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系統識別號 U0026-2408201120160400
論文名稱(中文) 台灣高鐵旅客之售票通路偏好
論文名稱(英文) Passengers’ Preference on Distribution Channel Service of Taiwan High Speed Rail
校院名稱 成功大學
系所名稱(中) 交通管理學系碩博士班
系所名稱(英) Department of Transportation & Communication Management Science
學年度 99
學期 2
出版年 100
研究生(中文) 黃亭瑜
研究生(英文) Ting-Yu Huang
學號 R56984087
學位類別 碩士
語文別 英文
論文頁數 85頁
口試委員 指導教授-鄭永祥
口試委員-張有恆
口試委員-李治綱
口試委員-蕭傑諭
中文關鍵字 售票通路  複合通路  多項羅吉特模式  結構方程模式 
英文關鍵字 Distribution channel  Multi-channel  Multinomial logit model  Structural equation modeling (SEM) 
學科別分類
中文摘要 複合通路目前已廣泛應用在許多領域當中,運輸產業也大量引進了複合通路的概念,但是少有研究針對運輸業者對複合通路之運用進行探討。本研究以台灣高鐵為個案分析之對象,將購票流程分為查詢、訂票、付款及取票等四個階段,探討影響高鐵旅客在不同購票階段中選擇通路之因素與不同族群旅客對通路選擇之行為差異。考量到目前行動通訊技術之發展,本研究亦設計一情境模擬高鐵引進手機通路,亦即透過手機上網與二維條碼(quick response code, QR code)之運用來販售高鐵車票,藉此探討旅客對手機通路之接受程度。本研究以心理帳戶理論及科技接受模型為理論基礎,發展研究架構與結構方程模式之模型。
本研究結果發現感知風險、感知效益及感知易用性確實影響旅客在不同購票階段中的通路偏好,且來自不同社經背景或具備不同旅次特性的旅客亦會有不同的通路選擇。在手機通路之接受程度方面,本研究分別探討旅客對手機上網與二維條碼車票的接受程度,結果發現個人創新特質會對手機上網及二維條碼車票之接受度產生正面影響,而就手機上網而言,感知風險與感知易用性並不會直接對接受意願產生影響,而是會透過感知有用性對接受意願產生影響。但是就二維條碼車票而言,感知風險、感知易用性、及感知有用性皆會對旅客的接受意願產生影響。本研究根據上述發現,針對台灣高鐵提出數項管理與通路發展方面之建議,且本研究結果未來可延伸為其他運輸產業發展售票通路之研究基礎。
英文摘要 A multi-channel strategy for purposes of marketing and ticketing has been widely employed in various fields, including the transportation industry. However, little research has been done on related issues. This study adopts Taiwan High Speed Rail (THSR) as a case study to identify passengers’ perceptions and preferences regarding key factors affecting the channel by which they receive their services, particularly across a four-stage ticket purchasing process. In addition to investigating passengers’ acceptance of mobile ticketing through use of mobile access and quick response code (QR code) in the ticket purchasing process, this research proposes a scenario for an innovative distribution channel that utilizes mobile technologies in the ticketing process. The framework of our research model by which to investigate these aspects and propose solutions is based upon mental accounting theory and the technology acceptance model (TAM).
The findings of our study demonstrate that perceived risk, perceived benefit, and perceived ease of use are critical factors influencing passengers’ channel preference among the ticket-purchasing processes. Perceptual differences are proven to exist due to various demographic factors and trip characteristics involved.
Specifically, in terms of passengers’ acceptance of the mobile channel, it is found that personal innovativeness has a positive effect on the acceptance of both mobile access and QR code. While perceived risk, perceived usefulness, and perceived ease of use all have influence on the acceptance of QR code, the use of mobile access is not directly affected by perceived risk or perceived ease of use, yet the perceived usefulness associated with such a system does have a positive and direct influence. The conclusions of this study have implications for the management of THSR and may also be generalized to the application of multiple distribution channels in other transportation industries.
