Advertisement

Information Technology & Tourism

, Volume 21, Issue 4, pp 483–514 | Cite as

The influence of ubiquitous connectivity, trust, personality and generational effects on mobile tourism purchases

  • Roberto P. Q. FalcaoEmail author
  • J. B. Ferreira
  • Murilo Carrazedo Marques da Costa Filho
Original Research
First Online:
  • 79 Downloads

Abstract

Tourism has been considerably impacted by technological advancements, in which smartphones have been key enablers of this transformation, offering convenience and flexibility for online platforms access anytime and anywhere for faster decision-making during a trip. We address this trend by devising and testing a comprehensive conceptual model for predicting travelers’ intentions of mobile tourism purchase. We extend the technology acceptance model (TAM) to include ubiquitous connectivity and trust, two constructs that have been shown to be relevant to both m-commerce and travel contexts. Additionally, we analyze personality traits as potential individual external variables. The results support most of the hypothesis of the proposed model, indicating that, in addition to the TAM constructs (perceived usefulness and perceived ease of use), perceived ubiquitous connectivity and trust, together with personality traits such as openness to experience and need for arousal, play a significant role in enhancing the explanation of travelers’ intentions to purchase tourism-related products and services through mobile. Differences in effects related to consumers’ generations (X and Y) are also discussed.

Keywords

Online travel Personality TAM Generation Ubiquitous connectivity 
This is a preview of subscription content, log in to check access.

