Understanding the antecedents of hedonic motivation in autonomous vehicle technology acceptance domain: A cross-country analysis
Tài liệu tham khảo
Beza, 2019, Potential effects of automated vehicles on road transportation: a literature review, Transport and Telecommunication, 20, 269, 10.2478/ttj-2019-0023
Childers, 2001, Hedonic and utilitarian motivations for online retail shopping behavior, J. Retail., 77, 511, 10.1016/S0022-4359(01)00056-2
Madigan, 2017, What influences the decision to use automated public transport? using utaut to understand public acceptance of automated road transport systems, Transport. Res. F Traffic Psychol. Behav., 50, 55, 10.1016/j.trf.2017.07.007
Tamilmani, 2019, The battle of brain vs. heart: a literature review and meta-analysis of “hedonic motivation” use in utaut2, Int. J. Inf. Manag., 46, 222, 10.1016/j.ijinfomgt.2019.01.008
Venkatesh, 2012, Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology, MIS Q., 157, 10.2307/41410412
Keszey, 2020, Behavioural intention to use autonomous vehicles: systematic review and empirical extension, Transport. Res. C Emerg. Technol., 119, 10.1016/j.trc.2020.102732
Meske, 2019, Explaining the emergence of hedonic motivations in enterprise social networks and their impact on sustainable user engagement: a four-drive perspective, J. Enterprise Inf. Manag., 32, 436, 10.1108/JEIM-08-2018-0177
Lin, 2012, Hedonic and utilitarian motivations for physical game systems use behavior, Int. J. Hum. Comput. Interact., 28, 445, 10.1080/10447318.2011.618097
Hamadneh, 2022, Travel behavior of car travelers with the presence of park-and-ride facilities and autonomous vehicles, Periodica Polytechn. Trans. Eng., 50, 101, 10.3311/PPtr.18020
2018, Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles. Technical report, SAE International, J3016
Nordhoff, 2020, Using the utaut2 model to explain public acceptance of conditionally automated (l3) cars: a questionnaire study among 9,118 car drivers from eight European countries, Transport. Res. F Traffic Psychol. Behav., 74, 280, 10.1016/j.trf.2020.07.015
Benleulmi, 2017, Investigating the factors influencing the acceptance of fully autonomous cars, vol. 23, 99
Garidis, 2020, Toward a user acceptance model of autonomous driving, 10.24251/HICSS.2020.170
Kapser, 2020, Acceptance of autonomous delivery vehicles for last-mile delivery in Germany–extending utaut2 with risk perceptions, Transport. Res. C Emerg. Technol., 111, 210, 10.1016/j.trc.2019.12.016
Morrison, 2020, Customer intentions towards autonomous vehicles in South Africa: an extended utaut model, 525
Nordhoff, 2020, Interrelationships among predictors of automated vehicle acceptance: a structural equation modelling approach, Theor. Issues Ergon. Sci., 1–26
Rombaut, 2020, Experience and acceptance of an autonomous shuttle in the brussels capital region, 77
Ernst, 2017
Kyriakidis, 2015, Public opinion on automated driving: results of an international questionnaire among 5000 respondents, Transport. Res. F Traffic Psychol. Behav., 32, 127, 10.1016/j.trf.2015.04.014
Moody, 2020, Public perceptions of autonomous vehicle safety: an international comparison, Saf. Sci., 121, 634, 10.1016/j.ssci.2019.07.022
Zefreh, 2023, Intention to use private autonomous vehicles in developed and developing countries: what are the differences among the influential factors, mediators, and moderators?, Travel Behaviour and Society, 32, 10.1016/j.tbs.2023.100592
Kapser, 2021, Autonomous delivery vehicles to fight the spread of Covid-19–How do men and women differ in their acceptance?, Transport. Res. Pol. Pract., 148, 183, 10.1016/j.tra.2021.02.020
Mayer, 1995, An integrative model of organizational trust, Acad. Manag. Rev., 20, 709, 10.2307/258792
Sukhu, 2015, Factors influencing information-sharing behaviors in social networking sites, Serv. Market. Q., 36, 317, 10.1080/15332969.2015.1076697
Hampes, 1999
Kim, 2019, The effect of trust on value on travel websites: enhancing well-being and word-of-mouth among the elderly, J. Trav. Tourism Market., 36, 76, 10.1080/10548408.2018.1494086
Alalwan, 2014
