Usage Intention of RFID System in Toll Payment among Klang Valley Residents

Aburbeian, A. M., Owda, A. Y., & Owda, M. A. (2022). Technology Acceptance Model survey of the metaverse prospects. AI, 3, 285-302. https://doi.org/10.3390/ai3020018
Adams, D. A., Nelson, R. R., & Todd, P. A. (1992). Perceived usefulness, ease of use, and usage of information technology: A replication. MIS Quarterly, 16(2) 227-247. https://doi.org/10.2307/249577
Agarwal, R., Sambamurthy, V., & Stair, R. M. (2000). The evolving relationship between general and specific computer self-efficacy: An empirical assessment. Information Systems Research, 11(4), 418-430. https://doi.org/10.1287/isre.11.4.418.11876
Ahmed, S., Tan, T. M., Mondol, A. M., Alam, Z., Nawal, N., & Uddin, J. (2019). Automated Toll Collection System Based on RFID Sensor. 2019 International Carnahan Conference on Security Technology (ICCST), 1-3. https://doi.org/10.1109/CCST.2019.8888429
Ajzen, I. (1991). The Theory of Planned Behaviour. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749- 5978(91)90020-T.
Aljaraideh, Y. (2019). Students’ perception of flipped classroom: A case study for private universities in Jordan. JOTSE: Journal of Technology and Science Education, 9(3), 368-377. https://doi.org/10.3926/jotse648
Bari, C. S., Navandar, Y. V., & Dhamaniya, A. (2022). Delay modelling at manually operated toll plazas under mixed traffic conditions. International Journal of Transportation Science and Technology, 11(1), 17-31. https://doi.org/10.1016/j.ijtst.2020.10.001.
Belanche, D., Flavián, M., & Pérez-Rueda, A. (2020). Mobile apps use and wom in the food delivery sector: The Role of planned behavior, perceived security and customer lifestyle compatibility. Sustainability, 12(10), 4275. http://dx.doi.org/10.3390/su12104275
Brennand, C. A. R. L., Filho, G. P. R., Maia, G., Cunha, F., Guidoni, D. L., & Villas, L. A. (2019). Towards a fog-enabled intelligent transportation system to reduce traffic jam. Sensors, 19(18), 3916. https://doi.org/10.3390/s19183916
Brückmann, G. (2022). The effects of policies providing information and trialing on the knowledge about and the intention to adopt new energy technologies. Energy Policy, 167, 113047. https://doi.org/10.1016/j.enpol.2022.113047
Buvaneswari, P. S., Swetha, M. S., Ragetha, T., & Nisha, D. (2021). Technology at doorstep: Consumer perception on food delivery aggregators. Materials Today: Proceedings. https://doi.org/10.1016/j.matpr.2021.01.735
Casella, G., Bigliardi, B. & Bottani, E. (2022). The evolution of RFID technology in the logistics field: A review. Procedia Computer Science, 200, 1582-1592. https://doi.org/10.1016/j.procs.2022.01.359.
Chattoraj, S., Bhowmik, S., Vishwakarma K., & Roy, P. (2017). Design and implementation of low-cost electronic toll collection system in India. 2017 Second International Conference on Electrical, Computer and Communication Technologies (ICECCT), 1-4. https://doi.org/10.1109/ICECCT.2017.8117934
Cheng, E. W. L. (2019). Choosing between the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM). Education Technology Research and Development, 67, 21–37. https://doi.org/10.1007/s11423-018-9598-6
Cheng, V. & Guo, R. (2021). The impact of consumers’ attitudes towards technology on the acceptance of hotel technology-based innovation. Journal of Hospitality and Tourism Technology, 12(4), 624-640.http://dx.doi.org/10.1108/JHTT-06-2020-0145
Das, A. K., & Mishra, S. (2016). Questionnaire for Survey of Technology-Enabled Learning in Educational Institutions. In A. Kirkwook & L. Price. Technology-Enabled Learning Implementation Handbook (ed.). Commonwealth of Learning
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. Retrieved from https://globalassistant.info/wp- content/uploads/2022/03/Technology-Acceptance- Model-Davis-1989- PDF.pdf
Edison, S., & Geissler, G. (2003). Measuring attitudes towards general technology: Antecedents, hypotheses and scale development. Journal of Targeting, Measurement, and Analysis for Marketing, 12, 137-156. https://doi.org/10.1057/palgrave.jt.5740104
Fletcher-Brown, J., Carter, D., Pereira, V. & Chandwani, R. (2021). Mobile technology to give a resource-based knowledge management advantage to community health nurses in an emerging economies context. Journal of Knowledge Management, 25(3), 525-544. https://doi.org/10.1108/JKM-01-2020-0018
Gantulga, U., Sample, B., & Tugsbat, A. (2022). Predicting RFID adoption towards urban smart mobility in Ulaanbaatar, Mongolia. Asia Marketing Journal, 24(1), 2. https://doi.org/10.53728/2765-6500.1584
Gefen, D. (2000). E-commerce: The role of familiarity and trust. Omega, 28(6), 725- 737. https://doi.org/10.1016/S0305-0483(00)00021-9
