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題名 行銷文字對不動產成交價之影響與預測:文字探勘法
The Influence and Prediction of Marketing Texts on Real Estate Transaction Price:Text Mining Approach
作者 陳奕全
Chen, Yi-Chuan
貢獻者 陳明吉
Chen, Ming-Chi
陳奕全
Chen, Yi-Chuan
關鍵詞 廣告行銷文字
文字探勘
不動產成交價
Marketing Text
Text Mining
Real Estate Transaction Price
日期 2022
上傳時間 1-Aug-2022 17:18:22 (UTC+8)
摘要 為了提升自家的產品形象及銷售表現，多數賣家皆會運用廣告行銷手法來達成此目的。透過廣告行銷，賣方能將資訊傳達給閱聽人，改變其對於特定產品的認知態度，並有機會進一步影響其後續購買行為。在不動產市場中，最常見的行銷方式莫過於在實體的看板以及網路上對待售標的進行列點式的特色整理，而這些特色整理基本以文字方式呈現。文字資料與與傳統銷售量等數字資料不同，屬於非結構資料。本文統整過往的研究，使用文字探勘的方式將不動產廣告行銷文字轉換為不同形式的有效變數，來探討在不動產市場中，廣告行銷文字的運用能否對房屋的成交價產生影響以及能否對不動產成交價的預測提供一定的幫助，進而增加預測的準確性。
本文利用特徵價格法，建立半對數迴歸模型，得到行銷文字確實能對不動產成交價產生顯著正負程度不等的影響，並且透過將文字變數分組後，觀察到行銷性文字、房屋特性文字以及房屋狀態文字對於不動產成交價較能產生正面影響。本文另外發現，公寓的購屋者相對於大樓的購屋者，更在意與房屋內部資訊相關的行銷文字。研究的最後也發現加入文字變數能夠有效提升對於房屋成交價的預測能力，幫助進行更精準的房屋大量估價，且預測能力好壞與加入的文字變數數量有正比關係。
In order to improve product image and sales performance, almost all sellers use marketing strategies. Through marketing, sellers can convey information to readers, changing their cognition and attitude towards a specific product and having the opportunity to further influence subsequent purchase behavior. In the real estate market,the most common way of marketing is to list the features of the houses to be sold on the physical billboards and on the Internet, and most of these features are shown in the form of text (written words). However, text data, unlike traditional digital data such as sales volume, is non-structured. This thesis integrates past research and uses text mining to convert real estate marketing text into different forms of effective variables to explore in the real estate market whether the use of marketing text can have an influence on the transaction price of houses and whether it can further provide some help in the prediction of real estate transaction prices.
This thesis uses the hedonic price method to establish a semi-logarithmic regression model, and finds that marketing words can indeed have significant positive and negative effects on real estate transaction prices. In addition, this thesis also finds that apartment buyers are more concerned about marketing text related to information about the interior of the house than building buyers. At the end of this study, it is also found that adding text variables can effectively increase the accuracy in predicting the transaction prices of houses and thereby helps when conducting the mass appraisal of house prices, and that the accuracy is proportional to the number of text added.
參考文獻 一、中文文獻
李吉弘、楊宗憲，2010，「預售屋與成屋價差比關係之研究－以台北市和台北縣為例」，『建築與規劃學報』，11(1) : 1-14。
林秋瑾、楊宗憲、張金鶚，1996，「住宅價格指數之研究—以台北市為例」，『住宅學報』，4 : 1-30。
邱志聖，2015。《行銷研究：實務與理論應用》。元照出版。
二、英文文獻
Abdallah, S. and Khashan, D. A., 2016, “Using Text Mining To Analyze Real Estate Classifieds”, Proceedings of the International Conference on Advanced Intelligent Systems and Informatics, Pages 193–202.
Adiyanto, O. and Jatmiko, H. A., 2019, ” Development Of Food Packaging Design With Kansei Engineering Approach”, International Journal of Scientific & Technology Research, 8(12) : 1778-1788.
Albion, M. S. and Farris, P. W., 1981, “The advertising controversy : evidence on the economic effects of advertising”, Boston, Mass. : Auburn.
