A Comprehensive Overview of Micro-Influencer Marketing: Decoding the Current Landscape, Impacts, and Trends
Abstract
:1. Introduction
2. Methodology
- Identifying key databases and reviewing publications.
- Defining critical domains and categorizing the literature examination into two segments—one focused on investigations within the realm of business administration and another on investigations outside the realm.
- Conducting bibliometric and content evaluations for each segment separately.
3. Primary Research
4. Systematic Review of the Two Paradigms
4.1. Key Journals with Published Papers on the Theme of Micro-Influencers
4.2. Research Focus Outside the Paradigm of Business and Management
4.3. Research Focus on Business and Management Paradigm
4.3.1. Consumption of Social Media as Platforms for Micro-Influencers
4.3.2. Popular Self-Affirmation Product Types with Micro-Influencer
4.3.3. Results from Co-Citation Analysis
4.3.4. Traditional and Monotonous Theory Development
4.3.5. Emerging Trends Amid the COVID-19 Pandemic
5. Discussion
6. Future Research Agenda
7. Limitations and Conclusions
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Baumeister, R.F.; Leary, M.R. Writing Narrative Literature Reviews. Rev. Gen. Psychol. 1997, 1, 311–320. [Google Scholar] [CrossRef]
- Zupic, I.; Čater, T. Bibliometric Methods in Management and Organization. Organ. Res. Methods 2015, 18, 429–472. [Google Scholar] [CrossRef]
- Merigó, J.M.; Mas-Tur, A.; Roig-Tierno, N.; Ribeiro-Soriano, D. A Bibliometric Overview of the Journal of Business Research between 1973 and 2014. J. Bus. Res. 2015, 68, 2645–2653. [Google Scholar] [CrossRef]
- Rowley, J.; Sbaffi, L. Academics’ Attitudes towards Peer Review in Scholarly Journals and the Effect of Role and Discipline. J. Inf. Sci. 2018, 44, 644–657. [Google Scholar] [CrossRef]
- Nightingale, A. A Guide to Systematic Literature Reviews. Surgery 2009, 27, 381–384. [Google Scholar] [CrossRef]
- Pozharliev, R.; Rossi, D.; De Angelis, M. A Picture Says More than a Thousand Words: Using Consumer Neuroscience to Study Instagram Users’ Responses to Influencer Advertising. Psychol. Mark. 2022, 39, 1336–1349. [Google Scholar] [CrossRef]
- Shen, Z. A Persuasive eWOM Model for Increasing Consumer Engagement on Social Media: Evidence from Irish Fashion Micro-Influencers. J. Res. Interact. Mark. 2021, 15, 181–199. [Google Scholar] [CrossRef]
- Boerman, S.C.; Meijers, M.H.C.; Zwart, W. The Importance of Influencer-Message Congruence When Employing Greenfluencers to Promote Pro-Environmental Behavior. Environ. Commun. 2022, 16, 920–941. [Google Scholar] [CrossRef]
- Li, W.; Zhao, F.; Lee, J.M.; Park, J.; Septianto, F.; Seo, Y. How Micro- (vs. Mega-) Influencers Generate Word of Mouth in the Digital Economy Age: The Moderating Role of Mindset. J. Bus. Res. 2024, 171, 114387. [Google Scholar] [CrossRef]
- Rungruangjit, W.; Charoenpornpanichkul, K. Building Stronger Brand Evangelism for Sustainable Marketing through Micro-Influencer-Generated Content on Instagram in the Fashion Industry. Sustainability 2022, 14, 15770. [Google Scholar] [CrossRef]