Auditianto, 2019, October. Discovering the influencing factors of physical gig economy usage: quantitative approach on clients9 perception, 357
Van Pinxteren, 2019, Trust in humanoid robots: implications for services marketing, Journal of Services Marketing, 33, 507, 10.1108/JSM-01-2018-0045
Al-Azawei, 2020, Predicting the intention to use and hedonic motivation for mobile learning: a comparative study in two middle eastern countries, Technol. Soc., 62, 10.1016/j.techsoc.2020.101325
Khalilzadeh, 2017, Security-related factors in extended UTAUT model for NFC based mobile payment in the restaurant industry, Comput. Hum. Behav., 70, 460, 10.1016/j.chb.2017.01.001
Kelman, 1958, Compliance, identification, and internalization three processes of attitude change, J. Conflict Resolut., 2, 51, 10.1177/002200275800200106
Kang, 2013, Determinants of sharing travel experiences in social media, J. Trav. Tourism Market., 30, 93, 10.1080/10548408.2013.751237
Joe, 2022, Effects of social influence and perceived enjoyment on Kiosk acceptance: a moderating role of gender, Int. J. Hospit. Tourism Adm., 23, 289
Koenig-Lewis, 2015, Enjoyment and social influence: predicting mobile payment adoption, Serv. Ind. J., 35, 537, 10.1080/02642069.2015.1043278
Kumar, 2019, Google classroom for mobile learning in higher education: modelling the initial perceptions of students, Educ. Inf. Technol., 24, 1793, 10.1007/s10639-018-09858-z
Park, 2019, Examining the role of anxiety and social influence in multi-benefits of mobile payment service, J. Retailing Consum. Serv., 47, 140, 10.1016/j.jretconser.2018.11.015
Sitar‐Tăut, 2021, Mobile learning acceptance in social distancing during the COVID‐19 outbreak: the mediation effect of hedonic motivation, Human Behavior and Emerging Technologies, 3, 366, 10.1002/hbe2.261
Siyal, 2021, Structural equation modeling and artificial neural networks approach to predict continued use of mobile taxi booking apps: the mediating role of hedonic motivation, Data Technol. Appl., 55, 372
Li, 2011, Online social network acceptance: a social perspective, Internet Res., 21, 562, 10.1108/10662241111176371
Bandura, 1977, Self-efficacy: toward a unifying theory of behavioral change, Psychol. Rev., 84, 191, 10.1037/0033-295X.84.2.191
Compeau, 1995, Computer self-efficacy: Development of a measure and initial test, MIS Q., 189, 10.2307/249688
Hoffman, 1996, Marketing in hypermedia computer-mediated environments: conceptual foundations, J. Market., 60, 50, 10.1177/002224299606000304
Kulviwat, 2014, Self-efficacy as an antecedent of cognition and affect in technology acceptance, J. Consum. Market., 31, 190, 10.1108/JCM-10-2013-0727
Liu, 2016, Understanding player behavior in online games: the role of gender, Technol. Forecast. Soc. Change, 111, 265, 10.1016/j.techfore.2016.07.018
Boonsiritomachai, 2019, Determinants affecting mobile banking adoption by generation Y based on the unified theory of acceptance and use of technology model modified by the technology acceptance model concept, Kasetsart Journal of Social Sciences, 40
Wang, 2015, Understanding the continuance use of social network sites: a computer self-efficacy perspective, Behav. Inf. Technol., 34, 204, 10.1080/0144929X.2014.952778
Osswald, 2012, Predicting information technology usage in the car: towards a car technology acceptance model, 51
Li, 2022, Examining the effects of AI contactless services on customer psychological safety, perceived value, and hospitality service quality during the COVID‐19 pandemic, J. Hospit. Market. Manag., 31, 24
Salimon, 2017, The mediating role of hedonic motivation on the relationship between adoption of e-banking and its determinants, Int. J. Bank Market., 35, 558, 10.1108/IJBM-05-2016-0060
Howard, 2014, Public perceptions of self-driving cars: the case of berkeley, California, Transportation Research Board 93rd Annual Meeting, 14, 1
Zoellick, 2019, Amused, accepted, and used? attitudes and emotions towards automated vehicles, their relationships, and predictive value for usage intention, Transport. Res. F Traffic Psychol. Behav., 65, 68, 10.1016/j.trf.2019.07.009
