Influencer Marketing: An Integrative Model
P Sanjaya Sarathy and Sanjay Patro
PUBLISHED : 07 NOV 2023
Abstract
During the pandemic’s rapid spread, the use of influencer marketing has expanded several
folds. As a result, it has evolved into an essential component of digital marketing strategy for
both marketing and revenue generation. Marketers have recently leveraged either Key Opinion
Leaders or Artificial Intelligence influencers, or both, to influence purchase intention for certain
products and services in order to improve sales success. As a first step in the process of building an
integrative model of Influencer Marketing (IM), the present study has explored the various issues
associated with IM, such as: Influencers and their classification, Social Media Influencers (SMI),
Key Opinion Leader Influencers (KOL), Artificial Intelligence Influencers (AI), Para Social
Relationship (PSR)and Consumer Decision Making Process (CDMC), based on the review of
extant literature. The second step was to clearly define the process of measurement, which was done
with a special focus on the research on Key Opinion Leaders and AI influencers, leading to
proposition of parasocial interaction as a moderating factor. The third and the final step was to
establish and integrate the multiple comparison standards into a single framework, which attempts
to bring together the different perspectives of influencer marketing. Contributions of this paper to
the literature on influencer marketing in the context of parasocial interactions are two-fold: firstly,
it identifies and assesses the contribution of variables that influence the purchase intention under
the IM strategy; and secondly, it integrates the multiple standards of comparison into a single
framework ‘IM2 model’, which is an Integrative Model of Influencer Marketing and so can stimulate
further discussion and research on IM.
Key Words
Influencer marketing, Key opinion leaders, Artificial intelligence, Consumer
behavior, Purchase intention, Parasocial interaction
Author Biography
P Sanjaya Sarathy Doctoral Scholar of Marketing, XLRI, Xavier School of Management, C. H. Area, Jamshedpur, India.
E-mail:
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Sanjay Patro
Dean-Academics and Professor of Marketing, XLRI, Xavier School of Management, C. H. Area, Jamshedpur,
India. E-mail:
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References
- Baron, R. A., & Byrne, D. E. (1977). Social psychology: Understanding human
interaction
. Boston; Toronto: Allyn and Bacon.
- Batra, R., & Ahtola, O. T. (1991). Measuring the hedonic and utilitarian sources
of consumer attitudes.
Marketing Letters, 2, 159-170.
- Bedard, Nicole S. A., & Tolmie, C. R. (2018). Millennials’ green consumption
behaviour: Exploring the role of social media.
Corporate Social Responsibility and
Environmental Management
, 25(6), 1388-1396.
- Belleau, B. D., Summers, T. A., Xu, Y., & Pinel, R. (2007). Theory of reasoned
action: Purchase intention of young consumers.
Clothing and Textiles Research Journal,
25(3), 244-257.
- Bergkvist, L., & Zhou, K. Q. (2016). Celebrity endorsements: A literature review
and research agenda.
International Journal of Advertising, 35(4), 642-663.
- Brandabur, R. E. (2012). Personal branding of a teacher - An approach into
e-educational environment. In
Conference proceedings of» eLearning and Software
for Education «(eLSE)
, 8(1), 44-49. Carol I National Defence University Publishing
House.
- Casalo, L. V., Flavián, C., & Ibáñez-Sánchez, S. (2020). Influencers on Instagram:
Antecedents and consequences of opinion leadership.
Journal of Business Research,
117, 510-519.
- Chahal, M. (2016). Social commerce: How willing are consumers to buy through
social media.
Marketing Week, 23, 7-17.
- Cho, Y., Hwang, J., & Lee, D. (2012). Identification of effective opinion leaders
in the diffusion of technological innovation: A social network approach.
Technological Forecasting and Social Change, 79(1), 97-106.
- Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer
technology: A comparison of two theoretical models.
Management Science, 35(8),
982-1003.
- De Veirman, M., Cauberghe, V., & Hudders, L. (2017). Marketing through
Instagram influencers: The impact of number of followers and product divergence
on brand attitude.
International Journal of Advertising, 36(5), 798-828.
- Djafarova, E., & Rushworth, C. (2017). Exploring the credibility of online
celebrities’ Instagram profiles in influencing the purchase decisions of young female
users.
Computers in Human Behavior, 68, 1-7.
- Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and
store information on buyers’ product evaluations.
Journal of Marketing Research,
28(3), 307-319.
- Fertik, M. (2020). Why is influencer marketing such a big deal right now.
Forbes.
- Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An
introduction to theory and research.
- Flynn, L. R., Goldsmith, R. E., & Eastman, J. K. (1996). Opinion leaders and
opinion seekers: Two new measurement scales.
Journal of the Academy of Marketing
Science
, 24, 137-147.
- Forsyth, D. R. (2014). How do leaders lead? Through social influence. In
Conceptions of leadership: Enduring ideas and emerging insights (pp. 185-200). New
York: Palgrave Macmillan US.