- Chiu, C.L.; Ho, H.C. Impact of Celebrity, Micro-Celebrity, and Virtual Influencers on Chinese Gen Z’s Purchase Intention Through Social Media. SAGE Open 2023, 13, 21582440231164034. Available online: https://journals.sagepub.com/doi/full/10.1177/21582440231164034 (accessed on 29 December 2023). [CrossRef]
- Pangarkar, A.; Rathee, S. The Role of Conspicuity: Impact of Social Influencers on Purchase Decisions of Luxury Consumers. Int. J. Advert. 2023, 42, 1150–1177. Available online: https://www.tandfonline.com/doi/abs/10.1080/02650487.2022.2084265 (accessed on 29 December 2023). [CrossRef]
- Li, G.; Cao, Y.; Lu, B.; Yu, Y.; Liu, H. Luxury Brands’ Live Streaming Sales: The Roles of Streamer Identity and Level Strategy. Int. J. Advert. 2023, 42, 1178–1200. [Google Scholar] [CrossRef]
- Hudders, L.; De Jans, S.; De Veirman, M. The Commercialization of Social Media Stars: A Literature Review and Conceptual Framework on the Strategic Use of Social Media Influencers. Int. J. Advert. 2021, 40, 327–375. [Google Scholar] [CrossRef]
- Muda, M.; Hamzah, M.I. Should I Suggest This YouTube Clip? The Impact of UGC Source Credibility on eWOM and Purchase Intention. J. Res. Interact. Mark. 2021, 15, 441–459. [Google Scholar] [CrossRef]
- Rosenthal, S.; Mckeown, K. Detecting Influencers in Multiple Online Genres. ACM Trans. Internet Technol. 2017, 17, 1–22. Available online: https://dl.acm.org/doi/abs/10.1145/3014164 (accessed on 30 December 2023). [CrossRef]
- Wang, S.; Gan, T.; Liu, Y.; Zhang, L.; Wu, J.; Nie, L. Discover Micro-Influencers for Brands via Better Understanding. IEEE Trans. Multimed. 2021, 24, 2595–2605. Available online: https://ieeexplore.ieee.org/abstract/document/9454334 (accessed on 18 December 2023). [CrossRef]
- Yang, X.; Kim, S.; Sun, Y. How Do Influencers Mention Brands in Social Media? In Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Vancouver, BC, Canada, 27–30 August 2019; Available online: https://dl.acm.org/doi/abs/10.1145/3341161.3342925 (accessed on 30 December 2023).
- Wang, S.; Gan, T.; Liu, Y.; Wu, J.; Cheng, Y.; Nie, L. Micro-Influencer Recommendation by Multi-Perspective Account Representation Learning. IEEE Trans. Multimed. 2023, 25, 2749–2760. [Google Scholar] [CrossRef]
- Leonardi, S.; Monti, D.; Rizzo, G.; Morisio, M. Mining Micro-Influencers from Social Media Posts. In Proceedings of the 35th Annual ACM Symposium on Applied Computing; Association for Computing Machinery, New York, NY, USA, 30 March 2020; pp. 867–874. [Google Scholar]
- Doshi, R.; Ramesh, A.; Rao, S. Modeling Influencer Marketing Campaigns in Social Networks. IEEE Trans. Comput. Soc. Syst. 2022, 10, 322–334. Available online: https://ieeexplore.ieee.org/abstract/document/9689053 (accessed on 30 December 2023). [CrossRef]
- Arous, I.; Yang, J.; Khayati, M.; Cudré-Mauroux, P. OpenCrowd: A Human-AI Collaborative Approach for Finding Social Influencers via Open-Ended Answers Aggregation. In Proceedings of the Web Conference 2020, Taipei, Taiwan, 20–24 April 2020; Available online: https://dl.acm.org/doi/abs/10.1145/3366423.3380254 (accessed on 30 December 2023).