Notes

References

  1. Adams DA, Nelson RR, Todd PA (1992) Perceived usefulness, ease of use, and usage of information technology: a replication. MIS Q 16(2):227–247CrossRefGoogle Scholar
  2. Ajzen I, Fishbein M (1977) Attitude-behavior relations: a theoretical analysis and review of empirical research. Psychol Bull 84(5):888–918CrossRefGoogle Scholar
  3. Amichai-Hamburger Y, Ben-Artzi E (2003) Loneliness and Internet use. Comput Hum Behav 19(1):71–80.  https://doi.org/10.1016/S0747-5632(02)00014-6 CrossRefGoogle Scholar
  4. Amiel T, Sargent SL (2004) Individual differences in internet usage motives. Comput Hum Behav 20(6):711–726.  https://doi.org/10.1016/j.chb.2004.09.002 CrossRefGoogle Scholar
  5. Anderson JC, Gerbing DW (1988) Structural equation modeling in practice: a review and recommended two-step approach. Psychol Bull 103(3):411–423CrossRefGoogle Scholar
  6. Augner C, Hacker GW (2012) Associations between problematic mobile phone use and psychological parameters in young adults. Int J Public Health 57(2):437–441.  https://doi.org/10.1007/s00038-011-0234-z CrossRefGoogle Scholar
  7. Bala H, Venkatesh V (2008) Technology acceptance model 3 and a research agenda on interventions. Decis Sci 39(2):273–315.  https://doi.org/10.1111/j.1540-5915.2008.00192.x CrossRefGoogle Scholar
  8. Barkhi R, Wallace L (2007) The impact of personality type on purchasing decisions in virtual stores. Inf Technol Manag 8(4):313–330.  https://doi.org/10.1007/s10799-007-0021-y CrossRefGoogle Scholar
  9. Benckendorff P, Moscardo G, Pendergast D (2010) Getting to know the Y generation. In: Benckendorff P, Moscardo G, Pendergast D (eds) Tourism and Generation Y. CABI, WallingfordGoogle Scholar
  10. Beranuy M, Oberst U, Carbonell X, Ander C (2009) Problematic Internet and mobile phone use and clinical symptoms in college students: the role of emotional intelligence. Comput Hum Behav 25(5):1182–1187.  https://doi.org/10.1016/j.chb.2009.03.001 CrossRefGoogle Scholar
  11. Bosnjak M, Galesic M, Tuten T (2007) Personality determinants of online shopping: explaining online purchase intentions using a hierarchical approach. J Bus Res 60(6):597–605.  https://doi.org/10.1016/j.jbusres.2006.06.008 CrossRefGoogle Scholar
  12. Brislin RW (1970) Back-translation for cross-cultural research. J Cross Cult Psychol 1(3):185–216CrossRefGoogle Scholar
  13. Bruner GC, Kumar A (2005) Explaining consumer acceptance of handheld internet devices. J Bus Res 58:553–558.  https://doi.org/10.1016/j.jbusres.2003.08.002 CrossRefGoogle Scholar
  14. Butt S, Phillips JG (2008) Personality and self reported mobile phone use. Comput Hum Behav 24(2):346–360.  https://doi.org/10.1016/j.chb.2007.01.019 CrossRefGoogle Scholar
  15. Byrne B (2010) Structural equation modeling with AMOS: basic concepts, applications and programming, 2nd edn. Routledge, New YorkGoogle Scholar
  16. Cellpoint Mobile (2018) Mobile outlook 2018: the future of global travel commerce. https://www.cellpointmobile.com. Accessed 10 July 2019
  17. Chittaranjan G, Blom J, Gatica-Perez D (2013) Mining large-scale smartphone data for personality studies. Pers Ubiquitous Comput 17(3):433–450.  https://doi.org/10.1007/s00779-011-0490-1 CrossRefGoogle Scholar
  18. Choi JK, Ji YG (2015) Investigating the importance of trust on adopting an autonomous vehicle. Int J Hum Comput Interact 31(10):692–702.  https://doi.org/10.1080/10447318.2015.1070549 CrossRefGoogle Scholar
  19. Chong AYL, Chan FTS, Ooi KB (2012) Predicting consumer decisions to adopt mobile commerce: cross country empirical examination between China and Malaysia. Decis Support Syst 53(1):34–43.  https://doi.org/10.1016/j.dss.2011.12.001 CrossRefGoogle Scholar