論文目次 1. Introduction 1
1.1 Research Background and Motivation 1
1.2 Research Objectives 4
1.3 Research Scope and Subjects 4
1.4 Research Framework 5
2. Literature Review 7
2.1 Multi-channel Application of THSRC 7
2.2 Application of Multi-channel Strategies and Channel Preference 8
2.3 Utilization of Mobile Technologies 10
2.4 Relative Literature of Theoretical Perspectives 12
2.4.1 Mental accounting theory 12
2.4.2 Technology acceptance model (TAM) 13
2.5 Summary 14
3. Research Design and Methodology 16
3.1 Ticket Purchasing Process of THSR 16
3.2 Methodology 17
3.3.1 Descriptive statistics 17
3.3.2 Reliability analysis 17
3.3.4 Analysis of variance (ANOVA) 18
3.3.5 Cramer’s V coefficient 18
3.3.6 Multinomial logit model 18
3.3.7 Structural equation modeling (SEM) 19
3.3 Research Design for Consumer Acceptance of Mobile Channel 20
4. Questionnaire Design 26
4.1 Demographic Information, Trip Characteristics, and Channel Usage 26
4.2 Measurement Items of the First-stage Questionnaire 27
4.3 Measurement Items of the Second-stage Questionnaire 30
5. Empirical Results 32
5.1 The First-stage Questionnaire Survey 32
5.1.1 Descriptive statistics (the first-stage survey) 32
5.1.2 ANOVA 36
5.1.3 Multinomial logit model 41
5.1.4 Cramer’s V coefficient 54
5.2 The Second-stage Questionnaire Survey 55
5.2.1 Descriptive statistics (the second-stage survey) 55
5.2.2 Analysis of passengers’ acceptance of mobile internet 59
5.2.3 Analysis of passengers’ acceptance of QR code 64
6. Conclusion and Discussion 68
6.1 Findings 68
6.2 Managerial Implications 70
6.3 Contributions 71
6.3.1 Academic contributions 71
6.3.2 Empirical contributions 72
6.4 Limitations and Future Research 72
Reference 74
Appendix A The first-stage questionnaire 80
Appendix B The second-stage questionnaire 83

參考文獻 1. Agatz, N.A.H., Fleischmann, M., Van Nunen, J.A.E.E. (2008). E-fulfillment and multi-channel distribution-A review. European Journal of Operational Research, 187(2), 339-356.
2. Ahn, T., Ryu, S., Han, I. (2004). The impact of the online and offline features on the user acceptance of Internet shopping malls. Electronic Commerce Research and Applications, 3(4), 405-420.
3. Ahuja, M., Gupta, B., Raman, P. (2003). An empirical investigation of online consumer purchasing behavior. Communications of the ACM, 46(12), 145-151.
4. Ajzen, I., Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice Hall.
5. Alamdari, F., Mason, K. (2006). The future of airline distribution. Journal of Air Transport Management, 12(3), 122-134.
6. Aldás-Manazano, J., Ruiz-Mafé, C., Sanz-Blas, S. (2009). Exploring individual personality factors as drivers of M-shopping acceptance. Industrial Management & Data Systems, 109 (6), 739-757.
7. Alptekinoğlu, A., Tang, C.S. (2005). A model for analyzing multi-channel distribution systems. European Journal of Operational Research, 13(3), 802-824.
8. Asare, A.K., Alejandro, T.G.B., Granot, E., Kashyap, V. (2011). The role of channel orientation in B2B technology adoption. Journal of Business & Industrial Marketing, 26(3), 193-201.
9. Balasubramanian, S., Raghunathan, R., Mahajan, V. (2005). Consumers in a multichannel environment: Product utility, process utility, and channel choice. Journal of Interactive Marketing, 19(2), 12-30.
10. Barberis, N., Huang, M. (2001). Mental accounting, loss aversion, and individual stock returns. The Journal of Finance, 56(4), 1247-1292.
11. Bigné, E., Hernández, B., Ruiz, C., Andreu, L. (2010). How motivation, opportunity and ability can drive online airline ticket purchases. Journal of Air Transport Management, 16(6), 346-349.
