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請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/97467
完整後設資料紀錄
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dc.contributor.advisor許鉅秉zh_TW
dc.contributor.advisorJiuh-Biing Sheuen
dc.contributor.author王韻婷zh_TW
dc.contributor.authorYun-Ting Wangen
dc.date.accessioned2025-06-18T16:16:31Z-
dc.date.available2025-06-19-
dc.date.copyright2025-06-18-
dc.date.issued2025-
dc.date.submitted2025-06-12-
dc.identifier.citation英文文獻
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Maimaiti, M., Zhao, X., Jia, M., Ru, Y., & Zhu, S. (2018). How we eat determines what we become: opportunities and challenges brought by food delivery industry in a changing world in China. European journal of clinical nutrition, 72(9), 1282-1286. https://doi.org/10.1038/s41430-018-0191-1
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Mehmann, J., Frehe, V., & Teuteberg, F. (2015). Crowd Logistics − A Literature Review and Maturity Model. Berlin: Epubli GmbH. https://www.econstor.eu/handle/10419/209253
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Sbihi, A., & Eglese, R. W. (2010). Combinatorial optimization and green logistics. Annals of Operations Research, 175, 159-175.
Seghezzi, A., Winkenbach, M., & Mangiaracina, R. (2021). On-demand food delivery: a systematic literature review. The International Journal of Logistics Management, 32(4), 1334–1355. https://doi.org/10.1108/IJLM-03-2020-0150
Shankar, A., Jebarajakirthy, C., Nayal, P., Maseeh, H. I., Kumar, A., & Sivapalan, A. (2022). Online food delivery: A systematic synthesis of literature and a framework development. International Journal of Hospitality Management, 104, 103240. https://doi.org/10.1016/j.ijhm.2022.103240
Song, G., Zhang, H., Duan, H., & Xu, M. (2018). Packaging waste from food delivery in China’s mega cities. Resources, conservation and recycling, 130, 226-227. https://doi.org/10.1016/j.resconrec.2017.12.007
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Sulaiman, Y., Khong, B. T. W., LUN, L., Ghani, N. H. A., & Khairi, M. Q. I. M. (2024). A New Adoption Intention Model of Drone Application in Food Delivery Services in Malaysia: A Conceptual Paper. WSEAS Transactions on Business and Economics, 21, 488-498.
Teng, Y. M., Wu, K. S., Wang, W. C., & Chen, L. W. (2023). What factors drive consumers’ desire to continue using food delivery apps (FDA) in Taiwan after the COVID-19 pandemic?. Journal of Hospitality and Tourism Technology, 14(5), 878-892. https://doi.org/10.1108/JHTT-09-2022-0259
The Straits Times. (2018). Meal delivery service foodpanda launches new option where customers do the pick-up. https://www.straitstimes.com/business/companies-markets/foodpanda-launches-new-service-where-customers-do-the-pick-up
Thiell, M., Zuluaga, J. P. S., Montañez, J. P. M., & van Hoof, B. (2011). Green logistics: Global practices and their implementation in emerging markets. In Green finance and sustainability: Environmentally-aware business models and technologies (pp. 334-357). IGI Global.
Tsai, P. H., Chen, C. J., Hsiao, W. H., & Lin, C. T. (2023). Factors influencing the consumers’ behavioural intention to use online food delivery service: Empirical evidence from Taiwan. Journal of Retailing and Consumer Services, 73, 103329. https://doi.org/10.1016/j.jretconser.2023.103329
Wen, Z., Zhang, Y., & Fu, D. (2019). The environmental impact assessment of a takeaway food delivery order based on of industry chain evaluation in China. China Environ. Sci, 39, 4017-4024.