  20. Cohen SA, Prayag G, Moital M (2014) Consumer behaviour in tourism: concepts, influences and opportunities. Curr Issues Tour 17(10):872–909.  https://doi.org/10.1080/13683500.2013.850064 CrossRefGoogle Scholar
  21. Correa T, Hinsley AW, Zúñiga HG (2010) Who interacts on the web? The intersection of users’ personality and social media use. Comput Hum Behav 26(2):247–253.  https://doi.org/10.1016/j.chb.2009.09.003 CrossRefGoogle Scholar
  22. Corritore CL, Kracher B, Wiedenbeck S (2003) On-line trust: concepts, evolving themes, a model. Int J Hum Comput Stud 58(6):737–758.  https://doi.org/10.1016/S1071-5819(03)00041-7 CrossRefGoogle Scholar
  23. Costa PT, McCrae RR (1992) Normal personality assessment in clinical practice: the NEO personality inventory SNPs and personality view project PERSONALITY STABILITY AND CHANGE View Project. Psychol Assess 4(1):5–13CrossRefGoogle Scholar
  24. Costa PT, McCrae RR (2006) Trait and Factor Theories. In: Thomas Jay, Segal Daniel (eds) Comprehensive handbook of personality and psychopathology. Wiley, HobokenGoogle Scholar
  25. Criteo (2018) Summer Travel ReportGoogle Scholar
  26. Dal Fiore F, Mokhtarian PL, Salomon I, Singer ME (2014) Nomads at last’? A set of perspectives on how mobile technology may affect travel. J Transp Geogr 41:97–106.  https://doi.org/10.1016/j.jtrangeo.2014.08.014 CrossRefGoogle Scholar
  27. Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technolog. MIS Q 13(3):319–340.  https://doi.org/10.2307/249008 CrossRefGoogle Scholar
  28. Davis FD, Bagozzi RP, Warshaw PR (1989) User acceptance of computer technology: a comparison of two theoretical models. Manag Sci 35(8):982–1003.  https://doi.org/10.1287/mnsc.35.8.982 CrossRefGoogle Scholar
  30. Devaraj US, Sarv U, Easley RF, Crant JM (2008) How does personality matter? Relating the five-factor model to technology acceptance and use. Inf Syst Res 19(1):93–105.  https://doi.org/10.1287/isre.1070.0153 CrossRefGoogle Scholar
  31. Dickinger A (2011) The trustworthiness of online channels for experience- and goal-directed search tasks. J Travel Res 50(4):378–391.  https://doi.org/10.1177/0047287510371694 CrossRefGoogle Scholar
  32. Digman JM (1989) Five robust trait dimensions: development, stability, and utility. Special issue: long-term stability and change in personality. J Pers 50:116–123Google Scholar
  33. Doll WJ, Hendrickson A, Deng X (1998) Using Davis’s perceived usefulness and ease-of-use instruments for decision making: a confirmatory and multigroup invariance analysis. Decis Sci 29(4):839–869.  https://doi.org/10.1111/j.1540-5915.1998.tb00879.x CrossRefGoogle Scholar
  34. Douglas A, Lubbe B, Van Rooyen A (2018) Business travellers’ use of mobile travel applications: a generational analysis. Inf Technol Tour 18(1–4):113–132.  https://doi.org/10.1007/s40558-017-0103-6 CrossRefGoogle Scholar
  35. Eastlick MA, Lotz SL, Warrington P (2006) Understanding online B-to-C relationships: an integrated model of privacy concerns, trust, and commitment. J Bus Res 59(8):877–886.  https://doi.org/10.1016/j.jbusres.2006.02.006 CrossRefGoogle Scholar
  36. Ert E, Fleischer A (2016) Mere position effect in booking hotels online. J Travel Res 55(3):311–321.  https://doi.org/10.1177/0047287514559035 CrossRefGoogle Scholar
  37. Ferreira JB, da Rocha A, da Silva JF (2014) Impacts of technology readiness on emotions and cognition in Brazil. J Bus Res 67(5):865–873.  https://doi.org/10.1016/j.jbusres.2013.07.005 CrossRefGoogle Scholar
  38. Fesenmaier DR, Xiang Z, Pan B, Law R (2011) A framework of search engine use for travel planning. J Travel Res 50(6):587–601.  https://doi.org/10.1177/0047287510385466 CrossRefGoogle Scholar
  39. Fishbein M, Ajzen I (2010) Predicting and changing behavior: the reasoned action approach. Psychology Press, New YorkGoogle Scholar