12. Bigné-Alcañiz, E., Ruiz-Mafé, C., Aldás-Manazano, J., Sanz-Blas, S (2008). Influence of online shopping information dependency and innovativeness on internet shopping adoption. Online Information Review, 32(5), 648-667.
13. Büyüközkan, G. (2009). Determining the mobile commerce user requirements using an analytic approach. Computer Standards & Interfaces, 31(1), 144-152.
14. Cheng, J.M.S., Sheen, G.J., Lou, G.C. (2006). Consumer acceptance of the internet as a channel of distribution in Taiwan-A channel function perspective. Technovation, 26(7), 856-864.
15. Cheng, S., Long, J.S. (2007). Testing for IIA in the multinomial logit model. Sociological Methods & Research, 35(4), 583-600.
16. Cheng, Y.H. (2010). High-speed rail in Taiwan: New experience and issues for future development. Transport Policy, 17(2), 51-63.
17. Chiam, M., Soutar, G., Yeo, A. (2009). Online and off-line travel packages preferences: A conjoint analysis. International Journal of Tourism Research, 11(1), 31-40.
18. Chu, H., Liao, S. (2010). Buying while expecting to sell: The economic psychology of online resale. Journal of Business Research, 63(9-10), 1073-1078.
19. Davis, F.D., Bagozzi, R.P., Warshaw, P.R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.
20. De Bruyn, A., Lilien, G.L. (2008). A multi-stage model of word-of-mouth influence through viral marketing. International Journal of Research in Marketing, 25(3), 151-163.
21. Farag, S., Schwanen, T., Dijst, M., Faber, J. (2007). Shopping online and/or in-store? A structural equation model of the relationships between e-shopping and in-store shopping. Transportation Research Part A, 41(2), 125-141.
22. Fornell, C., Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18 (1), 39-50.
23. Frambach, R.D., Roest, H.C.A., Krishnan, T.V. (2007). The impact of consumer Internet experience on channel preference and usage intentions across the different stages of the buying process. Journal of Interactive Marketing, 21(2), 26-41.
24. Gao, S., Moe, S.P., Krogstie, J. (2010). An empirical test of the mobile services acceptance model. 2010 Ninth International Conference on Mobile Business/2010 Ninth Global Mobility Roundtable.
25. Gkritza, K., Niemeier, D., Mannering, F. (2006). Airport security screening and changing passenger satisfaction: An exploratory assessment. Journal of Air Transport Management, 12(5), 213-219.
26. Gu, Y., Zhang, W. (2011). QR code recognition based on image processing. Published in International Conference on Information Science and Technology, Nanjing, Jiangsu, China.
27. Gupta, S., Kim, H.W. (2007). The moderating effect of transaction experience on the decision calculus in on-line repurchase. International Journal of Electronic Commerce, 12(1), 127-158.
28. Gupta, S., Kim, H.W. (2010). Value-driven internet shopping: The mental accounting theory perspective. Psychology & Marketing, 27(1), 13-35.
29. Ha, S., Stoel, L. (2009). Consumer e-shopping acceptance: Antecedents in a technology acceptance model. Journal of Business Research, 62(5), 565-571.
30. Hair, J.F., Black, B., Babin, B., Anderson, R.E., Tatham, R.L. (2006). Multivariate Data Analysis (6th Ed.): Pearson, New Jersey.
31. Huang, Y.C., Wu, C.H., Hsu, J.C.J. (2006). Using importance-performance analysis in evaluating Taiwan medium and long distance national highway passenger transportation service quality. Journal of American Academy of Business, 8(2), 98-104.
32. Jarach, D. (2002). The digitalisation of market relationships in the airline business: The impact and prospects of e-business. Journal of Air Transport Management, 8(2), 115-120.
33. Joo, Y.G., Sohn, S.Y. (2008). Structural equation model for effective CRM of digital content industry. Expert Systems with Application, 34(1), 63-71.
34. Khalifa, M., Shen, K.N. (2008). Explaining the adoption of transactional B2C mobile commerce. Journal of Enterprise Information Management, 21(2), 110-124.
