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Acceptance and Adoption of eTourism Technologies

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Handbook of e-Tourism

Abstract

The field of eTourism research encompasses a plethora of research on users’ adoption and acceptance of technologies. As a multidimensional phenomenon, an in-depth understanding of eTourism technology acceptance requires crossing the boundaries of tourism and hospitality, information and communication technologies, and marketing. Taking such a multidisciplinary approach enables researchers to integrate knowledge from the broader disciplines of psychology, sociology, and economics to construct a deep understanding of users’ behavior. However, while there have been some recent advances in broadening the horizons of research in this field, the majority of eTourism technology acceptance research relies on a few classical technology acceptance and consumer behavior theories. This chapter presents a summarized overview of the most important determinants of technology acceptance behavior and critically reviews most influential theoretical models that have been used as the foundation of the majority of existing research in this field. Subsequently, some major areas of theoretical and empirical gaps in our understanding of eTourism technology acceptance will be discussed to provide researchers with a pathway towards further expanding the boundaries of research in this field. This chapter assists emerging researchers in this field to gain an overall understanding of the progress of research so far. It also directs emerging researchers towards developing alternative research agendas to diversify the theoretical foundations of eTourism technology acceptance research and expand the boundaries of knowledge in this field beyond the status quo.

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References

  • Acheampong P, Zhiwen L, Antwi HA, Otoo AAA, Mensah WG, Sarpong PBJAJOMR (2017) Hybridizing an extended technology readiness index with Technology Acceptance Model (TAM) to predict E-Payment adoption in ghana. 5:172–184

    Google Scholar 

  • Ajzen I (1985) From intentions to actions: a theory of planned behavior. In: Kuhl J, Beckmann J (eds) Action control: from cognition to behavior. Springer, Berlin/Heidelberg

    Google Scholar 

  • Ajzen I (2011) The theory of planned behaviour: reactions and reflections. Psychol Health 26:1113–1127

    Article  Google Scholar 

  • Ajzen I (2012) Martin Fishbein’s legacy: the reasoned action approach. Ann Am Acad Polit Soc Sci 640:11–27

    Article  Google Scholar 

  • Ajzen I (2015) The theory of planned behaviour is alive and well, and not ready to retire: a commentary on sniehotta, presseau, and araújo-soares. Health Psychol Rev 9:131–137

    Article  Google Scholar 

  • Al-Jabri IM, Sohail MS (2012) Mobile banking adoption: application of diffusion of innovation theory. J Electron Commer Res 13:379–391

    Google Scholar 

  • Al-Rahmi WM, Yahaya N, Aldraiweesh AA, Alamri MM, Aljarboa NA, Alturki U, Aljeraiwi AA (2019) Integrating technology acceptance model with innovation diffusion theory: an empirical investigation on students’ intention to use e-learning systems. IEEE Acc 7:26797– 26809

    Article  Google Scholar 

  • Ali F, Nair PK, Hussain K (2016) An assessment of students’ acceptance and usage of computer supported collaborative classrooms in hospitality and tourism schools. J Hosp Leis Sport Tour Educ 18:51–60

    Google Scholar 

  • Amaro S, Duarte P (2015) An integrative model of consumers’ intentions to purchase travel online. Tour Manag 46:64–79

    Article  Google Scholar 

  • Amaro S, Duarte P (2016) Travellers’ intention to purchase travel online: integrating trust and risk to the theory of planned behaviour. Anatolia 27:389–400

    Article  Google Scholar 

  • Andaleeb A, Idrus RM, Ismail I, Mokaram AJDC (2010) Technology Readiness Index (TRI) among USM distance education students according to age. Int J Educ Pedagogical Sci 4(3):229–232

    Google Scholar 

  • Atkin DJ, Hunt DS, Lin CA (2015) Diffusion theory in the new media environment: toward an integrated technology adoption model. Mass Commun Soc 18:623–650

    Article  Google Scholar 

  • Ayeh JK, Au N, Law R (2013) Predicting the intention to use consumer-generated media for travel planning. Tour Manag 35:132–143

    Article  Google Scholar 

  • Bagozzi RP (2007) The legacy of the technology acceptance model and a proposal for a paradigm shift. J Assoc Inf Syst 8:244–254