  40. Fornell C, Larcker DF (1981) Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 18(1):39.  https://doi.org/10.2307/3151312 CrossRefGoogle Scholar
  41. Gefen D, Karahanna E, Straub DW (2003) Trust and TAM in online shopping. MIS Q 27(1):51–90.  https://doi.org/10.2307/30036519 CrossRefGoogle Scholar
  42. Giovannini CJ, Ferreira JB, da Silva JF, Ferreira DB (2015) The effects of trust transference, mobile attributes and enjoyment on mobile trust. BAR Braz Adm Rev 12(1):88–108.  https://doi.org/10.1590/1807-7692bar2015140052 CrossRefGoogle Scholar
  43. Goldberg L (1992) The development of markers for the big-five factor structure. Psychol Assess 4(1):26–42CrossRefGoogle Scholar
  44. Google (2017) Google consumer barometer. https://www.consumerbarometer.com. Accessed 10 July 2019
  45. Grabner-Kräuter S, Kaluscha EA (2003) Empirical research in on-line trust: a review and critical assessment. Int J Hum Comput Stud 58(6):783–812.  https://doi.org/10.1016/S1071-5819(03)00043-0 CrossRefGoogle Scholar
  46. Gretzel U, Fesenmaier DR, O’Leary JT (2006) The transformation of consumer behavior. In: Buhalis D, Costa C (eds) Tourism business frontiers. Elsevier Hutter-Heinemann, Oxford, pp 31–40Google Scholar
  47. Ha S, Stoel L (2009) Consumer E-shopping acceptance: antecedents in a technology acceptance model. J Bus Res 62(5):565–571.  https://doi.org/10.1016/j.jbusres.2008.06.016 CrossRefGoogle Scholar
  48. Hair J, Black W, Babin B, Anderson R (2013) Multivariate data analysis. Seventh. Pearson, HarlowGoogle Scholar
  49. Hassanein K, Head M (2007) Manipulating perceived social presence through the web interface and its impact on attitude towards online shopping. Int J Hum Comput Stud 65(8):689–708.  https://doi.org/10.1016/j.ijhcs.2006.11.018 CrossRefGoogle Scholar
  50. Heijden HVD, Verhagen T, Creemers M (2003) Understanding online purchase intentions: contributions from technology and trust perspectives. Eur J Inf Syst 12(1):41–48.  https://doi.org/10.1057/palgrave.ejis.3000445 CrossRefGoogle Scholar
  51. Hendrickson AR, Massey PD, Cronan TP (2018) On the test-retest reliability of perceived usefulness and perceived ease of use scales. 17(2): 227–230. https://www.jstor.org/stable/249803
  52. Hernandez B, Jimenez J, Martin MJ (2009) The impact of self-efficacy, ease of use and usefulness on e-purchasing: an analysis of experienced e-shoppers. Interact Comput 21(1–2):146–156.  https://doi.org/10.1016/j.intcom.2008.11.001 CrossRefGoogle Scholar
  53. Hjalager AM (2015) 100 innovations that transformed tourism. J Travel Res 54(1):3–21.  https://doi.org/10.1177/0047287513516390 CrossRefGoogle Scholar
  54. Hu LT, Bentler PM (1999) Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model 6(1):1–55.  https://doi.org/10.1080/10705519909540118 CrossRefGoogle Scholar
  55. Huang JH, Yang YC (2010) The relationship between personality traits and online shopping motivations. Soc Behav Pers Int J 38(5):673–679.  https://doi.org/10.2224/sbp.2010.38.5.673 CrossRefGoogle Scholar
  56. Islam JU, Rahman Z, Hollebeek LD (2017) Personality factors as predictors of online consumer engagement: an empirical investigation. Mark Intell Plan 35(4):510–528.  https://doi.org/10.1108/MIP-10-2016-0193 CrossRefGoogle Scholar
  58. Jani D, Jang JH, Hwang YH (2014) Big Five factors of personality and tourists’ internet search behavior. Asia Pac J Tour Res 19(5):600–615.  https://doi.org/10.1080/10941665.2013.773922 CrossRefGoogle Scholar
  59. Jenaro C, Flores N, Gómez-Vela M, González-Gil F, Caballo C (2007) Problematic Internet and cell-phone use: psychological, behavioral, and health correlates. Addict Res Theory 15(3):309–320.  https://doi.org/10.1080/16066350701350247 CrossRefGoogle Scholar