- Elwood, A.; Gasparin, A.; Rozza, A. Ranking Micro-Influencers: A Novel Multi-Task Learning and Interpretable Framework. In Proceedings of the 2021 IEEE International Symposium on Multimedia (ISM), Naple, Italy, 29 November–1 December 2021; pp. 130–137. [Google Scholar]
- Gan, T.; Wang, S.; Liu, M.; Song, X.; Yao, Y.; Nie, L. Seeking Micro-Influencers for Brand Promotion. In Proceedings of the 27th ACM International Conference on Multimedia, Nice, France, 15 October 2019; ACM: New York, NY, USA, 2019; pp. 1933–1941. [Google Scholar]
- Tabassum, S.; Gama, J.; Azevedo, P.J.; Cordeiro, M.; Martins, C.; Martins, A. Social Network Analytics and Visualization: Dynamic Topic-based Influence Analysis in Evolving Micro-blogs. Expert Syst. 2023, 40, e13195. Available online: https://onlinelibrary.wiley.com/doi/abs/10.1111/exsy.13195 (accessed on 30 December 2023). [CrossRef]
- Farseev, A.; Lepikhin, K.; Schwartz, H.; Ang, E.K.; Powar, K. SoMin.Ai: Social Multimedia Influencer Discovery Marketplace. In Proceedings of the 26th ACM international conference on Multimedia, Seoul, Republic of Korea, 22–26 October 2018; Association for Computing Machinery: New York, NY, USA, 2018; pp. 1234–1236. [Google Scholar]
- Kausar, S.; Tahir, B.; Mehmood, M.A. Understanding the Role of Political Micro-Influencers in Pakistan. In Proceedings of the 2021 International Conference on Frontiers of Information Technology (FIT), Islamabad, Pakistan, 13–14 December 2021; pp. 31–36. [Google Scholar]
- Oh, H.; Lee, J.; Lee, J.-S.; Kim, S.-M.; Lim, S.; Jung, D. Which Influencers Can Maximize PCR of E-Commerce? Electronics 2023, 12, 2626. [Google Scholar] [CrossRef]
- Rakoczy, M.E.; Bouzeghoub, A.; Lopes Gancarski, A.; Wegrzyn-Wolska, K. In the Search of Quality Influence on a Small Scale—Micro-Influencers Discovery. In Proceedings of the On the Move to Meaningful Internet Systems. OTM 2018 Conferences, Valletta, Malta, 22–26 October 2018; Panetto, H., Debruyne, C., Proper, H.A., Ardagna, C.A., Roman, D., Meersman, R., Eds.; Springer International Publishing: Cham, Switzerland, 2018; pp. 138–153. [Google Scholar]
- Yadav, J.; Misra, M.; Rana, N.P.; Singh, K. Exploring the Synergy between Nano-Influencers and Sports Community: Behavior Mapping through Machine Learning. ITP 2022, 35, 1829–1854. [Google Scholar] [CrossRef]
- Kirilenko, A.; Emin, K.; Tavares, K.C. Instagram Travel Influencers Coping with COVID-19 Travel Disruption. Inf. Technol. Tour. 2024, 26, 119–146. Available online: https://link.springer.com/article/10.1007/s40558-023-00276-7 (accessed on 30 December 2023). [CrossRef]
- Miguel, C.; Clare, C.; Ashworth, C.J.; Hoang, D. Self-Branding and Content Creation Strategies on Instagram: A Case Study of Foodie Influencers. Inf. Commun. Soc. 2023, 1–21. [Google Scholar] [CrossRef]
- Vizcaí no-Verdú, A.; De-Casas-Moreno, P.; Jaramillo-Dent, D. Thanks for Joining Our Life: Intimacy as Performativity on YouTube Parenting Vlogs. Prof. Inf. 2022, 31. [Google Scholar] [CrossRef]
- Ngai, N. Homemade Pet Celebrities: The Everyday Experience of Micro-Celebrity in Promoting the Self and Others. Celebr. Stud. 2023, 14, 437–454. [Google Scholar] [CrossRef]
- Abidin, C. #familygoals: Family Influencers, Calibrated Amateurism, and Justifying Young Digital Labor. Soc. Media + Soc. 2017, 3, 2056305117707191. [Google Scholar] [CrossRef]
