Don't exclude me: being excluded in a brand community owned by other users leads consumers to avoid the brand
DOI:
https://doi.org/10.51359/2526-7884.2022.254313Keywords:
social exclusion, brand community, brand relationship, belongingness, ostracism.Abstract
People are social animals and need to interact in communities to feel included. However, sometimes they face exclusion situations in many interactions. Nevertheless, little is known about how this issue affects consumers' purchases after being excluded from a brand community. In this study, We performed three laboratory experiments to demonstrate the proposed effects of social exclusion on consumer choice and sequential mediation. In this study, we demonstrated that after being excluded from a brand community, consumers perceive their relationship poorer compared with included consumers (study 1), exhibit lower perceptions of an ideal relationship with the brand (study 2), and are more prone to purchase a product in a rival brand (study 3). Furthermore, the sequential mediation of ideal perceptions of brand relationship and quality drives consumer intention to purchase a product from a rival brand. These findings contribute to the social exclusion theory and brand community literature by demonstrating how consumers felt after being excluded from a brand community and the psychological mechanisms underlying this effect.
References
Axios/Ipsos. (2020). Axios/Ipsos Coronavirus Index Wave 11 (Version 3) [Dataset]. Cornell University, Ithaca, NY: Roper Center for Public Opinion Research. doi:10.25940/ROPER-31117428
Atchley, C. (2021, September 17). Pandemic-induced consumption trends are here to stay. Food Business News: https://www.foodbusinessnews.net/articles/19626-pandemic-induced-consumer-trends-are-here-to-stay
Aurigemma, S. et al. (2019). Evaluating the core and full protection motivation theory nomologies for the voluntary adoption of password manager applications. Transactions on Replication Research, 5, 1-21. https://doi.org/10.17705/1atrr.00035
Barr, L. (2021, October 25). Hate crimes against Asians rose 76% in 2020 amid pandemic, FBI says. ABC News: https://abcnews.go.com/US/hate-crimes-asians-rose-76-2020-amid-pandemic/story?id=80746198
Brand, C., Schwanen, T., & Anable, J. (2020). Online Omnivores’ or ‘Willing but struggling’: Identifying online grocery shopping behavior segments using attitude theory, Journal of Retailing and Consumer Services, 57 (102195), 1-10,
https://doi.org/10.1016/j.jretconser.2020.102195
Bish, A., & Michie, S. (2010). Demographic and attitudinal determinants of protective behaviors during a pandemic: A review. British Journal of Health Psychology, 15, 797-824. https://doi.org/10.1348/135910710X485826
Brynjolfsson, E., Horton, J., Ozimek, A., Rock, D., Sharma, G. & Ye, H.Y.T. (2020), COVID-19 and Remote Work: An Early Look at US Data, available at: http://hdl.voced.edu.au/10707/537312.
Chua, G., Yuen, K. F., Wang, X., & Wong, Y. D. (2021). The Determinants of Panic Buying during COVID-19. International journal of environmental research and public health, 18(6), 3247. https://doi.org/10.3390/ijerph18063247
Centers for Disease Control and Prevention (CDC). (2020, September 11). Coronavirus Disease 2019 (COVID-19): Older adults. https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/older-adults.html
Ecola, L., Lu, H., & Rohr, C. (2020). How is COVID-19 changing Americans’ online shopping habits? RAND Corporation: https://www.rand.org/pubs/research_reports/RRA308-6.html
Eriksson, N., & Stenius, M. (2022). Online grocery shoppers due to the COVID-19 pandemic – An analysis of demographic and household characteristics, Procedia Computer Science, 196, 93-100. https://doi.org/10.1016/j.procs.2021.11.077
Fietkiewicz, K. J., Lins, E., Baran, K.S., & Stock, W. G. (2016). Inter-generational comparison of social media use: Investigating the online behavior of different generational cohorts. 49th Hawaii International Conference on System Sciences (HICSS) Conference Proceeding, Koloa, HI, 3829-3838. https://doi.org/10.1109/HICSS.2016.477
Friemel, T. N. (2016). The digital divide has grown old: Determinants of a digital divide among seniors. New Media & Society, 18(2), 313-331. https://doi.org/10.1177/1461444814538648
Gordon-Wilson, S. Consumption practices during the COVID-19 crisis. International Journal of Consumer Studies, 46, 575– 588. https://doi.org/10.1111/ijcs.12701
Grohol, J. M. (2020, March 19). Panic buying: The psychology of hoarding toilet paper. Beans, and soup. PsychCentral: https://psychcentral.com/blog/panic-buying-the-psychology-of-hoarding-toilet-paper-beans-soup
Gramlich, J., & Funk, C. (2020, June 4). Black Americans face higher COVID-19 risks, are more hesitant to trust medical scientists, get vaccinated. Pew Research Center: https://www.pewresearch.org/fact-tank/2020/06/04/black-americans-face-higher-covid-19-risks-are-more-hesitant-to-trust-medical-scientists-get-vaccinated/
Hao, T. H. (2019, November). Digital divide: Theoretical review and future research suggestions. Paper presented at 2019 National Communication Annual Convention, Baltimore, MD.