  60. Kim H, Jamal T (2007) Touristic quest for existential authenticity. Ann Tour Res 34(1):181–201.  https://doi.org/10.1016/j.annals.2006.07.009 CrossRefGoogle Scholar
  61. Kim Y, Jeong JS (2015) Personality predictors for the use of multiple internet functions. Internet Res 25(3):399–415.  https://doi.org/10.1108/IntR-11-2013-0250 CrossRefGoogle Scholar
  62. Kim HH, Law R (2015) Smartphones in tourism and hospitality marketing: a literature review. J Travel Tour Mark 32(6):692–711.  https://doi.org/10.1080/10548408.2014.943458 CrossRefGoogle Scholar
  63. Kim DY, Park J, Morrison AM (2008) A model of traveller acceptance of mobile technology. Int J Tour Res 10(5):393–407.  https://doi.org/10.1002/jtr.669 CrossRefGoogle Scholar
  64. Kim C, Mirusmonov M, Lee I (2010) An empirical examination of factors influencing the intention to use mobile payment. Comput Hum Behav 26(3):310–322.  https://doi.org/10.1016/j.chb.2009.10.013 CrossRefGoogle Scholar
  65. Kim H, Xiang Z, Fesenmaier DR (2015a) Use of the Internet for trip planning: a generational analysis. J Travel Tour Mark 32(3):276–289.  https://doi.org/10.1080/10548408.2014.896765 CrossRefGoogle Scholar
  66. Kim Y, Briley DA, Ocepek MG (2015b) Differential innovation of smartphone and application use by sociodemographics and personality. Comput Hum Behav 44:141–147.  https://doi.org/10.1016/j.chb.2014.11.059 CrossRefGoogle Scholar
  67. King WR, He J (2006) A Meta-analysis of the technology acceptance model. Inf Manag 43(6):740–755.  https://doi.org/10.1016/j.im.2006.05.003 CrossRefGoogle Scholar
  68. Kovacs MH, Farias SA (2004) Dimensões de Riscos Percebidos nas Compras pela Internet. RAE Eletrônica.  https://doi.org/10.1590/S1676-56482004000200013 CrossRefGoogle Scholar
  69. Kumar A, Lim H (2008) Age differences in mobile service perceptions: comparison of generation Y and baby boomers. J Serv Mark 22(7):568–577.  https://doi.org/10.1108/08876040810909695 CrossRefGoogle Scholar
  70. Kuvilvat S, Bruner G, Kumar A, Nasco S, Clark T (2007) Toward a unified theory of consumer acceptance technology. Psychol Mark 24(12):1059–1084.  https://doi.org/10.1002/mar.20196 CrossRefGoogle Scholar
  71. Lamsfus C, Wang D, Alzua-Sorzabal A, Xiang Z (2015) Going mobile: defining context for on-the-go travelers. J Travel Res 54(6):691–701.  https://doi.org/10.1177/0047287514538839 CrossRefGoogle Scholar
  72. Landers RN, Lounsbury JW (2006) An investigation of big five and narrow personality traits in relation to Internet usage. Comput Hum Behav 22(2):283–293.  https://doi.org/10.1016/j.chb.2004.06.001 CrossRefGoogle Scholar
  73. Lane W, Manner C (2010) The impact of personality traits on smartphone ownership and use. Int J Bus Soc Sci 2(17):22.  https://doi.org/10.1097/WNP.0b013e318246ae5c CrossRefGoogle Scholar
  74. Lee TM (2005) The impact of perceptions of interactivity on customer trust and transaction intentions in mobile commerce. J Electron Commer Res 6(3):165Google Scholar
  75. Legris P, Ingham J, Collerette P (2003) Why do people use information technology: a critical review of the literature. Inf Manag 40(3):191–204CrossRefGoogle Scholar
  76. Leung L (2008) Leisure boredom, sensation seeking, self-esteem, addiction: symptoms and patterns of cell phone use. In: Konijn EA, Tanis MA, Utz S, Linden A (eds) Mediated interpersonal communications. Lawrence Erlbaum Associates, Mahwah, pp 359–381Google Scholar
  77. Li R, Chung TL, Fiore AM (2017) Factors affecting current users’ attitude towards e-auctions in China: an extended TAM study. J Retail Consum Serv 34:19–29.  https://doi.org/10.1016/j.jretconser.2010.12.005 CrossRefGoogle Scholar
  78. Liébana-Cabanillas F, Sánchez-Fernández J, Muñoz-Leiva F (2014) Antecedents of the adoption of the new mobile payment systems: the moderating effect of age. Comput Hum Behav 35:464–478.  https://doi.org/10.1016/j.chb.2014.03.022 CrossRefGoogle Scholar