- Khamis, S.; Ang, L.; Welling, R. Self-Branding, ‘Micro-Celebrity’ and the Rise of Social Media Influencers. Celebr. Stud. 2017, 8, 191–208. [Google Scholar] [CrossRef]
- Maddox, J. Micro-Celebrities of Information: Mapping Calibrated Expertise and Knowledge Influencers among Social Media Veterinarians. Inf. Commun. Soc. 2023, 26, 2726–2752. [Google Scholar] [CrossRef]
- Gil-Quintana, J.; Vida De León, E.; Osuna-Acedo, S.; Marta-Lazo, C. Nano-Influencers Edutubers: Perspective of Centennial Generation Families in Spain. MaC 2022, 10, 247–258. [Google Scholar] [CrossRef]
- Erz, A.; Marder, B.; Osadchaya, E. Hashtags: Motivational Drivers, Their Use, and Differences between Influencers and Followers. Comput. Hum. Behav. 2018, 89, 48–60. [Google Scholar] [CrossRef]
- Lewis, R. “This Is What the News Won’t Show You”: YouTube Creators and the Reactionary Politics of Micro-Celebrity. Telev. New Media 2020, 21, 201–217. [Google Scholar] [CrossRef]
- Lawson, C.E. Skin Deep: Callout Strategies, Influencers, and Racism in the Online Beauty Community. New Media Soc. 2021, 23, 596–612. [Google Scholar] [CrossRef]
- Baker, S.A. Alt. Health Influencers: How Wellness Culture and Web Culture Have Been Weaponised to Promote Conspiracy Theories and Far-Right Extremism during the COVID-19 Pandemic. Eur. J. Cult. Stud. 2022, 25, 3–24. [Google Scholar] [CrossRef]
- Arnesson, J. ‘Endorsing a Dictatorship and Getting Paid for It’: Discursive Struggles over Intimacy and Authenticity in the Politicisation of Influencer Collaborations. New Media Soc. 2022, 14614448211064302. [Google Scholar] [CrossRef]
- Zhang, L.-T.; Zhao, S. Diaspora Micro-Influencers and COVID-19 Communication on Social Media: The Case of Chinese-Speaking YouTube Vloggers. Multilingua 2020, 39, 553–563. [Google Scholar] [CrossRef]
- Duffy, A.; Kang, H.Y.P. Follow Me, I’m Famous: Travel Bloggers’ Self-Mediated Performances of Everyday Exoticism. Media Cult. Soc. 2020, 42, 172–190. [Google Scholar] [CrossRef]
- Boerman, S.C. The Effects of the Standardized Instagram Disclosure for Micro- and Meso-Influencers. Comput. Hum. Behav. 2020, 103, 199–207. [Google Scholar] [CrossRef]
- Zielińska-Tomczak, Ł.; Przymuszała, P.; Tomczak, S.; Krzyśko-Pieczka, I.; Marciniak, R.; Cerbin-Koczorowska, M. How Do Dieticians on Instagram Teach? The Potential of the Kirkpatrick Model in the Evaluation of the Effectiveness of Nutritional Education in Social Media. Nutrients 2021, 13, 2005. [Google Scholar] [CrossRef]
- Carpenter, J.P.; Shelton, C.C.; Schroeder, S.E. The Education Influencer: A New Player in the Educator Professional Landscape. J. Res. Technol. Educ. 2023, 55, 749–764. [Google Scholar] [CrossRef]
- Silva, M.; Anaba, U.; Tulsani, N.J.; Sripad, P.; Walker, J.; Aisiri, A. Gender-Based Violence Narratives in Internet-Based Conversations in Nigeria: Social Listening Study. J. Med. Internet Res. 2023, 25, e46814. [Google Scholar] [CrossRef]
- van Eldik, A.K.; Kneer, J.; Lutkenhaus, R.O.; Jansz, J. Urban Influencers: An Analysis of Urban Identity in YouTube Content of Local Social Media Influencers in a Super-Diverse City. Front. Psychol. 2019, 10, 2876. [Google Scholar] [CrossRef]
- Bu, Y.; Parkinson, J.; Thaichon, P. Influencer Marketing: Sponsorship Disclosure and Value Co-Creation Behaviour. Mark. Intell. Plan. 2022, 40, 854–870. [Google Scholar] [CrossRef]