Hubbard, K. (2021, July 22). Outside of sleeping, Americans spend most of their time watching television, U.S. News: https://www.usnews.com/news/best-states/articles/2021-07-22/americans-spent-more-time-watching-television-during-covid-19-than-working
Ingilizian, Z. (2020, May 14). Is staying in the new going out? How the COVID-19 pandemic is fuelling the stay-at-home economy. World Economic Forum: https://www.weforum.org/agenda/2020/05/covid19-coronavirus-digital-economy-consumption-ecommerce-stay-at-home-online-education-streaming/
IBM (2010). Predictive modeling with IBM SPSS Modeler student guide. Course Code: 0A032. IMB.
Juliano, C., Castrucci, B., & Fraser, M. R. (2021). COVID-19 and Public Health: Looking Back, Moving Forward. Journal of public health management and practice (JPHMP), 27(Supplement 1), S1–S4. https://doi.org/10.1097/PHH.0000000000001300
Kassas, B., & Nayga, R. M. Jr. (2021). Understanding the importance and timing of panic buying among U.S. Households during the COVID-19 pandemic, Food Quality and Preference, 93 (104240), https://doi.org/10.1016/j.foodqual.2021.104240
Khosravi, M. (2020). Perceived risk of COVID-19 pandemic: The role of public worry and trust. Electronic Journal of General Medicine, 17(4), 1-2. https://doi.org/10.29333/ejgm/7856
Kim, J, Yang, K, Min, J, & White, B. (2021). Hope, fear, and consumer behavioral change amid COVID-19: Application of protection motivation theory. International Journal of Consumer Studies, 46, 558–574. https://doi.org/10.1111/ijcs.12700
Kohli, S., Timelin, B., Fabrius, &Veranen, S. M. (2020). How COVID-19 is changing consumer behavior - now and forever. Mckinsey & Company: https://www.mckinsey.com/~/media/McKinsey/Industries/Retail/Our%20Insights/How%20COVID%2019%20is%20changing%20consumer%20behavior%20now%20and%20forever/How-COVID-19-is-changing-consumer-behaviornow-and-forever.pdf?msclkid=2c73b35ed12d11ec96050efeeefdb11d
Kotler, P. (1997). Marketing management: Analysis plan and control. Prentice-Hall.
Kowalski, R. M., & Black, K. J. (2021). Protection motivation and the COVID-19 virus. Health Communication, 36(1), 15-22. https://doi.org/10.1080/10410236.2020.1847448
Laurincin, C. T., & McClinton, A. (2020). The COVID-19 pandemic: A call to action to identify and address racial and ethnic disparities. Journal of Racial and Ethnic Health Disparities, 7(3), 398-402. https://doi.org/10.1017/s40615-020-00756-0
Lopez, M.H., Rainie, L., & Budiman, A. (2020, May 5). Financial and health impacts of COVID-19 vary widely by race and ethnicity. Pew Research Center: https://www.pewresearch.org/fact-tank/2020/05/05/financial-and-health-impacts-of-covid-19-vary-widely-by-race-and-ethnicity/
Martins, J. M., & Brooks, G. (2010). Teaching consumer demographics to marketing students, Popular Research Policy Review, 29, 81-92. https://doi.org/10.1007/s11113-009-9146-5
Martins, J. M., Yusuf, F., & Swanson, D. A. (2012). Consumer demographics and behaviour: Markets are people. Springer.
Monmouth University Polling Institute. (2020). Monmouth University National Poll: April 2020 (Version 2) [Dataset]. Cornell University, Ithaca, NY: Roper Center for Public Opinion Research. doi:10.25940/ROPER-31117286
Mothersbaugh, D. L., Hawkins, D. I., & Kleiser, S. B. (2020). Consumer behavior: Building marketing strategy (14th ed.). McGraw Hill.