- Fox, J., Ahn, S. J., Janssen, J. H., Yeykelis, L., Segovia, K. Y., & Bailenson, J. N.
(2015). Avatars versus agents: A meta-analysis quantifying the effect of agency
on social influence.
Human–Computer Interaction, 30(5), 401-432.
- Ge, J., & Gretzel, U. (2018). Emoji rhetoric: A social media influencer perspective.
Journal of Marketing Management, 34(15-16), 1272-1295.
- George, J. F. (2004). The theory of planned behavior and Internet purchasing.
Internet Research, 14(3), 198-212.
- Hall, N. (2014). The Kardashian index: A measure of discrepant social media
profile for scientists.
Genome Biology, 15(7), 1-3.
- Han, S., & Yang, H. (2018). Understanding adoption of intelligent personal
assistants: A parasocial relationship perspective.
Industrial Management & Data
Systems
, 118(3), 618-636.
- Hartmann, T., Stuke, D., & Daschmann, G. (2008). Positive parasocial relationships
with drivers affect suspense in racing sport spectators.
Journal of Media Psychology,
20(1), 24-34.
- Hsu, C. L., ChuanChuan Lin, J., & Chiang, H. S. (2013). The effects of blogger
recommendations on customers’ online shopping intentions.
Internet Research,
23(1), 69-88.
- Hwang, C., Chung, T. L., & Sanders, E. A. (2016). Attitudes and purchase
intentions for smart clothing: Examining US consumers’ functional, expressive,
and aesthetic needs for solar-powered clothing.
Clothing and Textiles Research Journal,
34(3), 207-222.
- Hwang, K., & Zhang, Q. (2018). Influence of parasocial relationship between
digital celebrities and their followers on followers’ purchase and electronic wordof-mouth
intentions, and persuasion knowledge.
Computers in Human Behavior,
87, 155-173.
- Ismail, K. (2018). Social media influencers: Mega, macro, micro or nano.
CMS
Wire
, 10.
- Jin, S. V., Muqaddam, A., & Ryu, E. (2019). Instafamous and social media
influencer marketing.
Marketing Intelligence & Planning, 37(5), 567-579.
- Keller, E., & Berry, J. (2003).
The influentials: One American in ten tells the other nine
how to vote, where to eat, and what to buy
. Simon and Schuster.
- Khamis, S., Ang, L., & Welling, R. (2017). Self-branding, ‘micro-celebrity’ and
the rise of social media influencers.
Celebrity Studies, 8(2), 191-208.
- Khan, M. S. A., Abdullah, S., Ali, A., Amin, F., & Rahman, K. (2019). Hybrid
aggregation operators based on Pythagorean hesitant fuzzy sets and their
application to group decision making.
Granular Computing, 4, 469-482.
- Kim, S., & McGill, A. L. (2011). Gaming with Mr. Slot or gaming the slot machine?
Power, anthropomorphism, and risk perception.
Journal of Consumer Research, 38(1),
94-107.
- Kim, S., Kandampully, J., & Bilgihan, A. (2018). The influence of eWOM
communications: An application of online social network framework.
Computers
in Human Behavior
, 80, 243-254.
- Kotler, P., & Armstrong, G. (2003). Principles of Marketing (Prentice-Hall, New
Jersey).
- Kusumasondjaja, S., & Tjiptono, F. (2019). Endorsement and visual complexity
in food advertising on Instagram.
Internet Research, 29(4), 659-687.
- Lee, E., Lee, J. A., Moon, J. H., & Sung, Y. (2015). Pictures speak louder than
words: Motivations for using Instagram.
Cyberpsychology, Behavior, and Social
Networking
, 18(9), 552-556.
- Lee, J. A., & Eastin, M. S. (2020). I like what she’s# endorsing: The impact of
female social media influencers’ perceived sincerity, consumer envy, and product
type.
Journal of Interactive Advertising, 20(1), 76-91.
- Leibner, L., Stehr, P., Rössler, P., Doringer, E., Morsbach, M., & Simon, L. (2014).
Parasocial opinion leadership: Media personalities’ influence within parasocial
relations: Theoretical conceptualization and preliminary results.
Publizistik, 59,
247-267.
- Li, Y. M., Lee, Y. L., & Lien, N. J. (2012). Online social advertising via influential
endorsers.
International Journal of Electronic Commerce, 16(3), 119-154.
- Lou, C., & Yuan, S. (2019). Influencer marketing: How message value and
credibility affect consumer trust of branded content on social media.
Journal of
Interactive Advertising
, 19(1), 58-73.
- L. Percy, J.R. Rossiter, Advertising strategy: A communication theory approach,
1980 New York, NJ.
- Lyons, B., & Henderson, K. (2005). Opinion leadership in a computermediated
environment.
Journal of Consumer Behaviour: An International Research Review,
4(5), 319-329.
- Martensen, A., Brockenhuus-Schack, S., & Zahid, A. L. (2018). How citizen
influencers persuade their followers.