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中文文獻
台中市政府(2022年4月22日)。2050臺中市淨零碳排路徑。
台北市政府(2022年3月28日)。臺北市2050淨零行動白皮書。
台南市政府(2023年3月30日)。臺南市第二期溫室氣體減量執行方案。
行政院環境保護署(2016年6月)。溫室氣體排放量盤查登錄作業指引。
交通部(2023年4月)。運具電動化及無碳化關鍵戰略行動計畫。
交通部(2023年10月31日)。111年機車使用狀況調查報告。
交通部(2023年10月31日)。111年自用小客車使用狀況調查報告。
交通部公路局。機動車輛登記數-按縣市別及使用燃料分(101年9月起)。
交通部運輸研究所(2022)。運具溫室氣體排放及減碳措施效益推估參數精進之探討。
交通部運輸研究所(2023)。新式運輸服務型態對運輸排碳影響初探。
高雄市政府(2022年12月28日)。2022高雄市自願檢視報告。
財團法人聯合信用卡處理中心(2024年5月24日)。餐飲外送平台消費額屢破紀錄-解析千億元產業發展之消費樣態轉移~餐飲外送平台信用卡消費大數據分析PART3~。https://www.nccc.com.tw/wps/wcm/connect/zh/home/openinformation/CaseAnalysisIntroduce/CNT_05_998_20240524103750
勞動部職業安全衛生署(2024年1月30日)。113勞動部職安全衛生署預算。
新北市政府(2022年8月24日)。新北市2050淨零路徑暨氣候行動白皮書。
資策會產業情報研究所(2025年2月12日)。【外送大調查】兩大外送平台常用差距首度少於一成 四成用戶兩者皆用 外送訂閱會員達四成 18-25歲新訂閱戶漲幅最大。https://mic.iii.org.tw/news.aspx?id=706&List=1
經濟部能源署(2024年5月2日)。112年度電力排碳係數。
環境部氣候變遷署(2019年6月27日)。溫室氣體排放係數管理表6.0.4。
環境部氣候變遷署氣候公民對話平台(2024年)。運輸部門排放及減量情形。
Foodpanda(2022年7月6日)。foodpanda共享永續新食代來臨,愛地球才對味!。https://pandarider.foodpanda.com.tw/column/64
Uber(2023年12月19日)。Uber Eats 攜手Gogoro共推近10億價值「綠色永續外送方案」。https://www.uber.com/zh-TW/newsroom/greendelivery/
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/97467-
dc.description.abstract隨著COVID-19疫情帶動宅經濟發展,外送服務已成為台灣民眾日常飲食的重要選擇,線上餐飲外送平台的市場規模亦隨之迅速成長。然而,外送平台營運模式高度仰賴即時配送,外送員所使用之運具多屬於高頻次、高里程行駛的類型,便利性的背後實則隱含對環境永續之潛在衝擊。因此,鑒於外送服務所衍生之碳排放議題逐漸受到關注,而目前針對台灣外送產業之永續影響的量化研究仍屬有限,故本研究旨在探討外送平台不同取餐方式,亦即外送服務及自取服務,如何影響餐點配送過程中所產生之碳排放量。

本研究以台灣主要外送平台Foodpanda為研究對象,採用聯合國政府間氣候變化專門委員會(IPCC)的「排放係數法」估算碳排放量,並分析相關參數變動(如交通工具、取餐方式改變)對碳排放結果之影響。研究目的在於提供外送平台推動低碳營運策略之決策依據,亦作為政府部門制定外送產業永續政策之參考。

研究結果顯示,自取模式之平均碳排放量明顯低於外送模式,僅約為外送訂單碳排之五分之一。然而,目前國內仍以外送服務作為主要的取餐方式,且外送員普遍使用燃油機車進行配送,碳排強度較高。針對碳排相關參數之敏感度分析發現,若提升外送員使用電動機車遞送之比例,或鼓勵民眾選擇短程之自取服務,且自取時採用低碳運具(如電動機車、步行、自行車),皆可有效降低整體碳排放量。
zh_TW
dc.description.abstractDriven by the COVID-19 pandemic and the rise of the “Stay-at-Home Economy”, food delivery service has become an integral part of daily life in Taiwan, with platforms like Foodpanda experiencing rapid growth. However, the delivery model relies heavily on real-time logistics using high-frequency, high-mileage vehicles, raising sustainability concerns due to increased carbon emissions.

This study examines the carbon emissions generated from two food acquisition methods—delivery and pick-up—using Foodpanda as a case study. Based on the IPCC’s emission factor method, the study estimates emissions by incorporating variables such as transport mode and distance, and further assess the impact of changes in key parameters.