35. Kieseberg, P., Leithner, M., Mulazzani, M., Munroe, L., Schrittwieser, S., Sinha, M., Weippl, E. (2010). QR code security. Published in Proceedings of the 8th International Conference on Advances in Mobile Computing and Multimedia, Paris, France.
36. Kim, C., Mirusmonov, M., Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310-322.
37. Kim, D.J., Ferrin, D.L., Rao, H.R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44(2), 544-564.
38. Kim, H.W., Chan, H.C., Gupta, S. (2007). Value-based adoption of mobile internet: An empirical investigation. Decision Support Systems, 43(1), 111-126.
39. Kim, H.W., Gupta, S. (2009). A comparison of purchase decision calculus between potential and repeat customers of an online store. Decision Support System, 47(4), 477-487.
40. Kuo, Y.F., Yen, S.N. (2009). Towards an understanding of the behavioral intention to use 3G mobile value-added services. Computers in Human Behavior, 25(1), 103-110.
41. Laukkanen, T., Lauronen, J. (2005). Consumer value creation in mobile banking services. International Journal of Mobile Communications, 3(4), 325-338.
42. Lee, C.C., Cheng, H.K., Cheng, H.H. (2007). An empirical study of mobile commerce in insurance industry: Task-technology fit and individual differences. Decision Support Systems, 43(1), 95-110.
43. Liljander,V., Gillberg, F., Gummerus, J., Van Riel, A. (2006). Technology readiness and the evaluation and adoption of self-service technologies. Journal of Retailing and Consumer Services, 13(3), 177-191.
44. Lin, G.T.R., Sun, C.C. (2009). Factors influencing satisfaction and loyalty in online shopping: An integrated model. Online Information Review, 33(3), 458-475.
45. Lu, C.S., Lai, K.H., Cheng, T.C.E. (2007). Application of structural equation modeling to evaluate the intention of shippers to use Internet services in liner shipping. European Journal of Operational Research, 180(2), 845-867.
46. Lu, Y., Cao, Y., Wang, B., Yang, S. (2011). A study on factors that affect users’ behavioral intention to transfer usage from the offline to the online channel. Computers in Human Behavior, 27(1), 355-364.
47. Luo, X., Li, H., Zhang, J., Shim, J.P. (2010). Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: An empirical study of mobile banking services. Decision Support Systems, 49(2), 222-234.
48. Mahatanankoon, P., Wen, H.J., Lim, B. (2005). Consumer-based m-commerce: Exploring consumer perception of mobile applications. Computer Standards & Interfaces, 27(4), 347-357.
49. Mallat, N., Rossi, M., Tuunainen, V.K., Öörni, A. (2008). An empirical investigation of mobile ticketing service adoption in public transportation. Personal and Ubiquitous Computing, 12(1), 57-65.
50. Mallat, N., Rossi, M., Tuunainen, V.K., Öörni, A. (2009). The impact of use context on mobile services acceptance: The case of mobile ticketing. Information & Management, 46(3), 190-195.
51. McFadden, D. (1981). Econometric models of probabilistic choice. In: Manski, D., McFadden (Eds.), A Structural Analysis of Discrete Data with Econometric Applications. The MIT Press, Cambridge, MA.
52. Milkman, K.L., Beshears, J. (2009). Mental accounting and small windfalls: Evidence from an online grocer. Journal of Economic Behavior & Organization, 71(2), 384-394.
53. Milton, J.C., Shankar, V.N., Mannering, F.L. (2008). Highway accident severities and the mixed logit model: An exploratory empirical analysis. Accident Analysis and Prevention, 40(1), 260-266.
54. Miyazaki, A.D., Fernandez, A. (2001). Consumer perceptions of privacy and security risks for online shopping. The Journal of Consumer Affairs, 35(1), 27-44.
55. National Communications Commission (NCC) (2011). Available at http://www.ncc.gov.tw/default.htm. Visit on June 1, 2011.
56. Neslin, S.A., Grewal, D., Leghorn, R., Shankar, V., Teerling, M.L., Thomas, J.S., Verhoef, P.C. (2006). Challenges and opportunities in multichannel customer management. Journal of Service Research, 9(2), 95-112.