Guo, A., Zhao, J., Zhao, X., Zhou, M., Kong, W., & Zhou, T. (2021). Research on the economic impact of Shandong Expressway Development. Urban Transport Systems, 2(1), 1-9. http://dx.doi.org/10.23977/uts.2021.020101
Hair, J., Black, W., Babin, B., Anderson, R., & Tatham, R. (2006). Multivariate Data Analysis. 6th Edition. Pearson Prentice Hall, Upper Saddle River.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial Least Squares Structural Equation Modeling: Rigorous Applications, Better Results and Higher Acceptance. Long Range Planning, 46,1-12. https://doi.org/10.1016/j.lrp.2013.01.001
Hidayat, R., & Akhmad, S. (2021). Radio Frequency Identification (RFID) application analysis on E-toll in Indonesia. IOP Conference Series. Materials Science and Engineering, 1125(1), 012050. https://doi.org/10.1088/1757-899x/1125/1/012050
Huang, X., Lin, Y., Lim, M. K., Tseng, M. L. & Zhou, F. (2021). The influence of knowledge management on adoption intention of electric vehicles: Perspective on technological knowledge. Industrial Management and Data Systems. http://dx.doi.org/10.1108/IMDS-07-2020-0411
Johnson, A. M., Jacovina, M. E., Russell, D. G., & Soto, C. M. (2016). Challenges and Solutions when Using Technologies in the Classroom. In Adaptive Educational Technologies for Literacy Instruction, 13–30. Retrieved from
https://files.eric.ed.gov/fulltext/ED577147.pdf
Kim, J. Y., Choi, D. S., Sung, C.-S., & Park, J. Y. (2018). The role of problem-solving ability on innovative behavior and opportunity recognition in university students. Journal of Open Innovation: Technology, Market, and Complexity, 4(1). http://dx.doi.org/10.1186/s40852-018-0085-4
Kotrlik, J. W. & Higgins, C. C. (2001). Organizational research: Determining appropriate sample size in survey research appropriate sample size in survey research. Information Technology, Learning, and Performance Journal, 19(1), 43. Retrieved from https://www.opalco.com/wp- content/uploads/2014/10/Reading-Sample-Size1.pdf
Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610.
https://doi.org/10.1177/001316447003000308
Kwon, S. (2022). Interdisciplinary knowledge integration as a unique knowledge source for technology development and the role of funding allocation. Technological Forecasting and Social Change, 181, 121767. https://doi.org/10.1016/j.techfore.2022.121767
Lai, C. H., Hsiao, P. K., Yang, Y. T., Lin, S. M. & Lung, S. C. C. (2021). Effects of the manual and electronic toll collection systems on the particulate pollutant levels on highways in Taiwan. Atmospheric Pollution Research, 12(3), 25- 32.
https://doi.org/10.1016/j.apr.2021.01.020.
Lederer, A. L., Maupin, D. J., Sena, M. P., & Zhuang, Y. (2000). The Technology Acceptance Model and the World Wide Web. Decision Support Systems, 29(3), 269-282. https://doi.org/10.1016/S0167-9236(00)00076-2
Lee, J. & Park, K. (2022). Consumer response to the radio frequency identification (RFID) technology-based self-service beauty specialty store: Moderating effects of consumer traits. International Textile and Apparel Association Annual Conference Proceedings, 78(1). https://doi.org/10.31274/itaa.13714
Li, L., Wang, Z., Li, Y., & Liao, A. (2021). Consumer innovativeness and organic food adoption: The mediation effects of consumer knowledge and attitudes. Sustainable Production and Consumption, 28, 1465-1474. https://doi.org/10.1016/j.spc.2021.08.022
Liu, T. P., Chen, Y. Y. & Yu, J. Y. (2021). Implementation and evaluation of mobile shopping services based on RFID sensing technology. Sensors and Materials, 33(5), 1501. http://dx.doi.org/10.18494/SAM.2021.3194
Madsen, P. & Desai, V.M. (2010). Failing to learn? The effects of failure and success on organizational learning in the global orbital launch vehicle industry. The Academy of Management Journal, 53(3), 451-476.
McCormick, R. (2004). Issues of learning and knowledge in technology education. International Journal of Technology and Design Education. 14. 21-44. http://dx.doi.org/10.1023/B:ITDE.0000007359.81781.7c
New Straits Times. (2022). RFID Lanes Available at Juru-Skudai NSE Stretch from Jan 15. Retrieved from https://www.nst.com.my/news/nation/2022/01/762662/rfid-lanes- available- juru-skudai-nse-stretch-jan-15
Nguyen, D. H., Zomorrodi, M. & Karmakar, N. C. (2019). Spatial-based chipless RFID System. IEEE Journal of Radio Frequency Identification, 3(1), 46-55.
https://doi.org/10.1109/JRFID.2018.2887162
Nolder, C. J., & Kadous, K. (2018). Grounding the professional skepticism construct in mindset and attitude theory: A way forward. Accounting, Organizations and Society. 67, 1-14. https://doi.org/10.1016/j.aos.2018.03.010.
Norusis, M. J. (1992). SPSS for Windows: Base System User's Guide, Release 5.0. SPSS Incorporated.
