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題名 以特徵價格法探討旅館類型與線上訂房網站訂價影響因素之關聯性研究
Applying Hedonic Price Approach to Explore the Relationship between Hotel Types and Pricing Determinants作者 屠介允
Tu, Chieh-Yun貢獻者 洪為璽
Hung, Frank
屠介允
Tu, Chieh-Yun關鍵詞 旅館
線上訂房網站
特徵價格
多元迴歸
訂價因素
Hotel
OTA
Hedonic Price Method
Multiple Regression
Pricing Attributes日期 2020 上傳時間 2-九月-2020 13:18:03 (UTC+8) 摘要 隨著全球觀光業蓬勃發展，線上訂房網站(OTA)整合了旅館資訊、評論和瀏覽、線上訂房和訂交通票券的服務，其便利性也刺激自助旅行消費行為的發展。大大小小的旅館業者，無不爭相與OTA合作，並且OTA也快速地成為旅館業者重要的銷售管道。在全球消費者都習慣於旅遊前到線上查詢旅館價格和進行比價，旅館業者一方面依賴OTA所提供的流量以及訂單，但另一方面卻又面臨OTA上的價格透明化競爭，導致旅館業者陷入了兩難的情境。在OTA上如何訂價，並有效的了解消費者對於不同的產品特徵所願付的價格，是從競爭激烈的市場中脫穎而出的關鍵。本研究的目的是希望協助不同類型的旅館業者詳細了解消費者對於該旅館種類的特徵偏好，以及其願付價格，藉此提供給旅館業者管理建議，協助其擬定策略，提升經營績效。本研究以Agoda.com為研究對象，透過網路爬蟲的方式收集台北車站周邊不同種類的旅館資料，並且以特徵價格法探討北車附近不同旅館的特徵價格，分析消費者對於不同種類的產品需求差異。研究結果顯示，整體來說，傳統星級仍是重要的影響價格特徵。以飯店類型來說，影響其價格最重要的因素是設備的多寡，越豐富的設備，越能帶來相對應的價格。以青年旅館來說，新興崛起的網路服務例如BNPL (Buy Now Pay Later) 服務或是線上預訂，現場付款的服務，可以提高價格。而網路評論則是重質不重量，網路評論的數量並不影響旅館價格，而是消費者給予的網路評分會有效的影響價格。
With thriving of the global tourism industry, online travel agents (OTAs) which integrate hotel and transport tickets booking sevice along with relative information and reviews. They not only facilitate travelers, but also stimulate the development of self-service travel. In view of this, OTAs have become important sales platform for hoteliers, while hotel of all sizes are competing with OTAs simultaneously. Global consumers are growing more accustomed to checking and comparing hotel prices online before traveling. From the perspective of hotel operators, they face a dilemma of traffic and orders earned through OTAs and price competition on the OTAs. In order to stand out in this fiercely competitive market, how to list price on the OTAs with thorough understanding of the prices consumers consent to pay for various product characteristics.The purpose of this study is to investigate consumers` preference for hotel type and willingness to pay, and to provide hoteliers with management suggestions,which help them formulate pricing strategies and improve business performance.This study analyzes data of different types of hotels around Taipei Main Station acquired from Agoda.com by running a web crawler. By approaching the hedonic price method, the price of different hotels near Taipei Main Station are explored, while consumers` needs in different products features are analyzed.To conclude, the research results indicate that star rating still has an siginificant influence on price. In terms of hotel types, the most important factor affecting price is the number of amenities. The more perfect the equipments are, the higher the corresponding price are. As for youth hostels, innovative online services such as buy now pay later (BNPL) schemes, direct online booking, or on-site payment service can help raise the strike price. When it comes to online reviews, it is quality rather than quantity that matters. The amount of reviews does not affect the prices of hotels, while the ratings given by previous guests affect prices effectively.