Advertisement

An integrated model of factors affecting consumer attitudes and intentions towards youtuber-generated product content

  • Sandra MirandaEmail author
  • Patrícia Cunha
  • Margarida Duarte
Review Paper

Abstract

This study examines the factors affecting consumers’ perceptions regarding the credibility of YouTuber-generated product content (YGPC) and its perceived usefulness, and how such perceptions can influence attitudes and intentions towards YGPC use for purchase decisions. This study applies the maximum likelihood-based structural equation modeling approach to an online survey of 315 YouTuber followers. Our findings highlight the importance of investigating the dimensions of source credibility to understand better how YouTuber-generated content use affects attitude and behavior intentions regarding product purchase decisions.

Keywords

Credibility Usefulness Argument quality Digital influencers Social network site YouTubers 

JEL classification

M31 M37 

Notes

Acknowledgements

I gratefully acknowledge financial support from FCT- Fundação para a Ciencia e Tecnologia (Portugal), national funding through research Grant UID/SOC/04521/2019.

References

  1. Ajzen I (1991) The theory of planned behaviour. Organ Behav and Human Decis Process 50(2):179–211CrossRefGoogle Scholar
  2. Anderson M (2015) 5 facts about online video, for Youtube’s 10th birthday. Pew Research Center. http://www.pewresearch.org/fact-tank/2015/02/12/5-facts-about-online-video-for-Youtubes-10th-birthday/. Accessed 27 Jan 2019
  3. Arnold A (2017) Why Youtube stars influence millennials more than traditional celebrities. Forbes. https://www.forbes.com/sites/under30network/2017/06/20/why-youtube-stars-influence-millennials-more-than-traditional-celebrities/#58443b5d48c6. Accessed 27 Jan 2019
  4. Ayeh JK, Au N, Law R (2013) Do we believe in TripAdvisor? Examining credibility perceptions and online travelers’ attitude toward using user-generated content. J Travel Res 52(4):437–452CrossRefGoogle Scholar
  5. Bahtar AZ, Muda M (2016) The impact of user-generated content (UGC) on product reviews towards online purchasing—a conceptual framework. Procedia Econ Financ 37:337–342CrossRefGoogle Scholar
  6. Banville D, Desrosiers P, Genet-Volet Y (2000) Translating questionnaires and inventories using a cross-cultural translation technique. J Teach Phys Educ 19:374–387CrossRefGoogle Scholar
  7. Bhattacherjee A, Sanford C (2006) Influence processes for information technology acceptance: an elaboration likelihood model. MIS Q 30(4):805–825CrossRefGoogle Scholar
  8. Borghol Y, Ardon S, Carlsson N, Eager D, Mahanti, A (2012) The untold story of the clones: content-agnostic factors that impact Youtube video popularity. In: Eighteenth ACM SIGKDD international conference on knowledge discovery and data mining (KDD 2012). Beijing, ChinaGoogle Scholar
  9. Bouhlel O, Mzoughi N, Ghachem MS, Negra A (2010) Online purchase intention: understanding the blogosphere effect. Int J e-Bus Manag 4(2):37–51Google Scholar
  10. Bouncken R, Roig-Tierno N, Kraus S (2019) Knowledge- and innovation-based business models for future growth: digitalized business models and portfolio considerations. Rev Manag Sci.  https://doi.org/10.1007/s11846-019-00366-z(in print) CrossRefGoogle Scholar
  11. Brown J, Broderick A, Lee N (2007) Word of mouth communication within online communities: conceptualizing the online social network. J Interact Market 21(3):1–20CrossRefGoogle Scholar
  12. Bruyn A, Lilien GL (2008) A multi-stage model of word-of-mouth influence through viral marketing. Int J Res Mark 25:151–163CrossRefGoogle Scholar
  13. Burgess J, Green J (2009) Youtube e a revolução digital. Editora Aleph, São PauloGoogle Scholar
  14. Burgess S, Sellitto C, Cox C, Buultjens J (2009). User-generated content (UGC) in tourism: Benefits and concerns of online consumers. Seventeenth European Conference on Information Systems. Verona, ItalyGoogle Scholar
  15. Byrne BM (2000) Structural equation modeling with AMOS: basic concepts, applications, and programming. Lawrence Erlbaum Associates, MahwahGoogle Scholar
  16. Chapple C, Cownie F (2017) An investigation into viewers’ trust in and response towards disclosed paid-for-endorsements by Youtube lifestyle vloggers. J Promot Commun 5(2):110–136Google Scholar
