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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 潘雪 | zh_TW |
| dc.contributor.advisor | Shweta Pandey | en |
| dc.contributor.author | 蘇凱文 | zh_TW |
| dc.contributor.author | Kawin Suwanban | en |
| dc.date.accessioned | 2023-07-24T16:06:56Z | - |
| dc.date.available | 2023-11-09 | - |
| dc.date.copyright | 2023-07-24 | - |
| dc.date.issued | 2023 | - |
| dc.date.submitted | 2023-05-29 | - |
| dc.identifier.citation | Aburumman, O. J., Omar, K., Al Shbail, M., & Aldoghan, M. (2023). How to Deal with the Results of PLS-SEM? In B. Alareeni & A. Hamdan (Eds.), Explore Business, Technology Opportunities and Challenges After the Covid-19 Pandemic (Vol. 495, pp. 1196–1206). Springer International Publishing. https://doi.org/10.1007/978-3-031-08954-1_101
Afonso, C. M., Roldán, J. L., & Sánchez-Franco, M. (2012). The moderator role of Gender in the Unified Theory of Acceptance and Use of Technology (UTAUT): A study on users of Electronic Document Management Systems. Alghamdi, A. M., Alsuhaymi, D. S., Alghamdi, F. A., Farhan, A. M., Shehata, S. M., & Sakoury, M. M. (2022). University students’ behavioral intention and gender differences toward the acceptance of shifting regular field training courses to e-training courses. Education and Information Technologies, 27(1), 451–468. https://doi.org/10.1007/s10639-021-10701-1 Analysis INN. (2020, February 27). Discriminant Validity through Fornell-Larcker Criterion. Analysis INN. https://www.analysisinn.com/post/discriminant-validity-through-fronell-larcker-criterion/ Angelakis, E., Azhar, E. I., Bibi, F., Yasir, M., Al-Ghamdi, A. K., Ashshi, A. M., Elshemi, A. G., & Raoult, D. (2014). Paper money and coins as potential vectors of transmissible disease. Future Microbiology, 9(2), 249–261. https://doi.org/10.2217/fmb.13.161 Arning, K., & Ziefle, M. (2007). Understanding age differences in PDA acceptance and performance. Computers in Human Behavior, 23(6), 2904–2927. https://doi.org/10.1016/j.chb.2006.06.005 Aseng, A. C. (2020). Factors Influencing Generation Z Intention in Using FinTech Digital Payment Services. CogITo Smart Journal, 6(2), 155–166. https://doi.org/10.31154/cogito.v6i2.260.155-166 Bank of Thailand. (2020, July). PromptPay: The Game Changer for Payments. https://www.bot.or.th:443/Thai/BOTMagazine/Pages/256303_TheKnowledge_PromptPay.aspx Bank of Thailand, & Hothai, C. (2021). Payment systems report. Bank of Thailand. Banks.am. (2022). History of contactless payments: From past century to the present day. Banks.Am. https://banks.am/en/news/fintech/22668 Bansal, H. S. (2005). “Migrating” to New Service Providers: Toward a Unifying Framework of Consumers’ Switching Behaviors. Journal of the Academy of Marketing Science, 33(1), 96–115. https://doi.org/10.1177/0092070304267928 Bonem, E., Ellsworth, P., & Gonzalez, R. (2015). Age Differences in Risk: Perceptions, Intentions and Domains. Journal of Behavioral Decision Making, 28. https://doi.org/10.1002/bdm.1848 Buchanan, J., Dillon, S., & Al-Otaibi, K. (2014). Perceived Risk and Online Shopping Intention: A Study Across Gender and Product Type. International Journal of E-Business Research, 10, 17–39. https://doi.org/10.4018/ijebr.2014100102 Buddhika, D. (2018, May 7). How Apple Pay Works Under the Hood. FreeCodeCamp.Org. https://www.freecodecamp.org/news/how-apple-pay-works-under-the-hood-8c3978238324/ Carlson, K. D., & Herdman, A. O. (2012). Understanding the Impact of Convergent Validity on Research Results. Organizational Research Methods, 15(1), 17–32. https://doi.org/10.1177/1094428110392383 Castañeda, J. A., Muñoz-Leiva, F., & Luque, T. (2007). Web Acceptance Model (WAM): Moderating effects of user experience. Information & Management, 44(4), 384–396. https://doi.org/10.1016/j.im.2007.02.003 CH7 news. (2022, June 12). ผู้เสียหาย ร้องแอปฯ ช็อปปิงออนไลน์ ตัดเงินในบัญชี. CH7 Thailand. https://news.ch7.com/detail/609684 Chang, C.-M., Liu, L.-W., Huang, H.-C., & Hsieh, H.