參考文獻 中文文獻1. 簡禎富、許嘉裕(2014)：《資料挖礦與大數據分析》。台北：前程文化事業有限公司。2. 鈕先鉞(2009)：《旅館營運管理與實務》。台北：揚智文化事業股份有限公司。3. 尹章華(2012)：《旅館餐飲法律實務》。台北：永然文化出版股份有限公司。4. 盧慶龍、郭曉怡、陳善珮(2013)：〈旅館產業住宿服務的訂價因素與特徵價格之研究〉，《臺北城市大學學報》第36 期，第263-278 頁。5. 侯佩妤、陳俊智、包曉天(2017)：〈國際觀光旅館的房間訂價決定因素 ̶ 以臺灣為例〉，《觀光與休閒管理期刊》2017年第5卷第1 期，第138-146頁。6. 林宗良、黃秀卿(2014)：〈應用整合科技接受模式探討國際觀光飯店消費者網路訂房行為〉，《運動休閒管理學報》第十一卷第三期，第71-86 頁。7. 黃仁宗、盧炳志、陳芝伊(2014)：〈觀光旅館訂價評估：基於AHP 先驗機率的貝氏機率網路法〉，《觀光與休閒管理期刊》2014 年第2卷第1 期，第92-107頁。8. 于健、魏棋(2013)：〈影響民宿訂價特徵因素之研究－以宜蘭縣為例〉，《管理資訊計算》2013年第2卷第1期，第176-186頁。9. 葉樺蓁(2015)：〈以booking.com為依據之旅館住宿滿意度資料採礦〉，碩士論文，東海大學統計系。10. 蔡潘欣(2009)：〈觀光遊憩資源對影響旅館價格之研究〉，碩士論文，萬能科技大學經營管理研究所。11. 鄭貞怡(2012)：〈台灣即飲包裝茶特徵價格之研究〉，碩士論文，台灣大學生物資源暨農業經濟學系。12. 盧子軒(2018)：〈共享型旅宿之旅客知覺評價策略分析〉，碩士論文，屏東大學休閒事業經營學系。外文文獻1. Bull, A.O., Alcock, K.M., 1993. “Patron preferences for features offered by licensed clubs,” International Journal of Contemporary Hospitality Management ,5 (1):28–32.2. Bull, A. O., 1994, “Pricing a Motel’s Location,” International Journal of Contemporary Hospitality Management, 6:10-15.3. Cheung, C., and R. Law, 2001, “Determinants of Tourism Hotel Expenditure in Hong Kong,” International Journal of Contemporary Hospitality Management, 13:151-158.4. Espinet, J.M., M. Saez, G. Coenders, and M. Fluiva, 2003, “Effect on Prices of the Attributes of Holiday Hotels: A Hedonic Price Approach,” Tourism Economics, 9:165-177.5. Fang, B., Ye, Q., Kucukusta, D., Law, R., 2016, “Analysis of the perceived value of online tourism reviews: influence of readability and reviewer characteristics,” Tourism Manage. 52:498–506.6. Goldberg, S.M., Green, P.E., Wind, Y., 1984, “Conjoint analysis of price premiums forhotel amenities,” The Journal of Business, 57 (1), 111–132.7. Guo, X., Ling, L., Dong, Y., & Liang, L., 2013, “Cooperation contract in tourism supply chains: the optimal pricing strategy of hotels for cooperative third party strategic websites,” Annals of Tourism Research, 41:20-41.8. Hartman, R.S., 1989, “Hedonic methods for evaluating product design and pricing strategies,” Journal of Economics and Business, 41 (3):197-212.9. Heba., 2011, “Dynamic room pricing model for hotel revenue management systems,” Egyptian Informatics Journal ,12:177-183.10. Hong, W., Thong, J.Y.L., Tam, K.Y., 2004, “Designing product listing pages on ecommerce websites: an examination of presentation mode and information format,” Int. J. Hum Comput Stud, 61 (4): 481–503.11. Hung, W. T., J. K. Shang, and F. C. Wang., 2010, “Pricing Determinants in the Hotel Industry: Quantile Regression Analysis,” International Journal of Hospitality Management, 29 (3):378–384.12. Israeli, A.A., 2002, “Star rating and corporate affiliation: their influence on room price and performance of hotels in Israel,” International Journal of Hospitality Management, 25 (1):129–145.13. Kelvin J. Lancaster.,1966, “A New Approach to Consumer Theory,” Journal of Political Economy, 74: 132-157.14. Monty, B. and Skidmore, M., 2003, “Hedonic pricing and willingness