Mongey, S. (2020, April 3). Who are the workers who cannot work from home? Becker Friedman Institute: https://bfi.uchicago.edu/insight/finding/who-are-the-workers-who-cannot-work-from-home/
Morgan, B. (2020, December 14). 3 lasting changes to grocery shopping after COVID-19. Forbes: https://www.forbes.com/sites/blakemorgan/2020/12/14/3-lasting-changes-to-grocery-shopping-after-covid-19/?sh=7f0548f354e7
Ntontis, E., Vestergren, S., Saavedra, P., Neville, F., Jurstakova, K., Cocking, C., Lay, S., Drury, J., Stott, C., Reicher, S., & Vignoles, V. L. (2022). Is it really “panic buying”? Public perceptions and experiences of extra buying at the onset of the COVID-19 pandemic. PloS one, 17(2), e0264618. https://doi.org/10.1371/journal.pone.0264618
Okuhara, T., Okada, H., & Kiuchi, T. (2020). Examining persuasive message type to encourage staying at home during the COVID-19 pandemic and social lockdown: A randomized controlled study in Japan, Patient Education and Counseling (103), 12, 2588-2593. https://doi.org/10.1016/j.pec.2020.08.016.
Quan-Haase, A., Williams, C., Kicevski, M., Elueze, I., & Wellman, B. (2018). Dividing the grey divide: Deconstructing myths about older adults’ online activities, skills, and attitudes. American Behavioral Scientist, 62(9), 1207-1228. https://doi.org/10.1177/0002764218777572
Rogers, R. W. (1975). A protection motivation theory of fear appeals and attitude change. Journal of Psychology, 91(1), 93-114. https://doi.org/10.1080/002239890.1975.9915803
Rokach, L., Maimon, O. (2008). Data mining with decision trees: Theory and applications. World Scientific Pub.
Sadlier, A. (2020, September 10). People spend more time than ever binge watching moves, TV this summer. New York Post: https://nypost.com/2020/09/10/amount-of-time-people-spend-binge-watching-movies-and-tv-streamed-upward-during-the-summer/
Scopelliti, M., Pacilli, M. G., & Aquino, A. (2021). TV News and COVID-19: Media Influence on Healthy Behavior in Public Spaces. International journal of environmental research and public health, 18(4), 1879. https://doi.org/10.3390/ijerph18041879
Sheth, J. (1977, June 1). Demographics in consumer behaviors. JAG: https://jagsheth.com/marketing-theory/demographics-in-consumer-behavior/
Sigre-Leirós, V., Billieux, J., Mohr, C., Maurage, P., King, D. L., Schimmenti, A., & Flayelle, M. (2022). Binge-watching in times of COVID-19: A longitudinal examination of changes in affect and TV series consumption patterns during lockdown. Psychology of Popular Media. Advance online publication. https://doi.org/10.1037/ppm0000390
Song, E., & Yoo, H. J. (2020). Impact of social support and social trust on public viral risk response: A Covid-19 survey study. International Journal of Environmental Research and Public Health, 17(6589), 1-14.
Spence, P. R., Lachlan, K. A., Burke, J. M., & Seeger, M. W. (2007). Media use and information needs of the disabled during a natural disaster. Journal of Health Care for the Poor and Underserved, 18 (2), 394–404. https://doi.org/10.1353/hpu.2007.0047
Spence, P. R., Lachlan, K. A., & Burke, J. A. (2008). Crisis preparation, media use, and information seeking: Patterns across Katrina evacuees and lessons learned for crisis communication. Journal of Emergency Management, 6(1), 11–23.
Strickland, J. (2014). Predictive analytics using R. Lulu.
Van Droogenbroeck, E. & Van Hove, L. (2017). Adoption of Online Grocery Shopping: Personal or Household Characteristics? Journal of Internet Commerce, 16, 255-286. https://doi.org/0.1080/15332861.2017.1317149
Wu, M. Y. (2018). Ethical Customer Relations in Electronic Commerce Environment: Dialogic Communication and Making Customers’ Expectations Real. China Media Research, 14(3), 34-43.
Wu, M. Y. (2020, June 6). How has COVID-19 impacted consumer behaviors and organizational responses? Northeastern University: https://www.northeastern.edu/orgcomm/2020/06/06/how-covid-19-is-impacting-consumer-behaviors-and-organizational-response-strategies/
Wu, M. Y. (2022a). Exploring How Perceived Risk and Demographic Factors Affect Consumer Behaviors Amid the COVID-19 Pandemic with Predictive Analytics. Top paper presented at 2022 Eastern Communication Association (ECA) Annual Convention, Applied Communication Division, Philadelphia, PA.
Wu, M. Y. (2022b). Fostering resilience: Understanding generational differences in information and communication technology (ICT) and social media use, Journal of Communication Technology, 5(2), 30-52, https://doi.org/10.51548/joctec-2022-007
Downloads
Published
Issue
Section
License
Copyright Statement
- The authors authorize the publication of the article in the journal.
- The opinions and ideas expressed in articles are the authors' sole responsibility.
- The authors guarantee that the article is not the result of plagiarism. Failure to do so may result in penalties for the situation.
- Editors can adjust the text and formatting to fit the article according to the journal's publication standards.
- The articles published are the property of CBR and are protected by copyright. However, authors can disclose and make their articles available for free.