- Holiday, S.; Hayes, J.L.; Park, H.; Lyu, Y.; Zhou, Y. A Multimodal Emotion Perspective on Social Media Influencer Marketing: The Effectiveness of Influencer Emotions, Network Size, and Branding on Consumer Brand Engagement Using Facial Expression and Linguistic Analysis. J. Interact. Mark. 2023, 10949968231171104. Available online: https://journals.sagepub.com/doi/abs/10.1177/10949968231171104 (accessed on 29 December 2023). [CrossRef]
- Han, W.; Zhang, T. Can Residents Engage Potential Tourists as ‘Micro’ and ‘Nano’ Influencers? Curr. Issues Tour. 2023, 1–17. Available online: https://www.tandfonline.com/doi/abs/10.1080/13683500.2023.2260062 (accessed on 29 December 2023). [CrossRef]
- Pozharliev, R.; Rossi, D.; De Angelis, M. Consumers’ Self-Reported and Brain Responses to Advertising Post on Instagram: The Effect of Number of Followers and Argument Quality. Eur. J. Mark. 2022, 56, 922–948. [Google Scholar] [CrossRef]
- Berne-Manero, C.; Marzo-Navarro, M. Exploring How Influencer and Relationship Marketing Serve Corporate Sustainability. Sustainability 2020, 12, 4392. [Google Scholar] [CrossRef]
- Bainotti, L. How Conspicuousness Becomes Productive on Social Media—Lucia Bainotti. Mark. Theory 2023, 14705931231202435. Available online: https://journals.sagepub.com/doi/full/10.1177/14705931231202435 (accessed on 29 December 2023). [CrossRef]
- Lee, S.S.; Chen, H.; Lee, Y.-H. How Endorser-Product Congruity and Self-Expressiveness Affect Instagram Micro-Celebrities’ Native Advertising Effectiveness. J. Prod. Brand Manag. 2021, 31, 149–162. [Google Scholar] [CrossRef]
- Syrdal, H.A.; Myers, S.; Sen, S.; Woodroof, P.J.; McDowell, W.C. Influencer Marketing and the Growth of Affiliates: The Effects of Language Features on Engagement Behavior. J. Bus. Res. 2023, 163, 113875. [Google Scholar] [CrossRef]
- Hernández-Méndez, J.; Baute-Díaz, N. Influencer Marketing in the Promotion of Tourist Destinations: Mega, Macro and Micro-Influencers. Curr. Issues Tour. 2023, 0, 1–11. [Google Scholar] [CrossRef]
- Pradhan, D.; Kuanr, A.; Anupurba Pahi, S.; Akram, M.S. Influencer Marketing: When and Why Gen Z Consumers Avoid Influencers and Endorsed Brands. Psychol. Mark. 2023, 40, 27–47. [Google Scholar] [CrossRef]
- Sheng, J.; Lee, Y.H.; Lan, H. Parasocial Relationships with Micro-Influencers: Do Sponsorship Disclosure and Electronic Word-of-Mouth Disrupt? Internet Res. 2023; ahead-of-print. [Google Scholar] [CrossRef]
- Alassani, R.; Göretz, J. Product Placements by Micro and Macro Influencers on Instagram. In Proceedings of the Social Computing and Social Media. Communication and Social Communities, Orlando, FL, USA, 26–31 July 2019; Meiselwitz, G., Ed.; Springer International Publishing: Cham, Switzerland, 2019; pp. 251–267. [Google Scholar]
- Rao Hill, S.; Qesja, B. Social Media Influencer Popularity and Authenticity Perception in the Travel Industry. Serv. Ind. J. 2023, 43, 289–311. Available online: https://www.tandfonline.com/doi/abs/10.1080/02642069.2022.2149740 (accessed on 29 December 2023). [CrossRef]
- Kim, D.Y.; Kim, H.Y. Social Media Influencers as Human Brands: An Interactive Marketing Perspective|Emerald Insight. J. Res. Interact. Mark. 2022, 17, 94–109. Available online: https://www.emerald.com/insight/content/doi/10.1108/jrim-08-2021-0200/full/html (accessed on 29 December 2023).