to pay for bed and breakfast amenities in southeast Wisconsin,” Journal of Travel Research, 42(2):195-199.15. O’Connor, P., 2003, “On-line pricing: an analysis of hotel-company practices,” Cornell Hotel and Restaurant Administration Quarterly, 44(1):88–96.16. Öğüt, H., and Taş, B. K. O. ,2012, “The influence of internet customer reviews on the online sales and prices in hotel industry,” Industries Journal, 32(2):197-214.17. Rosen, S. ,1974, “Hedonic Price and Implicit Markets:Product Differentiation in Pure Competition,” Journal of Political Economy, 82: 34-55.18. Ruggero Harwood.,2011, “RevPAR determinants of individual hotels: Evidences from Milan,” International Journal of Contemporary Hospitality Management, 23(3):298-31119. Sahay, A., 2007, “How to reap higher profits with dynamic pricing,” MIT Sloan Management Review ,48:53-60.20. Singh, D., and Torres, E., 2015, “Hotel online reviews and their impact on booking transaction value,” Proceedings of XVI Annual Conference, 992-999.21. Thrane, C, 2007, “Examining the Determinants of Room Rates for Hotels in Capital Cities: the Oslo Experience,” Journal of Revenue and Pricing Management, 5:315-323.22. Thrane, C., 2005, “Hedonic Price Models and Sun-and-Beach Package Tours: the Norwegian Case,” Journal of Travel Research, 43:302-308.23. White, P.J., Mulligan, G.F., 2002, “Hedonic estimates of lodging rate in the four corners region,” The Professional Geographer, 54 (4):533-543.24. Wind, J., Green, P.E., Shifflet, D., Scarbrough, M., 1989. “Courtyard by Marriott:designing a hotel facility with consumer-based marketing models,” Interfaces, 19 (1): 25-47.25. Zhang, H., J. Zhang, S. Lu, S. Cheng, and J. Zhang, 2011, “Modeling Hotel RoomPrice with Geographically Weighted Regression,” International Journal of Hospitality Management, 30 (4):1036-1043中文網路文獻1. TTR台灣趨勢研究院(2019)。產業分析：旅行及相關服務業發展趨勢(2019年)。資料擷取自2020年6月30日http://www.twtrend.com/share_cont.php?id=752. 交通部觀光局(2019)。交通部觀光局行政資訊系統，觀光市場調查，2019 年國人旅遊狀況調查。資料來源取自2020 年7 月3 日https://stat.taiwan.net.tw/3. 交通部觀光局（2015）公佈「2015 年國際觀光旅館營運分析報告摘要」。資料來源取自2020 年7 月5 日https://admin.taiwan.net.tw/FileUploadCategoryListC003340.aspx?CategoryID=024c327f-d488-4b9a-b5c2-7598c91651e1英文網路文獻1. Euromonitor International(2014)：OTA Sector Between Increasing Consolidation and the Possible Rise of New Key Playershttps://blog.euromonitor.com/ota-sector-between-increasing-consolidation-and-the-possible-rise-of-new-key-players/2. PhoCusWright(2015)：In Online Travel, Size Mattershttps://www.phocuswright.com/Travel-Research/Research-Updates/2015/In-Online-Travel-Size-Matters3. Skift Research analysis(2018): What Booking Sites Get for Every Marketing Dollar Spent: Skift Research Does the Mathhttps://skift.com/2018/06/26/what-booking-sites-get-for-every-marketing-dollar-spent-skift-research-does-the-math/ 描述 碩士
國立政治大學
企業管理研究所(MBA學位學程)