    Google Scholar 

  • Balouchi M, Abdul Aziz Y, Hasangholipour T, Khanlari A, Abd Rahman A, Raja-Yusof RN (2017) Explaining and predicting online tourists’ behavioural intention in accepting consumer generated contents. J Hosp Tour Technol 8:168–189

    Google Scholar 

  • Bandura A (1986) Social foundations of thought and action: a social cognitive theory. Prentice-Hall, Inc., Englewood Cliffs

    Google Scholar 

  • Bandura A (2001) Social cognitive theory: an agentic perspective. Ann Rev Psychology 52:1–26

    Article  Google Scholar 

  • Benbasat I, Barki H (2007) Quo vadis TAM? J Assoc Inf Syst 8:211–218

    Google Scholar 

  • Bettman JR (1979) An information processing theory of consumer choice. Addison-Wesley Publishing Company, Reading

    Google Scholar 

  • Bonsón Ponte E, Carvajal Trujillo E, Escobar Rodríguez T (2015) Influence of trust and perceived value on the intention to purchase travel online: integrating the effects of assurance on trust antecedents. Tour Manag 47:286–302

    Article  Google Scholar 

  • Buhalis D, Law R (2008) Progress in information technology and tourism management: 20 years on and 10 years after the internet—the state of etourism research. Tour Manag 29:609–623

    Article  Google Scholar 

  • Cai W, Richter S, Mckenna B (2019) Progress on technology use in tourism. J Hosp Tour Technol 10(4):651–672

    Google Scholar 

  • Chan ESW, Okumus F, Chan W (2018) Barriers to environmental technology adoption in hotels. J Hosp Tour Technol 42:829–852

    Article  Google Scholar 

  • Chang IC, Chou P-C, Yeh RK-J, Tseng H-T (2016) Factors influencing Chinese tourists’ intentions to use the Taiwan Medical Travel App. Telematics Inform 33:401–409

    Article  Google Scholar 

  • Chia-Yu Chen F (2007) Passenger use intentions for electronic tickets on international flights. J Air Transp Manag 13:110–115

    Article  Google Scholar 

  • Chong AYL, Khong KW, Ma T, Mccabe S, Wang Y (2018) Analyzing key influences of tourists’ acceptance of online reviews in travel decisions. Internet Res 28:564–586

    Article  Google Scholar 

  • Compeau DR, Higgins CA (1995) Computer self-efficacy: development of a measure and initial test. MIS Q 19:189–211

    Article  Google Scholar 

  • Compeau DR, Higgins CA, Huff S (1999) Social cognitive theory and individual reactions to computing technology: a longitudinal study. MIS Q 23(2):145–158. https://doi.org/10.2307/249749

    Article  Google Scholar 

  • Csikszentmihalyi M (1975a) Beyond boredom and anxiety. Jossey-Bass Publishers, San Francisco

    Google Scholar 

  • Csikszentmihalyi M (1975b) Play and intrinsic rewards. J Humanist Psychol 15:41–63

    Article  Google Scholar 

  • Csikszentmihalyi M (1997) Finding flow: the psychology of engagement with everyday life. BasicBooks, New York

    Google Scholar 

  • Csikszentmihalyi M, Abuhamdeh S, Nakamura J (2014) Flow. In: Csikszentmihalyi M (ed) Flow and the foundations of positive psychology: the collected works of Mihaly Csikszentmihalyi. Springer Netherlands, Dordrecht

    Chapter  Google Scholar 

  • Davis FD (1985) A technology acceptance model for empirically testing new end-user information systems: theory and results. Thesis, Massachusetts Institute of Technology

    Google Scholar 

  • Davis FD, Bagozzi RP, Warshaw PR (1992) Extrinsic and intrinsic motivation to use computers in the workplace. J Appl Soc Psychol 22:1111–1132

    Article  Google Scholar 

  • Dinhopl A, Gretzel U (2016) Selfie-taking as touristic looking. Ann Tour Res 57:126–139

    Article  Google Scholar 

  • Durrheim K (1997) Social constructionism, discourse, and psychology. S Afr J Psychol 27: 175–182

    Article  Google Scholar 

  • Erdoğmuş N, Esen M (2011) An investigation of the effects of technology readiness on technology acceptance in e-HRM. Procedia Soc Behav Sci 24:487–495

    Article  Google Scholar 

  • Ertmer PA, Newby TJ (1993) Behaviorism, cognitivism, constructivism: comparing critical features from an instructional design perspective. Perform Improv Q 6:50–72

