research-article

Avoidance of Social Media Advertising: A Latent Profile Analysis

Authors:

Christian Maier,

Heinrich GraserAuthors Info & Claims

SIGMIS-CPR'18: Proceedings of the 2018 ACM SIGMIS Conference on Computers and People Research

Pages 50 - 57

https://doi.org/10.1145/3209626.3209705

Published: 18 June 2018 Publication History

Abstract

Some individuals actively avoid social media advertising, for instance by scrolling over ads or ignoring ads. Therefore, this research aims to identify distinct profiles of individuals avoiding social media advertising. We build upon the advertising avoidance model and take a person-centered approach, using latent profile analysis to identify different profiles of individuals, who avoid social media advertising. We identified three distinct profiles of individuals, differing in their perception and their level of avoidance: unconcerned users, playful avoiding users and goal-oriented users. We contribute by characterizing individuals avoiding SMA, so that companies can use these profiles to derive different strategies how to deal with different profiles.

References

[1]

Apter, M.J. The experience of motivation: The theory of psychological reversals: Academic Pr, 1982.

[2]

Bapna, R; Goes, P; Gupta, A; and Jin, Y. User heterogeneity and its impact on electronic auction market design: An empirical exploration. MIS Quarterly (2004), 21--43.

Digital Library

[3]

Bennett, A.A; Gabriel, A.S; Calderwood, C; Dahling, J.J; and Trougakos, J.P. Better together? Examining profiles of employee recovery experiences. The Journal of applied psychology, 101, 12 (2016), 1635--1654.

[4]

Bleier, A. and Eisenbeiss, M. Personalized Online Advertising Effectiveness: The Interplay of What, When, and Where. Marketing Science, 34, 5 (2015), 669--688.

Digital Library

[5]

Campbell, C; Mattison Thompson, F; Grimm, P.E; and Robson, K. Understanding Why Consumers Don't Skip Pre-Roll Video Ads. Journal of Advertising, 46, 3 (2017), 411--423.

[6]

Cho, C.-H. and Cheon, H.J. Why do people avoid advertising on the internet? Journal of Advertising, 33, 4 (2004), 89--97.

[7]

Elliott, M.T. and Speck, P.S. Consumer Perceptions of Advertising Clutter and Its Impact Across Various Media. Journal of Advertising Research, 38, 1 (1998), 29--41.

[8]

Fortune. Social Media Ad Spending Is Expected to Pass Newspapers by 2020. (11 October 2017) (available at http://fortune.com/2016/12/05/social-media-ad-spending-newspapers-zenith-2020/).

[9]

Gabriel, A.S; Daniels, M.A; Diefendorff, J.M; and Greguras, G.J. Emotional labor actors: a latent profile analysis of emotional labor strategies. The Journal of applied psychology, 100, 3 (2015), 863--879.

[10]

Hervet, G; Guérard, K; Tremblay, S; and Chtourou, M.S. Is banner blindness genuine? Eye tracking internet text advertising. Applied cognitive psychology, 25, 5 (2011), 708--716.

[11]

Infolinks. The Banner Blindness Infographic. (3 February 2017) (available at http://www.infolinks.com/blog/infographic/the-banner-blindness-infographic/).

[12]

Jung, T. and Wickrama, K.A.S. An introduction to latent class growth analysis and growth mixture modeling. Social and personality psychology compass, 2, 1 (2008), 302--317.

[13]

Kabins, A.H; Xu, X; Bergman, M.E; Berry, C.M; and Willson, V.L. A profile of profiles: A meta-analysis of the nomological net of commitment profiles. The Journal of applied psychology, 101, 6 (2016), 881--904.

[14]

Knoll, J. Advertising in social media: A review of empirical evidence. International Journal of Advertising, 35, 2 (2016), 266--300.

[15]

Kolb, D. Experiential education: Experience as the source of learning and development. Englewood Cliffs, NJ (1984).

[16]

Kouchaki, M. and Jami, A. Everything We Do, You Do: The Licensing Effect of Prosocial Marketing Messages on Consumer Behavior. Management Science, 2016 (2016).

Digital Library

[17]

Laumer, S; Maier, C; Eckhardt, A; and Weitzel, T. User personality and resistance to mandatory information systems in organizations: A theoretical model and empirical test of dispositional resistance to change. J Inf Technol, 31, 1 (2016), 67--82.