-H. (2019). Factors Influencing Online Hotel Booking: Extending UTAUT2 with Age, Gender, and Experience as Moderators. Information, 10(9), 281. https://doi.org/10.3390/info10090281 Chang, I.-C., Liu, C.-C., & Chen, K. (2014). The push, pull and mooring effects in virtual migration for social networking sites: Virtual migration for social networking sites. Information Systems Journal, 24(4), 323–346. https://doi.org/10.1111/isj.12030 Changchit, C., Lonkani, R., & Sampet, J. (2017). Mobile banking: Exploring determinants of its adoption. Journal of Organizational Computing and Electronic Commerce, 27(3), 239–261. https://doi.org/10.1080/10919392.2017.1332145 Changchit, C., Lonkani, R., & Sampet, J. (2018). Determinants of Mobile Banking Adoption: A Comparative Study Between U.S. and Thailand. Journal of Global Information Management, 26(4), 158–184. https://doi.org/10.4018/JGIM.2018100109 Chapree, C. (2022, October 5). ShopeePay Malaysia To Discontinue Withdrawal To Bank Account Feature. Lowyat.NET. https://www.lowyat.net/2022/286126/shopeepay-malaysia-withdrawal-dc/ Chen, C.-C. B., Chen, H., & Wang, Y.-C. (2022). Cash, credit card, or mobile? Examining customer payment preferences at chain restaurants in Taiwan. Journal of Foodservice Business Research, 25(2), 148–167. https://doi.org/10.1080/15378020.2021.1934251 Dynata, LLC. (2020). Global consumer trends: The COVID-19 Edition. European Payments Council. (2017). Mobile proximity payments. European Payments Council. https://www.europeanpaymentscouncil.eu/what-we-do/other-sepa-payments/sepa-goes-mobile/mobile-proximity-payments Faqih, K. M. S., & Jaradat, M.-I. R. M. (2021). Integrating TTF and UTAUT2 theories to investigate the adoption of augmented reality technology in education: Perspective from a developing country. Technology in Society, 67, 101787. https://doi.org/10.1016/j.techsoc.2021.101787 Goswami, A., & Dutta, S. (2016). Gender Differences in Technology Usage—A Literature Review. Open Journal of Business and Management, 04(01), 51–59. https://doi.org/10.4236/ojbm.2016.41006 Hair, J., & Alamer, A. (2022). Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example. Research Methods in Applied Linguistics, 1(3), 100027. https://doi.org/10.1016/j.rmal.2022.100027 Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203 Hair, J., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2014). A Primer on Partial Least Squares Structural Equation Modeling. Hillingdon, A. Y., Flecther, J., & Prideaux, B. (2012). Tourism Development in a Difficult Environment: A Study of Consumer Attitudes, Travel Risk Perceptions and the Termination of Demand. Tourism Economics, 18. https://doi.org/10.5367/te.2012.0162 Humbani, M., & Wiese, M. (2019). An integrated framework for the adoption and continuance intention to use mobile payment apps. International Journal of Bank Marketing, 37(2), 646–664. https://doi.org/10.1108/IJBM-03-2018-0072 Imtiaz, S. (2018). The Studies of Unified Theory of Acceptance and Use of Technology (UTAUT) in M-Commerce Context. International Journal of Information Communication Technology and Digital Convergence, 3, 42–56. Intarot, P., & Beokhaimook, C. (2018). Influencing Factor in E-Wallet Acceptant and Use. International Journal of Business and Administrative Studies, 4(4), 167–175. Iqbal, J., & Idrees, M. (2022). Understanding the IOT Adoption for Home Automation in the Perspective of UTAUT2. Global Business Review, 097215092211320. https://doi.org/10.1177/09721509221132058 Izkair, A. S., & Lakulu, M. M. (2021). Experience moderator effect on the variables that influence intention to use mobile learning. Bulletin of Electrical Engineering and Informatics, 10(5), 2875–2883. https://doi.org/10.11591/eei.v10i5.3109 Jayarathne, P. G. S. A., Chathuranga, B. T. K., Dewasiri, N. J., & Rana, S. (2022). Motives of mobile payment adoption during COVID-19 pandemic in Sri Lanka: A holistic approach of both customers’ and retailers’ perspectives. South Asian Journal of Marketing, 4(1), 51–73. https://doi.org/10.1108/SAJM-03-2022-0013 Kang, K., Wang, T., Chen, S., & Su, Y.