  17. Cheung CMK, Lee MKO, Rabjohn N (2008) The impact of electronic word of mouth: the adoption of online opinions in online customer communities. Internet Res 18(3):229–247CrossRefGoogle Scholar
  18. Chung N, Han H, Koo C (2015) Adoption of travel information in user-generated content on social media: the moderating effect of social presence. Behav Inf Technol 34(9):902–919CrossRefGoogle Scholar
  19. Curran PJ, West SG, Finch JF (1996) The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychol Methods 1(1):16–29CrossRefGoogle Scholar
  20. Davis FD, Bagozzi RP, Warshaw PR (1989) User acceptance of computer technology: a comparison of two theoretical models. Manag Sci 35(8):982–1003CrossRefGoogle Scholar
  21. DeSarbo WS, Harshman RA (1985) Celebrity-brand congruence analysis. Curr Issues Res Advert 8(1):17–52Google Scholar
  22. Erdogan BZ (1999) Celebrity endorsement: a literature review. J Market Manag 15(3):291–314CrossRefGoogle Scholar
  23. Farías P (2017) Identifying the factors that influence eWOM in SNSs: the case of Chile. Int J Advert 36(6):852–869CrossRefGoogle Scholar
  24. Fazio R (1986) How do attitudes guide behavior? In: Sorrentino R, Higgins E (eds) Handbook of motivation and cognition. Guilford, New York, pp 204–243Google Scholar
  25. Ferchaud A, Grzeslo J, Orme S, LaGroue J (2017) Parasocial attributes and YouTube personalities: exploring content trends across the most subscribed YouTube channels. Comput Hum Behav 80:88–96CrossRefGoogle Scholar
  26. Fishbein M, Ajzen I (1975) Prediction of behavior. In: Fishbein M, Ajzen I (eds) Belief, attitude, intention, and behavior: an introduction to theory and research. Addison-Wesley, Reading, MA, pp 335–383Google Scholar
  27. Fornell C, Larcker DF (1981) Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 18(1):39–50CrossRefGoogle Scholar
  28. Freeman KS, Spyridakis JH (2004) An examination of factors that affect the credibility of online health information. Tech Commun 51(2):239–263Google Scholar
  29. Gilly MC, Graham JL, Wolfinbarger MF, Yale LJ (1998) A dyadic study of interpersonal information search. J Acad Mark Sci 26(2):83–100CrossRefGoogle Scholar
  30. Hair JF, Black WC, Babin B, Anderson RE, Tatham RL (2005) Multivariate data analysis, 6th edn. Prentice-Hall, New YorkGoogle Scholar
  31. Haridakis PM, Hanson GL (2009) Social interaction and coviewing with Youtube: blending mass communication reception and social connection. J Broadcast Electron Media 53(2):317–335CrossRefGoogle Scholar
  32. Holland M (2016) How Youtube developed into a successful platform for user-generated content. Elon J Undergrad Res Commun 7(1):52–59Google Scholar
  33. Hovland CI, Janis IL, Kelley JJ (1953) Communication and persuasion: psychological studies of opinion change. Yale University Press, New HavenGoogle Scholar
  34. Hu LT, Bentler PM (1998) Fit indices in covariance structure modeling: sensitivity to underparameterized model misspecification. Psychol Methods 3(4):424CrossRefGoogle Scholar
  35. Jerslev A (2016) Media times in the time of the microcelebrity: celebrification and the Youtuber Zoella. Int J Commun 10:5233–5251Google Scholar
  36. Kline RB (1998) Principles and practice of structural equation modeling. The Guilford Press, New YorkGoogle Scholar
  37. Laumann EO (1966) Prestige and association in an urban community. Bobbs-Merrill, IndianapolisGoogle Scholar
  38. Lazarsfeld PF, Merton RK (1954) Friendship as a social process: a substantive and methodological analysis. In: Berger M (ed) Freedom and control in modern society. Van Nostrand, New York, pp 18–66Google Scholar
  39. Lee JE, Watkins B (2016) Youtube vloggers’ influence on consumer luxury brand perceptions and intentions. J Bus Res 69:5753–5760CrossRefGoogle Scholar
  40. Malhotra NK (2010) Marketing research: an applied orientation. Prentice Hall, New JerseyCrossRefGoogle Scholar
  41. McCroskey JC (1966) Scales for the measurement of ethos. Speech Monogr 33:65–72CrossRefGoogle Scholar
  42. McPherson JM, Smith-Lovin L (1987) Homophily in voluntary organizations: status, distance and the composition of face-to-face groups. Am Sociol Rev 52:370–379CrossRefGoogle Scholar
  43. McPherson M, Smith-Lovin L, Cook JM (2001) Birds of a feather: homophily in social networks. Ann Rev Sociol 27(1):415–444CrossRefGoogle Scholar