  79. Lu J, Mao Z, Mengbin W, Hu L (2015) Goodbye maps, hello apps? Exploring the influential determinants of travel app adoption. Curr Issues Tour 18(11):1059–1079.  https://doi.org/10.1080/13683500.2015.1043248 CrossRefGoogle Scholar
  80. Marriott HR, Williams MD (2018) Exploring consumers perceived risk and trust for mobile shopping: a theoretical framework and empirical study. J Retail Consum Serv 42(February):133–146.  https://doi.org/10.1016/j.jretconser.2018.01.017 CrossRefGoogle Scholar
  81. McCole P, Ramsey E, Williams J (2010) Trust considerations on attitudes towards online purchasing: the moderating effect of privacy and security concerns. J Bus Res 63(9–10):1018–1024.  https://doi.org/10.1016/j.jbusres.2009.02.025 CrossRefGoogle Scholar
  82. McCrae RR, Costa PT (1987) Validation of the five-factor model of personality across instruments and observers. J Pers Soc Psychol 52(1):81–90.  https://doi.org/10.1037/0022-3514.52.1.81 CrossRefGoogle Scholar
  83. Montag C, Błaszkiewicz K, Sariyska R, Lachmann B, Andone I, Trendafilov B, Eibes M, Markowetz A (2015) Smartphone usage in the 21st century: who is active on WhatsApp? BMC Res Notes 8(1):4–9.  https://doi.org/10.1186/s13104-015-1280-z CrossRefGoogle Scholar
  84. Morosan C (2014) Toward an integrated model of adoption of mobile phones for purchasing ancillary services in air travel. Int J Contemp Hosp Manag 26(2):246–271.  https://doi.org/10.1108/IJCHM-11-2012-0221 CrossRefGoogle Scholar
  85. Morosan C, DeFranco A (2016) Modeling guests’ intentions to use mobile apps in hotels: the roles of personalization, privacy, and involvement. Int J Contemp Hosp Manag 28(9):1968–1991.  https://doi.org/10.1108/IJCHM-07-2015-0349 CrossRefGoogle Scholar
  86. Mowen J (2000) The 3M model of motivation and personality: theory and empirical applications to consumer behavior. Kluwer Academic, BostonCrossRefGoogle Scholar
  87. Mowen JC, Spears N (1999) Understanding compulsive buying among college students: a hierarchical approach understanding compulsive buying among college students: a hierarchical approach. J Consum Psychol 8(4):407–430CrossRefGoogle Scholar
  88. Nunkoo R, Ramkissoon H (2013) Travelers’ e-purchase intent of tourism products and services. J Hosp Mark Manag 22(5):505–529.  https://doi.org/10.1080/19368623.2012.680240 CrossRefGoogle Scholar
  89. Olsson UH, Foss T, Troye SV, Howell RD (2000) The performance of ML, GLS, and WLS estimation in structural equation modeling under conditions of misspecification and nonnormality. Struct Eqn Model 7(4):557–595CrossRefGoogle Scholar
  90. Özbek V, Alnıaçık U, Koc F, Akkılıç ME, Kaş E (2014) The impact of personality on technology acceptance: a study on smart phone users. Procedia Soc Behav Sci 150:541–551.  https://doi.org/10.1016/j.sbspro.2014.09.073 CrossRefGoogle Scholar
  91. Palvia P (2009) The role of trust in e-commerce relational exchange: a unified model. Inf Manag 46(4):213–220.  https://doi.org/10.1016/j.im.2009.02.003 CrossRefGoogle Scholar
  92. Parasuraman A (2000) Technology readiness index (TRI): a multiple item scale to measure readiness to embrace new technologies. J Serv Res 2:307CrossRefGoogle Scholar
  93. Pavlou PA (2003) Consumer acceptance of electronic commerce: integrating trust and risk with the technology acceptance model. Int J Electron Commer 7(3):101–134.  https://doi.org/10.1080/10864415.2003.11044275 CrossRefGoogle Scholar
  94. Pendergast D (2009) Generational theory and home economics: future proofing the profession. Fam Consum Sci Res J 37(4):504–522.  https://doi.org/10.1177/1077727X09333186 CrossRefGoogle Scholar