    Article  Google Scholar 

  • Escobar-Rodríguez T, Carvajal-Trujillo E (2013) Online drivers of consumer purchase of website airline tickets. J Air Transp Manag 32:58–64

    Article  Google Scholar 

  • Fishbein M, Ajzen I (1975) Belief, attitude, intention and behaviour: an introduction th theory and research. Addison-Wesley, Reading

    Google Scholar 

  • Fuchs M, Hxxxomloxxxpken W, Eybl A, Flxxxomloxxxck A (2013) Online auctions for selling accommodation packages: A readiness-intensity-impact analysis. In: Information and communication technologies in tourism 2014 . Springer, Cham, pp 813–826

    Chapter  Google Scholar 

  • Fuchs M, Hxxxomloxxxpken W, Fxxxomloxxxger A, Kunz M (2010) E-business readiness, intensity, and impact: an Austrian destination management organization study. J Travel Res 49(2):165–178

    Article  Google Scholar 

  • Fuchs M, Hxxxomloxxxpken W, Rasinger J (2011) Behavioral intention to use mobile information services in tourism: the case of the tourist guide Dolomitisuperski. Mobi. Inf Technol Tour 13(4):285–307

    Article  Google Scholar 

  • Gao L, Bai X (2014) Online consumer behaviour and its relationship to website atmospheric induced flow: Insights into online travel agencies in china. J Retail Consum Serv 21:653–665

    Article  Google Scholar 

  • Garay L, Font X, Corrons A (2018) Sustainability-Oriented Innovation in tourism: an analysis based on the decomposed theory of planned behavior. J Travel Res 58:622–636

    Article  Google Scholar 

  • Ghani JA, Deshpande SP (1994) Task characteristics and the experience of optimal flow in human—computer interaction. J Psychol 128:381–391

    Article  Google Scholar 

  • Ghani JA, Supnick R, Rooney P (1991) The experience of flow in computer-mediated and in face-to-face groups. In: Degross J, Benbasat I, Desanctis G, Beath CM (eds) International Conference on Information Systems (ICIS 1991). Association for Information Systems, Minneapolis

    Google Scholar 

  • Godoe P, Johansen T (2012) Understanding adoption of new technologies: technology readiness and technology acceptance as an integrated concept. J Eur Psychol Stud 3:38–52

    Article  Google Scholar 

  • Gretzel U (2011) Intelligent systems in tourism: a social science perspective. Ann Tour Res 38:757–779

    Article  Google Scholar 

  • Gretzel U (2016) The new technologies tsunami in the hotel industry. In: Ivanov S, et al. (eds) The routledge handbook of hotel chain management. Routledge, New York

    Google Scholar 

  • Gupta A, Dogra N (2017) Tourist adoption of mapping apps: a UTAUT2 perspective of smart travellers. Tour Hosp Manag 23:145–161

    Article  Google Scholar 

  • Han D-ID, Tom Dieck MC, Jung T (2019) Augmented reality smart glasses (ARSG) visitor adoption in cultural tourism. Leis Stud 1–16

    Google Scholar 

  • Han H, Kim W, Lee SJJODM, Management (2018) Stimulating visitors’ goal-directed behavior for environmentally responsible museums: testing the role of moderator variables. J Des Marketing Manage 8:290–300

    Google Scholar 

  • Han H, Park A, Chung N, Lee KJ (2016) A near field communication adoption and its impact on Expo visitors’ behavior. Int J Inf Manag 36:1328–1339

    Article  Google Scholar 

  • HARRÉ R (1992) Introduction: the second cognitive revolution. Am Behav Sci 36:5–7

    Google Scholar 

  • Herrero Á, San Martín H (2012) Developing and testing a global model to explain the adoption of websites by users in rural tourism accommodations. Int J Hosp Manag 31:1178–1186

    Article  Google Scholar 

  • Herrero Á, San Martín H, Garcia-De Los Salmones MDM (2017) Explaining the adoption of social networks sites for sharing user-generated content: a revision of the UTAUT2. Comput Hum Behav 71:209–217

    Article  Google Scholar 

  • Huang Y-C, Backman SJ, Backman KF, Moore D (2013) Exploring user acceptance of 3D virtual worlds in travel and tourism marketing. Tour Manage 36:490–501