Nunnally, J. C. (1978). Psychometric Theory, 2nd edition. McGraw-Hill College.
Ovezmyradov, B., & Kurata, H. (2022). omnichannel fulfillment and item-level rfid tracking in Fashion Retailing. Computers and Industrial Engineering, 168, 108108.https://doi.org/10.1016/j.cie.2022.108108.
Paaske, S., Bauer, A., Moser, T., & Seckman, C. (2017). The Benefits and Barriers to RFID Technology in Healthcare. On-line Journal of Nursing Informatics. Retrieved from https://www.proquest.com/scholarly-journals/benefits-barriers-rfid-technology-healthcare/docview/1984766816/se-2
Palka, D., Brodny, J., & Stecu?a, K. (2017). Modern Means of Production and the Staff Awareness of the Technical in the Plant of the Mining Industry. CBU International Conference Proceedings, 5, 1190.https://dx.doi.org/10.12955/cbup.v5.1094
Ping, Y., Gao, C., Liu, T., Du, X., Luo, H., Jin, D., & Li, Y. (2021). User Consumption Intention Prediction in Meituan. Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 3472-3482. https://doi.org/10.1145/3447548.3467178
Qiong, O. (2017). A brief introduction to perception. Studies in Literature and Language, 15(4), 18-28. http://dx.doi.org/10.3968/10055
van Rensburg, S., Ankiewicz, P., & Myburgh, C. P. (1999). Assessing South Africa learners’ attitudes towards technology by using the PATT (Pupils’ Attitudes Towards Technology) Questionnaire. International Journal of Technology and Design Education, 9, 137-151.
Salloum, S. A., Alhamad, A. Q. M., Al-Emran, M., Monem A. A., & Shaalan K. (2019). Exploring students’ acceptance of e-learning through the development of a comprehensive Technology Acceptance Model. IEEE Access, 7, 128445- 128462. https://doi.org/10.1109/ACCESS.2019.2939467
Scuotto, V., Beatrice, O., Valentina, C., Nicotra, M., Gioia, L. D., & Briamonte, M. F. (2020). Uncovering the micro-foundations of knowledge sharing in open innovation partnerships: An intention-based perspective of technology transfer. Technological Forecasting and Social Change, 152, 119906.
https://doi.org/10.1016/j.techfore.2019.119906.
Shirani, F., Groves, C., Henwood, K., Pidgeon, N., & Roberts, E. (2020). ‘I'm the smart meter’: Perceptions of smart technology amongst vulnerable consumers. Energy Policy, 144, 111637. https://doi.org/10.1016/j.enpol.2020.111637.
Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.
https://doi.org/10.1287/isre.6.2.144
Tsai, C.-C. (2017). Conceptions of learning in technology-enhanced learning environments: A review of case studies in Taiwan. Asian Association of Open Universities Journal, 12(2), 184-205. https://doi.org/10.1108/AAOUJ-12-2017-0038
Tseng, T. S. L., Wang, Y.-S., & Liu, H.-X. (2019). Investigating teachers’ adoption of MOOCs: The perspective of UTAUT2. Interactive Learning Environments, 30(2),1-16. https://doi: 10.1080/10494820.2019.1674888
Tomczyk, L. (2020). Attitude to ICT and self-evaluation of fluency in using new digital devices, websites and software among pre-service teachers. International Journal of Emerging Technologies in Learning (IJET), 15(19), 200. https://doi.org/10.3991/ijet.v15i19.16657
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
Vigar-Ellis, D. (2016). Consumer knowledge and its implications for aspects of consumer purchasing behaviour in the case of information-intensive products. (PhD dissertation, KTH Royal Institute of Technology). Retrieved from
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-177297
Vijayasarathy, L. R. (2004). Predicting consumer intentions to use on-line shopping: The case for an Augmented Technology Acceptance Model. Information and Management, 41, 747-762. http://dx.doi.org/10.1016/j.im.2003.08.011
Wang, X., Wong, Y. D., Chen, T., & Yuen, K. F. (2022). An investigation of technology-dependent shopping in the pandemic era: Integrating response efficacy and identity expressiveness into Theory of Planned Behaviour. Journal of Business Research, 142, 1053-1067. https://doi.org/10.1016/j.jbusres.2022.01.042
Wang, Y., Chi, Y., Xu, J. H., & Yuan, Y. (2022). Consumers’ attitudes and their effects on electric vehicle sales and charging infrastructure construction: An empirical study in China. Energy Policy, 165, 112983. https://doi.org/10.1016/j.enpol.2022.112983.
Zhang, W., He, L., & Yuan, H. (2022). Enterprises’ decisions on adopting low- carbon technology by considering consumer perception disparity. Technovation, 117, 102238. https://doi.org/10.1016/j.technovation.2021.102238
Zhang, X., Liu, S., Wang, L., Zhang, Y., and Wang, J. (2020). Mobile Health service adoption in China: Integration of Theory of Planned Behavior, Protection Motivation Theory and Personal Health Differences. Online Information Review, 44(1), 1-23. https://doi.org/10.1108/OIR-11-2016-0339

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