  95. Podsakoff P, Organ D (1986) Self-reports in organizational research: problems and prospects. J Manag 12(4):531–544Google Scholar
  96. Podsakoff PM, MacKenzie SB, Lee JY, Podsakoff NP (2003) Common method biases in behavioral research: a critical review of the literature and recommended remedies. J Appl Psychol 88(5):879–903CrossRefGoogle Scholar
  97. Roberts JA, Pullig C, Manolis C (2015) I need my smartphone: a hierarchical model of personality and cell-phone addiction. Pers Individ Differ 79:13–19.  https://doi.org/10.1016/j.paid.2015.01.049 CrossRefGoogle Scholar
  98. Sahli AB, Legohérel P (2015) The tourism web acceptance model: a study of intention to book tourism products online. J Vacat Mark 22(2):179–194.  https://doi.org/10.1177/1356766715607589 CrossRefGoogle Scholar
  99. Schepers J, Wetzels M (2007) A meta-analysis of the technology acceptance model: investigating subjective norm and moderation effects. Inf Manag 44(1):90–103.  https://doi.org/10.1016/j.im.2006.10.007 CrossRefGoogle Scholar
  100. Schultz D, Schultz S (2016) Theories of personality, 11th edn. Cengage Learning, BostonGoogle Scholar
  101. Stachl C, Hilbert S, Au JQ, Buschek D, De Luca A, Bischl B, Hussmann H, Bühner M (2017) Personality traits predict smartphone usage. Eur J Pers 31(6):701–722.  https://doi.org/10.1002/per.2113 CrossRefGoogle Scholar
  102. Stafford TF, Turan AH, Raisinghani MS (2004) International and cross-cultural influences on online shopping behavior. J Glob Inf Technol Manag 7(2):70–87.  https://doi.org/10.1080/1097198X.2004.10856373 CrossRefGoogle Scholar
  103. Straub DW (2012) Editor’s comments—does MIS have native theories? MIS Quarterly 36(2):iii–xii.  https://doi.org/10.1016/S1262-3636(07)70146-5 CrossRefGoogle Scholar
  104. Suh B, Han I (2003) The impact of customer trust and perception of security control on the acceptance of electronic commerce. Int J Electron Commer 7(3):135–161.  https://doi.org/10.1080/10864415.2003.11044270 CrossRefGoogle Scholar
  105. Svendsen GB, Johnsen JAK, Almås-Sørensen L, Vittersø J (2013) Personality and technology acceptance: the influence of personality factors on the core constructs of the technology acceptance model. Behav Inf Technol 32(4):323–334.  https://doi.org/10.1080/0144929X.2011.553740 CrossRefGoogle Scholar
  106. Tan F, Sutherland P (2004) Online consumer trust: a multi-dimensional model. J Electron Commer Org (JECO) 2(3):40–58CrossRefGoogle Scholar
  107. Tanti A, Buhalis D (2017) The influences and consequences of being digitally connected and/or disconnected to travellers. Inf Technol Tour 17(1):121–141.  https://doi.org/10.1007/s40558-017-0081-8 CrossRefGoogle Scholar
  108. Tsao WC, Chang HR (2010) Exploring the impact of personality traits on online shopping behavior. Afr J Bus Manag 4(9):1800–1812Google Scholar
  109. Tung FC, Chang SC, Chou CM (2008) An extension of trust and TAM model with IDT in the adoption of the electronic logistics information system in HIS in the medical industry. Int J Med Inform 77(5):324–335.  https://doi.org/10.1016/j.ijmedinf.2007.06.006 CrossRefGoogle Scholar
  110. Tussyadiah IP, Wang D (2014) Tourists’ attitudes toward proactive smartphone systems. J Travel Res 55(4):493–508.  https://doi.org/10.1177/0047287514563168 CrossRefGoogle Scholar
  111. Ukpabi DC, Karjaluoto H (2017) Consumers’ acceptance of information and communications technology in tourism: a review. Telemat Inform 34(5):618–644.  https://doi.org/10.1016/j.tele.2016.12.002 CrossRefGoogle Scholar
  112. UNWTO (2015) Tourism highlights 2015. https://www.e-unwto.org. Accessed 10 July 2019
  113. UNWTO (2018) International tourism trends 2017. https://www.e-unwto.org. Accessed 10 July 2019