    Article  Google Scholar 

  • Huh HJ, Kim T, Law R (2009) A comparison of competing theoretical models for understanding acceptance behavior of information systems in upscale hotels. Int J Hosp Manag 28:121–134

    Article  Google Scholar 

  • Ihde D (1990) Technology and the lifeworld: from garden to earth, Indiana University Press, Bloomington

    Google Scholar 

  • Jacoby J (2002) Stimulus-organism-response reconsidered: an evolutionary step in modeling (consumer) behavior. J Consum Psychol 12:51–57

    Article  Google Scholar 

  • Jeong M, Oh H, Gregoire M (2003) Conceptualizing Web site quality and its consequences in the lodging industry. Int J Hosp Manag 22:161–175

    Article  Google Scholar 

  • Khalilzadeh J, Ozturk AB, Bilgihan A (2017) Security-related factors in extended UTAUT model for NFC based mobile payment in the restaurant industry. Comput Hum Behav 70:460–474

    Article  Google Scholar 

  • Kim D-Y, Park J, Morrison AM (2008) A model of traveller acceptance of mobile technology. Int J Tour Res 10:393–407

    Article  Google Scholar 

  • Kim J (2016) An extended technology acceptance model in behavioral intention toward hotel tablet apps with moderating effects of gender and age. Int J Contemp Hosp Manag 28:1535–1553

    Article  Google Scholar 

  • Kim M-J, Lee C-K, Chung N (2012a) Investigating the role of trust and gender in online tourism shopping in South Korea. J Hosp Tour Res 37:377–401

    Article  Google Scholar 

  • Kim M-J, Lee MJ, Lee C-K, Song H-J (2012b) Does gender affect Korean tourists’ overseas travel? Applying the model of goal-directed behavior. Asia Pac J Tour Res 17:509–533

    Article  Google Scholar 

  • Kim MJ, Preis MWJJOT, Marketing T (2016) Why seniors use mobile devices: applying an extended model of goal-directed behavior. 33:404–423

    Google Scholar 

  • Koufaris M (2002) Applying the technology acceptance model and flow theory to online consumer behavior. Inf Syst Res 13:205–223

    Article  Google Scholar 

  • Ku ECS (2011) Recommendations from a virtual community as a catalytic agent of travel decisions. Int Res 21:282–303

    Google Scholar 

  • Ku ECS, Chen C-D (2015) Cultivating travellers’ revisit intention to e-tourism service: the moderating effect of website interactivity. Behav Inform Technol 34:465–478

    Article  Google Scholar 

  • Lai IKW (2013) Traveler acceptance of an app-based mobile tour guide. J Hosp Tour Res 39: 401–432

    Article  Google Scholar 

  • Lee BC (2015) The impact of social capital on tourism technology adoption for destination marketing. Curr Issue Tour 18:561–578

    Article  Google Scholar 

  • Lee C-K, Song H-J, Bendle LJ, Kim M-J, Han HJTM (2012) The impact of non-pharmaceutical interventions for 2009 H1N1 influenza on travel intentions: a model of goal-directed behavior. Tour Manag 33:89–99

    Article  Google Scholar 

  • Lee HY, Kim WG, Lee YK (2006) Testing the determinants of computerized reservation system users’ intention to use via a structural equation model. J Hosp Tour Res 30:246–266

    Article  Google Scholar 

  • Letheren K, Russell-Bennett R, Mulcahy RF, Mcandrew RJEJOM (2019) Rules of (household) engagement: technology as manager, assistant and intern

    Google Scholar 

  • Liljander V, Gillberg F, Gummerus J, Van Riel A, Services C (2006) Technology readiness and the evaluation and adoption of self-service technologies. J Retail 13:177–191

    Google Scholar 

  • Lin C-H, Shih H-Y, Sher PJ (2007) Integrating technology readiness into technology acceptance: the TRAM model. Psychol Mark 24:641–657

    Article  Google Scholar 

  • López-Nicolás C, Molina-Castillo FJ, Bouwman H (2008) An assessment of advanced mobile services acceptance: contributions from TAM and diffusion theory models. Inf Manag 45: 359–364

    Article  Google Scholar 

  • Lu J, Mao Z, Wang M, Hu L (2015) Goodbye maps, hello apps? Exploring the influential determinants of travel app adoption. Curr Issue Tour 18:1059–1079

