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  1. NTU Theses and Dissertations Repository
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請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/86308
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dc.contributor.advisor任立中(Li-Chung Jen)
dc.contributor.authorChia-Chan Wuen
dc.contributor.author吳佳展zh_TW
dc.date.accessioned2023-03-19T23:48:13Z-
dc.date.copyright2022-08-29
dc.date.issued2022
dc.date.submitted2022-08-29
dc.identifier.citation[1] 任立中、陳靜怡,「大數據行銷:邁向智能行銷之路」,民國 108 年 [2] 吳長生,「聯合分析法之行銷應用探討」,國立空中大學商學學報,第七期, 民國 88 年,13-31 頁 [3] 任立中、林婷鈴、陳靜怡,「解析自有品牌策略與績效關係的迷思:層級貝氏迴 歸模式之運用」,臺大管理論叢,第十八卷第一期,民國 96 年,117-150 頁 [4] 任立中、劉秀雯、林育理,「貝氏統計於選擇氏聯合分析法之個人與市場區隔 參數之推論」,管理與系統,第十九卷第四期,民國 101 年,673-699 頁 [5] 黃群傑,「以層級貝氏聯合分析模型探討汽車產業品牌權益」,國立臺灣大學 國際企業研究所碩士論文,民國 103 年 [6] 任立中、陳靜怡,「顧客價值遷移路徑分析:馬可夫鏈模型」,臺大管理論叢, 第十七卷第二期,民國 96 年,117-150 頁 [7] Alfred Marshall, “Principles of Economics”, 1890 [8] Greg M Allenby, Nino Hardt, Peter E. Rossi, “Handbook of the Economics of Marketing”, Chapter 3, 2019 [9] Greg M Allenby, Jaehwan Kim and Peter E. Rossi, “Handbook of Marketing”, Chapter 7, 2017 [10] Takuya Satomura, Jeff D. Brazell, Greg M. Allenby, “Choice Models for Budgeted Demand and Constrained Allocation”, 2011 [11] YiChun Miriam Liu, Jeff D. Brazell, Greg M. Allenby, “An Integrative Model for Complex Conjoint Analysis”, 2021 [12] R.Duncan Luce and John W.Tukey, “Simultaneous Conjoint Measurement : A New Type of Fundamental Measurement”, 1964 [13] Green, Paul E. and Rao, Vithala R., “Conjoint Measurement for Quantifying Judgmental Data”, 1971 [14] Green and Srinivasan, “Conjoint Analysis in Consumer Research: Issues and Outlook”,1978 [15] PE Green, V Srinivasan, “Conjoint Analysis in Marketing: New Developments with Implications for Research and Practice”,1990 [16] Peter E. Rossi, Greg M. Allenby and Robert McCulloch, “Bayesian Statistics and Marketing”, 2005
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/86308-
dc.description.abstract過往在選擇式聯合分析中,實驗設計多半為觀測受試者之單一購買決策行為, 忽略市場消費者在挑選序列產品組合中預算遞減之動態性捕捉。本文旨在研究每 一位消費者對於同樣的菜單產品組合內容、不同的順序呈現方式,存在著不一樣 的價格敏感度,此次研究透過設計線上動態式調整菜單,並且在固定預算限制提 供給受試者的條件下,觀察受試者在面臨不同菜單順序之價格敏感度差異,利用 聯合分析法的架構,使用層級貝式迴歸分析、馬可夫鏈蒙地卡羅估計方式,以獲 得每一位獨立的受試者在各點餐階段的價格敏感度之變化,並做市場消費者分群, 以利於廠商在設計菜單時,不論是要針對每一位獨立的消費者作出客製化的菜單 推薦、或是將市場上消費者進行分群後並設計出數個版本的菜單架構,鎖定消費 者的動態價格敏感度來調整菜單順序的設計,有效的提高餐飲業者之利潤。zh_TW
dc.description.abstractChoice-based Conjoint Analysis was mostly to observe the single purchase decision making in the past, ignoring the dynamically decreasing budget of consumers when selecting the sequential product combinations. This thesis aims to study the different price sensitivity of each consumer to the same menu product combination content but not the same presentation order. In this paper, we design an online dynamically adjustment menu, and given the fixed budget for subjects, to observe the price sensitivity when they take some menu of different presentation order, by using the framework of Conjoint Analysis, Hierarchical Bayesian regression analysis, and Markov chain Monte Carlo estimation to obtain everyone’s price sensitivities in each stage of the menu and do consumer clustering. So that when caterers design menus, whether it is to make customized menu recommendations for each independent consumer, or to group consumers in the market and design several versions menu, adjusting the menu according to the dynamic price sensitivity of consumers can effectively improve the profit of the catering industry.en
dc.description.provenanceMade available in DSpace on 2023-03-19T23:48:13Z (GMT). No. of bitstreams: 1
