淡江大學覺生紀念圖書館 (TKU Library)
進階搜尋


下載電子全文限經由淡江IP使用) 
系統識別號 U0002-1107202022462700
中文論文名稱 共享旅宿風險分析與探討
英文論文名稱 Risk Analysis and Assessment in Airbnb
校院名稱 淡江大學
系所名稱(中) 管理科學學系企業經營碩士班
系所名稱(英) Master's Program In Business And Management, Department Of Management Sciences
學年度 108
學期 2
出版年 109
研究生中文姓名 鄭至芸
研究生英文姓名 Chih-Yun Cheng
學號 608620125
學位類別 碩士
語文別 英文
口試日期 2020-06-30
論文頁數 30頁
口試委員 指導教授-曹銳勤
委員-陳水蓮
委員-劉祥得
中文關鍵字 愛彼迎  品質機能展開  失效模式與影響分析  理想解類似度偏好順序評估法  風險分析 
英文關鍵字 Airbnb  QFD  FMEA  TOPSIS  Risk analysis 
學科別分類
中文摘要 隨著人們對於資源循環利用有新的見解後,經濟模式產生了變化,共享經濟也就在這時候出現,它讓不具有資產所有權的參與者也能夠共同分擔成本,以交換或是租用資源達到協同消費的目的,但是隨著頻繁使用後,漸漸產生出許多風險與問題,而這些風險問題並沒有受到很大的重視和改善,尤其在共享旅宿-Airbnb中,房客和屋主和平台業者之間常常因為缺乏有效的溝通和合作而產生許多誤會與誤解,讓許多有意願使用Airbnb的消費者呈現觀望狀態,所以如何製定出一套有效的安全機制是值得被重視的議題,最終目的就是讓共享旅宿平台傳達出一種讓更多消費者願意安心使用的信念,同時,也讓更多人瞭解共享旅宿平台上的服務與體驗也是一個安心且有保障的選擇。
本研究將以共享旅宿-Airbnb為例,進一步探討風險議題該如何被衡量與重視,我們先歸納出在Airbnb的使用經驗上可能面臨的風險細項,並使用QFD得到使用者心聲和FMEA來評估風險屬性,結合兩種方法建構出一份風險檢核表,提供平台業者自我檢測風險,最後,以案例研究的方式,使用TOPSIS方式來進行其他中小型共享旅宿平台的評估與分析。
英文摘要 As people have new insights into resource recycling, the economic model has changed, and the sharing economy has emerged at this time. It allows participants who do not have asset ownership to share costs together in exchange or rent resources. The purpose of collaborative consumption, but with frequent use, many risks and problems gradually emerge, and these risk problems have not received much attention and improvement, especially in Airbnb, tenants and homeowners and platform operators Because of the lack of effective communication and cooperation, many misunderstandings and misunderstandings often occur, and many consumers who are willing to use Airbnb present a wait-and-see state. Therefore, how to develop an effective security mechanism is a topic worthy of attention. The ultimate goal is to let The shared travel platform conveys a belief that more consumers are willing to use it at the same time. At the same time, it also allows more people to understand the services and experiences on the shared travel platform. It is also a safe and secure choice.
In this study, we will use the Airbnb as an example to further discuss how risk issues should be measured and evaluated. We first summarize the possible risks in Airbnb's experience and use QFD to obtain user voices and FMEA to evaluate risk attributes, combined with two methods to construct a risk checklist, provide platform operators with self-detection of risks. Finally, we use TOPSIS to evaluate and analyze other small and medium-sized shared travelodge platforms in case study.
論文目次 Contents

Contents I
List of Tables II
List of Figure III
Chapter 1 Introduction 1
1.1 Research background 1
1.2 Research motivation and purpose 2
Chapter 2 Literature Review 4
2.1 The rise of the platform economy 4
2.2 Perceived risks 5
2.3 Collection and classification of Airbnb risk factors 5
Chapter 3 Research methods 7
3.1 The QFD methodology 7
3.2 The FMEA methodology 8
3.3 Perform QFD risk assessment and FMEA Self-Platform Risk Checklist 9
3.4 TOPSIS assessment platform risks 10
3.5 Perform TOPSIS to assess risks on other platforms 11
Chapter 4 Results and Case study 13
4.1 Results of QFD risk assessment 13
4.1.1 Explaining data results 13
4.2 Constructed the FMEA Self-Platform Risk Checklist 16
4.2.1 Explaining data results 16
4.2.2 How to use the FMEA Self-Platform Risk Checklist 16
4.3 Score other online platform 19
4.3.1 Use FMEA Self-Platform Risk Checklist to score 19
4.3.2 Use TOPSIS to evaluate the platform 20
Chapter 5 Conclusion 23
5.1 Limitations of the study 25
5.2 Research direction 26
References 26