[18]

Li, G; Yang, H; Sun, L; and Sohal, A.S. The impact of IT implementation on supply chain integration and performance. International Journal of Production Economics, 120, 1 (2009), 125--138.

[19]

Lowry, P.B; D'Arcy, J; Hammer, B; and Moody, G.D. "Cargo Cult" science in traditional organization and information systems survey research: A case for using nontraditional methods of data collection, including Mechanical Turk and online panels. The Journal of Strategic Information Systems, 25, 3 (2016), 232--240.

Digital Library

[20]

Maier, C. Personality within information systems research: A literature analysis. ECIS 2012 Proceedings, Barcelona, Spain (2012).

[21]

Maier, C; Laumer, S; Eckhardt, A; and Weitzel, T. Giving too much social support: Social overload on social networking sites. Eur J Inf Syst, 24, 5 (2015), 447--464.

[22]

Maier, C; Laumer, S; Weinert, C; and Weitzel, T. The effects of technostress and switching stress on discontinued use of social networking services: A study of Facebook use. Info Systems J, 25, 3 (2015), 275--308.

Digital Library

[23]

Melas, C.D; Zampetakis, L.A; Dimopoulou, A; and Moustakis, V.S. An empirical investigation of Technology Readiness among medical staff based in Greek hospitals. Eur J Inf Syst, 23, 6 (2014), 672--690.

[24]

Merz, E.L. and Roesch, S.C. A latent profile analysis of the Five Factor Model of personality: Modeling trait interactions. Personality and individual differences, 51, 8 (2011), 915--919.

[25]

Meyer, J.P. and Morin, A.J.S. A person-centered approach to commitment research: Theory, research, and methodology. Journal of Organizational Behavior, 37, 4 (2016), 584--612.

[26]

Meyer, J.P; Stanley, L.J; and Vandenberg, R.J. A person-centered approach to the study of commitment. Human Resource Management Review, 23, 2 (2013), 190--202.

[27]

Meyers, L.S; Gamst, G; and Guarino, A.J. Applied multivariate research: Design and interpretation: SAGE Publications, 2016.

[28]

Morin, A.J.S; Meyer, J.P; Creusier, J; and Biétry, F. Multiple-group analysis of similarity in latent profile solutions. Organizational Research Methods, 19, 2 (2016), 231--254.

[29]

Müller, L; Mattke, J; Maier, C; and Weitzel, T. The Curse of Mobile Marketing: A Mixed Methods Study on Individuals' Switch to Mobile Ad Blockers. ICIS 2017 Proceedings (2017).

[30]

Muthén, L.K. and Muthén, B.O. Mplus User's Guide (7th ed.). Los Angeles, CA: Muthén & (1998--2015).

[31]

Nunnally, J. Psychometric methods. New York: McGraw-Hill, 1978.

[32]

Nylund, K.L; Asparouhov, T; and Muthén, B.O. Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural equation modeling, 14, 4 (2007), 535--569.

[33]

PageFair. 2016 Mobile Adblocking Report. (9 January 2017) (available at https://pagefair.com/blog/2016/mobile-adblocking-report/).

[34]

Puccinelli, N.M; Wilcox, K; and Grewal, D. Consumers' Response to Commercials: When the Energy Level in the Commercial Conflicts with the Media Context. Journal of Marketing, 79, 2 (2015), 1--18.

[35]

Resnick, M. and Albert, W. The impact of advertising location and user task on the emergence of banner ad blindness: An eye-tracking study. International Journal of Human-Computer Interaction, 30, 3 (2014), 206--219.

[36]

Seyedghorban, Z; Tahernejad, H; and Matanda, M.J. Reinquiry into advertising avoidance on the internet: A conceptual replication and extension. Journal of Advertising, 45, 1 (2016), 120--129.

[37]

Shannon, C.E. and Weaver, W. The mathematical theory of communication: University of Illinois press, 1998.

[38]

Speck, P.S. and Elliott, M.T. Predictors of advertising avoidance in print and broadcast media. Journal of Advertising, 26, 3 (1997), 61--76.