- Giuffredi-Kähr, A.; Petrova, A.; Malär, L. Sponsorship Disclosure of Influencers—A Curse or a Blessing? J. Interact. Mark. 2022, 57, 18–34. Available online: https://journals.sagepub.com/doi/full/10.1177/10949968221075686 (accessed on 29 December 2023). [CrossRef]
- Panopoulos, A.; Poulis, A.; Theodoridis, P.; Kalampakas, A. Influencing Green Purchase Intention through Eco Labels and User-Generated Content. Sustainability 2022, 15, 764. Available online: https://www.mdpi.com/2071-1050/15/1/764 (accessed on 27 December 2023). [CrossRef]
- Valsesia, F.; Proserpio, D.; Nunes, J.C. The Positive Effect of Not Following Others on Social Media. J. Mark. Res. 2020, 57, 1152–1168. [Google Scholar] [CrossRef]
- Hassanzadeh, M.; Taheri, M.; Shokouhyar, S.; Shokoohyar, S. Who One Is, Whom One Knows? Evaluating the Importance of Personal and Social Characteristics of Influential People in Social Networks. Aslib J. Inf. Manag. 2022, 75, 1008–1032. [Google Scholar] [CrossRef]
- Sun, S.; Kim, M.; Nan, D.; Kim, J.H. Relationship between Hashtags Usage and Reach Rate in Instagram. In Proceedings of the 2022 16th International Conference on Ubiquitous Information Management and Communication (IMCOM), Seoul, Republic of Korea, 3–5 January 2022; pp. 1–4. [Google Scholar]
- McQuail’s Media and Mass Communication Theory|Denis McQuail, Mark Deuze|Download on Z-Library. Available online: https://singlelogin.re/book/17242958/f3b5fc/mcquails-media-and-mass-communication-theory.html (accessed on 30 December 2023).
- Fietkiewicz, K.J.; Dorsch, I.; Scheibe, K.; Zimmer, F.; Stock, W.G. Dreaming of Stardom and Money: Micro-Celebrities and Influencers on Live Streaming Services. In Proceedings of the Social Computing and Social Media. User Experience and Behavior, Las Vegas, NV, USA, 15–20 July 2018; Meiselwitz, G., Ed.; Springer International Publishing: Cham, Switzerland, 2018; pp. 240–253. [Google Scholar]
- Su, J.; Shao, P.; Fang, J. A Model for Adoption of Online Shopping: A Perceived Characteristics of Web as a Shopping Channel View. In Proceedings of the 2007 International Conference on Service Systems and Service Management, Chengdu, China, 9–11 June 2007; pp. 1–5. [Google Scholar]
- Kim, D.Y.; Kim, H.-Y. Influencer Advertising on Social Media: The Multiple Inference Model on Influencer-Product Congruence and Sponsorship Disclosure. J. Bus. Res. 2021, 130, 405–415. [Google Scholar] [CrossRef]
- Haenlein, M.; Libai, B. Seeding, Referral, and Recommendation: Creating Profitable Word-of-Mouth Programs. Calif. Manag. Rev. 2017, 59, 68–91. [Google Scholar] [CrossRef]
- Teresa Borges-Tiago, M.; Santiago, J.; Tiago, F. Mega or Macro Social Media Influencers: Who Endorses Brands Better? J. Bus. Res. 2023, 157, 113606. [Google Scholar] [CrossRef]
- Kay, S.; Mulcahy, R.; Parkinson, J. When Less Is More: The Impact of Macro and Micro Social Media Influencers’ Disclosure. J. Mark. Manag. 2020, 36, 248–278. Available online: https://www.tandfonline.com/doi/abs/10.1080/0267257X.2020.1718740 (accessed on 29 December 2023). [CrossRef]
- Campbell, C.; Farrell, J.R. More than Meets the Eye: The Functional Components Underlying Influencer Marketing. Bus. Horiz. 2020, 63, 469–479. [Google Scholar] [CrossRef]
- Park, J.; Lee, J.M.; Xiong, V.Y.; Septianto, F.; Seo, Y. David and Goliath: When and Why Micro-Influencers Are More Persuasive Than Mega-Influencers. J. Advert. 2021, 50, 584–602. Available online: https://www.tandfonline.com/doi/abs/10.1080/00913367.2021.1980470 (accessed on 29 December 2023). [CrossRef]
- Digital 2023: Global Overview Report. Available online: https://datareportal.com/reports/digital-2023-global-overview-report (accessed on 29 December 2023).
