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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 黃崇興(Chung-Hsing Huang) | |
dc.contributor.author | Zhe-Wen Zhang | en |
dc.contributor.author | 張哲聞 | zh_TW |
dc.date.accessioned | 2021-06-17T03:24:43Z | - |
dc.date.available | 2023-06-13 | |
dc.date.copyright | 2018-06-13 | |
dc.date.issued | 2018 | |
dc.date.submitted | 2018-06-02 | |
dc.identifier.citation | 參考文獻
1. 彼得.聖吉 (2009)。第五項修煉. 2. 郭馨梅,施珊珊(2017)。 電商管道與實體零售管道融合發展的主要模式與對策。商業經濟研究 2017-04: 13-16。 3. 郭馨梅,張健麗(2014)。我國零售業線上線下融合發展的主要模式及對策分析。北京工商大學學報:社會科學版 29.5: 44-48。 4. 黃敏學(2004)。電子商務第二版。 5. 賈康,程瑜,張鵬(2017)。中國大型零售業現狀、趨勢及行業發展戰略設想。經濟研究參考 2017 年第 46 期。 6. 黎志成,劉枚蓮(2002)。電子商務環境下的消費者行為研究 (Doctoraldissertation)。 7. 林娟娟,岱昀(2008)。網站購買意願影響因素之探討。管理與系統, 15(2), 209-235。 8. 柳井正(2011)。成功一日可以丟棄。 9. 欒斌,陳苡任(2003)。電子商務─應用與科技發展(第二版) ISBN:9789865647841。 10. 彭娟(2014)。中國零售業態分類研究。商業研究, (7), 42-49。 11. 孫永波,劉曉敏(2014)。電商新趨勢下影響網路消費者購買行為因素研究。北京工商大學學報: 社會科學版, 29(4), 93-101。 100 12. 王承豪(1999)。系統思考實用手冊。台北縣: 世茂。 13. 葉萬春(2001)。服務行銷學。 14. 張波(2010)。系統動力學簡介及其相關軟體綜述。環境與可持續發展 2 (2010):1-4。 15. 趙廷超(2003)。電子商務是社會經濟發展的必然趨勢。電子商務世界 12 (2003):000。 1. Burdin, T. Omni-channel retailing: the brick, click and mobile revolution. 2013-01- 05]. http://www. cegid. com/retail. 2. Hsiao, M. H. (2009). Shopping mode choice: Physical store shopping versus e- shopping. Selim, H., & Ozkarahan, I. (2008). Transportation Research Part E-Logistics and Transportation Review. Collaborative production distribution planning in supply chain: a fuzzy goal programming approach, 44, 396-419. 3. Jarvenpaa, S. L., & Todd, P. A. (1996). Consumer reactions to electronic shopping on the World Wide Web. International Journal of electronic commerce, 1(2), 59-88. 4. Meadows, D. H. (2008). Thinking in systems: A primer. chelsea green publishing. 5. Shih, H. P. (2004). An empirical study on predicting user acceptance of e-shopping on the Web. Information & Management, 41(3), 351-368. 6. Sterman, J. D. (2000). Business dynamics: systems thinking and modeling for a complex world (No. HD30. 2 S7835 2000). 7. Storbacka, K., Strandvik, T., & Grönroos, C. (1994). Managing customer relationships for profit: the dynamics of relationship quality. International journal of service industry management, 5(5), 21-38. 8. Tan, H. H., Foo, M. D., & Kwek, M. H. (2004). The effects of customer personality traits on the display of positive emotions. Academy of Management Journal, 47(2), 99-287-296. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/69709 | - |
dc.description.abstract | 零售業不斷發展,線上與線下界限逐步模糊,單純選擇線上或線下的顧客逐步 減少,更多的顧客在全通路上購物。潛在消費者的流向變化受多個因素影響,並形 成一個系統,在系統中影響因素相互之間存在聯繫,改變其中一項會如蝴蝶效應一 般對其他量產生影響。
本論文建立一個基於 Bass 擴散模型的系統動力學模型,通過對線上或線下顧 客的轉換進行系統動力學分析,改變其中的迴圈狀態數量值進而調控整個系統的 變化,在隨著時間推移的動態模擬中發現客流的變化,並找尋相關的影響因素。並 且通過利潤模型反應改變系統迴圈的狀態量之後對於利潤的影響效果。 研究的結果發現線上或線下顧客在向全通路顧客轉換過程中,轉移使用場景 所引起的延遲效應會對線下顧客數量帶來一定影響,社交網路平台傳播的可觸及 的人數會影響顧客轉換的速率。引導潛在顧客消費對於利潤的影響較大,零售商在 投入在引導顧客全通路購物同時也需要引導潛在消費者購物進而確保利潤最大化。 本研究的意義在於通過系統動力學方法對線上線下轉換過程簡化模型進行動 態模擬,從而展現短期到長期的不同狀態下的變化,也是第一次將 Bass 擴散模型 應用在線上線下轉化的系統動力學模擬中。在後繼研究中可以提供模型基礎,通過 增加模型複雜度展開研究,同時也為企業提供了系統動力學對於本身零售線上線 下預測及分析的模型基礎。 | zh_TW |
dc.description.abstract | With the continuous development of the retail industry, the boundaries between online and offline are gradually blurred, and the customers who simply choose either online or offline to shopping are gradually decreasing. More customers are shopping in both ways. The preferences of the potential consumers is affected by multiple factors in a form of system. The factors in the system are corelated to each other, and changing one of them will have an impact on others.
