100].start |
387.27846875 |
transcript.pyannote[100].end |
392.34096875 |
transcript.pyannote[101].speaker |
SPEAKER_00 |
transcript.pyannote[101].start |
390.50159375 |
transcript.pyannote[101].end |
390.90659375 |
transcript.pyannote[102].speaker |
SPEAKER_00 |
transcript.pyannote[102].start |
392.34096875 |
transcript.pyannote[102].end |
392.96534375 |
transcript.pyannote[103].speaker |
SPEAKER_01 |
transcript.pyannote[103].start |
393.03284375 |
transcript.pyannote[103].end |
393.75846875 |
transcript.pyannote[104].speaker |
SPEAKER_01 |
transcript.pyannote[104].start |
394.18034375 |
transcript.pyannote[104].end |
394.60221875 |
transcript.whisperx[0].start |
12.13 |
transcript.whisperx[0].end |
37.159 |
transcript.whisperx[0].text |
麻煩請經濟部長郭部長委員好部長好請問一下我們現在經濟部或行政院有沒有盤點出目前因為川普關稅政策導致受影響的產值全國的產值跟勞工的人數目前有盤點出這個數字出來嗎 |
transcript.whisperx[1].start |
38.786 |
transcript.whisperx[1].end |
54.838 |
transcript.whisperx[1].text |
報告委員我們現在因為今天12點以後才是開始適用32%的稅率那我們現在不斷的在update這些data因為這個事情其實也不是一個突發事件 |
transcript.whisperx[2].start |
55.859 |
transcript.whisperx[2].end |
72.337 |
transcript.whisperx[2].text |
就從去年11月我們之前在經濟委員會也都問過類似話題那時候經濟部的回應都是說都有在盤點了啦都開過座談會了啦都是說有做了很多事情那目前你掌握可能受到影響的產值跟高空我可以跟委員報告大概影響是9千億啦12萬人 |
transcript.whisperx[3].start |
73.658 |
transcript.whisperx[3].end |
92.583 |
transcript.whisperx[3].text |
影響9000億跟12萬人那因為現在週五以後這個關稅就要實施了嘛那現在目前之前很多廠商說他們的貨櫃都已經在路上了啦還有一些廠商在想說那接下來是不是要繼續生產所以其實政府明確的政策對他們來說非常重要那目前 |
transcript.whisperx[4].start |
93.343 |
transcript.whisperx[4].end |
114.597 |
transcript.whisperx[4].text |
委員剛才在講的這個說在路上的部分其實他5月27號以前進到美國他的稅率跟過去是一樣的那因為我們現在行政院所提出來是880億的一個補助的方案那這個方案大概會持續多久那因為主要就是說我覺得很多廠商想要知道 |
transcript.whisperx[5].start |
115.598 |
transcript.whisperx[5].end |
131.726 |
transcript.whisperx[5].text |
廠商知道說第一個他們可以得到相關的比如說補助啊或者優惠嘛那政府會利用這個期間會均跟美國談判嘛那預計來說大概期限是到什麼時候要讓廠商做一點準備啦因為像比如說我是來自於新北市我們新北市兩萬家工廠 |
transcript.whisperx[6].start |
132.546 |
transcript.whisperx[6].end |
151.587 |
transcript.whisperx[6].text |
大概佔了全國的五分之一啦那新北市政府他也有盤點出相關的產業出來嘛比如說在新北市金屬跟製品就佔了25%機械12%所以其實對新北市的廠商來說影響很大我覺得現在政府的政策越明確對他們來說他們的規劃 |
transcript.whisperx[7].start |
153.689 |
transcript.whisperx[7].end |
170.019 |
transcript.whisperx[7].text |