- Conde, R.; Casais, B. Micro, Macro and Mega-Influencers on Instagram: The Power of Persuasion via the Parasocial Relationship. J. Bus. Res. 2023, 158, 113708. [Google Scholar] [CrossRef]
- Arnesson, J. Influencers as Ideological Intermediaries: Promotional Politics and Authenticity Labour in Influencer Collaborations. Media Cult. Soc. 2023, 45, 528–544. [Google Scholar] [CrossRef]
- Marques, I.R.; Casais, B.; Camilleri, M.A. The Effect of Macrocelebrity and Microinfluencer Endorsements on Consumer–Brand Engagement in Instagram; Emerald Insight: Leeds, UK, 2021; Available online: https://www.emerald.com/insight/content/doi/10.1108/978-1-80071-264-520211008/full/html (accessed on 30 December 2023).
- Kim, E.; McDonald-Liu, C. Influencers with #NoFilter: How Micro-Celebrities Use Self-Branding Practices on Instagram. Comput. Hum. Behav. 2023, 148, 107892. [Google Scholar] [CrossRef]
- Lv, J.; Yang, R.; Yu, J.; Yao, W.; Wang, Y. Macro-Influencers or Meso-Influencers, How Do Companies Choose? Ind. Manag. Data Syst. 2023, 123, 3018–3037. [Google Scholar] [CrossRef]
Source | Category Quartile of JCR | Percentage of Publications in the Area | Total Citations | Article Count | Subject Area |
---|---|---|---|---|---|
Computers in Human Behavior | Q1 | 100% | 585 | 3 | Experimental Physiology |
Media Culture & Society | Q1 | 100% | 41 | 2 | Sociology |
Current Issues in Tourism | Q1 | 100% | 5 | 2 | Hospitality, Leisure, Sport, and Tourism |
Sustainability | Q2 | 80% | 157 | 4 | Environmental Studies |
IEEE Transactions on Multimedia | Q1 | 66.7% | 22 | 2 | Information Systems |
Celebrity Studies | Q2 | 66.7% | 1822 | 2 | Cultural Studies |
Journal of Research in Interactive Marketing | Q1 | 59% | 793 | 3 | Business |
Journal of Business Research | Q1 | 3 | |||
Journal of Interactive Marketing | Q1 | 2 | |||
International Journal of Advertising | Q2 | 3 | |||
Psychology & Marketing | Q2 | 2 | |||
Information Communication & Society | Q1 | 50% | 47 | 2 | Communication |
New Media & Society | Q1 | 2 |
Main Perspective | Research Focus | Key Themes | Number of Articles Involved | Number of Articles (Q1) | Fields Covered | Percentage |
---|---|---|---|---|---|---|
Technical measurement methods | Micro-influencer cognition techniques | Influencer account content | 5 | 12 (1) | Computer science/ telecommunication/ information science and library/ environmental studies/hospitality, leisure, sport and tourism | 30% |
Audience interests, intentions, sentiments, and behaviors | 5 | |||||
Influencer account data | 3 | |||||
Influencer personal characteristics | 2 | |||||
Product nature | 1 | |||||
Brand investment limit | 1 | |||||
Micro-influencer ranking framework | Influencer account content | 4 | 5 (2) | 12.5% | ||
Audience interests, intentions, emotions, and behaviors | 1 | |||||
Influencer personal characteristics | 1 | |||||
Influencer collaboration preferences | 1 | |||||
Accounts | Presentation strategy | Disclosure of private information | 4 | 6 (6) | Communication/ cultural study/ physiology/ sociology | 15% |
Intentional behind-the-scenes performances | 3 | |||||
Self-focused, self-expressive | 2 | |||||
Creative talents in music, theater, and the arts | 1 | |||||
Connected to urban culture or local influencers | 1 | |||||
Characteristics of Micro-influencer | Media role construction strategy | Authenticity | 6 | 8 (7) | Communication/ physiology/ sociology/ cultural study | 20% |
Affinity | 3 | |||||
Social responsibility | 2 | |||||
Constantly crossing boundaries and blurring the lines between work and play | 2 | |||||
Ordinary, enjoyable experience, inclusive, entrepreneurial, self-promotional, belonging, heroic | 1 | |||||
Communications strategy | A combination of producer, distributor, and interactor | 2 | 2 (1) | Communication/ physiology/ | 5% | |
Use of hashtags | 2 | |||||
Weak cross-media skills | 1 | |||||