-S. (2021). Push-Pull-Mooring Analysis of Massive Open Online Courses and College Students During the COVID-19 Pandemic. Frontiers in Psychology, 12, 755137. https://doi.org/10.3389/fpsyg.2021.755137 Karjaluoto, H., Shaikh, A. A., Leppäniemi, M., & Luomala, R. (2019). Examining consumers’ usage intention of contactless payment systems. International Journal of Bank Marketing, 38(2), 332–351. https://doi.org/10.1108/IJBM-04-2019-0155 Kastrenakes, J. (2014, September 3). ISIS mobile wallet changes name to Softcard to avoid association with militant group. The Verge. https://www.theverge.com/2014/9/3/6101035/isis-rebrands-as-softcard-to-avoid-association-with-militant-group Kim, M., Kim, S., & Kim, J. (2019). Can mobile and biometric payments replace cards in the Korean offline payments market? Consumer preference analysis for payment systems using a discrete choice model. Telematics and Informatics, 38, 46–58. https://doi.org/10.1016/j.tele.2019.02.003 Koul, S., & Eydgahi, A. (2017). A systematic review of technology adoption frameworks and their applications. Journal of Technology Management & Innovation, 12(4), 106–113. https://doi.org/10.4067/S0718-27242017000400011 Lake, L. (2019, January 14). Learn About Perceived Risk and How to Overcome It With Messaging. LiveAbout. https://www.liveabout.com/what-is-perceived-risk-2295541 LauraCS. (2023, February 27). Multiple-Group Analysis in Structural Equation Modeling. JMP User Community. https://community.jmp.com/t5/JMP-Blog/Multiple-Group-Analysis-in-Structural-Equation-Modeling/ba-p/604714 Lee, E. S. (1966). A Theory of Migration. Leesa-nguansuk, S. (2021, September 23). NCSA investigates two data leakage episodes. Bangkok Post. https://www.bangkokpost.com/business/2186279/ncsa-investigates-two-data-leakage-episodes Limayem, Hirt, & Cheung. (2007). How Habit Limits the Predictive Power of Intention: The Case of Information Systems Continuance. MIS Quarterly, 31(4), 705. https://doi.org/10.2307/25148817 Ma, Q., Chan, A. H. S., & Teh, P.-L. (2021). Insights into Older Adults’ Technology Acceptance through Meta-Analysis. International Journal of Human–Computer Interaction, 37(11), 1049–1062. https://doi.org/10.1080/10447318.2020.1865005 Macedo, I. M. (2017). Predicting the acceptance and use of information and communication technology by older adults: An empirical examination of the revised UTAUT2. Computers in Human Behavior, 75, 935–948. https://doi.org/10.1016/j.chb.2017.06.013 MacKenzie, S. B., & Podsakoff, P. M. (2012). Common Method Bias in Marketing: Causes, Mechanisms, and Procedural Remedies. Journal of Retailing, 88(4), 542–555. https://doi.org/10.1016/j.jretai.2012.08.001 Marikyan, D. (2021). Unified Theory of Acceptance and Use of Technology. https://open.ncl.ac.uk/ Martins, M., Farias, J. S., Albuquerque, P. H. M., & Pereira, D. S. (2018). Adoption of Technology for Reading Purposes: A Study of E-Books Acceptance. BBR. Brazilian Business Review, 15(6), 568–588. Mastercard. (2011, July 19). Isis Forms Relationships with Visa, MasterCard, Discover and American Express. MasterCard Social Newsroom. https://newsroom.mastercard.com/press-releases/isis-forms-relationships-with-visa-mastercard-discover-and-american-express/ Moon, B. (1995). Paradigms in migration research: Exploring “moorings” as a schema. Progress in Human Geography, 19(4), 504–524. https://doi.org/10.1177/030913259501900404 Moorthy, K., Tzu Yee, T., Chun T’ing, L., & Vija Kumaran, V. (2019). Habit and hedonic motivation are the strongest influences in mobile learning behaviours among higher education students in Malaysia. Australasian Journal of Educational Technology, 35(4). https://doi.org/10.14742/ajet.4432 Morosan, C., & DeFranco, A. (2016). It’s about time: Revisiting UTAUT2 to examine consumers’ intentions to use NFC mobile payments in hotels. International Journal of Hospitality Management, 53, 17–29. https://doi.org/10.1016/j.ijhm.2015.11.003 Mortimer, G., Neale, L., Hasan, S. F. E., & Dunphy, B. (2015). Investigating the factors influencing the adoption of m-banking: A cross cultural study. International Journal of Bank Marketing, 33(4), 545–570. https://doi.org/10.1108/IJBM-07-2014-0100 Mu, H.