可以更精準就不會在這過程當中不知道怎麼辦所以部長可不可以很明確的來做一個說明謝謝委員我想我們輸出到美國的或造成影響的產業其實是只有侷限於在一些比較小的部分 |
transcript.whisperx[8].start |
170.979 |
transcript.whisperx[8].end |
195.854 |
transcript.whisperx[8].text |
那我們輸出美國就是一個小的部分是什麼意思?出差的比較有優勢的產品,譬如說伺服器,譬如說半導體這個是美國需要的產品,它沒有替代性的那這個部分他不擔心32%的稅對他有什麼影響怎麼會不擔心?因為他們是做,譬如說你剛剛講的部分嘛我的了解是有一些很多是做代工的嘛 |
transcript.whisperx[9].start |
196.99 |
transcript.whisperx[9].end |
214.802 |
transcript.whisperx[9].text |
那代工的話現在衍生出一個問題就是因為代工就品牌商委託他們代工嘛那32%應該是品牌商吸收還是代工廠吸收品牌商可是實際上我的了解啦很多廠商其實很擔心沒有那回事品牌商會壓縮代工廠的利潤我們都盤點過盤點每一個伺服器做代工的廠商我們都一一盤點對他們來講他們當然每一廠在討論啦 |
transcript.whisperx[10].start |
226.89 |
transcript.whisperx[10].end |
235.395 |
transcript.whisperx[10].text |
我聽到就是說有的原廠就會去跟代工廠去談嘛現在就加了32%的成本啊代工廠的利潤只有10%代工廠的利潤只有10% |
transcript.whisperx[11].start |
256.349 |
transcript.whisperx[11].end |
269.019 |
transcript.whisperx[11].text |
這些廠商現在要做什麼然後政府的比如補助公開透明的步驟或期限很明確告訴大家都有我們的方法就是從這個從簡從速從寬這三個原則啊來給他們舒緩給他們補助這是第一點第二點呢 |
transcript.whisperx[12].start |
277.225 |
transcript.whisperx[12].end |
293.685 |
transcript.whisperx[12].text |
我們對這些廠商他原有的貸款我們也不會雨天收傘我們讓他延後最起碼6個月那我們現在推出的這些措施大概原則上是4年有效4年有效對你那個80還81是怎麼預估出來的 |
transcript.whisperx[13].start |
296.609 |
transcript.whisperx[13].end |
305.594 |
transcript.whisperx[13].text |
880億是根據過去我們在第一個時間裡面所推論的可能會影響說我們現在的談判不是去談32%接受 |
transcript.whisperx[14].start |
307.515 |
transcript.whisperx[14].end |
330.633 |
transcript.whisperx[14].text |
是談說30%以下美國會對我們課多少實際課多少所以那個X是我們用那個X來假設說如果在那個階段我們假設我可以談到10%的話大概這個881是夠的如果高於這個談到高於10%那我當然就要再加碼反正你會盡量加碼到夠啦 |
transcript.whisperx[15].start |
335.643 |
transcript.whisperx[15].end |
354.861 |
transcript.whisperx[15].text |
對最後一個問題因為現在其實各縣市政府都有盤點出在各縣市裡面可能會影響影響到的中小企業而且中小企業都有一些回饋給縣市政府我不知道我們經營部有沒有去跟這些各縣市政府對接去了解一下他們需求我們會跟各縣市的工業會市政府 |
transcript.whisperx[16].start |
357.603 |
transcript.whisperx[16].end |
386.912 |
transcript.whisperx[16].text |
跟縣市政府縣市政府的工業會有嗎 什麼已經對接了嗎有對接已經對接了嗎那會召開一個比較擴大會做談會我們從過去的一直在做了所以經濟部本身有66個工業區我們都透過我們自己的這個單位跟在我們區外的單位整合來談好 我就說之前啦我說因為他們這兩天也都很密集在跟中小企業在開會啦希望部長中央的角度也去了解一下各縣市政府的需求 |
transcript.whisperx[17].start |
387.472 |
transcript.whisperx[17].end |
391.561 |
transcript.whisperx[17].text |
我們都是中央合作啦中央與地方合作啦全力來度過這個難關好 謝謝謝謝委員好 |