|
Abdullah, S. I. N. W., Samdin, Z., Ho, J. A., & Ng, S. I. (2020). Sustainability of marine parks: Is knowledge–attitude–behaviour still relevant? Environment, Development and Sustainability, 22, 7357–7384. Adu-Gyamfi, G., Song, H., Nketiah, E., Obuobi, B., Adjei, M., & Cudjoe, D. (2022). Determinants of adoption intention of battery swap technology for electric vehicles. Energy, 251. Ahmad, A., Madi, Y., Abuhashesh, M., Nusairat, N. M., & Masa’deh, R. (2020). The knowledge, attitude, and practice of the adoption of green fashion innovation. Journal of Open Innovation: Technology, Market, and Complexity 2020, Vol. 6, Page 107, 6, 107. Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action control (pp. 11–39). Ajzen, I. (1991). The theory of planned behavior. In Organizational Behavior and Human Decision Processes (Vol. 50, pp. 438–459). Ajzen, I. (2012). The theory of planned behavior. In Handbook of Theories of Social Psychology: Volume 1 (Vol. 50, pp. 438–459). Ajzen, I., Fishbein, M., & Heilbroner, R. L. (1980). Understanding attitudes and predicting social behavior (Vol. 278). Prentice-hall Englewood Cliffs, NJ. Ajzen, I., Joyce, N., Sheikh, S., & Cote, N. G. (2011). Knowledge and the prediction of behavior: The role of information accuracy in the theory of planned behavior. Basic and Applied Social Psychology, 33, 101–117. Alba, J. W., & Hutchinson, J. W. (2000). Knowledge calibration: What consumers know and what they think they know. Journal of Consumer Research, 27, 123–156. Allal, A. A., Mansouri, K., Youssfi, M., & Qbadou, M. (2018). Toward energy saving and environmental protection by implementation of autonomous ship. 2018 19th IEEE Mediterranean Electrotechnical Conference (MELECON). Al-Zoubi, M. I. (2013). Predicting e-business adoption through integrating the constructs of the rogers’s diffusion of innovation theory combined with technology-organization-environment model. International Journal of Advanced Computer Research, 3, 2277–7970. Awa, H. O., Ukoha, O., & Emecheta, B. C. (2016). Using T-O-E theoretical framework to study the adoption of ERP solution. Cogent Business and Management, 3, 1–23. Baird, A. J. (2000). The Japan coastal ferry system. Maritime Policy & Management, 27, 3–16. Bansal, P., Kockelman, K. M., & Singh, A. (2016). Assessing public opinions of and interest in new vehicle technologies: An Austin perspective. Transportation Research Part C: Emerging Technologies, 67, 1–14. Bimbraw, K. (2015). Autonomous cars: past, present and future. 2015 12th International Conference on Informatics in Control, Automation and Robotics (ICINCO), 191–198. Borhan, M. N., Ibrahim, A. N. H., & Miskeen, M. A. A. (2019). Extending the theory of planned behaviour to predict the intention to take the new high-speed rail for intercity travel in Libya: Assessment of the influence of novelty seeking, trust and external influence. Transportation Research Part A: Policy and Practice, 130, 373–384. BPS-Statistics Indonesia. (2019). Sea transportation statistics. (Subdirectorate of Transportation Statistics, Ed.). Jakarta: BPS-Statistics Indonesia. Bruzzone, A. (2012). Guidelines for ferry transportation services. Washington, D.C.: National Academies Press. https://doi.org/10.17226/14644 Buckley, L., Kaye, S. A., & Pradhan, A. K. (2018). Psychosocial factors associated with intended use of automated vehicles: A simulated driving study. Accident Analysis and Prevention, 115, 202–208. Burton-Jones, A., & Hubona, G. S. (2006). The mediation of external variables in the technology acceptance model. Information & Management, 43, 706–717. Byrne, B. M. (2016). Structural equation modeling with AMOS. Structural Equation Modeling With AMOS. Routledge. Calantone, R. J., Chan, K., & Cui, A. S. (2006). Decomposing product innovativeness and its effects on new product success. Journal of Product Innovation Management, 23, 408–421. Charness, N., Yoon, J. S., Souders, D., Stothart, C., & Yehnert, C. (2018). Predictors