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Previous issue date: 2022
en
dc.description.tableofcontents目錄 第壹章 緒論 ··························································1 第一節、研究背景與動機················································1 第二節、研究目的······················································2 第三節、研究流程······················································3 第貳章 文獻探討 ······················································4 第一節、需求價格彈性··················································4 第二節、聯合分析法····················································4 (一)基本概念 ·······················································4 (二)發展沿革 ······················································· 5 (三)分析步驟 ························································6 第三節、K-MEANS 集群分析 ············································ 7 (一)基本概念 ························································7 (二)分析步驟 ······················································· 8 第參章 研究方法 ······················································10 第一節、研究架構 ·····················································10 第二節、問卷設計 ·····················································10 (一)研究對象與情境 ················································ 10 (二)問卷內容與架構設計 ·············································11 第三節、資料結構與變數定義 ···········································15 第四節、個人化參數推論方法 ···········································17 (一)個人化分析問題 ·················································17 (二)層級貝氏模型架構 ·············································· 18 第肆章 實證分析 ······················································20 第一節、樣本資料概述 ·················································20 第二節、個人化價格彈性表現 ···········································24 第三節、菜單餐點次序與顧客分群········································27 第四節、各群體與特徵統計 ·············································35 (一)各類特徵之探討 ················································· 35 (二)江山易改 vs. 本性難移 ··········································· 39 第伍章 研究結論與行銷建議 ············································43 第一節、研究結論 ·····················································43 第二節、行銷建議 ·····················································44 第三節、後續研究方向建議 ·············································45 參考資料 ·····························································46 REFRENCES ··························································47 附錄 ·································································48 附錄一:正式問卷 ·····················································48 附錄二:問卷操作說明逐字稿 ···········································56
dc.language.isozh-TW
dc.subject層級貝氏zh_TW
dc.subject聯合分析法zh_TW
dc.subject價格彈性zh_TW
dc.subject產品組合zh_TW
dc.subject菜單設計zh_TW
dc.subject動態序列zh_TW
dc.subjectmenu designen
dc.subjectproduct combinationen
dc.subjectprice sensitivityen
dc.subjectConjoint Analysisen
dc.subjectHierarchical Bayesianen
dc.subjectdynamic sequenceen
dc.title以層級貝氏模型探討於預算限制下序列決策模型之需求價格彈性推論zh_TW
dc.titleExploring the Price Elasticity of Demand Under the Sequential Decision-Making with Hierarchical Bayesian Modelen
dc.typeThesis
dc.date.schoolyear110-2
dc.description.degree碩士
dc.contributor.oralexamcommittee蔡政安(Chen-An Tsai),王鴻龍(Hong-Long Wang)
dc.subject.keyword聯合分析法,價格彈性,產品組合,菜單設計,動態序列,層級貝氏,zh_TW
dc.subject.keywordConjoint Analysis,price sensitivity,product combination,menu design,dynamic sequence,Hierarchical Bayesian,en
dc.relation.page57
dc.identifier.doi10.6342/NTU202202853
dc.rights.note同意授權(全球公開)
dc.date.accepted2022-08-29
dc.contributor.author-college共同教育中心zh_TW
dc.contributor.author-dept統計碩士學位學程zh_TW
dc.date.embargo-lift2022-08-29-
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