108363042資料來源 http://thesis.lib.nccu.edu.tw/record/#G0108363042 資料類型 thesis dc.contributor.advisor 洪為璽 zh_TW dc.contributor.advisor Hung, Frank en_US dc.contributor.author (作者) 屠介允 zh_TW dc.contributor.author (作者) Tu, Chieh-Yun en_US dc.creator (作者) 屠介允 zh_TW dc.creator (作者) Tu, Chieh-Yun en_US dc.date (日期) 2020 en_US dc.date.accessioned 2-九月-2020 13:18:03 (UTC+8) - dc.date.available 2-九月-2020 13:18:03 (UTC+8) - dc.date.issued (上傳時間) 2-九月-2020 13:18:03 (UTC+8) - dc.identifier (其他 識別碼) G0108363042 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/131952 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 企業管理研究所(MBA學位學程) zh_TW dc.description (描述) 108363042 zh_TW dc.description.abstract (摘要) 隨著全球觀光業蓬勃發展，線上訂房網站(OTA)整合了旅館資訊、評論和瀏覽、線上訂房和訂交通票券的服務，其便利性也刺激自助旅行消費行為的發展。大大小小的旅館業者，無不爭相與OTA合作，並且OTA也快速地成為旅館業者重要的銷售管道。在全球消費者都習慣於旅遊前到線上查詢旅館價格和進行比價，旅館業者一方面依賴OTA所提供的流量以及訂單，但另一方面卻又面臨OTA上的價格透明化競爭，導致旅館業者陷入了兩難的情境。在OTA上如何訂價，並有效的了解消費者對於不同的產品特徵所願付的價格，是從競爭激烈的市場中脫穎而出的關鍵。本研究的目的是希望協助不同類型的旅館業者詳細了解消費者對於該旅館種類的特徵偏好，以及其願付價格，藉此提供給旅館業者管理建議，協助其擬定策略，提升經營績效。本研究以Agoda.com為研究對象，透過網路爬蟲的方式收集台北車站周邊不同種類的旅館資料，並且以特徵價格法探討北車附近不同旅館的特徵價格，分析消費者對於不同種類的產品需求差異。研究結果顯示，整體來說，傳統星級仍是重要的影響價格特徵。以飯店類型來說，影響其價格最重要的因素是設備的多寡，越豐富的設備，越能帶來相對應的價格。以青年旅館來說，新興崛起的網路服務例如BNPL (Buy Now Pay Later) 服務或是線上預訂，現場付款的服務，可以提高價格。而網路評論則是重質不重量，網路評論的數量並不影響旅館價格，而是消費者給予的網路評分會有效的影響價格。 zh_TW dc.description.abstract (摘要) With thriving of the global tourism industry, online travel agents (OTAs) which integrate hotel and transport tickets booking sevice along with relative information and reviews. They not only facilitate travelers, but also stimulate the development of self-service travel. In view of this, OTAs have become important sales platform for hoteliers, while hotel of all sizes are competing with OTAs simultaneously. Global consumers are growing more accustomed to checking and comparing hotel prices online before traveling. From the perspective of hotel operators, they face a dilemma of traffic and orders earned through OTAs and price competition on the OTAs. In order to stand out in this fiercely competitive market, how to list price on the OTAs with thorough understanding of the prices consumers consent to pay for various product characteristics.The purpose of this study is to investigate consumers` preference for hotel type and willingness to pay, and to provide hoteliers with management suggestions,which help them formulate pricing strategies and improve business performance.This study analyzes data of different types of hotels around Taipei Main Station acquired from Agoda.com by running a web crawler. By approaching the hedonic price method, the price of different hotels near Taipei Main Station are explored, while consumers` needs in different products features are analyzed.To conclude, the research results indicate that star rating still has an siginificant influence on price. In terms of hotel types, the most important factor affecting price is the number of amenities. The more perfect the equipments are, the higher the corresponding price are. As for youth hostels, innovative online services such as buy now pay later (BNPL) schemes, direct online booking, or on-site payment service can help