    Article  Google Scholar 

  • Lyytinen K, Damsgaard J (2001) What’s wrong with the diffusion of innovation theory? In: Working conference on diffusing software product and process innovations, Boston. Springer US, 173–190

    Chapter  Google Scholar 

  • Meng B, Choi KJTM (2016) The role of authenticity in forming slow tourists’ intentions: developing an extended model of goal-directed behavior. Tour Manag 57:397–410

    Article  Google Scholar 

  • Min S, So KKF, Jeong M (2018) Consumer adoption of the Uber mobile application: insights from diffusion of innovation theory and technology acceptance model. J Travel Tour Mark 36: 1–14

    Google Scholar 

  • Moore GC, Benbasat I (1991) Development of an instrument to measure the perceptions of adopting an information technology innovation. Inf Syst Res 2:192–222

    Article  Google Scholar 

  • Moore GC, Benbasat I (1996) Integrating diffusion of innovations and theory of reasoned action models to predict utilization of information technology by end-users. In: Kautz K, Pries-Heje J (eds) Diffusion and adoption of information technology: proceedings of the first Ifip Wg 8.6 working conference on the diffusion and adoption of information technology, Oslo, Oct 1995. Springer US, Boston

    Google Scholar 

  • Muñoz-Leiva F, Hernández-Méndez J, Sánchez-Fernández J (2012) Generalising user behaviour in online travel sites through the Travel 2.0 website acceptance model. Online Inf Rev 36: 879–902

    Article  Google Scholar 

  • Nakamura J, Csikszentmihalyi M (2014) The concept of flow. In: Csikszentmihalyi M (ed) Flow and the foundations of positive psychology: the collected works of Mihaly Csikszentmihalyi. Springer Netherlands, Dordrecht

    Google Scholar 

  • Neuhofer B (2016) Value co-creation and co-destruction in connected tourist experiences. Springer International Publishing, Cham, pp 779–792

    Google Scholar 

  • Neuhofer B, Buhalis D, Ladkin A (2015a) Smart technologies for personalized experiences: a case study in the hospitality domain. Electron Mark 25:243–254

    Article  Google Scholar 

  • Neuhofer B, Buhalis D, Ladkin A (2015b) Technology as a catalyst of change: enablers and barriers of the tourist experience and their consequences. Springer International Publishing, Cham, pp 789–802

    Google Scholar 

  • No E, Kim JK (2014) Determinants of the adoption for travel information on smartphone. Int J Tour Res 16:534–545

    Article  Google Scholar 

  • Noone BM, Robson SKA (2016) Understanding consumers’ inferences from price and nonprice information in the online lodging purchase decision. Serv Sci 8:108–123

    Article  Google Scholar 

  • Norton JA, Bass FM (1987) A diffusion theory model of adoption and substitution for successive generations of high-technology products. Manag Sci 33:1069–1086

    Article  Google Scholar 

  • Novak TP, Hoffman DL, Yung YF (2000) Measuring the customer experience in online environments: a structural modeling approach. Mark Sci 19:22–42

    Article  Google Scholar 

  • Obadă DR (2013) Flow theory and online marketing outcomes: a critical literature review. Proc Econ Finan 6:550–561

    Article  Google Scholar 

  • Palau-Saumell R, Forgas-Coll S, Sánchez-García J, Robres E (2019) User acceptance of mobile apps for restaurants: an expanded and extended UTAUT-2. 11 1210

    Google Scholar 

  • Papathanassis A, Knolle F (2011) Exploring the adoption and processing of online holiday reviews: a grounded theory approach. Tour Manag 32:215–224

    Article  Google Scholar 

  • Parasuraman A (1996) Understanding and leveraging the role of customer service in external, interactive and internal marketing. In: Frontiers in services conference, Nashville

    Google Scholar 

  • Parasuraman A (2000) Technology Readiness Index (TRI) a multiple-item scale to measure readiness to embrace new technologies. J Serv Res 2:307–320

    Article  Google Scholar 

  • Parasuraman A, Colby CL (2014) An updated and streamlined technology readiness index: TRI 2.0. J Serv Res 18:59–74

    Article  Google Scholar 

  • Paulo MM, Rita P, Oliveira T, Moro S (2018) Understanding mobile augmented reality adoption in a consumer context. J Hosp Tour Technol 9:142–157

