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題名 電商平台促銷方法對銷售額的影響分析
The Sales Effect of Promotion Methods on Order Value in E-commerce Platforms
作者 張芷瑄
Chih-Hsuan, Chang
貢獻者 莊皓鈞
CHUANG,HAO-CHUN
張芷瑄
Chih-Hsuan, Chang
關鍵詞 電子商務
促銷
隨機森林
E-commerce
promotion
Random Forest
Shapley value
日期 2023
上傳時間 1-Sep-2023 15:01:21 (UTC+8)
摘要 從疫情爆發開始，人們待在家裡的時間變長，使用越來越多的時間進行線上購 物，造成電商市場的蓬勃發展，電子商務的重要性不可忽略。而因為是線上銷售模式 ，故主要是靠行銷手法吸引顧客購買，本研究即針對這個層面，取了京東的交易數據 分析電子商務平台的各種促銷方法的效果，分別是直接折扣、數量折扣 、折價券 、 綁售 、贈品。首先，運用迴歸分析與隨機森林分析各促銷變數對訂單總金額的影響力 ，並用 Shapley value 做模型解釋。結果顯示，直接折扣和數量折扣是有效提升訂單總 金額的促銷方式，而折價券則無顯著影響。此外，針對京東的分析還顯示，對高消費 京東 Plus 會員提供數量折扣更可有效提升訂單金額。
Since the outbreak of the pandemic, people have been spending more time at home, leading to an increasing reliance on online shopping and a flourishing e-commerce market. The importance of electronic commerce cannot be overlooked. As online sales rely heavily on marketing strategies to attract customers, this study focuses on analyzing the effectiveness of various promotional methods on an e-commerce platform using transaction data from Jingdong (JD.com). The promotional methods investigated include direct discounts, quantity discounts, coupons, bundled sales, and free gifts.
Firstly, regression analysis and random forest analysis were employed to examine the impact of each promotional variable on the total order amount. Shapley value was used for model interpretation. The results indicated that direct discounts and quantity discounts are effective in increasing the total order amount, while coupons showed no significant impact. Additionally, the analysis specific to JD.com revealed that offering quantity discounts to high-spending JD Plus members can effectively boost their order amounts.
參考文獻 宋靜靜(2022 年 3 月 1 日)。中國電商滲透率達37%，國貨電商出海成新趨勢。億恩 网。https://chuhaiyi.baidu.com/news/detail/20404122
庹曉驊(2019 年 12 月 30 日)。風生物起，國貨來潮〔專題演講〕。2019 新國貨盛 典，廈門市，中國。
2022年您該擁有的中國電商新思維(2022 年 4 月 1 日)。AsiaPac。 https://www.asiapacdigital.com/zh-cht/digital-marketing-insight/china-ecommerce-2022 Chris(2021 年 11 月 12 日)。低調中破紀錄，阿里巴巴雙十一 5403 億人民幣作收。
INSIDE。https://www.inside.com.tw/article/25531-alibaba-double-11-2021-end Tiffany(2020 年 12 月 2 日)。咖啡「買一送一」為什麼不直接半價?3張圖告訴你 背後全都是套路。Cheers https://www.cheers.com.tw/article/article.action?id=5098326
Abolghasemi, M., Tarr, G., & Bergmeir, C. (2022). Machine learning applications in hierarchical time series forecasting: Investigating the impact of promotions. International Journal of Forecasting. Forthcoming. https://doi.org/10.1016/j.ijforecast.2022.07.004
Buil, I., de Chernatony, L. and Montaner, T. (2013). Factors influencing consumer evaluations of gift promotions. European Journal of Marketing, 47(3/4), pp. 574-595. eMarketer (2022). Global E-Commerce Forecast 2022: As 2-Year Boom Subsides, Plenty of Bright Spots Remain. ChannelAdvisor.
Li, X., Zhuang, Y., Lu, B., & Chen, G. (2019). A multi-stage hidden Markov model of customer repurchase motivation in online shopping. Decision Support Systems, 120, 72-80. Lundberg SM, Erion G, Chen H, DeGrave A, Prutkin JM, Nair B,Katz R, Himmelfarb J, Bansal N, Lee SI (2020) From local ex-planations to global understanding with explainable AI fortrees. Nature Machine Intelligence 2(1):56–67.
