博碩士論文 etd-0623120-145023 詳細資訊


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姓名 黃柏勳(Bo-Shiun Huang) 電子郵件信箱 E-mail 資料不公開
畢業系所 企業管理學系研究所(Department of Business Management)
畢業學位 碩士(Master) 畢業時期 108學年第2學期
論文名稱(中) 天氣因子與電子商務平台產品銷售量關係-以尿布產品為例
論文名稱(英) The relationship between weather and sales of diaper on an E-commerce platform
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    紙本論文:3 年後公開 (2023-07-23 公開)

    電子論文:使用者自訂權限:校內 3 年後、校外 3 年後公開

    論文語文/頁數 中文/56
    統計 本論文已被瀏覽 5599 次,被下載 0 次
    摘要(中) 過往有許多研究探討那些影響人們消費決策的因素,而關於外在環境的探討無可厚非的就會提及到天氣。天氣為一非常特殊的自然系統,不管是對經濟活動或是日常生活皆有巨大影響力;對於零售業而言,不少產品都會因天氣狀況不同而有大幅的銷量變動,例如冷氣機、電暖器以及像是一些日常生活必需品等。
    近年來,消費管道已不僅僅侷限於實體通路,時代的演進促成電商的崛起,更改變了人們的生活,在幾乎人人都有過網購經驗的現代社會,天氣是否還會影響人們在消費上的決策即是本研究欲想探究的問題。本研究以日常快速消費品-尿布為研究標的;在研究樣本單位上,筆者縮小至全台的第三級行政區位-鄉、鎮、縣轄市、區,並以距離該地最近的氣象站觀測數據做為該地天氣因子數值。資料期間為2018年10月1日至2019年10月7日,為期一年多的每日交易資料。
    在控制銷售量之時間趨勢、各地0~5歲人口數後,並使用固定效果模型加以分析,而後再以季節區分和交互作用解析下,研究結果發現,電商平台上所販售之民生必需品仍有「1°C效應」,當氣溫比起平均氣溫上升1°C時,銷售量會減少0.3%,而此效應在夏季尤其明顯,並會隨著降雨量、相對濕度狀況不同而有所改變。
    摘要(英) There have been many studies in the past to discuss the factors that affect people's consumption decisions, some of which would focus on the weather. Weather, a very special natural system, whether it has a huge influence on economic activities or daily life. Taking the retail industry for example, many products will have large sales changes due to different weather conditions, such as air conditioners, electricity warmers and somethings like daily necessities.
    In recent years, the consumption channel has not only been limited to physical channels. Online's share of total retail sales has steadily been on the rise—with ecommerce penetration, and it has also changed people’s lives. In the modern society, everyone almost has experience in shopping on the Internet. So, whether the weather still affect people’s consumption or not is the main question in this research we want to explore. In this study, diaper, one of the fast moving consumer goods, is used as the research target. We take the third-level administrative region for this research sample unit. The daily data period is from October 1st, 2018 to October 7th, 2019.
    After controlling the time series of the sales volume and the number of people aged 0-5 years in the township, we use fixed effect model to analyze it. We found that there is still a "weather effect" on e-commerce platforms, such as the temperature. When the temperature rises 1°C, the sales would decrease 0.3%.