    Google Scholar 

  • Peres R, Correia A, Moital M (2011) The indicators of intention to adopt mobile electronic tourist guides. J Hosp Tour Technol 2:120–138

    Google Scholar 

  • Perugini M, Bagozzi RP (2001) The role of desires and anticipated emotions in goal-directed behaviours: broadening and deepening the theory of planned behaviour. Br J Soc Psychol 40: 79–98

    Article  Google Scholar 

  • Pourfakhimi S, Duncan T, Coetzee W (2018) A synthesis of technology acceptance research in tourism & hospitality. In: Stangl B, Pesonen J (eds) Information and communication technologies in tourism 2018. Springer International Publishing, Cham

    Google Scholar 

  • Pourfakhimi S, Duncan T, Coetzee W (2019) A critique of the progress of eTourism technology acceptance research: time for a hike? J Hosp Tour Technol 10:689–746

    Google Scholar 

  • Pourfakhimi S, Ying T (2015) The evolution of etourism research: a case of enter conference. In: Tussyadiah IP, Inversini A (eds) Information and communication technologies in tourism 2015. Springer International Publishing, Cham

    Google Scholar 

  • Riemenschneider CK, Harrison DA, Mykytyn PPJR (2003) Understanding it adoption decisions in small business: integrating current theories. Inf Manag 40:269–285

    Article  Google Scholar 

  • Rogers EM (1983) Diffusion of innovations. Free Press, Collier Macmillan, New York

    Google Scholar 

  • Rogers EM (2010) Diffusion of innovations. Simon and Schuster, New York

    Google Scholar 

  • Sahili AB, Legohérel P (2014) Using the decomposed theory of planned behavior (DTPB) to explain the intention to book tourism products online. Int J Online Market 4:1–10

    Article  Google Scholar 

  • Sahin I (2006) Detailed review of Rogers’ diffusion of innovations theory and educational technology-related studies based on Rogers’ theory. Turk Online J Educ Technol

    Google Scholar 

  • Salovaara A, Tamminen S (2009) Acceptance or appropriation? A design-oriented critique of technology acceptance models. In: Isomxxxomlaxxxki H, Saariluoma P (eds) Future interaction design II. Springer, London

    Google Scholar 

  • San Martín H, Herrero Á (2012) Influence of the user’s psychological factors on the online purchase intention in rural tourism: integrating innovativeness to the UTAUT framework. Tour Manag 33:341–350

    Article  Google Scholar 

  • Schrier T, Erdem M, Brewer P (2010) Merging task-technology fit and technology acceptance models to assess guest empowerment technology usage in hotels. J Hosp Tour Technol 1: 201–217

    Google Scholar 

  • Schuster L, Drennan J, Lings IN (2013) Consumer acceptance of m-wellbeing services: a social marketing perspective. Eur J Mark 47:1439–1457

    Article  Google Scholar 

  • Shih Y-C, Fan S-T (2013) Adoption of instant messaging by travel agency workers in Taiwan: integrating technology readiness with the theory of planned behavior. Int J Bus Inf 8:120–136

    Google Scholar 

  • Sigala M (2011) Special issue on web 2.0 in travel and tourism: empowering and changing the role of travelers. Comput Hum Behav 27:607–608

    Article  Google Scholar 

  • Sniehotta FF, Presseau J, Araújo-Soares V (2014) Time to retire the theory of planned behaviour. Health Psychol Rev 8:1–7

    Article  Google Scholar 

  • Song HJ, Lee C-K, Kang SK, Boo S-J (2012) The effect of environmentally friendly perceptions on festival visitors’ decision-making process using an extended model of goal-directed behavior. Tour Manag 33:1417–1428

    Article  Google Scholar 

  • Taylor S, Todd PA (1995) Understanding information technology usage: a test of competing models. Inf Syst Res 6:144–176

    Article  Google Scholar 

  • Taylor SA (2007) The addition of anticipated regret to attitudinally based, goal-directed models of information search behaviours under conditions of uncertainty and risk. Br J Soc Psychol 46:739–768

    Article  Google Scholar 

  • Thompson RL, Higgins CA, Howell JM (1991) Personal computing: toward a conceptual model of utilization. MIS Q 15:125–143