Aune, M., 2012, “Making energy visible in domestic property markets: The influence of advertisements”, Building Research and Information, 40(6) : 1-11.
Berrar, D., 2018, “Cross-Validation”, In book: Reference Module in Life Sciences.
Boyd, D., and Crawford, K., 2012, “Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon”, Information, Communication & Society, 15(5) : 662–679.
Chen, G., Wan, Y and Xu, X., 2016, “An Analysis of the Sales and Consumer Preferences of E-cigarettes Based on Text Mining of Online Reviews”, Conference: 2016 3rd International Conference on Systems and Informatics.
Cheung, S. C. H. and MA, E. K. W., 2007, “Advertising Modernity: Home, Space and Privacy”, Visual Anthropology, 18:1,65-80.
Chung, Y. and Sarnikar, S., 2021, “Understanding Host Marketing Strategies on Airbnb and Their Impact on Listing Performance: A Text Analytics Approach”, Information Technology & People.
Colley, R. H., 1961, “Defining advertising goals for measured advertising results”, New York : Association of National Advertisers.
Collins, D. and Kearns, R., 2008, “Uninterrupted Views: Real-Estate Advertising and Changing Perspectives on Coastal Property in New Zealand”, Environment and Planning A: 40(12):2914-2932.
Frew, J. and Jud, G. D., 2003, “Estimating the Value of Apartment Buildings”, Journal of Real Estate Research, 25(1):77-86.
Goo, P., 2010, “A Study on the Meaning and Strategy of Keyword Advertising Marketing”, Journal of Distribution Science 8-3:49-56.
Guan, J., Zurada, J. and Levitan, A. S., 2008, “An Adaptive Neuro-Fuzzy Inference System Based Approach to Real Estate Property Assessment”, Journal of Real Estate Research, 30(4):395-422.
Halseth, G., Hall, C. M. and Muller, D. K., 2004, “The ‘Cottage’ Privilege: Increasingly Elite Landscapes of Second Homes in Canada”, Tourism, Mobility and Second Homes: Between elite landscape and common ground, 35-54.
Holbrook, M. B. and Batra, R., 1987, “Assessing the Role of Emotions as Mediators of Consumer Responses to Advertising”, Journal of Consumer Research 14(3):404-420.
Isa, I. G. T., 2018, “Kansei Engineering Approach in Software Interface Design”, Journal of Science Innovare, 1(01) : 22-26.
Isen, A. M. and Means, B., 2011, “The Influence of Positive Affect on Decision-Making Strategy”, Social Cognition 2(1).
Kiel, K. A. and Zabel J. E., 2008, “Location, location, location: The 3L Approach to house price determination”, Journal of Housing Economics, 17: 175-190.
Kotler, P. and Gertner, D., 2002, “Country as Brand, Product, and Beyond: A Place Marketing and Brand Management Perspective”, The Journal of Brand Management, 9, 249-261.
Lau, K. N., Lee, K. H. and Ho, Y., 2005, “Text Mining for the Hotel Industry”, Cornell Hospitality Quarterly, 46(3):344-362.
Lawson, G., 2013, “A rhetorical study of in-flight real estate advertisements as a potential site of ethical transformation in Chinese cities”, Cities, 31:85-95.
Li, K., Zhang, L., Wang, D. and Pan, D., 2021, “The Effects of Online Information on E-Book Pricing Strategies: A Text Analytics Approach”, Mathematical Problems in Engineering, 2021(2):1-11.
Little, J. D., 1979, “Decision Support Systems for Marketing Managers”, Journal of Marketing, Summer 43(3): 9.
Lyu, F. and Choi, J., 2020, “The Forecasting Sales Volume and Satisfaction of Organic Products through Text Mining on Web Customer Reviews”, Sustainability, 12(11) : 4383.
Morgan, N. A., Whitler, K. A., Feng, H. and Chari, S., 2018, “Research in marketing strategy”, Journal of the Academy of Marketing Science, 47:4-29.
Novgorodov, S., Guy, I., Elad, G. and Radinsky, K., 2019, “Generating Product Descriptions from User Reviews”, The World Wide Web Conference, Pages 1354-1364.