-L., & Lee, Y.-C. (2022). Will proximity mobile payments substitute traditional payments? Examining factors influencing customers’ switching intention during the COVID-19 pandemic. International Journal of Bank Marketing, 40(5), 1051–1070. https://doi.org/10.1108/IJBM-06-2021-0284 Namabira, J. (2022). Gender and Perceived Usefulness of e-HRM Technologies. A Case of the Bankers’ Experience in Tanzania. TEXILA INTERNATIONAL JOURNAL OF MANAGEMENT, 8(1), 132–138. https://doi.org/10.21522/TIJMG.2015.08.01.Art010 Ohman, S. (2017). Previous Experiences and Risk Perception: The Role of Transference. Journal of Education, Society and Behavioural Science, 23, 1–10. https://doi.org/10.9734/JESBS/2017/35101 Oliveira, T., Faria, M., Thomas, M. A., & Popovič, A. (2014). Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM. International Journal of Information Management, 34(5), 689–703. https://doi.org/10.1016/j.ijinfomgt.2014.06.004 Ong, C.-S., & Lai, J.-Y. (2006). Gender differences in perceptions and relationships among dominants of e-learning acceptance. Computers in Human Behavior, 22(5), 816–829. https://doi.org/10.1016/j.chb.2004.03.006 Owusu Kwateng, K., Osei Atiemo, K. A., & Appiah, C. (2019). Acceptance and use of mobile banking: An application of UTAUT2. Journal of Enterprise Information Management, 32(1), 118–151. https://doi.org/10.1108/JEIM-03-2018-0055 PayPal Inc. (2020, September 1). The rise of contactless payments for health and safety—Zettle Blog. https://blog.zettle.com/gb/news-trends/rise-of-contactless-payments/ Prastiawan, D. I., Aisjah, S., & Rofiaty, R. (2021). The Effect of Perceived Usefulness, Perceived Ease of Use, and Social Influence on the Use of Mobile Banking through the Mediation of Attitude Toward Use. Asia Pacific Management and Business Application, 009(03), 243–260. https://doi.org/10.21776/ub.apmba.2021.009.03.4 PricewaterhouseCoopers. (2022, September 20). Payments 2025 and Beyond. PwC. https://www.pwc.com/gx/en/industries/financial-services/publications/financial-services-in-2025/payments-in-2025.html Purohit, S., & Arora, R. (2021). Role of gender on Intention to adopt mobile payments among generation Z. Transnational Marketing Journal, 9(1). https://doi.org/10.33182/tmj.v9i1.1011 Reibstein, D., Bradlow, E., & Zhang, Z. J. (2014, August 13). Why Consumers Aren’t Buying the Idea of Mobile Wallets – Yet. Knowledge at Wharton. https://knowledge.wharton.upenn.edu/article/consumers-arent-buying-mobile-wallets-yet/ Sara, L. (2021, September 8). Proximity mobile pay is on the rise worldwide—Insider Intelligence Trends, Forecasts & Statistics. https://www.insiderintelligence.com/content/proximity-mobile-pay-on-rise-worldwide Schmitz, A., Díaz-Martín, A. M., & Yagüe Guillén, M. J. (2022). Modifying UTAUT2 for a cross-country comparison of telemedicine adoption. Computers in Human Behavior, 130, 107183. https://doi.org/10.1016/j.chb.2022.107183 Schomakers, E.-M., Lidynia, C., Vervier, L. S., Valdez, A. C., & Ziefle, M. (2022). Applying an Extended UTAUT2 Model to Explain User Acceptance of Lifestyle and Therapy Mobile Health Apps: Survey Study. JMIR MHealth and UHealth, 10(1), e27095. https://doi.org/10.2196/27095 Souiden, N., Ladhari, R., & Chaouali, W. (2020). Mobile banking adoption: A systematic review. International Journal of Bank Marketing, 39(2), 214–241. https://doi.org/10.1108/IJBM-04-2020-0182 Tamilmani, K., Rana, N. P., Wamba, S. F., & Dwivedi, R. (2021). The extended Unified Theory of Acceptance and Use of Technology (UTAUT2): A systematic literature review and theory evaluation. International Journal of Information Management, 57, 102269. https://doi.org/10.1016/j.ijinfomgt.2020.102269 ThaiPublica. (2021, February 11). คนไทยใช้โมบายแบงกิ้งอันดับ 1 ของโลก—ThaiPublica. https://thaipublica.org/2021/02/thais-using-mobile-banking-is-the-worlds-highest/ The Nation Thailand. (2023, January 19). Scale of Thai cybercrime revealed as almost 60,000 bank accounts frozen. Nationthailand. https://www.nationthailand.com/thailand/general/40024161 Tseng, T. H., Lin, S., Wang, Y.