List of Tables

Table 2-1. List of risk factors 6
Table 4-1. QFD analysis table 15
Table 4-2. FMEA risk factor ranking table 17
Table 4-3. FMEA Self-Platform Risk Checklist 18
Table 4-4. Scores evaluated by platform operators 19
Table 4-5. Risk weights 20
Table 4-6. Corresponding scores of various platform operators in each risk category 20
Table 4-7. Comparison of PIS (+) and NIS (-) results with the values of various operators 21
Table 4-8. TOPSIS ranking results and FMEA Self-Platform Risk Checklist score comparison table 23

List of Figure

Figure 3-1.The House of Quality 7

參考文獻 1.Aytac, A., & Deniz, V. (2005). Quality function deployment in education: a curriculum review. Quality and Quantity, 39(4), 507-51
2.Akao, Y. (1990). QFD: integrating customer requirements into product design. Cambridge, MA.
3.Amaro, S., Andreu, L., & Huang, S. (2019). Millenials’ intentions to book on Airbnb. Current Issues in Tourism, 22(18), 2284-2298.
4.Belk, R. (2014). You are what you can access: Sharing and collaborative consumption online. Journal of business research, 67(8), 1595-1600.
5.Balck, B., & Cracau, D. (2015). Empirical analysis of customer motives in the shareconomy. working paper series, University of Magdeburg, Magdebur, available at: www. fww. ovgu. de/fww_media/femm/femm_2015/2015_02-EGOTEC-pfuspggp6m5tm4cr9hkm6h00i1. pdf (accessed 5 November 2017).
6.Botsman, R., & Rogers, R. (2010). What’s mine is yours. The rise of collaborative consumption.
7.Behzadian, M., Otaghsara, S. K., Yazdani, M., & Ignatius, J. (2012). A state-of the-art survey of TOPSIS applications. Expert Systems with applications, 39(17), 13051-13069.
8.Belarmino, A., Whalen, E., Koh, Y., & Bowen, J. T. (2019). Comparing guests’ key attributes of peer-to-peer accommodations and hotels: mixed-methods approach. Current Issues in Tourism, 22(1), 1-7.
9.Chang, K. H., & Cheng, C. H. (2010). A risk assessment methodology using intuitionistic fuzzy set in FMEA. International Journal of Systems Science, 41(12), 1457-1471.
10.Cheng, M., & Jin, X. (2019). What do Airbnb users care about? An analysis of online review comments. International Journal of Hospitality Management, 76, 58-70.
11.Carbone, T. A., & Tippett, D. D. (2004). Project risk management using the project risk FMEA. Engineering management journal, 16(4), 28-35.
12.Culnan, M. J., & Armstrong, P. K. (1999). Information privacy concerns, procedural fairness, and impersonal trust: An empirical investigation. Organization science, 10(1), 104-115.
13.Cui, R., Li, J., & Zhang, D. (2017). Discrimination with incomplete information in the sharing economy: Evidence from field experiments on Airbnb. Harvard Business School, 1-35.
14.Edelman, B., Luca, M., & Svirsky, D. (2017). Racial discrimination in the sharing economy: Evidence from a field experiment. American Economic Journal: Applied Economics, 9(2), 1-22.
15.Edelman, B., & Geradin, D. (2016). Spontaneous deregulation. Harvard business review, 94(4), 80-87.
16.Edelman, B. G., & Geradin, D. (2015). Efficiencies and regulatory shortcuts: How should we regulate companies like Airbnb and Uber. Stan. Tech. L. Rev., 19, 293.
17.Ert, E., Fleischer, A., & Magen, N. (2016). Trust and reputation in the sharing economy: The role of personal photos in Airbnb. Tourism Management, 55, 62-73.
18.Filieri, R. (2016). What makes an online consumer review trustworthy?. Annals of Tourism Research, 58, 46-64.
19.Frenken, K., & Schor, J. (2019). Putting the sharing economy into perspective. In A Research Agenda for Sustainable Consumption Governance. Edward Elgar Publishing.
20.Ford Motor Company (1988), Potential Failure Mode and Effects Analysis, Instruction Manual, Ford Motor Company, Basildon.
21.Fussell, S. (2019). Airbnb has a hidden-camera problem. The Atlantic.
22.Guttentag, D. (2015). Airbnb: disruptive innovation and the rise of an informal tourism accommodation sector. Current issues in Tourism, 18(12), 1192-1217.
23.Guttentag, D. A., & Smith, S. L. (2017). Assessing Airbnb as a disruptive innovation relative to hotels: Substitution and comparative performance expectations. International Journal of Hospitality Management, 64, 1-10.
24.Harland, C., Brenchley, R., & Walker, H. (2003). Risk in supply networks. Journal of Purchasing and Supply management, 9(2), 51-62.