Journal of Fashion Marketing and Management:
An International Journal
, 22(3), 335-353.
- McQuarrie, E. F., Miller, J., & Phillips, B. J. (2013). The megaphone effect: Taste
and audience in fashion blogging.
Journal of Consumer Research, 40(1), 136-158.
- Meng, F., Wei, J., & Zhu, Q. (2011, May). Study on the impacts of opinion leader
in online consuming decision. In
2011 International Joint Conference on Service
Sciences
(pp. 140-144). IEEE.
- Moravec, P., Minas, R., & Dennis, A. R. (2018). Fake news on social media:
People believe what they want to believe when it makes no sense at all.
Kelley
School of Business Research Paper
, 18-87.
- Noor, N., Rao Hill, S., & Troshani, I. (2022). Artificial intelligence service agents:
Role of parasocial relationship.
Journal of Computer Information Systems, 62(5),
1009-1023.
- Nunes, R. H., Ferreira, J. B., Freitas, A. S. D., & Ramos, F. L. (2018). The effects
of social media opinion leaders’ recommendations on followers’ intention to buy.
Revista Brasileira de Gestao de Negocios, 20, 57-73.
- Ohanian, R. (1990). Construction and validation of a scale to measure celebrity
endorsers’ perceived expertise, trustworthiness, and attractiveness.
Journal of
Advertising
, 19(3), 39-52.
- Park, J., & Stoel, L. (2005). Effect of brand familiarity, experience and information
on online apparel purchase.
International Journal of Retail & Distribution Management,
33(2), 148-160.
- Peter, P. and Olson, J. (2007). Consumer Behaviour. McGraw-Hill, London.
- Peters, T. (1997). The brand called you.Fast Company, 10(10), 83-90.
- Porteous, J. (2018). Micro Influencers vs Macro Influencers, What’s Best for Your
Business? Social bakers.
- Rajagopal, A. (2020). Defining Functional Concepts of Brands: Conceptualization
and Literature Review.
Available at SSRN 3528603.
- Rodgers, S. (2021). Themed issue introduction: Promises and perils of artificial
intelligence and advertising.
Journal of Advertising, 50(1), 1-10.
- Rossiter, J. R., & Smidts, A. (2001). Presenter Effects in Advertising: the Viscap
Model.
ACR European Advances.
- Rutter, R. N., Barnes, S. J., Roper, S., Nadeau, J., & Lettice, F. (2021). Social
media influencers, product placement and network engagement: using AI image
analysis to empirically test relationships.
Industrial Management & Data Systems,
121(12), 2387-2410.
- Sands, S., Campbell, C. L., Plangger, K., & Ferraro, C. (2022). Unreal influence:
leveraging AI in influencer marketing.
European Journal of Marketing, 56(6),
1721-1747.
- Sokolova, K., & Kefi, H. (2020). Instagram and YouTube bloggers promote it, why
should I buy? How credibility and parasocial interaction influence purchase
intentions.
Journal of Retailing and Consumer Services, 53, 101742.
- Spreng, R. A., & Olshavsky, R. W. (1993). A desires congruency model of consumer
satisfaction.
Journal of the Academy of Marketing Science, 21, 169-177.
- Thomas, V. L., & Fowler, K. (2021). Close encounters of the AI kind: Use of AI
influencers as brand endorsers.
Journal of Advertising, 50(1), 11-25.
- Tsai, W. H. S., & Men, L. R. (2017). Consumer engagement with brands on social
network sites: A cross-cultural comparison of China and the USA.
Journal of
Marketing Communications
, 23(1), 2-21.
- Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research
agenda on interventions.
Decision sciences, 39(2), 273-315.
- Venkatesh, V., & Davis, F.D. (2000). A theoretical extension of the technology
acceptance model: Four longitudinal field studies.
Management Science, 46(2),
186-204.
- Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance
of information technology: Toward a unified view.
MIS Quarterly, 425-478.
- Vidani, J. (2019, February). Influencer Marketing: A New Trend. In
JN Vidani
(2019), Influencer Marketing: A New Trend, Compendium of Research Papers of
National Conference on Multidisciplinary in Social science and Management Studies
,
6(1), 344-353.
- Williams, J., & Chinn, S. J. (2010). Meeting relationship-marketing goals through
social media: A conceptual model for sport marketers.
International Journal of Sport
Communication
, 3(4), 422-437.
- Winarno, W. A., & Putra, H. S. (2020). Technology acceptance model of the
Indonesian government financial reporting information systems.
International Journal
of Public Sector Performance Management
, 6(1), 68-84.
- Yang, K., & Jolly, L. D. (2009). The effects of consumer perceived value and
subjective norm on mobile data service adoption between American and Korean
consumers.
Journal of Retailing and Consumer Services, 16(6), 502-508.
- Yang, L. W., Aggarwal, P., & McGill, A. L. (2020). The 3 C’s of anthropomorphism:
Connection, comprehension, and competition.
Consumer Psychology Review, 3(1),
3-19.
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