57. Ngai, E.W.T., Gunasekaran, A. (2007). A review for mobile commerce research and applications. Decision Support Systems, 43(1), 3-15.
58. Nunes, P.F., Cespedes, F.V. (2003). The customer has escaped. Harvard Business Review, 81(11), 96-105.
59. Parasuraman, A., Zeithaml, V.A., Malhotra, A. (2005). E-S-QUAL: A multiple-item scale for assessing electronic service quality. Journal of Service Research, 7(3), 213-233.
60. Rangaswamy, A, Van Bruggen, G.H. (2005). Opportunities and challenges in multichannel marketing: An introduction to the special issue. Journal of Interactive Marketing, 19(2), 5-11.
61. Rogers, E.M. (1995). Diffusion of innovations (4th edition). New York: Free Press.
62. Ruiz-Mafé, C., Sanz-Blas, S., Aldás-Manzano, J. (2009). Drivers and barriers to online airline ticket purchasing. Journal of Air Transport Management, 15(6), 294-298.
63. Schierz, P.G., Schilke, O., Wirtz, B.W. (2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications, 9(3), 209-216.
64. Schoenbachler, D.D., Gorden, G.L. (2002). Multi-channel shopping: Understanding what drives channel choice. Journal of Consumer Marketing, 19(1), 42-53.
65. Schröder, H., Zaharia, S. (2008). Linking multi-channel customer behavior with shopping motives: An empirical investigation of a German retailer. Journal of Retailing and Consumer Services, 15 (6), 452-468.
66. Sharma, A., Mehrotra, A. (2007). Choosing an optimal channel mix in multichannel environments. Industrial Marketing Management, 36(1), 21-28.
67. Shih, H.P. (2004). An empirical study on predicting user acceptance of e-shopping on the Web. Information & Management, 41(3), 351-368.
68. Shon, Z.Y., Chen, F.Y., Chang, Y.H. (2003). Airline e-commerce: The revolution in ticketing channels. Journal of Air Transport Management, 9(5), 325-331.
69. Tait, A.R., Voepel-Lewis, T., Malviya, S. (2003). Participation of children in clinical research: Factors that influence a parent's decision to consent. Anesthesiology, 99(4), 819-825.
70. Taiwan High Speed Rail Corporation (2011). 2010 Annual Report, Taipei.
71. Taiwan High Speed Rail. Available at http://www.thsrc.com.tw/tc/index.asp. Visited on September 20, 2010.
72. Thaler, R.H. (1999). Mental accounting matters. Journal of Behavioral Decision Making, 12(3), 183-206.
73. Van Birgelen, M., De Jong, A., De Ruyter, K. (2006). Multi-channel service retailing: The effects of channel performance satisfaction on behavioral intentions. Journal of Retailing, 82(4), 367-377.
74. Venkatesan, R., Kumar, V., Ravishanker, N. (2007). Multichannel shopping: Causes and consequences. Journal of Marketing 71(2), 114-132.
75. Weinberg, B.D., Parise, S., Guinan, P.J. (2007). Multichannel marketing: Mindset and program development. Business Horizons, 50(5), 385-394.
76. Wu, C.S., Cheng, F.F., Yen, D.C., Huang, Y.W. (2011). User acceptance of wireless technology in organizations: A comparison of alternative models. Computer Standards & Interfaces, 33(1), 50-58.
77. Wu, J.H., Wang, S.C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information & Management, 42(5), 719-729.
78. Wu, J.H., Wang, Y.M. (2006). Measuring KMS success: A respecification of the DeLone and McLean’s model. Information & Management, 43(6), 728-739.
79. Xia, Y., Zhang, G.P. (2010). The impact of the online channel on retailers’ performances: An empirical evaluation. Decision Science, 41(3), 517-546.
80. Yang, K.C.C. (2005). Exploring factors affecting the adoption of mobile commerce in Singapore. Telematics and Informatics, 22(3), 257-277.
81. Yoon, M.G., Yoon, D.Y., Yang, T.W. (2006). Impact of e-business on air travel markets: Distribution of airline tickets in Korea. Journal of Air Transport Management, 12 (5), 253-260.
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