    關鍵字(中)
  • 固定效果模型
  • 追蹤資料
  • 天氣效應
  • 電子商務
  • 日常快速消費品
  • 關鍵字(英)
  • e-commerce
  • fast moving consumer goods
  • weather effect
  • panel data
  • fixed effect
  • 論文目次 學位論文審定書.........i
    誌 謝.........ii
    摘 要.........iii
    Abstract.........iv
    目 錄.........v
    表 次.........vi
    圖 次.........viii
    1. 緒論.........1
    1.1 研究背景與動機.........2
    1.2 研究問題.........5
    2. 文獻回顧.........7
    2.1 台灣電子購物及郵購產業.........7
    2.1.1 快速流通消費品在電商扮演的角色.........10
    2.1.2 個案電商資訊.........12
    2.2 天氣對於零售業銷售數據影響.........15
    2.2.1 天氣效應.........15
    2.2.2 天氣效應實證研究.........15
    3. 研究方法.........18
    3.1 資料來源與處理.........18
    3.1.1 交易紀錄資料介紹.........18
    3.1.2 天氣資料取得.........19
    3.1.3 天氣變數介紹.........23
    3.1.4 鄉鎮市區天氣判斷.........24
    3.1.5 其他控制變數.........24
    3.2 分析工具.........25
    3.2.1 多元迴歸的建立.........25
    3.2.2 考慮時間趨勢性.........26
    3.2.3 追蹤資料結構處理.........27
    4. 研究結果.........29
    4.1 敘述統計.........29
    4.2 實證結果.........31
    4.3 進階分析結果.........36
    4.3.1 夏季與非夏季下模型結果.........36
    4.3.2 交互作用.........37
    5. 結論與建議.........40
    5.1 研究結論.........40
    5.2 研究建議與未來方向.........42
    參考文獻.........43
    參考文獻 1. 中文文獻
    梁定澎. (2002). 電子商務理論與實務. 台北: 華泰文化事業股份有限公司.
    陳雲蘭, 陳品妤, 詹智雄, 沈里音, 馮智勇, 劉家豪,& 林佑蓉. (2014). 台灣自動氣象站氣溫資料補遺方法探討及網格化分析. 交通部中央氣象局103年天氣分析與預報研討會論文彙編.
    2. 英文文獻
    Agnew, M. D., & Thornes, J. E. (1995). The weather sensitivity of the UK food retail and distribution industry. Meteorological Applications, 2(2), 137-147.
    Anderson, J., Daultani, V., Muman, T., & Batran, M. (2019, December). The Importance of Weather for E-Commerce Orders Forecasting. In Proceedings of the 2019 International Conference on E-Business and E-commerce Engineering (pp. 15-19).
    Appelqvist, P., Babongo, F., Chavez-Demoulin, V., Hameri, A. P., & Niemi, T. (2016). Weather and supply chain performance in sport goods distribution. International Journal of Retail & Distribution Management.
    Arunraj, N. S., & Ahrens, D. (2016). Estimation of non-catastrophic weather impacts for retail industry. International Journal of Retail & Distribution Management.
    Babongo, F., Appelqvist, P., Chavez-Demoulin, V., Hameri, A. P., & Niemi, T. (2018). Using weather data to improve demand forecasting for seasonal products. International Journal of Services and Operations Management, 31(1), 53-76.
    Badorf, F., & Hoberg, K. (2020). The impact of daily weather on retail sales: An empirical study in brick-and-mortar stores. Journal of Retailing and Consumer Services, 52, 101921.
    Bahng, Y., & Kincade, D. H. (2012). The relationship between temperature and sales. International Journal of Retail & Distribution Management.
    Bertrand, J. L., Brusset, X., & Fortin, M. (2015). Assessing and hedging the cost of unseasonal weather: Case of the apparel sector. European Journal of Operational Research, 244(1), 261-276.
    Bertrand, J. L., & Parnaudeau, M. (2017). No more blaming the weather: a retailer’s approach to measuring and managing weather variability. International Journal of Retail & Distribution Management.
    Buchheim, L., & Kolaska, T. (2017). Weather and the psychology of purchasing outdoor movie tickets. Management Science, 63(11), 3718-3738.
    Buuren, S. V., & Groothuis-Oudshoorn, K. (2010). mice: Multivariate imputation by chained equations in R. Journal of statistical software, 1-68.
    Cachon, G. P., Gallino, S., & Olivares, M. (2012). Severe weather and automobile assembly productivity. Columbia Business School Research Paper, (12/37).
    Canova, L., & Nicolini, M. (2019). Online price search across desktop and mobile devices: Evidence on cyberslacking and weather effects. Journal of Retailing and Consumer Services, 47, 32-39.
    Dutton, J. A. (2002). Opportunities and priorities in a new era for weather and climate services. Bulletin of the American Meteorological Society, 83(9), 1303-1312.
    Fergus, J. T. (1999). Where, when, and by how much does abnormal weather affect housing construction?. The Journal of Real Estate Finance and Economics, 18(1), 63-87.