-S., & Liu, H.-X. (2022). Investigating teachers’ adoption of MOOCs: The perspective of UTAUT2. Interactive Learning Environments, 30(4), 635–650. https://doi.org/10.1080/10494820.2019.1674888 Upadhyay, N., Upadhyay, S., Abed, S. S., & Dwivedi, Y. K. (2022). Consumer adoption of mobile payment services during COVID-19: Extending meta-UTAUT with perceived severity and self-efficacy. International Journal of Bank Marketing, 40(5), 960–991. https://doi.org/10.1108/IJBM-06-2021-0262 Venkatesh, Morris, Davis, & Davis. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425. https://doi.org/10.2307/30036540 Venkatesh, Thong, & Xu. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157. https://doi.org/10.2307/41410412 Venkatesh, V., & Morris, M. G. (2000). Why Don’t Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior. MIS Quarterly, 24(1), 115. https://doi.org/10.2307/3250981 Venkatesh, V., Thong, J., Hong Kong University of Science and Technology, Xu, X., & The Hong Kong Polytechnic University. (2016). Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead. Journal of the Association for Information Systems, 17(5), 328–376. https://doi.org/10.17705/1jais.00428 Verkijika, S. F. (2018). Factors influencing the adoption of mobile commerce applications in Cameroon. Telematics and Informatics, 35(6), 1665–1674. https://doi.org/10.1016/j.tele.2018.04.012 Wang, G., & Shin, C. (2022). Influencing Factors of Usage Intention of Metaverse Education Application Platform: Empirical Evidence Based on PPM and TAM Models. Sustainability, 14(24), 17037. https://doi.org/10.3390/su142417037 Warren, C. (2011, May 26). Google Reveals Mobile Payment System: Google Wallet. Mashable. https://mashable.com/archive/google-mobile-payment-system-liveblog Windasari, N. A., Kusumawati, N., Larasati, N., & Amelia, R. P. (2022). Digital-only banking experience: Insights from gen Y and gen Z. Journal of Innovation & Knowledge, 7(2), 100170. https://doi.org/10.1016/j.jik.2022.100170 Wu, J., Zeng, M., & Xie, K. L. (2017). Chinese travelers’ behavioral intentions toward room-sharing platforms: The influence of motivations, perceived trust, and past experience. International Journal of Contemporary Hospitality Management, 29(10), 2688–2707. https://doi.org/10.1108/IJCHM-08-2016-0481 Yang, X., Yang, J., Hou, Y., Li, S., & Sun, S. (2023). Gamification of mobile wallet as an unconventional innovation for promoting Fintech: An fsQCA approach. Journal of Business Research, 155, 113406. https://doi.org/10.1016/j.jbusres.2022.113406 Yu, S.-Y., & Chen, D. C. (2022). Consumers’ Switching from Cash to Mobile Payment under the Fear of COVID-19 in Taiwan. Sustainability, 14(14), 8489. https://doi.org/10.3390/su14148489 | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/87855 | - |
| dc.description.abstract | 本研究調查了促使泰國人從傳統支付轉向近距離移動支付 (PMP) 的關鍵因素。與之前專注於 TAM、UTAUT 和 UTAUT2 等採用模型的研究不同，本研究採用獨特的“轉換”方法，考慮從傳統支付方式的過渡。該研究是在大流行後時期進行的，為尋求在大流行後環境中促進 PMP 使用的泰國企業和公共組織提供了新的見解和啟示。該研究模型是基於遷移理論和反映切換行為的UTAUT2形成的。我們從泰國的樣本中收集數據，並使用 PLS-SEM 分析數據，以調查基於 168 個響應的變量之間的因果關係。結果表明，習慣對轉換意圖的影響最大，這與現有研究一致。相反，結果提出了一個新的決定因素：對傳統支付方式的不滿。此外，我們發現性別會調節績效預期，從而導致與女性相比，男性的影響力更大。相反，努力預期被發現只影響女性。這項研究有一些啟示。首先，該研究建議 PMP 公司應建立一種機制，不斷提醒用戶使用 PMP。其次，宣傳使用 PMP 對健康安全的好處可以促進採用。最後，推廣 PMP 的優勢（例如更快的支付）可以幫助吸引男性用戶，簡化的用戶體驗和用戶界面也可以吸引女性。這項研究也有一些局限性。本研究使用便利抽樣，我們沒有區分接觸率不同的案例和銀行卡。 | zh_TW |