The research has conducted a system dynamics analysis based on the Bass diffusion model. The model can simulate the consumer flow between the online and offline in the timeline, by controlling the loop’s status value, the variances can help to explore the key influencing factors. And through the profit model shows the change of the profit. The results of the study found that the online or offline customers in the process of transitioning to full-channel customers, the delay effect caused by the transfer of usage scenarios will have an impact on the number of offline customers, the number of reachable persons of social network platforms will affect the rate of conversion. Leading potential customers to consumption has a greater impact on profitability. Retailers invest in directing customers' full-channel shopping. They also need to lead potential consumers to purchase and thus ensure profit maximization. This research use dynamic simulation of the simplified model of the online and offline conversion process through system dynamics, to show the changes in different conditions from short-term to long-term, and it is also the first time that the Bass diffusion model is applied online and offline conversion system. In the follow-up studies, the model foundation can be provided, and the research can be carried out by increasing the complexity of the model. At the same time, it also provides the model foundation for system dynamics for the online offline forecasting and analysis of retail sales. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T03:24:43Z (GMT). No. of bitstreams: 1 ntu-107-R05741062-1.pdf: 4795628 bytes, checksum: 23f5b325b69eed07d9b72ed3c8719405 (MD5) Previous issue date: 2018 | en |
dc.description.tableofcontents | 目錄
誌謝........................................................................................I 中文摘要.................................................................................II ABSTRACT............................................................................III 目錄........................................................................................IV 圖目錄 ...................................................................................VI 表目錄 ...................................................................................IX 第一章 緒論 ...........................................................................1 第一節 研究背景.................................................................1 第二節 研究目的及意義......................................................2 第三節 研究方法.................................................................4 第四節 章節架構.....................................................................5 第二章 文獻回顧與探討..........................................................7 第一節 零售及其發展介紹...................................................7 第二節 零售渠道的研究發展...............................................11 第三節 LOGISTIC 與 BASS 擴散模型 ...............................19 第三章 系統動力學介紹 .........................................................23 第四章 系統動力學模型設計...................................................30 第一節 潛在顧客轉為線上線下顧客的系統構建...................30 第二節 線上與線下顧客引導之另一種途徑的系統...............34 第三節 成本與利潤簡化模型................................................38 第五章 動態模擬......................................................................53 第六章 研究結論......................................................................65 第一節 延遲效應對顧客數量變化影響..................................65 第二節 利潤變化...................................................................68 第三節 研究存在的不足與展望.............................................72 附件一:系統動力學模型參數資料 .............................................74 附件二:改變單一迴圈的模擬運行結果 ......................................79 附件三:改變多個迴圈的模擬運行結果 ......................................87 參考文獻 ..................................................................................99 | |
dc.language.iso | zh-TW | |
dc.title | 以系統動力學方法模擬零售業線上線下跨平台營運 | zh_TW |
dc.title | Using System Dynamics in a Simulation of On-line/Off- line Retail Operations | en |
dc.type | Thesis | |
dc.date.schoolyear | 106-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 余峻瑜(Jiun-Yu Yu),葉明義(Ming Yi Yeh) | |
dc.subject.keyword | 系統動力學,線上到線下,零售業,動態模擬, | zh_TW |
dc.subject.keyword | System dynamic,Online to Offline,Dynamic simulation, | en |
dc.relation.page | 101 | |
dc.identifier.doi | 10.6342/NTU201800879 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2018-06-04 | |
dc.contributor.author-college | 管理學院 | zh_TW |
dc.contributor.author-dept | 商學研究所 | zh_TW |
顯示於系所單位: | 商學研究所 |
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