of attitudes toward autonomous vehicles: The roles of age, gender, prior knowledge, and personality. Frontiers in Psychology, 9. Chen, C. Der, Fan, Y. W., & Farn, C. K. (2007). Predicting electronic toll collection service adoption: An integration of the technology acceptance model and the theory of planned behavior. Transportation Research Part C: Emerging Technologies, 15, 300–311. Cheng, E. W. L. (2019). Choosing between the theory of planned behavior (TPB) and the technology acceptance model (TAM). Educational Technology Research and Development, 67, 21–37. Choi, J. K., & Ji, Y. G. (2015). Investigating the importance of trust on adopting an autonomous vehicle. International Journal of Human-Computer Interaction, 31, 692–702. Chuttur, M. (2009). Overview of the technology acceptance model: origins , developments and future directions. Sprouts: Working Papers on Information Systems, 9, 1–23. Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297–334. Czaja, S. J., Charness, N., Fisk, A. D., Hertzog, C., Nair, S. N., Rogers, W. A., & Sharit, J. (2006). Factors predicting the use of technology: Findings from the Center for Research and Education on Aging and Technology Enhancement (CREATE). Psychology and Aging, 21, 333–352. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35, 982–1003. Dieplinger, M., & Fürst, E. (2014). The acceptability of road pricing: Evidence from two studies in Vienna and four other European cities. Transport Policy, 36, 10–18. Ding, Y., Li, R., Wang, X., & Schmid, J. (2022). Heterogeneity of autonomous vehicle adoption behavior due to peer effects and prior-AV knowledge. Transportation, 49, 1837–1860. Donald, I. J., Cooper, S. R., & Conchie, S. M. (2014). An extended theory of planned behaviour model of the psychological factors affecting commuters’ transport mode use. Journal of Environmental Psychology, 40, 39–48. Drucker, P. F. (1985). Innovation and entrepreneurship practice and principles. Du, H., Liu, D., Sovacool, B. K., Wang, Y., Ma, S., & Li, R. Y. M. (2018). Who buys new energy vehicles in China? Assessing social-psychological predictors of purchasing awareness, intention, and policy. Transportation Research Part F: Traffic Psychology and Behaviour, 58, 56–69. Fahruddin, H. E. (2021, December 1). Tourism faces PPKM level 3 during Christmas, New Year holiday. Retrieved March 23, 2024, from https://www.thejakartapost.com/paper/2021/11/30/tourism-faces-ppkm-level-3-during-christmas-new-year-holiday.html Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research. Focus Taiwan. (2023, April 18). New cargo-passenger vessel to operate Taiwan-Matsu route. Retrieved February 23, 2024, from https://ocacnews.net/article/337778 Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and Measurements Error. Journal of Marketing Research, XVIII, 39–50. Garver, M. S., & Mentzer, J. T. (1999). Logistics research methods: employing structural equation modeling to test for construct validity. Journal of Business Logistics, 20, 33–57. Goerlandt, F., & Pulsifer, K. (2022). An exploratory investigation of public perceptions towards autonomous urban ferries. Safety Science, 145, 105496. Gupta, N., Fischer, A. R. H., & Frewer, L. J. (2012). Socio-psychological determinants of public acceptance of technologies: A review. Public Understanding of Science, 21, 782–795. Haboucha, C. J., Ishaq, R., & Shiftan, Y. (2017). User preferences regarding autonomous vehicles. Transportation Research Part C: Emerging Technologies, 78, 37–49. Hair, J.F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis with readings (5nd ed.). Prentice-Hall, Upper Saddle River. Hair, Joseph F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis. Ham, M., Jeger, M., & Frajman Ivković, A. (2015). The role of subjective norms in forming the intention to purchase green food. Economic Research-Ekonomska Istraživanja, 28, 738–748. Han, H. (2015). Travelers’ pro-environmental behavior in a green lodging context: Converging value-belief-norm theory and the theory of planned behavior. Tourism Management, 47, 164–177. Heath, Y. Y., & Gifford, R. (2002). Extending the theory of planned behavior: Predicting the use of public transportation. Journal of Applied Social Psychology, 32, 2154–2189. Herno Della, R., & Rachmannullah, A. F. (2021). Perspektif kepuasan penumpang dalam kualitas pelayanan kapal feri: Studi kasus pelabuhan penyeberangan Merak-Bakauheni. Cantilever: Jurnal Penelitian Dan Kajian Bidang Teknik Sipil, 10, 1–9. Horiuchi, S., & Jin, T. (1982). Human Behavior. In National Bureau of Standards, Special Publication (Vol. 55, pp. 26–30). Hsu, W. K. K., Chen, J. W., Huynh, N. T., & Lin, Y. Y. (2022). Risk assessment of navigation safety for ferries. Journal of Marine Science and Engineering, 10. IMO. (2019). Autonomous shipping. Retrieved December 13, 2019, from http://www.imo.org/en/MediaCentre/HotTopics/Pages/Autonomous-shipping.aspx Jackson, D. L. (2003). Revisiting sample size and number of parameter estimates: Some support for the N:q hypothesis. Structural Equation Modeling, 10, 128–141. Jan Rødseth, Ø. (2017). Definitions for autonomous merchant ships NFAS Norwegian forum for autonomous ships document information title definition for autonomous merchant ships. japan-guide.com. (2018). Japanese ferries (Domestic routes). Retrieved September 3, 2018, from https://www.japan-guide.com/e/e2355.html Jing, P., Huang, H., Ran, B., Zhan, F., & Shi, Y. (2019). Exploring the factors affecting mode choice intention of autonomous vehicle based on an extended theory of planned behavior-A case study in China. Sustainability (Switzerland), 11, 1–20. Joe, T., Bessant, J., & Pavitt, K. (2005). Managing innovation: integrating technological, market and organizational change. John Wiley & Sons. Jones, M. L. (2007). Hofstede-culturally questionable? Oxford Business & Economics Conference. Joseph, R. (2006). Calculated risks: The toxicity and human health risks of chemicals in our environment. News.Ge. Kaplan, S. (1991). Beyond rationality: Clarity-based decision making. Environment, Cognition, and Action: An Integrated Approach, 171–190. Kassaw, C., Pandey, · Digvijay, Pandey, D., & Abdul, A. P. J. (2020). COVID-19 pandemic related to anxiety disorder among communities using public transport at Addis Ababa, Ethiopia, March 2020: Cross-sectional Study Design. Human Arenas. Kaye, S. A., Lewis, I., Buckley, L., & Rakotonirainy, A. (2020). Assessing the feasibility of the theory of planned behaviour in predicting drivers’ intentions to operate conditional and full automated vehicles. Transportation Research Part F: Traffic Psychology and Behaviour, 74, 173–183. Kaye, S. A., Lewis, I., Forward, S., & Delhomme, P. (2020). A priori acceptance of highly automated cars in Australia, France, and Sweden: A theoretically-informed investigation guided by the TPB and UTAUT. Accident Analysis and Prevention. Kinantya, P. (2022, April 19). Rencana implementasi sarana angkutan umum autonomous berbasis energi listrik di wilayah ibu kota negara baru. Retrieved October 29, 2022, from https://baketrans.dephub.go.id/berita/rencana-implementasi-sarana-angkutan-umum-autonomous-berbasis-energi-listrik-di-wilayah-ibu-kota-negara-baru Kline, R. B. (2015). Principles and practices of structural equation modelling. Methodology in the social sciences (4th ed.). Koufteros, X. A. (1999). Testing a model of pull production: a paradigm for manufacturing research using structural equation modeling. Journal of Operations Management, 17, 467–488. Kurniawan, A., Hutapea, G., Hardianto, S., Suhartana, I. K., Yuliani, A., Putra, T. P., Siahaan, W. J., Hidayat, K., Humang, W. P., Paotonan, C., & Paroka, D. (2022). Finding a new home: rerouting of ferry ships from Merak–Bakauheni to east Indonesian trajectories. Sustainability, 15, 630. Lai, M. F., & Lo, H. K. (2004). Ferry service network design: optimal fleet size, routing, and scheduling. Transportation Research Part A: Policy and Practice, 38, 305–328. Laurinen, M. (2016). Remote and autonomous ships: The next steps. AAWA: Advanced Autonomous Waterborne Applications. Lawson, C., & Weisbrod, R. (2005). Ferry transport: The realm of responsibility for ferry disasters in developing nations. Journal of Public Transportation, 8, 17–31. Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40, 191–204. Levander, O. (2017). Autonomous ships on the high seas. IEEE Spectrum, 54, 26–31. Li, M., & Zhao, J. (2019). Gaining acceptance by informing the people? Public knowledge, attitudes, and acceptance of transportation policies. Journal of Planning Education and Research, 39, 166–183. Liao, C., Yu, H., & Zhu, W. (2020). Perceived knowledge, coping efficacy and consumer consumption changes in response to food recall. Sustainability, 12, 2696. Liao, F., Molin, E., Timmermans, H., & van Wee, B. (2019). Consumer preferences for business models in electric vehicle adoption. Transport Policy, 73, 12–24. Liljamo, T., Liimatainen, H., & Pöllänen, M. (2018). Attitudes and concerns on automated vehicles. Transportation Research Part F: Traffic Psychology and Behaviour, 59, 24–44. Lin, S. H., Lee, H. C., Chang, C. Ter, & James Fu, C. (2020). Behavioral intention towards mobile learning in Taiwan, China, Indonesia, and Vietnam. Technology in Society, 63, 101387. Lirn, T.-C., Rachmannullah, A. F., & Della, R. H. (2023). Autonomous ship: Review of concept, definition, and challenging. In AIP Conference Proceedings (Vol. 2689). Lu, C.-S., & Tseng, P.-H. (2012). Identifying crucial safety assessment criteria for passenger ferry services. Safety Science, 50, 1462–1471. Madigan, R., Louw, T., Wilbrink, M., Schieben, A., & Merat, N. (2017). What influences the decision to use automated public transport? Using UTAUT to understand public acceptance of automated road transport systems. Transportation Research Part F: Traffic Psychology and Behaviour, 50, 55–64. Maritime Port Bureau. (2024, February 21). The maritime port bureau has achieved extraordinary results in 2023 and looks forward to achieving four major goals in 2024. Retrieved February 23, 2024, from https://www.motcmpb.gov.tw/En/Information/Detail/d790658f-53ab-4a10-8147-7e4f2117203e?SiteId=2&NodeId=10014 Marsh, H. W., Hau, K.-T., & Wen, Z. (2009). Structural equation modeling in search of golden rules: Comment on hypothesis-testing approaches to setting cut off values for fit indexes and dangers in overgeneralizing Hu and Bentler’s (1999) findings. Mathew, S. (2021, May 27). Ferry planned for south Taiwan-Penghu route to transport 80 cars, 4 buses. Retrieved February 23, 2024, from https://www.taiwannews.com.tw/en/news/4211310 Mathieson. (1991). Comparing the technology acceptance model with the theory of planned behaviour. Information Systems Research, 2, 3, 173–191. Merriam-Webster. (n.d.). Ferry. Retrieved February 20, 2024, from https://www.merriam-webster.com/dictionary/ferry Min, S., So, K. K. F., & Jeong, M. (2019). Consumer adoption of the Uber mobile application: Insights from diffusion of innovation theory and technology acceptance model. Journal of Travel and Tourism Marketing, 36, 770–783. Ministry of Transportation. (2015). Strategic plan ministry of transport 2015-2019. Ministry of Transportation. (2020). Indonesian transportation statistic 2020 Vol.1. Ministry of Transportation. Pustikom-Kementrian Perhubungan. MOL. (2022). MOL and partners set world records for time and distance in autonomous navigation with sea trial using large commercial car ferry - Follows successful trial of coastal containership in autonomous sailing - | Mitsui O.S.K. Lines. Retrieved June 8, 2022, from https://www.mol.co.jp/en/pr/2022/22017.html Moons, I., & De Pelsmacker, P. (2015). An extended decomposed theory of planned behaviour to predict the usage intention of the electric car: A multi-group comparison. Sustainability, 7, 6212–6245. Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2, 192–222. Moták, L., Neuville, E., Chambres, P., Marmoiton, F., Monéger, F., Coutarel, F., & Izaute, M. (2017). Antecedent variables of intentions to use an autonomous shuttle: Moving beyond TAM and TPB? Revue Europeenne de Psychologie Appliquee, 67, 269–278. Mun, Y. Y., Jackson, J. D., Park, J. S., & Probst, J. C. (2006). Understanding information technology acceptance by individual professionals: Toward an integrative view. Information & Management, 43, 350–363. Munim, Z. H. (2019). Autonomous ships: a review, innovative applications and future maritime business models. Supply Chain Forum: An International Journal, 20, 266–279. MUNIN. (n.d.). The autonomous ship | MUNIN. Retrieved December 13, 2019, from http://www.unmanned-ship.org/munin/about/the-autonomus-ship/ Nordhoff, S., De Winter, J., Kyriakidis, M., Van Arem, B., & Happee, R. (2018). Acceptance of driverless vehicles: Results from a large cross-national questionnaire study. Journal of Advanced Transportation, 2018. Odonkor, S. T., & Adams, S. (2020). An assessment of public knowledge, perception and acceptance of nuclear energy in Ghana. Journal of Cleaner Production, 269. OECD. (2017). Public acceptance and emerging production technologies. In The Next Production Revolution (pp. 277–298). OECD. Panagiotopoulos, I., & Dimitrakopoulos, G. (2018). An empirical investigation on consumers’ intentions towards autonomous driving. Transportation Research Part C: Emerging Technologies, 95, 773–784. Park, C. W., Gardner, M. P., & Thukral, V. K. (1988). Self-perceived knowledge: Some effects on information processing for a choice task. Source: The American Journal of Psychology (Vol. 101). Retrieved from http://www.jstor.orgURL:http://www.jstor.org/stable/1423087 Park, E., & Ohm, J. Y. (2014). Factors influencing the public intention to use renewable energy technologies in South Korea: Effects of the fukushima nuclear accident. Energy Policy, 65, 198–211. Park, W., Mothersbaugh, D. L., & Feick, L. (1994). Consumer knowledge assessment. Journal of Consumer Research, 21, 71. Parkins, J. R., Rollins, C., Anders, S., & Comeau, L. (2018). Predicting intention to adopt solar technology in Canada: The role of knowledge, public engagement, and visibility. Energy Policy, 114, 114–122. Payre, W., Cestac, J., & Delhomme, P. (2014). Intention to use a fully automated car: Attitudes and a priori acceptability. Transportation Research Part F: Traffic Psychology and Behaviour, 27, 252–263. Pricilia, S. E. (2018). Model mitigasi risiko operasi pada industri penyeberangan: studi kasus lintasan penyeberangan Ketapang - Gilimanuk. Institut Teknologi Sepuluh Nopember. Retrieved from http://repository.its.ac.id/id/eprint/50521 Rachmannullah, A. F. (2019). The study on the determinants of ferry subsidy status in Indonesia (Master Thesis). 航運管理學系. 國立臺灣海洋大學, 基隆市. Retrieved from https://hdl.handle.net/11296/2x5s4a Rachmannullah, A. F., Lirn, T. C., & Shang, K. C. (2024). Exploring market segmentation for autonomous ferries. Journal of Marine Science and Technology, 32, 1–15. Roberts. (2018). Infomaritime.eu - Autonomous ships timeline (1970 - 2018). Retrieved December 13, 2019, from http://infomaritime.eu/index.php/2018/06/08/timeline-development-of-autonomous-ships/ Robertson, R. D., Meister, S. R., & Vanlaar, W. G. (2016). Automated vehicles: driver knowledge, attitudes and practices, 37p. Retrieved from http://www.tirf.ca/publications/PDF_publications/Automated Vehicles Driver Knowledge Attitudes and Practices-9.pdf Roche, M. Y., Mourato, S., Fischedick, M., Pietzner, K., & Viebahn, P. (2010). Public attitudes towards and demand for hydrogen and fuel cell vehicles: A review of the evidence and methodological implications. Energy Policy, 38, 5301–5310. Rogers, E. M. (1983). Diffusion of innovation (Third Edit). New York: The Free Press. Rogers, E. M. (1993). The diffusion of innovations model. Nato Asi Series D Behavioural and Social Sciences, 70, 9. Rogers, E. M., Singhal, A., & Quinlan, M. M. (2014). Diffusion of innovations. In An integrated approach to communication theory and research (pp. 432–448). Routledge. Rolls-Royce. (2016). Autonomous ships : The next step. Marine Ship Intelligence, 1–8. Rolls-Royce. (2018). Rolls-Royce and Finferries demonstrate world’s first fully autonomous ferry. Schönknecht, R., & Bertholdt, J. (1983). Ships and shipping of tomorrow. Cornell Maritime Press. Schreiber, J. B., Stage, F. K., King, J., Nora, A., & Barlow, E. A. (2006). Reporting structural equation modeling and confirmatory factor analysis results: A review. Journal of Educational Research. Routledge. Schwartz, N. E. (1976). Nutrition knowledge, attitudes and practices of canadian public health nurses. Journal of Nutrition Education, 8, 28–31. Shaaban, K., & Maher, A. (2020). Using the theory of planned behavior to predict the use of an upcoming public transportation service in Qatar. Case Studies on Transport Policy, 8, 484–491. Shan, S. (2021, July 30). Contract for new ferry to serve Penghu signed. Retrieved February 23, 2024, from https://www.taipeitimes.com/News/taiwan/archives/2021/07/30/2003761720 Shang, Y. Y., Chia, H. C., Hsin, Y. C., & Tze, C. Lou. (2007). Optimal scheduling models for ferry companies under alliances. Journal of Marine Science and Technology, 15, 53–66. Retrieved from http://www.airitilibrary.com/Publication/alDetailedMesh?DocID=15633470-201003-201004010077-201004010077-11-20 Shih, Y. Y., & Fang, K. (2004). The use of a decomposed theory of planned behavior to study Internet banking in Taiwan. Internet Research, 14, 213–223. Ship and Ocean Industries R&D Center. (2020). Maritime autonomous surface ship (MASS) - 財團法人船舶暨海洋產業研發中心. Retrieved September 2, 2020, from https://www.soic.org.tw/en/ship-engineering/自動駕駛船舶/ Ship Technology News. (2020). Eight countries to promote maritime autonomous ship development. Retrieved September 2, 2020, from https://www.ship-technology.com/news/eight-countries-maritime-autonomous-ship-development/ Simon, A. (2014). ReVolt – next generation short sea shipping - DNV GL. Retrieved December 22, 2019, from https://www.dnvgl.com/news/revolt-next-generation-short-sea-shipping-7279 Singh, V., Singh, V., & Vaibhav, S. (2020). A review and simple meta-analysis of factors influencing adoption of electric vehicles. Transportation Research Part D: Transport and Environment, 86. Sun, K. K., He, S. Y., & Thøgersen, J. (2022). The purchase intention of electric vehicles in Hong Kong, a high-density Asian context, and main differences from a Nordic context. Transport Policy, 128, 98–112. Sun, Y., Bhattacherjee, A., & Ma, Q. (2009). Extending technology usage to work settings: The role of perceived work compatibility in ERP implementation. Information and Management, 46, 351–356. Tabachnick, B. G., Fidell, L. S., & Ullman, J. B. (2007). Using multivariate statistics (Vol. 5). Pearson Boston, MA. Talebian, A., & Mishra, S. (2018). Predicting the adoption of connected autonomous vehicles: A new approach based on the theory of diffusion of innovations. Transportation Research Part C: Emerging Technologies, 95, 363–380. Tanya, K. (2008). Attitude : A concept analysis. Nursing Forum, 43, 144–150. Tao, C. C., & Fan, C. C. (2017). A modified decomposed theory of planned behaviour model to analyze user intention towards distance-based electronic toll collection services. Promet - Traffic - Traffico, 29, 85–97. Taylor, S., & Todd, P. (1995). Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions. International Journal of Research in Marketing, 12, 137–155. The Maritime Executive. (2020). Demonstration of autonomous and remote-controlled ship operations. Retrieved May 4, 2021, from https://www.maritime-executive.com/article/demonstration-of-autonomous-and-remote-controlled-ship-operations The Nippon Foundation. (2021). 