AAL stock forecast的問題，透過圖書和論文來找解法和答案更準確安心。 我們找到下列各種有用的問答集和懶人包

供應鏈在疫情下的個案分析-以ZARA, 美國塞港與美國航空為例

為了解決AAL stock forecast的問題，作者周彥宏 這樣論述：

Currently, one of the most important challenges in 2022 that humans confront on a daily basis is COVID-19. It affects every aspects of our daily life. Supply chain is one of the most serious issues facing not only manufacturers but also customers. From manufacturers perspectives, all industries inc

luding apparel and airline encounter labour, material, and logistics shortage, resulting in supply disruptions and not meeting demand level. From customers perspectives, multination locked down changed consumers’ behaviour - moving from physical channel to online channel. The situation forced retai

l and apparel giants to do digitalization. This study includes three supply chain cases during COVID-19. The first case looks at what supply chain challenges that ZARA faced during pandemic period and what they should do for their US supply chain and upcoming Gen Zers. The second case describes why

US ports especially Los Angeles port faced serious congestion and what initiatives did US government do to reduce the queueing time for vessels. The last case looks what factors affect airline industry during Covid-19 period and what kind of preparation American Airline is doing post Covid-19 time.

庫存管理實作及分析預測之研究

為了解決AAL stock forecast的問題，作者余梓賓 這樣論述：

進貨或存貨管理系統(SMS)提供幾個主要工作執行：資產存貨、緩衝/安全儲備控制、補充、儲存檢索，要求預測和領先優異的存貨預測。例如，大多的原始器材製造者(OEMs)喜好賺取更多的回扣和傭金，然後才給予較大的訂單。在此同時，營運現金在緩慢的存貨去化下經常造成缺口，而且將聯結機會成本(選擇做一產品而放棄做另一產品)和存貨風險來衝擊他們。 如何提供在OEMs庫存管理下的高質量又準確的預測變得越來越重要。在本文，我們將提出真實的管理案件(超過4000個紀錄/月)作為需求預測的測驗數據。我們根據歷史的數據比較了幾個共同的需求預測方法，然後比較這些的測量預測的準確性。我們的實驗結果顯示，不同的部份的需求

將導致其挑選不同的預測方法來減少誤差率。但在通常的案例中， Holt-LCL提供了更多準確性需求的預測(大約20%)。 此外，我們也改進了取到平滑法指數的樂觀參數。