| dc.description.abstract | This study investigates the key factors that drive Thai people from traditional payments to proximity mobile payment (PMP). Unlike previous studies that focused on adoption models like TAM, UTAUT, and UTAUT2, this research takes a unique "switching" approach that considers the transition from traditional payment methods. Conducted during the post-pandemic period, the study offers new insights and implications for Thai businesses and public organizations seeking to promote PMP usage in the post-pandemic environment. The research model was formed based on migration theory and UTAUT2 reflecting the switching behavior. We collected data from sample in Thailand and analyzed the data using PLS-SEM to investigate causal relationship between variables based on 168 responses. Result indicated that habit has the strongest influence on switching intention which is found to be aligned with existing studies. On the contrary, the result presented a new determinant: dissatisfaction with traditional payments. Also, we found that gender moderates performance expectations leading to higher influence in males compared to females. On the contrary, effort expectancy was found to influence only females. There are some implications to this study. Firstly, the study suggests that PMP firms should create a mechanism that constantly reminds users to use the PMP. Secondly, communicating health safety benefit from using PMP could promote adoption. Lastly, promoting PMP benefit such as faster payment could help to attract male users and simplified UX and UI could also attract females. This study also has some limitations. This study used convenience sampling and we did not differentiate between cases and bank cards, which have different contact rates. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2023-07-24T16:06:56Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2023-07-24T16:06:56Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | Table of Contents
Acknowledgment I Abstract II Table of Contents III Figures and Table List V Chapter 1: Introduction 1 1.1Research Background 1 1.2Scope of The Research 2 1.3Importance & Significance of The Research 2 1.4Research Overview 3 Chapter 2: Literature Review 4 2.1 Proximity Mobile Payment (PMP) 4 2.2 Proximity Mobile Payment Usage Trend. 5 2.3 Proximity Mobile Payment Development in Thailand. 6 2.4 Existing Research 7 2.5 Theoretical Background 8 2.5 Research Model Hypotheses Development 17 Chapter 3: Methodology 20 3.1 Research Design 20 3.2 Research Process 20 3.3 Data Collection 21 3.4 Descriptive Analysis 22 3.5 Data Analysis 25 Chapter 4: Research Finding 29 4.1 Measurement Model Analysis (Outer Model) 29 4.2 Multi-Collinearity Assessment 31 4.3 Assessment of Structural Model 31 4.4 Coefficients of Determination (R2 and adjusted R2) 32 4.5 Effect Size (f2) 32 4.6 Moderation Effect Analysis 33 Chapter 5: Interpretation & Conclusion 36 5.1 Theoretical Implication 36 5.2 Managerial Implication 39 5.3 Conclusion 41 5.4 Limitations 41 Appendixes 56 | - |
| dc.language.iso | en | - |
| dc.title | 在泰國近距離行動支付足以取代傳統支付方式嗎？論近距離行動支付的使用誘因 | zh_TW |
| dc.title | Will PMP (Proximity Mobile Payment) substitute traditional payment in Thailand?: A study on key factors of switching intention from traditional payment to PMP. | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 111-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.coadvisor | 孔令傑 | zh_TW |
| dc.contributor.coadvisor | Ling-Chieh Kung | en |
| dc.contributor.oralexamcommittee | 許文馨;堯里昂 | zh_TW |
| dc.contributor.oralexamcommittee | Wen-Hsin Hsu;Leon van Jaarsveldt | en |
| dc.subject.keyword | 就近移動支付,傳統支付,遷徙論,UTAUT2, | zh_TW |
| dc.subject.keyword | Proximity mobile payment,Traditional payment,Migration theory,UTAUT2, | en |
| dc.relation.page | 57 | - |
| dc.identifier.doi | 10.6342/NTU202300901 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2023-05-30 | - |
| dc.contributor.author-college | 管理學院 | - |
| dc.contributor.author-dept | 企業管理碩士專班 | - |
| 顯示於系所單位： | 管理學院企業管理專班(Global MBA) | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-111-2.pdf | 1.41 MB | Adobe PDF | 檢視/開啟 |
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