Oly-Ndubisi, N., & Tung-Moi, C. (2006). Awareness and usage of promotional tools by Malaysian consumers: the case of low involvement products. Management Research News, 29(1/2), 28-40.
Sinha, I. and Smith, M. F. (2000). Consumers` perceptions of promotional framing of price. Psychology & Marketing, 17(3), 257-275.
Senoner, J., Netland, T. and Feuerriegel, S. (2021). Using Explainable Artificial Intelligence to Improve Process Quality: Evidence from Semiconductor Manufacturing. Management Science 68(8), pp. 5704-5723.
Shen, M., Tang, C. S., Wu, D., Yuan, R., & Zhou, W. (2020). JD.Com: Transaction-Level Data for the 2020 MSOM Data Driven Research Challenge. Manufacturing & Service Operations Management, pp. 1–9.
Tong, T., Xu, X., Yan, N., & Xu, J. (2022). Impact of Different Platform Promotions on Online Sales and Conversion Rate: The Role of Business Model and Product Line Length. Decision Support Systems, 156(113746).
描述 碩士
國立政治大學
企業管理研究所(MBA學位學程)
110363073
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0110363073
資料類型 thesis
dc.contributor.advisor 莊皓鈞zh_TW
dc.contributor.advisor CHUANG,HAO-CHUNen_US
dc.contributor.author (Authors) 張芷瑄zh_TW
dc.contributor.author (Authors) Chih-Hsuan, Changen_US
dc.creator (作者) 張芷瑄zh_TW
dc.creator (作者) Chih-Hsuan, Changen_US
dc.date (日期) 2023en_US
dc.date.accessioned 1-Sep-2023 15:01:21 (UTC+8)-
dc.date.available 1-Sep-2023 15:01:21 (UTC+8)-
dc.date.issued (上傳時間) 1-Sep-2023 15:01:21 (UTC+8)-
dc.identifier (Other Identifiers) G0110363073en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/146922-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 企業管理研究所(MBA學位學程)zh_TW
dc.description (描述) 110363073zh_TW
dc.description.abstract (摘要) 從疫情爆發開始，人們待在家裡的時間變長，使用越來越多的時間進行線上購 物，造成電商市場的蓬勃發展，電子商務的重要性不可忽略。而因為是線上銷售模式 ，故主要是靠行銷手法吸引顧客購買，本研究即針對這個層面，取了京東的交易數據 分析電子商務平台的各種促銷方法的效果，分別是直接折扣、數量折扣 、折價券 、 綁售 、贈品。首先，運用迴歸分析與隨機森林分析各促銷變數對訂單總金額的影響力 ，並用 Shapley value 做模型解釋。結果顯示，直接折扣和數量折扣是有效提升訂單總 金額的促銷方式，而折價券則無顯著影響。此外，針對京東的分析還顯示，對高消費 京東 Plus 會員提供數量折扣更可有效提升訂單金額。zh_TW
dc.description.abstract (摘要) Since the outbreak of the pandemic, people have been spending more time at home, leading to an increasing reliance on online shopping and a flourishing e-commerce market. The importance of electronic commerce cannot be overlooked. As online sales rely heavily on marketing strategies to attract customers, this study focuses on analyzing the effectiveness of various promotional methods on an e-commerce platform using transaction data from Jingdong (JD.com). The promotional methods investigated include direct discounts, quantity discounts, coupons, bundled sales, and free gifts.