    Article  Google Scholar 

  • Trakulmaykee N, Benrit P (2014) Mobile tourism guide in the context of Thai national parks: the effects of mobile design qualities in TAM2. In: 4th international conference on tourism research (4ICTR). SHS Web of Conferences, Kota Kinabalu, Sabah

    Google Scholar 

  • Triandis HC (1977) Interpersonal behavior. Brooks/Cole Pub. Co, Monterey

    Google Scholar 

  • Tussyadiah IP, Jung TH, Tom Dieck MC (2018) Embodiment of wearable augmented reality technology in tourism experiences. 57:597–611

    Google Scholar 

  • Ukpabi DC, Karjaluoto H (2017) Consumers’ acceptance of information and communications technology in tourism: a review. Telematics Inform 34:618–644

    Article  Google Scholar 

  • Urry J (2002) The tourist gaze. Sage, London

    Google Scholar 

  • Varol ES, Tarcan E (2009) An empirical study on the user acceptance of hotel information systems. Tourism 57:115–133

    Google Scholar 

  • Venkatesh V, Bala H (2008) Technology acceptance model 3 and a research agenda on interventions. Decis Sci 39:273–315

    Article  Google Scholar 

  • Venkatesh V, Davis FD (2000) A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci 46:186–204

    Article  Google Scholar 

  • Venkatesh V, Morris MG, Gordon BD, Davis FD (2003) User acceptance of information technology: toward a unified view. MIS Q 27:425–478

    Article  Google Scholar 

  • Venkatesh V, Thong JYL, Xu X (2012) Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q 36:157–178

    Article  Google Scholar 

  • Victorino L, Karniouchina E, Verma R (2009) Exploring the use of the abbreviated technology readiness index for hotel customer segmentation. Cornell Hosp Q 50:342–359

    Article  Google Scholar 

  • Walczuch R, Lemmink J, Streukens S (2007) The effect of service employees’ technology readiness on technology acceptance. Inf Manag 44:206–215

    Article  Google Scholar 

  • Wang L, Law R, Guillet BD, Hung K, Fong DKC (2015) Impact of hotel website quality on online booking intentions: etrust as a mediator. Int J Hosp Manag 47:108–115

    Article  Google Scholar 

  • Wang Y, So KKF, Sparks BA (2016) Technology readiness and customer satisfaction with travel technologies: a cross-country investigation. J Travel Res 56:563–577

    Article  Google Scholar 

  • Wxxxomloxxxber K, Gretzel U (2000) Tourism managers’ adoption of marketing decision support systems. J Travel Res 39:172–181

    Article  Google Scholar 

  • Wozniak T, Schaffner D, Stanoevska-Slabeva K, Lenz-Kesekamp VJIT, Tourism (2018) Psychological antecedents of mobile consumer behaviour and implications for customer journeys in tourism. Inf Technol Tour 18:85–112

    Google Scholar 

  • Wu M-Y, Chou H-P, Weng Y-C, Huang Y-H (2008) A study of web 2.0 website usage behavior using TAM 2. In: IEEE Asia-Pacific services computing conference, 9–12 Dec 2008, pp 1477–1482

    Google Scholar 

  • Yang FX (2013) Effects of restaurant satisfaction and knowledge sharing motivation on eWOM Intentions. J Hosp Tour Res 41:93–127

    Article  Google Scholar 

  • Yi-Hsuan L, Yi-Chuan H, Chia-Ning H (2011) Adding innovation diffusion theory to the technology acceptance model: supporting employees’ intentions to use e-learning systems. J Educ Technol Soc 14:124–137

    Google Scholar 

  • Yuqiong Z (2008) Voluntary adopters versus forced adopters: integrating the diffusion of innovation theory and the technology acceptance model to study intra-organizational adoption. New Media Soc 10:475–496

    Article  Google Scholar 

  • Zhao X, Wang L, Guo X, Law R (2015) The influence of online reviews to online hotel booking intentions. Int J Contemp Hosp Manag 27:1343–1364

    Article  Google Scholar 

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Pourfakhimi, S., Duncan, T., Ould, L., Allan, K., Coetzee, W. (2022). Acceptance and Adoption of eTourism Technologies. In: Xiang, Z., Fuchs, M., Gretzel, U., Höpken, W. (eds) Handbook of e-Tourism. Springer, Cham. https://doi.org/10.1007/978-3-030-48652-5_58

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