  44. Mir IA, Rehman KU (2013) Factors affecting consumer attitudes and intentions toward user-generated product content on YouTube. Manag Market 8(4):637–654Google Scholar
  45. Mir I, Zaheer A (2012) Verification of social impact theory claims in social media context. J Internet Bank Commer 17(1):1–15Google Scholar
  46. Molyneaux H, O’Donnell S, Gibson K, Singer J (2008) Exploring the gender divide on Youtube: an analysis of the creation and reception of vlogs. Am Commun J 10(1):1–14Google Scholar
  47. O’Neil-Hart C, Blumenstein, H (2016) Why Youtube stars are more influential than traditional celebrities. Think With Google. https://www.thinkwithgoogle.com/consumer-insights/Youtube-stars-influence/. Accessed 27 Jan 2019)
  48. Ohanian R (1990) Construction and validation of a scale to measure celebrity endorsers’ perceived expertise, trustworthiness, and attractiveness. J Advert 19(3):39–52CrossRefGoogle Scholar
  49. Perlstein, T (2017) Gen Z actually wants your branded content, social first is preferred & influencers are still celebrities. Fullscreen. https://fullscreenmedia.co/2017/05/23/fullscreen-original-research-results/Pew. Accessed 27 Jan 2019
  50. Petty RE, Cacioppo JT, Goldman R (1981) Personal involvement as a determinant of argument-based persuasion. J Pers Soc Psychol 41(5):847–855CrossRefGoogle Scholar
  51. Pornpitakpan C (2004) The persuasiveness of source credibility: a critical review of five decades’ evidence. J Appl Psychol 34(2):243–281Google Scholar
  52. Rogers EM (1983) Diffusion of innovations. FreePress, New YorkGoogle Scholar
  53. Ruef M, Aldrich HE, Carter NM (2003) The structure of founding teams: homophily, strong ties and isolation among U.S. entrepreneurs. Am Sociol Rev 68:195–222CrossRefGoogle Scholar
  54. Schmengler K, Kraus S (2010) Entrepreneurial marketing over the internet: an explorative qualitative empirical analysis. Int J Entrep Ventur 2(1):56–71CrossRefGoogle Scholar
  55. Simonsen TM (2011) Categorising Youtube. J Media Commun Res 51:72–93Google Scholar
  56. Smith DR (2016) Imagining others more complexly: celebrity and the ideology of fame among Youtube’s “Nerdfighteria”. Celeb Stud 7(3):339–353CrossRefGoogle Scholar
  57. Sussman SW, Siegal WS (2003) Informational influence in organizations: an integrated approach to knowledge adoption. Inf Syst Res 14(1):47–65CrossRefGoogle Scholar
  58. Tseng S, Fogg BJ (1999) Credibility and computing technology. Commun ACM 42(5):39–44CrossRefGoogle Scholar
  59. Wang Z, Walther JB, Pingree S, Hawkins RP (2008) Health information, credibility, homophily, and influence via the internet: web sites versus discussion groups. Health Commun 23:358–368CrossRefGoogle Scholar
  60. West SG, Finch JF, Curran PJ (1995) Structural equation models with nonnormal variables: problems and remedies. In: Hoyle RH (ed) Structural equation modelling: concepts, issues, and applications. Sage Publications Inc, Thousand Oaks, California, US, pp 56–75Google Scholar
  61. Whitehead JL (1968) Factors of source credibility. Q J Speech 54(1):59–63CrossRefGoogle Scholar
  62. Wright KB (2000) Perceptions of on-line support providers: an examination of perceived homophily, source credibility, communication and social support within on-line support groups. Commun Q 48:44–59CrossRefGoogle Scholar
  63. Wunsch-Vincent S, Vickery G (2007) Participative web and user-created content: Web 2.0, wikis and social networking. OECD, ParisGoogle Scholar
  64. Yoo KH, Gretzel U (2008) The influence of perceived credibility on preferences for recommender systems as sources of advice. Inf Technol Tour 10(2):133–146CrossRefGoogle Scholar
  65. Yuksel HF (2016) Factors affecting purchase intention in youtube videos. J Knowl Econ Knowl Manag 11(Fall):33–47Google Scholar
  66. Zernigah KI, Sohail K (2012) Consumers’ attitude towards viral marketing in Pakistan. Manag Market Chall Knowl Soc 7(4):645–662Google Scholar
  67. Zhou R, Khemmarat S, Gao L, Wan J, Zhang J (2016) How Youtube videos are discovered and its impact on video views. Multimed Tools Appl 75(10):6035–6058CrossRefGoogle Scholar

Copyright information

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

Authors and Affiliations

  1. 1.Advance/CSG, ISEGUniversidade de LisboaLisbonPortugal
  2. 2.ISEGUniversidade de LisboaLisbonPortugal
  3. 3.Advance/CSG, ISEGUniversidade de LisboaLisbonPortugal

Personalised recommendations