Nowak, A. and Smith, P., 2017, “Textual Analysis in Real Estate”, Journal of Applied Econometrics, 32(4) : 896-918.
Peladeau, N. and Davoodi, E., 2018, “Comparison of Latent Dirichlet Modeling and Factor Analysis for Topic Extraction: A Lesson of History”, Conference: Hawaii International Conference on System Sciences.
Pryzant, R., Chung, Y. and Jurafsky, D., 2017, “Predicting Sales from the Language of Product Descriptions”, International Journal of Engineering and Technical Research, 9(04).
Shahrokh, Z. D. and Pourhosseini, A. H., 2013, “Performance Implications of Sales & Marketing Strategy”, Journal of Business Management, 5(1) : 61-84.
Shen, L., 2021, “Information value of property description: A Machine learning approach”, Journal of Urban Economics, 121 : 103299.
Weiss, R. F., 1969, “Repetition of Persuasion”, SAGE Journals, Psychological Reports.
描述 碩士
國立政治大學
財務管理學系
109357011
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0109357011
資料類型 thesis
dc.contributor.advisor 陳明吉zh_TW
dc.contributor.advisor Chen, Ming-Chien_US
dc.contributor.author (Authors) 陳奕全zh_TW
dc.contributor.author (Authors) Chen, Yi-Chuanen_US
dc.creator (作者) 陳奕全zh_TW
dc.creator (作者) Chen, Yi-Chuanen_US
dc.date (日期) 2022en_US
dc.date.accessioned 1-Aug-2022 17:18:22 (UTC+8)-
dc.date.available 1-Aug-2022 17:18:22 (UTC+8)-
dc.date.issued (上傳時間) 1-Aug-2022 17:18:22 (UTC+8)-
dc.identifier (Other Identifiers) G0109357011en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/141019-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 財務管理學系zh_TW
dc.description (描述) 109357011zh_TW
dc.description.abstract (摘要) 為了提升自家的產品形象及銷售表現，多數賣家皆會運用廣告行銷手法來達成此目的。透過廣告行銷，賣方能將資訊傳達給閱聽人，改變其對於特定產品的認知態度，並有機會進一步影響其後續購買行為。在不動產市場中，最常見的行銷方式莫過於在實體的看板以及網路上對待售標的進行列點式的特色整理，而這些特色整理基本以文字方式呈現。文字資料與與傳統銷售量等數字資料不同，屬於非結構資料。本文統整過往的研究，使用文字探勘的方式將不動產廣告行銷文字轉換為不同形式的有效變數，來探討在不動產市場中，廣告行銷文字的運用能否對房屋的成交價產生影響以及能否對不動產成交價的預測提供一定的幫助，進而增加預測的準確性。
本文利用特徵價格法，建立半對數迴歸模型，得到行銷文字確實能對不動產成交價產生顯著正負程度不等的影響，並且透過將文字變數分組後，觀察到行銷性文字、房屋特性文字以及房屋狀態文字對於不動產成交價較能產生正面影響。本文另外發現，公寓的購屋者相對於大樓的購屋者，更在意與房屋內部資訊相關的行銷文字。研究的最後也發現加入文字變數能夠有效提升對於房屋成交價的預測能力，幫助進行更精準的房屋大量估價，且預測能力好壞與加入的文字變數數量有正比關係。		zh_TW
dc.description.abstract (摘要) In order to improve product image and sales performance, almost all sellers use marketing strategies. Through marketing, sellers can convey information to readers, changing their cognition and attitude towards a specific product and having the opportunity to further influence subsequent purchase behavior. In the real estate market,the most common way of marketing is to list the features of the houses to be sold on the physical billboards and on the Internet, and most of these features are shown in the form of text (written words). However, text data, unlike traditional digital data such as sales volume, is non-structured. This thesis integrates past research and uses text mining to convert real estate marketing text into different forms of effective variables to explore in the real estate market whether the use of marketing text can have an influence on the transaction price of houses and whether it can further provide some help in the prediction of real estate transaction prices.