Hagman, 2010, Driving pleasure: a key concept in Swedish car culture, Mobilities, 5, 25, 10.1080/17450100903435037
Rödel, 2014, Towards autonomous cars: the effect of autonomy levels on acceptance and user experience, 1
Eckoldt, 2012
Chaveesuk, 2022, Continuance intention to use digital payments in mitigating the spread of COVID-19 virus, International Journal of Data and Network Science, 6, 527, 10.5267/j.ijdns.2021.12.001
Khalid, 2021, Moocs adoption in higher education: a management perspective, Polish Journal of Management Studies, 23, 10.17512/pjms.2021.23.1.15
Cohen, 1992, A power primer, Psychol. Bull., 112, 155, 10.1037/0033-2909.112.1.155
Faul, 2009, Statistical power analyses using G* Power 3.1: tests for correlation and regression analyses, Behav. Res. Methods, 41, 1149, 10.3758/BRM.41.4.1149
Rahman, 2019, How the older population perceives self-driving vehicles, Transport. Res. F Traffic Psychol. Behav., 65, 242, 10.1016/j.trf.2019.08.002
Hegner, 2019, In automatic we trust: investigating the impact of trust, control, personality characteristics, and extrinsic and intrinsic motivations on the acceptance of autonomous vehicles, Int. J. Hum. Comput. Interact., 35, 1769, 10.1080/10447318.2019.1572353
Hewitt, 2019, March. Assessing public perception of self-driving cars: the autonomous vehicle acceptance model, 518
Zhou, 2020, Understanding consumers' behavior to adopt self-service parcel services for last-mile delivery, J. Retailing Consum. Serv., 52, 10.1016/j.jretconser.2019.101911
Acheampong, 2019, Capturing the behavioural determinants behind the adoption of autonomous vehicles: conceptual frameworks and measurement models to predict public transport, sharing and ownership trends of self-driving cars, Transport. Res. F Traffic Psychol. Behav., 62, 349, 10.1016/j.trf.2019.01.009
Henseler, 2009, The use of partial least squares path modeling in international marketing
Ringle, 2015, 2015
Chin, 1998, The partial least squares approach to structural equation modeling, Modern methods for business research, 295, 295
Hair, 2016
Fornell, 1981, Evaluating structural equation models with unobservable variables and measurement error, J. Market. Res., 18, 39, 10.1177/002224378101800104
De Oña, 2021, Understanding the mediator role of satisfaction in public transport: a cross-country analysis, Transport Pol., 100, 129, 10.1016/j.tranpol.2020.09.011
de Oña, 2021, How does private vehicle users perceive the public transport service quality in large metropolitan areas? A European comparison, Transport Pol., 112, 173, 10.1016/j.tranpol.2021.08.005
Tenenhaus, 2005, Pls path modeling, Comput. Stat. Data Anal., 48, 159, 10.1016/j.csda.2004.03.005
Hu, 1999, Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives, Struct. Equ. Model.: A Multidiscip. J., 6, 1, 10.1080/10705519909540118
Babin, 2001, International students' travel behavior: a model of the travel-related consumer/dissatisfaction process, J. Trav. Tourism Market., 10, 93, 10.1300/J073v10n01_06
Montoro, 2019, Perceived safety and attributed value as predictors of the intention to use autonomous vehicles: a national study with Spanish drivers, Saf. Sci., 120, 865, 10.1016/j.ssci.2019.07.041
Lee, 2016, Personal values as determinants of intentions to use self-service technology in retailing, Comput. Hum. Behav., 60, 322, 10.1016/j.chb.2016.02.051
Lewis, 2016, Self-efficacy versus perceived enjoyment as predictors of physical activity behaviour, Psychol. Health, 31, 456, 10.1080/08870446.2015.1111372
Bandura, 1996
Zhang, 2020, Automated vehicle acceptance in China: social influence and initial trust are key determinants, Transport. Res. C Emerg. Technol., 112, 220, 10.1016/j.trc.2020.01.027
Du, 2021, Why travelers trust and accept self-driving cars: an empirical study, Travel behaviour and society, 22, 1, 10.1016/j.tbs.2020.06.012
Choi, 2015, Investigating the importance of trust on adopting an autonomous vehicle, Int. J. Hum. Comput. Interact., 31, 692, 10.1080/10447318.2015.1070549
Sukhu, 2015, Factors influencing information-sharing behaviors in social networking sites, Serv. Market. Q., 36, 317, 10.1080/15332969.2015.1076697