25.Hwang, C. L., & Yoon, K. (1981). Methods for multiple attribute decision making. In Multiple attribute decision making (pp. 58-191). Springer, Berlin, Heidelberg.
26.Halog, A., Schultmann, F., & Rentz, O. (2001). Using quality function deployment for technique selection for optimum environmental performance improvement. Journal of Cleaner Production, 9(5), 387-394.
27.Johnson, S. K. (1998). Combining QFD and FMEA to optimize performance. In ASQ World Conference on Quality and Improvement Proceedings (p. 564). American Society for Quality.
28.Kuo, T. (2017). A modified TOPSIS with a different ranking index. European Journal of Operational Research, 260(1), 152-160.
29.Koopman, C., Mitchell, M., & Thierer, A. (2014). The sharing economy and consumer protection regulation: The case for policy change. J. Bus. Entrepreneurship & L., 8, 529.
30.Lee, C. K., Song, H. J., Bendle, L. J., Kim, M. J., & Han, H. (2012). The impact of non-pharmaceutical interventions for 2009 H1N1 influenza on travel intentions: A model of goal-directed behavior. Tourism Management, 33(1), 89-99.
31.Lin, P. M. (2020). Is Airbnb a good choice for family travel?. Journal of China Tourism Research, 16(1), 140-157.
32.Manuj, I., & Mentzer, J. T. (2008). Global supply chain risk management strategies. International Journal of Physical Distribution & Logistics Management.
33.Malhotra, N. K., Kim, S. S., & Agarwal, J. (2004). Internet users' information privacy concerns (IUIPC): The construct, the scale, and a causal model. Information systems research, 15(4), 336-355.
34.Mauri, A. G., & Minazzi, R. (2013). Web reviews influence on expectations and purchasing intentions of hotel potential customers. International Journal of Hospitality Management, 34, 99-107.
35.Malazizi, N., Alipour, H., & Olya, H. (2018). Risk perceptions of airbnb hosts: Evidence from a mediterranean island. Sustainability, 10(5), 1349.
36.Picard, E. (2018). Racial discrimination in the sharing economy: evidence from online experiments (Master's thesis).
37.Santana, J., & Parigi, P. (2015). Risk aversion and engagement in the sharing economy. Games, 6(4), 560-573.
38.Tzeng, G. H., & Huang, J. J. (2011). Multiple attribute decision making: methods and applications. CRC press.
39.Tsaur, R. C. (2011). Decision risk analysis for an interval TOPSIS method. Applied Mathematics and Computation, 218(8), 4295-4304.
40.Tussyadiah, I. P., & Pesonen, J. (2016). Impacts of peer-to-peer accommodation use on travel patterns. Journal of Travel Research, 55(8), 1022-1040.
41.Tussyadiah, I. P. (2016). Factors of satisfaction and intention to use peer-to-peer accommodation. International Journal of Hospitality Management, 55, 70-80.
42.Vinodh, S., & Chintha, S. K. (2011). Application of fuzzy QFD for enabling agility in a manufacturing organization. The TQM Journal, Vol. 23 No. 3,343-357.
43.Wu, J., & Gaytán, E. A. A. (2013). The role of online seller reviews and product price on buyers' willingness-to-pay: a risk perspective. European Journal of Information Systems, 22(4), 416-433.
44.Wang, D., & Nicolau, J. L. (2017). Price determinants of sharing economy based accommodation rental: A study of listings from 33 cities on Airbnb. com. International Journal of Hospitality Management, 62, 120-131.
45.Xin, C. (2009, April). P2P-based E-commerce Trust Model and Strategies. In 2009 International Conference on Networks Security, Wireless Communications and Trusted Computing (Vol. 2, pp. 481-483). IEEE.
46.Yang, M., Khan, F. I., Sadiq, R., & Amyotte, P. (2011). A rough set-based quality function deployment (QFD) approach for environmental performance evaluation: a case of offshore oil and gas operations. Journal of Cleaner Production, 19(13), 1513-1526.
47.Y Yang, C. C., Lin, W. T., Lin, M. Y., & Huang, J. T. (2006). A study on applying FMEA to improving ERP introduction. International Journal of Quality & Reliability Management,Vol. 23 No. 3, 298-322
48.Zhu, Y., Cheng, M., Wang, J., Ma, L., & Jiang, R. (2019). The construction of home feeling by Airbnb guests in the sharing economy: A semantics perspective. Annals of Tourism Research, 75, 308-321.
論文使用權限
  • 同意紙本無償授權給館內讀者為學術之目的重製使用,於2020-07-14公開。
  • 同意授權瀏覽/列印電子全文服務,於2020-07-14起公開。


  • 若您有任何疑問,請與我們聯絡!
    圖書館: 請來電 (02)2621-5656 轉 2486 或 來信