This thesis uses the hedonic price method to establish a semi-logarithmic regression model, and finds that marketing words can indeed have significant positive and negative effects on real estate transaction prices. In addition, this thesis also finds that apartment buyers are more concerned about marketing text related to information about the interior of the house than building buyers. At the end of this study, it is also found that adding text variables can effectively increase the accuracy in predicting the transaction prices of houses and thereby helps when conducting the mass appraisal of house prices, and that the accuracy is proportional to the number of text added.		en_US
dc.description.tableofcontents 第一章 緒論 1
第一節 研究動機與問題 1
第二節 研究範圍與限制 3
第三節 研究架構與流程 4
第二章 文獻回顧 6
第一節 廣告行銷理論及效果 6
第二節 文字探勘在行銷上的應用 9
第三節 影響不動產價格之微觀因素 12
第三章 研究設計 13
第一節 研究假說 13
第二節 模型設計 14
第三節 文字處理方式 16
第四節 預測模型訓練方式及效果評估 19
第四章 實證研究 21
第一節 資料處理與敘述統計 21
第二節 行銷文字對不動產成交價之影響 31
第三節 分組後行銷文字對不動產成交價之影響 35
第四節 行銷文字對不動產成交價之預測效果 37
第五章 結論、建議與後續研究 38
第一節 結論 38
第二節 建議與後續研究 39
參考文獻 40
附錄一 初步斷詞表內容 44
附錄二 本研究文字變數內容 45		zh_TW
dc.format.extent 2330884 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0109357011en_US
dc.subject (關鍵詞) 廣告行銷文字zh_TW
dc.subject (關鍵詞) 文字探勘zh_TW
dc.subject (關鍵詞) 不動產成交價zh_TW
dc.subject (關鍵詞) Marketing Texten_US
dc.subject (關鍵詞) Text Miningen_US
dc.subject (關鍵詞) Real Estate Transaction Priceen_US
dc.title (題名) 行銷文字對不動產成交價之影響與預測:文字探勘法zh_TW
dc.title (題名) The Influence and Prediction of Marketing Texts on Real Estate Transaction Price:Text Mining Approachen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 一、中文文獻
李吉弘、楊宗憲，2010，「預售屋與成屋價差比關係之研究－以台北市和台北縣為例」，『建築與規劃學報』，11(1) : 1-14。
林秋瑾、楊宗憲、張金鶚，1996，「住宅價格指數之研究—以台北市為例」，『住宅學報』，4 : 1-30。
邱志聖，2015。《行銷研究：實務與理論應用》。元照出版。
二、英文文獻
Abdallah, S. and Khashan, D. A., 2016, “Using Text Mining To Analyze Real Estate Classifieds”, Proceedings of the International Conference on Advanced Intelligent Systems and Informatics, Pages 193–202.
Adiyanto, O. and Jatmiko, H. A., 2019, ” Development Of Food Packaging Design With Kansei Engineering Approach”, International Journal of Scientific & Technology Research, 8(12) : 1778-1788.
Albion, M. S. and Farris, P. W., 1981, “The advertising controversy : evidence on the economic effects of advertising”, Boston, Mass. : Auburn.
Aune, M., 2012, “Making energy visible in domestic property markets: The influence of advertisements”, Building Research and Information, 40(6) : 1-11.
Berrar, D., 2018, “Cross-Validation”, In book: Reference Module in Life Sciences.
Boyd, D., and Crawford, K., 2012, “Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon”, Information, Communication & Society, 15(5) : 662–679.
Chen, G., Wan, Y and Xu, X., 2016, “An Analysis of the Sales and Consumer Preferences of E-cigarettes Based on Text Mining of Online Reviews”, Conference: 2016 3rd International Conference on Systems and Informatics.
Cheung, S. C. H. and MA, E. K. W., 2007, “Advertising Modernity: Home, Space and Privacy”, Visual Anthropology, 18:1,65-80.
Chung, Y. and Sarnikar, S., 2021, “Understanding Host Marketing Strategies on Airbnb and Their Impact on Listing Performance: A Text Analytics Approach”, Information Technology & People.
Colley, R. H., 1961, “Defining advertising goals for measured advertising results”, New York : Association of National Advertisers.