Firstly, regression analysis and random forest analysis were employed to examine the impact of each promotional variable on the total order amount. Shapley value was used for model interpretation. The results indicated that direct discounts and quantity discounts are effective in increasing the total order amount, while coupons showed no significant impact. Additionally, the analysis specific to JD.com revealed that offering quantity discounts to high-spending JD Plus members can effectively boost their order amounts.		en_US
dc.description.tableofcontents 第一章 緒論...7
第二章 文獻回顧...9
第三章 資料與變數說明...11
第四章 資料分析與結果...13
第一節 線性迴歸分析...14
第二節 隨機森林與 Shapley value...20
第五章 結論與討論...24
參考文獻...26		zh_TW
dc.format.extent 2034634 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0110363073en_US
dc.subject (關鍵詞) 電子商務zh_TW
dc.subject (關鍵詞) 促銷zh_TW
dc.subject (關鍵詞) 隨機森林zh_TW
dc.subject (關鍵詞) E-commerceen_US
dc.subject (關鍵詞) promotionen_US
dc.subject (關鍵詞) Random Foresten_US
dc.subject (關鍵詞) Shapley valueen_US
dc.title (題名) 電商平台促銷方法對銷售額的影響分析zh_TW
dc.title (題名) The Sales Effect of Promotion Methods on Order Value in E-commerce Platformsen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 宋靜靜(2022 年 3 月 1 日)。中國電商滲透率達37%，國貨電商出海成新趨勢。億恩 网。https://chuhaiyi.baidu.com/news/detail/20404122
庹曉驊(2019 年 12 月 30 日)。風生物起，國貨來潮〔專題演講〕。2019 新國貨盛 典，廈門市，中國。
2022年您該擁有的中國電商新思維(2022 年 4 月 1 日)。AsiaPac。 https://www.asiapacdigital.com/zh-cht/digital-marketing-insight/china-ecommerce-2022 Chris(2021 年 11 月 12 日)。低調中破紀錄，阿里巴巴雙十一 5403 億人民幣作收。
INSIDE。https://www.inside.com.tw/article/25531-alibaba-double-11-2021-end Tiffany(2020 年 12 月 2 日)。咖啡「買一送一」為什麼不直接半價?3張圖告訴你 背後全都是套路。Cheers https://www.cheers.com.tw/article/article.action?id=5098326
Abolghasemi, M., Tarr, G., & Bergmeir, C. (2022). Machine learning applications in hierarchical time series forecasting: Investigating the impact of promotions. International Journal of Forecasting. Forthcoming. https://doi.org/10.1016/j.ijforecast.2022.07.004
Buil, I., de Chernatony, L. and Montaner, T. (2013). Factors influencing consumer evaluations of gift promotions. European Journal of Marketing, 47(3/4), pp. 574-595. eMarketer (2022). Global E-Commerce Forecast 2022: As 2-Year Boom Subsides, Plenty of Bright Spots Remain. ChannelAdvisor.
Li, X., Zhuang, Y., Lu, B., & Chen, G. (2019). A multi-stage hidden Markov model of customer repurchase motivation in online shopping. Decision Support Systems, 120, 72-80. Lundberg SM, Erion G, Chen H, DeGrave A, Prutkin JM, Nair B,Katz R, Himmelfarb J, Bansal N, Lee SI (2020) From local ex-planations to global understanding with explainable AI fortrees. Nature Machine Intelligence 2(1):56–67.
Oly-Ndubisi, N., & Tung-Moi, C. (2006). Awareness and usage of promotional tools by Malaysian consumers: the case of low involvement products. Management Research News, 29(1/2), 28-40.
Sinha, I. and Smith, M. F. (2000). Consumers` perceptions of promotional framing of price. Psychology & Marketing, 17(3), 257-275.
Senoner, J., Netland, T. and Feuerriegel, S. (2021). Using Explainable Artificial Intelligence to Improve Process Quality: Evidence from Semiconductor Manufacturing. Management Science 68(8), pp. 5704-5723.
Shen, M., Tang, C. S., Wu, D., Yuan, R., & Zhou, W. (2020). JD.Com: Transaction-Level Data for the 2020 MSOM Data Driven Research Challenge. Manufacturing & Service Operations Management, pp. 1–9.
Tong, T., Xu, X., Yan, N., & Xu, J. (2022). Impact of Different Platform Promotions on Online Sales and Conversion Rate: The Role of Business Model and Product Line Length. Decision Support Systems, 156(113746).		zh_TW