  114. Walczuch R, Lundgren H (2004) Psychological antecedents of institution-based consumer trust in e-retailing. Inf Manag 42(1):159–177.  https://doi.org/10.1016/j.im.2003.12.009 CrossRefGoogle Scholar
  115. Wang S, Wang S, Wang MT (2006) Shopping online or not? Cognition and personality matters. J Technol Appl Electron Commer Res 1(3):68–80Google Scholar
  116. Wang CC, Hui-Wen Y, City T (2008) Passion for online shopping: the influence of personality and compulsive buying. Inf Manag 36(5):693–706.  https://doi.org/10.2224/sbp.2008.36.5.693 CrossRefGoogle Scholar
  117. Wang D, Park S, Fesenmaier DR (2012) The role of smartphones in mediating the touristic experience. J Travel Res 51(4):371–387.  https://doi.org/10.1177/0047287511426341 CrossRefGoogle Scholar
  118. Wang D, Xiang Z, Fesenmaier DR (2016) Smartphone use in everyday life and travel. J Travel Res 55(1):52–63.  https://doi.org/10.1177/0047287514535847 CrossRefGoogle Scholar
  119. Wen C, Prybutok VR, Xu C (2011) An integrated model for customer online repurchase intention. J Comput Inf Syst 52(1):14–23Google Scholar
  120. Wu IL, Chen JL (2005) An extension of trust and TAM model with TPB in the initial adoption of on-line tax: an empirical study. Int J Hum Comput Stud 62(6):784–808.  https://doi.org/10.1016/j.ijhcs.2005.03.003 CrossRefGoogle Scholar
  121. Wu JH, Wang SC (2005) What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Inf Manag 42:719–729.  https://doi.org/10.1016/j.im.2004.07.001 CrossRefGoogle Scholar
  122. Wu G, Hu X, Wu Y (2010) Effects of perceived interactivity, perceived web assurance and disposition to trust on initial online trust. J Comput Med Commun 16(1):1–26.  https://doi.org/10.1111/j.1083-6101.2010.01528.x CrossRefGoogle Scholar
  123. Xiang Z, Magnini VP, Fesenmaier DR (2015) Information technology and consumer behavior in travel and tourism: insights from travel planning using the Internet. J Retail Consum Serv 22:244–249.  https://doi.org/10.1016/j.jretconser.2014.08.005 CrossRefGoogle Scholar
  124. Xu R, Frey RM, Fleisch E, Ilic A (2016) Understanding the impact of personality traits on mobile app adoption—insights from a large-scale field study. Comput Hum Behav 62:244–256.  https://doi.org/10.1016/j.chb.2016.04.011 CrossRefGoogle Scholar
  125. Yang S, Lu Y, Gupta S, Cao Y, Zhang R (2012) Mobile payment services adoption across time: an empirical study of the effects of behavioral beliefs, social influences, and personal traits. Comput Hum Behav 28(1):129–142.  https://doi.org/10.1016/j.chb.2011.08.019 CrossRefGoogle Scholar
  126. Yu J, Ha I, Choi M, Rho J (2005) Extending the TAM for a T-commerce. Inf Manag 42(7):965–976.  https://doi.org/10.1016/j.im.2004.11.001 CrossRefGoogle Scholar
  127. Yu X, Anaya GJ, Miao L, Lehto X, Wong IKA (2018) The impact of smartphones on the family vacation experience. J Travel Res 57(5):579–596.  https://doi.org/10.1177/0047287517706263 CrossRefGoogle Scholar
  128. Zhou T (2014) An empirical examination of initial trust in mobile payment. Wirel Pers Commun 77(2):1519–1531.  https://doi.org/10.1007/s11277-013-1596-8 CrossRefGoogle Scholar
  129. Zhou T, Lu Y (2011) The effects of personality traits on user acceptance of mobile commerce. Int J Hum Comput Interact 27(6):545–561.  https://doi.org/10.1080/10447318.2011.555298 CrossRefGoogle Scholar
  130. Zimmer JC, Arsal RE, Al-Marzouq M, Grover V (2010) Investigating online information disclosure: effects of information relevance, trust and risk. Inf Manag 47(2):115–123.  https://doi.org/10.1016/j.im.2009.12.003 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019
corrected publication 2019

Authors and Affiliations

  1. 1.Universidade Federal Fluminense, PPGENiteróiBrazil
  2. 2.Pontifícia Universidade Católica, IAGRio de JaneiroBrazil

Personalised recommendations

Cite article

Buy options