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| Title: | 購物籃分析：以服飾和飾品店為例
Market Basket Analysis: A Case Study of a Clothing and Accessory Store in Taiwan |
| Authors: | 黃浩
Huang, Clyde Hau |
| Contributors: | 胡昌亞
Hu, Changya
黃浩
Huang, Clyde Hau |
| Keywords: | 購物籃分析
服飾和飾品
物品組合
Market Basket Analysis
Clothing and accessory
Item pairs |
| Date: | 2025 |
| Issue Date: | 2025-02-04 15:53:49 (UTC+8) |
| Abstract: | 購物籃分析是一個能夠從銷售資料產出物品組合的資料探勘方式。本研究以技術報告的模式進行一間服飾及飾品店的購物籃分析。使用的資料是為期一年(10月2022至9 月2023)的銷售資料，此外也把一年的資料分成每三個月一期進行購物籃分析和比較。資料包含206,357件物品、79,747筆交易，第一期有47,133件物品、第二期有41,951件物品、第三期有35,221件物品、第四期有82,052件物品。分析結果包括各個時間段的支持度、信賴度、和提升，其中高於門檻值的物品組合便會進行討論，門檻值為信賴度高於0.3和提升高於1.1或提升低於0.9。研究結果發現所有時間段，每三個月和年度分析都支持 前項：下身服裝、後項：上身服裝 的組合，以及 前項：戒指、後項：耳環 的組合。另外只有在每三個月中最後一季的分析中出現的 前項：腳環、後項：上身服裝 組合卻因為這季的銷售量特別高、支持度、信賴度、和提升的指數也都很高，導致在年度的購物籃分析也出現此組合。本研究也提出相關的研究限制及建議。
Market Basket Analysis is a data mining method that allows the discovery of association relationships between merchandise. The analysis makes use of transaction records to provide insight into relationships that may or may not be intuitive to businesses. This study focused on the practical application of Market Basket Analysis on a Clothing and Accessory store based in Taiwan. The analysis was done using transaction records spanning one year from October 2022 to September 2023, and additional analysis was done by splitting the one year data into four quarters. The dataset included 206,357 item sales which correspond to 79,747 transactions. The First Quarter consists of 47,133 item sales, Second Quarter 41,951 item sales, Third Quarter 35,221 item sales, and Fourth Quarter 82,052 item sales. The support, confidence, and lift of the category pairs with association are then presented while combinations that passed the threshold value of Confidence greater than 0.3 and Lift greater than 1.1 or Lift less than 0.9 were highlighted. Results showed that item pairs of Antecedent: Bottom and Consequent: Top, as well as Antecedent: Ring and Consequent: Earring are consistently highly associated in all quarters and one year analyses. Item pairing Antecedent: Anklet and Consequent: Top was only prominent in the Fourth Quarter, yet due to its high values in all three metrics, it was still highly associated in the one year analysis. Further analysis, limitations, and recommendations of the study were discussed. |
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Yung, R., Zerili, M. (2024). Build a market basket analysis dashboard using nested filters in Amazon QuickSight. AWS Business Intelligence Blog. https://aws.amazon.com/blogs/business-intelligence/build-a-market-basket-analysis-dashboard-using-nested-filters-in-amazon-quicksight/. Retrieved on December 10, 2024.
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| Description: | 碩士
國立政治大學
企業管理研究所(MBA學位學程)
111363102 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0111363102 |
| Data Type: | thesis |
| Appears in Collections: | [企業管理研究所（MBA學位學程）] 學位論文
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