Collins, D. and Kearns, R., 2008, “Uninterrupted Views: Real-Estate Advertising and Changing Perspectives on Coastal Property in New Zealand”, Environment and Planning A: 40(12):2914-2932.
Frew, J. and Jud, G. D., 2003, “Estimating the Value of Apartment Buildings”, Journal of Real Estate Research, 25(1):77-86.
Goo, P., 2010, “A Study on the Meaning and Strategy of Keyword Advertising Marketing”, Journal of Distribution Science 8-3:49-56.
Guan, J., Zurada, J. and Levitan, A. S., 2008, “An Adaptive Neuro-Fuzzy Inference System Based Approach to Real Estate Property Assessment”, Journal of Real Estate Research, 30(4):395-422.
Halseth, G., Hall, C. M. and Muller, D. K., 2004, “The ‘Cottage’ Privilege: Increasingly Elite Landscapes of Second Homes in Canada”, Tourism, Mobility and Second Homes: Between elite landscape and common ground, 35-54.
Holbrook, M. B. and Batra, R., 1987, “Assessing the Role of Emotions as Mediators of Consumer Responses to Advertising”, Journal of Consumer Research 14(3):404-420.
Isa, I. G. T., 2018, “Kansei Engineering Approach in Software Interface Design”, Journal of Science Innovare, 1(01) : 22-26.
Isen, A. M. and Means, B., 2011, “The Influence of Positive Affect on Decision-Making Strategy”, Social Cognition 2(1).
Kiel, K. A. and Zabel J. E., 2008, “Location, location, location: The 3L Approach to house price determination”, Journal of Housing Economics, 17: 175-190.
Kotler, P. and Gertner, D., 2002, “Country as Brand, Product, and Beyond: A Place Marketing and Brand Management Perspective”, The Journal of Brand Management, 9, 249-261.
Lau, K. N., Lee, K. H. and Ho, Y., 2005, “Text Mining for the Hotel Industry”, Cornell Hospitality Quarterly, 46(3):344-362.
Lawson, G., 2013, “A rhetorical study of in-flight real estate advertisements as a potential site of ethical transformation in Chinese cities”, Cities, 31:85-95.
Li, K., Zhang, L., Wang, D. and Pan, D., 2021, “The Effects of Online Information on E-Book Pricing Strategies: A Text Analytics Approach”, Mathematical Problems in Engineering, 2021(2):1-11.
Little, J. D., 1979, “Decision Support Systems for Marketing Managers”, Journal of Marketing, Summer 43(3): 9.
Lyu, F. and Choi, J., 2020, “The Forecasting Sales Volume and Satisfaction of Organic Products through Text Mining on Web Customer Reviews”, Sustainability, 12(11) : 4383.
Morgan, N. A., Whitler, K. A., Feng, H. and Chari, S., 2018, “Research in marketing strategy”, Journal of the Academy of Marketing Science, 47:4-29.
Novgorodov, S., Guy, I., Elad, G. and Radinsky, K., 2019, “Generating Product Descriptions from User Reviews”, The World Wide Web Conference, Pages 1354-1364.
Nowak, A. and Smith, P., 2017, “Textual Analysis in Real Estate”, Journal of Applied Econometrics, 32(4) : 896-918.
Peladeau, N. and Davoodi, E., 2018, “Comparison of Latent Dirichlet Modeling and Factor Analysis for Topic Extraction: A Lesson of History”, Conference: Hawaii International Conference on System Sciences.
Pryzant, R., Chung, Y. and Jurafsky, D., 2017, “Predicting Sales from the Language of Product Descriptions”, International Journal of Engineering and Technical Research, 9(04).
Shahrokh, Z. D. and Pourhosseini, A. H., 2013, “Performance Implications of Sales & Marketing Strategy”, Journal of Business Management, 5(1) : 61-84.
Shen, L., 2021, “Information value of property description: A Machine learning approach”, Journal of Urban Economics, 121 : 103299.
Weiss, R. F., 1969, “Repetition of Persuasion”, SAGE Journals, Psychological Reports.		zh_TW
dc.identifier.doi (DOI) 10.6814/NCCU202200784en_US