raise the strike price. When it comes to online reviews, it is quality rather than quantity that matters. The amount of reviews does not affect the prices of hotels, while the ratings given by previous guests affect prices effectively. en_US dc.description.tableofcontents 誌謝詞 2摘要 5目次 7表目錄 8圖目錄 9第一章 緒論 10第一節 研究背景 10第二節 研究動機 11第三節 研究目的和研究問題 12第四節 研究流程與架構 13第二章 文獻探討 14第一節 台灣旅宿業概況 14第二節 旅館房價訂價方法 16第三節 特徵價格理論模型 18第四節 特徵價格推估函式 23第五節 旅館房價的影響變數 24第六節 線上訂房網站(OTA)的發展 26第七節 旅館之類型 28第三章 研究方法 30第一節 研究設計 30第二節 變數說明 33第四章 研究分析 41第一節 敘述型統計 41第二節 實證分析 43第三節 變數分析與特徵價格 51第四節 不同種類旅館之特徵價格分析 58第五節 小結 69第五章 結論 71第一節 研究結論 71第二節 研究限制與未來方向 72參考文獻 73 zh_TW dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0108363042 en_US dc.subject (關鍵詞) 旅館 zh_TW dc.subject (關鍵詞) 線上訂房網站 zh_TW dc.subject (關鍵詞) 特徵價格 zh_TW dc.subject (關鍵詞) 多元迴歸 zh_TW dc.subject (關鍵詞) 訂價因素 zh_TW dc.subject (關鍵詞) Hotel en_US dc.subject (關鍵詞) OTA en_US dc.subject (關鍵詞) Hedonic Price Method en_US dc.subject (關鍵詞) Multiple Regression en_US dc.subject (關鍵詞) Pricing Attributes en_US dc.title (題名) 以特徵價格法探討旅館類型與線上訂房網站訂價影響因素之關聯性研究 zh_TW dc.title (題名) Applying Hedonic Price Approach to Explore the Relationship between Hotel Types and Pricing Determinants en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 中文文獻1. 簡禎富、許嘉裕(2014)：《資料挖礦與大數據分析》。台北：前程文化事業有限公司。2. 鈕先鉞(2009)：《旅館營運管理與實務》。台北：揚智文化事業股份有限公司。3. 尹章華(2012)：《旅館餐飲法律實務》。台北：永然文化出版股份有限公司。4. 盧慶龍、郭曉怡、陳善珮(2013)：〈旅館產業住宿服務的訂價因素與特徵價格之研究〉，《臺北城市大學學報》第36 期，第263-278 頁。5. 侯佩妤、陳俊智、包曉天(2017)：〈國際觀光旅館的房間訂價決定因素 ̶ 以臺灣為例〉，《觀光與休閒管理期刊》2017年第5卷第1 期，第138-146頁。6. 林宗良、黃秀卿(2014)：〈應用整合科技接受模式探討國際觀光飯店消費者網路訂房行為〉，《運動休閒管理學報》第十一卷第三期，第71-86 頁。7. 黃仁宗、盧炳志、陳芝伊(2014)：〈觀光旅館訂價評估：基於AHP 先驗機率的貝氏機率網路法〉，《觀光與休閒管理期刊》2014 年第2卷第1 期，第92-107頁。8. 于健、魏棋(2013)：〈影響民宿訂價特徵因素之研究－以宜蘭縣為例〉，《管理資訊計算》2013年第2卷第1期，第176-186頁。9. 葉樺蓁(2015)：〈以booking.com為依據之旅館住宿滿意度資料採礦〉，碩士論文，東海大學統計系。10. 蔡潘欣(2009)：〈觀光遊憩資源對影響旅館價格之研究〉，碩士論文，萬能科技大學經營管理研究所。11. 鄭貞怡(2012)：〈台灣即飲包裝茶特徵價格之研究〉，碩士論文，台灣大學生物資源暨農業經濟學系。12. 盧子軒(2018)：〈共享型旅宿之旅客知覺評價策略分析〉，碩士論文，屏東大學休閒事業經營學系。外文文獻1. Bull, A.O., Alcock, K.M., 1993. “Patron preferences for features offered by licensed clubs,” International Journal of Contemporary Hospitality Management ,5 (1):28–32.2. Bull, A. O., 1994, “Pricing a Motel’s Location,” International Journal of Contemporary Hospitality Management, 6:10-15.3. Cheung, C., and R. Law, 2001, “Determinants of Tourism Hotel Expenditure in Hong Kong,” International Journal of Contemporary Hospitality Management, 13:151-158.4. Espinet, J.M., M. Saez, G. Coenders, and M. Fluiva, 2003, “Effect on Prices of the Attributes of Holiday Hotels: A Hedonic Price Approach,” Tourism Economics, 9:165-177.5. Fang, B., Ye, Q., Kucukusta, D., Law, R., 2016, “Analysis of the perceived value of online tourism reviews: influence of readability and reviewer characteristics,” Tourism Manage. 52:498–506.6. Goldberg, S.M., Green, P.E., Wind, Y., 1984, “Conjoint analysis of price premiums forhotel amenities,” The Journal of Business, 57 (1), 111–132.7. 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