    Keller, M. C., Fredrickson, B. L., Ybarra, O., Côté, S., Johnson, K., Mikels, J., ... & Wager, T. (2005). A warm heart and a clear head: The contingent effects of weather on mood and cognition. Psychological science, 16(9), 724-731.
    Larsen, P. H. (2006). Estimating the sensitivity of US economic sectors to weather. Graduate Thesis. Cornell University Library, May.
    Martínez-de-Albéniz, V., & Belkaid, A. (2020). Here comes the sun: Fashion goods retailing under weather fluctuations. European Journal of Operational Research.
    Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. the MIT Press.
    Murray, K. B., Di Muro, F., Finn, A., & Leszczyc, P. P. (2010). The effect of weather on consumer spending. Journal of Retailing and Consumer Services, 17(6), 512-520.
    Parsons, A. G. (2001). The association between daily weather and daily shopping patterns. Australasian Marketing Journal (AMJ), 9(2), 78-84.
    Robert, D., & John, R. (1982). Store atmosphere: an environmental psychology approach. Journal of retailing, 58(1), 34-57.
    Shahzad, F. (2019). Does weather influence investor behavior, stock returns, and volatility? Evidence from the Greater China region. Physica A: Statistical Mechanics and its Applications, 523, 525-543.
    Steele, A. T. (1951). Weather's effect on the sales of a department store. Journal of Marketing, 15(4), 436-443.
    Steinker, S., Hoberg, K., & Thonemann, U. W. (2017). The value of weather information for e‐commerce operations. Production and Operations Management, 26(10), 1854-1874.
    Štulec, I., Petljak, K., & Naletina, D. (2019). Weather impact on retail sales: How can weather derivatives help with adverse weather deviations?. Journal of Retailing and Consumer Services, 49, 1-10.
    Taylor, S. J., & Letham, B. (2018). Forecasting at scale. The American Statistician, 72(1), 37-45.
    Tian, J., Zhang, Y., & Zhang, C. (2018). Predicting consumer variety-seeking through weather data analytics. Electronic Commerce Research and Applications, 28, 194-207.
    Turban, E., King, D., Lee, J., & Viehland, D. (2002). Electronic commerce: A managerial perspective 2002. Prentice Hall: ISBN 0, 13(975285), 4.
    Verstraete, G., Aghezzaf, E. H., & Desmet, B. (2019). A data-driven framework for predicting weather impact on high-volume low-margin retail products. Journal of Retailing and Consumer Services, 48, 169-177.
    3. 相關網站
    尼爾森(2018). 快速流通消費品線上銷售速度比線下快四倍. Website: https://www.nielsen.com/tw/zh/insights/article/2018/online-fmcg-sales-growing-4x-faster-than-offline/
    交通部中央氣象局(2020). Website: https://www.cwb.gov.tw/V8/C/
    安侯建業(2016). 亞太電商概覽. Website: https://home.kpmg/tw/zh/home/insights/2017/01/aspac-e-commerce-guideline.html
    社會經濟資料服務平台(2020). Website: https://segis.moi.gov.tw/STAT/Web/Portal/STAT_PortalHome.aspx
    陳俊廷(2018). 台灣電商如何在高度競爭的電商混戰中站穩腳步? 數位時代. Website: https://www.bnext.com.tw/article/49887/taiwan-emarket-uiux
    經濟部統計處(2020). Website: https://www.moea.gov.tw/Mns/dos/home/Home.aspx
    資訊工業策進會(2020).《網購大調查系列》行動下單急追PC呈五五波 行動商務正式成為主流. Website: https://mic.iii.org.tw/news.aspx?id=555&List=1
    International Trade Administration. (2019). Taiwan-Ecommerce. Website: https://www.export.gov/apex/article2?id=Taiwan-ecommerce
    Kantar. (2019). Global online FMCG sales grew by 20% in 2018. Website: https://www.kantarworldpanel.com/global/News/Global-online-FMCG-sales-grew-by-20-in-2018
    口試委員
  • 黃浩霆 - 召集委員
  • 卓雍然 - 委員
  • 佘健源 - 指導教授
  • 口試日期 2020-07-15 繳交日期 2020-07-23

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