5th Demonstration test of fully autonomous ship navigation successfully completed | The Nippon Foundation. Retrieved September 28, 2022, from https://www.nippon-foundation.or.jp/en/news/articles/2022/20220301-67775.html Tornatzky, L. G., & Klein, K. J. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of finding. IEEE Transactions on Engineering Management, EM-29, 28–45. Veal, R., Tsimplis, M., & Serdyc, A. (2019). The legal status and operation of unmanned maritime vehicles. Ocean Development and International Law, 50, 23–48. Wang, S., Fan, J., Zhao, D., Yang, S., & Fu, Y. (2016). Predicting consumers’ intention to adopt hybrid electric vehicles: using an extended version of the theory of planned behavior model. Transportation, 43, 123–143. Wang, S., Wang, J., Li, J., Wang, J., & Liang, L. (2018). Policy implications for promoting the adoption of electric vehicles: Do consumer’s knowledge, perceived risk and financial incentive policy matter? Transportation Research Part A: Policy and Practice, 117, 58–69. Wang, S., Wang, J., Lin, S., & Li, J. (2019). Public perceptions and acceptance of nuclear energy in China: The role of public knowledge, perceived benefit, perceived risk and public engagement. Energy Policy, 126, 352–360. Wang, X., Yuen, K. F., Wong, Y. D., & Teo, C. C. (2019). Consumer participation in last-mile logistics service: an investigation on cognitions and affects. International Journal of Physical Distribution and Logistics Management, 49, 217–238. Wang, Y., Cheng, L., & Li, S. (2019). Study on the influence of subway passengers’ non-adaptive behavior based on Knowledge-Attitude-Practice theory. In 2019 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS) (pp. 72–76). IEEE. Weisbrod, R. E., & Lawson, C. T. (2003). Ferry systems: Planning for the revitalization of U.S. cities. Journal of Urban Technology, 10, 47–68. Wergeland, T. (2012). Ferry passenger markets. In The Blackwell Companion to Maritime Economics (pp. 161–183). Wiley. Wu, I. L., & Chiu, M. L. (2015). Organizational applications of IT innovation and firm’s competitive performance: A resource-based view and the innovation diffusion approach. Journal of Engineering and Technology Management - JET-M, 35, 25–44. Wu, X. (2018). Role of workplace charging opportunities on adoption of plug-in electric vehicles – Analysis based on GPS-based longitudinal travel data. Energy Policy, 114, 367–379. Xia, Y., & Yang, Y. (2018). RMSEA, CFI, and TLI in structural equation modeling with ordered categorical data: The story they tell depends on the estimation methods. Yuen, K. F., Chua, G., Wang, X., Ma, F., & Li, K. X. (2020). Understanding public acceptance of autonomous vehicles using the theory of planned behaviour. International Journal of Environmental Research and Public Health, 17, 1–19. Yuen, K. F., Thi, D., Huyen, K., Wang, X., & Qi, G. (2020). Factors influencing the adoption of shared autonomous vehicles. International Journal of Environmental Research and Public Health. Yuen, K. F., Wang, X., Ng, L. T. W., & Wong, Y. D. (2018). An investigation of customers’ intention to use self-collection services for last-mile delivery. Transport Policy, 66, 1–8. Zhang, T., Tan, H., Li, S., Zhu, H., & Tao, D. (2019). Public’s acceptance of automated vehicles: the role of initial trust and subjective norm. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 63, 919–923. Zhang, Y., & Li, L. (2020). Intention of Chinese college students to use carsharing: An application of the theory of planned behavior. Transportation Research Part F: Traffic Psychology and Behaviour, 75, 106–119. Zhao, P., & Gao, Y. (2022). Public transit travel choice in the post COVID-19 pandemic era: An application of the extended Theory of Planned behavior. Travel Behaviour and Society, 28, 181–195.
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