[39]

Stanley, L; Kellermanns, F.W; and Zellweger, T.M. Latent Profile Analysis. Family Business Review, 30, 1 (2017), 84--102.

[40]

Statista. Global social network ad revenues 2017 | Statistic. (7 November 2017) (available at https://www.statista.com/statistics/271406/advertising-revenue-of-social-networks-worldwide/).

[41]

Steelman, Z.R; Hammer, B.I; and Limayem, M. Data Collection in the Digital Age: Innovative Alternatives to Student Samples. MIS Quarterly, 38, 2 (2014).

Digital Library

[42]

Sun, Y; Lim, K.H; and Peng, J.Z. Solving the Distinctiveness -- Blindness Debate: A Unified Model for Understanding Banner Processing. Journal of the Association for Information Systems, 14, 2 (2013), 49--71.

[43]

Tofighi, D. and Enders, C.K. Identifying the correct number of classes in growth mixture models. Advances in latent variable mixture models, Information Age Publishing, Inc (2008), 317--341.

Cited By

Reis LMaier CWeitzel TGallivan MZaza SArmstrong DGuzman IRodriguez-Abitia G(2022)Chatbots in MarketingProceedings of the 2022 Computers and People Research Conference10.1145/3510606.3550204(1-8)Online publication date: 2-Jun-2022
https://dl.acm.org/doi/10.1145/3510606.3550204
Huo HLiu ZMin Q(2020)Social media advertising reactance model: a theoretical reviewInternet Research10.1108/INTR-02-2020-0072ahead-of-print:ahead-of-printOnline publication date: 25-Nov-2020
https://doi.org/10.1108/INTR-02-2020-0072
Sutherland KSutherland K(2020)IntroductionStrategic Social Media Management10.1007/978-981-15-4658-7_1(1-4)Online publication date: 22-Dec-2020
https://doi.org/10.1007/978-981-15-4658-7_1
Show More Cited By

Index Terms

Avoidance of Social Media Advertising: A Latent Profile Analysis
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing theory, concepts and paradigms
      1. Social media
2. Information systems
  1. World Wide Web
    1. Online advertising
      1. Display advertising
      2. Social advertising

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cover image ACM Conferences

SIGMIS-CPR'18: Proceedings of the 2018 ACM SIGMIS Conference on Computers and People Research

June 2018

216 pages

ISBN:9781450357685

DOI:10.1145/3209626

General Chairs:
Rajiv Kishore
University of Nevada, Las Vegas, USA
,
Daniel Beimborn
Frankfurt School of Finance & Management, Germany
,
Rajendra K. Bandi
Indian Institute of Management Bangalore, India
,
Program Chairs:
Benoit Aubert
Dalhousie University, Canada
,
Deborah Compeau
Washington State University, USA
,
Monideepa Tarafdar
Lancaster University, UK

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Published: 18 June 2018

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SIGMIS-CPR '18: 2018 Computers and People Research Conference

June 18 - 20, 2018

NY, Buffalo-Niagara Falls, USA

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Cited By

Reis LMaier CWeitzel TGallivan MZaza SArmstrong DGuzman IRodriguez-Abitia G(2022)Chatbots in MarketingProceedings of the 2022 Computers and People Research Conference10.1145/3510606.3550204(1-8)Online publication date: 2-Jun-2022
https://dl.acm.org/doi/10.1145/3510606.3550204
Huo HLiu ZMin Q(2020)Social media advertising reactance model: a theoretical reviewInternet Research10.1108/INTR-02-2020-0072ahead-of-print:ahead-of-printOnline publication date: 25-Nov-2020
https://doi.org/10.1108/INTR-02-2020-0072
Sutherland KSutherland K(2020)IntroductionStrategic Social Media Management10.1007/978-981-15-4658-7_1(1-4)Online publication date: 22-Dec-2020
https://doi.org/10.1007/978-981-15-4658-7_1
Müller LMattke JMaier CWeitzel TGraser HJoseph DVan Slyke CAllen JQuesenberry JWiesche M(2019)Chatbot AcceptanceProceedings of the 2019 on Computers and People Research Conference10.1145/3322385.3322392(35-42)Online publication date: 12-Jun-2019
https://dl.acm.org/doi/10.1145/3322385.3322392

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