Results show that pick-up produces significantly lower emissions—only one-fifth of delivery orders on average. Nevertheless, delivery remains the dominant food acquisition method in Taiwan, with most riders using gasoline scooters. Sensitivity analysis indicates that promoting electric scooters among riders and encouraging low-carbon pick-up methods, such as walking or biking, can effectively reduce total emissions.
en
dc.description.provenanceSubmitted by admin ntu (admin@lib.ntu.edu.tw) on 2025-06-18T16:16:31Z
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dc.description.provenanceMade available in DSpace on 2025-06-18T16:16:31Z (GMT). No. of bitstreams: 0en
dc.description.tableofcontents誌謝 i
摘要 ii
Abstract iii
目次 iv
圖次 vi
表次 viii
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 2
1.3 研究範圍與對象 2
1.4 研究內容與架構 3
第二章 文獻回顧 4
2.1 外送平台 4
2.1.1 外送平台概念及興起 4
2.1.2 外送平台運作模式 4
2.2 外送服務對於永續之影響 6
2.2.1 經濟影響 6
2.2.2 社會影響 6
2.2.3 環境影響 7
2.3 綠色物流 8
2.3.1 綠色物流簡介 8
2.3.2 綠色物流應用 9
2.4 小結 10
第三章 研究方法 11
3.1 研究流程 11
3.1.1 外送與自取流程 11
3.1.2 碳排計算方法及參數 13
3.1.3 敏感度分析設計 15
3.2 問卷調查 16
3.2.1 問卷設計 16
3.2.2 問卷蒐集結果 17
3.3 資料蒐集與處理 19
3.3.1 外送平台訂單量 19
3.3.2 外送與自取比例 20
3.3.3 交通運具 20
3.3.4 行駛距離 22
3.3.5 運具碳排係數 25
第四章 研究結果 27
4.1 碳排結果分析 27
4.1.1 全台外送與自取碳排結果 27
4.1.2 各直轄市外送與自取碳排結果 29
4.2 敏感度分析 33
4.2.1 外送平台訂單量 33
4.2.2 運具使用比例 34
4.2.3 外送與自取比例 50
4.2.4 外送距離 52
4.3 研究結果討論 55
第五章 結論與建議 57
5.1 研究結論 57
5.2 管理意涵 59
5.3 研究限制與未來研究方向 61
參考文獻 63
附錄:問卷 70
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dc.language.isozh_TW-
dc.subject外送碳排zh_TW
dc.subject低碳轉型zh_TW
dc.subject外送平台zh_TW
dc.subject自取碳排zh_TW
dc.subject淨零碳排zh_TW
dc.subjectNet-Zero Carbon Emissionsen
dc.subjectLow-Carbon Transitionen
dc.subjectCarbon Emissions from Deliveryen
dc.subjectFood Deliveryen
dc.subjectCarbon Emissions from Pick-upen
dc.title外送平台取餐方式對碳排放量影響之探討—以 Foodpanda 為例zh_TW
dc.titleThe Impact of Food Acquisition Methods on Carbon Emissions in Food Delivery: The Case of Foodpandaen
dc.typeThesis-
dc.date.schoolyear113-2-
dc.description.degree碩士-
dc.contributor.oralexamcommittee陳穆臻;郭人介zh_TW
dc.contributor.oralexamcommitteeMu-Chen Chen;Ren-Jieh Kuoen
dc.subject.keyword外送平台,外送碳排,自取碳排,淨零碳排,低碳轉型,zh_TW
dc.subject.keywordFood Delivery,Carbon Emissions from Delivery,Carbon Emissions from Pick-up,Net-Zero Carbon Emissions,Low-Carbon Transition,en
dc.relation.page70-
dc.identifier.doi10.6342/NTU202500946-
dc.rights.note同意授權(限校園內公開)-
dc.date.accepted2025-06-13-
dc.contributor.author-college管理學院-
dc.contributor.author-dept商學研究所-
dc.date.embargo-lift2030-06-12-
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