Personality traits | Significantly more female than male | 3 | 5 (4) | Physiology/ health care sciences and services/ sociology/ computer/ communication | 12.5% | |
Personality traits tend to be narcissistic, neurotic, extroverted, open, agreeable, conscientious, self-monitoring | 1 | |||||
No preference for more popular brands, perform better in non-luxury collaborations | 1 | |||||
Capability to convince their followers to feel a rapport and identify with them | 1 | |||||
Audience | Audience interpretation of micro-influencer role constructs | Authenticity can be performed; consistency and transparency are more important | 2 | 3 (2) | Communication/ sociology/ computer | 7.5% |
Consistency and transparency can produce intimacy | 2 | |||||
Meaning needs to be co-produced and followers are responsible for it | 1 | |||||
Sponsorship disclosure has no effect on willingness to purchase | 1 | |||||
Audience assessment of the effectiveness of content shared by micro-influencers | Except for the skills of the learning dimension, the four dimensions of satisfaction, engagement, and relevance (feedback dimension); knowledge, attitude, confidence, and recognition (learning dimension);behavioral dimension; and outcome dimension all had better results | 1 | 1 (1) | Nutrients | 2.5% | |
Role of the audience | Consumers as media producers | 1 | 1 (1) | Physiology | 2.5% | |
Mechanisms of influence | To followers | Through self-branding | 3 | 8 (6) | Communication/ cultural study sociology education linguistics/ computer science/health care sciences and services | 17.5% |
Through sophisticated engagement | 2 | |||||
Through influence on audience lifestyles | 2 | |||||
Through dual performances of the extraordinary and the ordinary, choosing one to emphasize the other | 1 | |||||
Through building trust and intimacy | 1 | |||||
By co-constructing emotional experiences | 1 | |||||
To stakeholders | By influencing social consciousness | 2 | ||||
To market | By co-commoditizing “self” and followers | 1 | ||||
Accelerating the market process by increasing brand familiarity through a multitude of micro-influencers | 1 | |||||
Impact through sustainable development, which other influencers are not able to do | 1 | |||||
Context | Cultural context of the rise of the micro-influencer | Neoliberalism | 4 | 7 (5) | Communication/ cultural study/ sociology/ health care sciences and services | 15% |
Individualism | 1 | |||||
Consumerism | 1 | |||||
Opposition to gender-based violence | 1 |
Media Platform | Platform Attribute | Number of Mentioned Articles | Sample Size (Audiences) |
---|---|---|---|
social media | 24 | 9053 | |
social media | 2 | 786,255 | |
YouTube | social media | 2 | 717 |
TikTok | social media | 1 | 996 |
social media | 1 | 350 | |
Xiaohongshu | social media | 1 | 279 |
social media | 1 | 130 | |
Microblogging | social media | 1 | / |
Periscope | social media | 1 | 7667 |
Ustream | social media | 1 | |
Younow | social media | 1 | |
Taobao | e-commerce website | 1 | / |
Author(s) | Theory | Research Method | Independent Variable | Mediator | Moderator | Dependent Variable |
---|---|---|---|---|---|---|
Bu et al. | social capital theory | experiment | influencer type × sponsorship disclosure | \ | \ | audience value co-creation behavior (participation &citizenship behavior) |
Pozharliev et al. | source credibility theory\ contemporary theories of persuasion | experiment | influencer type | perceived source credibility | argument quality | electronic word-of-mouth, cognitive work |
Pozharliev et al. | dual coding theory | experiment | influencer type | attention allocation to visual and verbal cues | argument quality | behavioral activation system |
Sheng et al. | attribution theory/ consumer inference theory | experiment | parasocial relationship with micro-influencers | \ | sponsorship disclosure, negative eWOM | customer engagement, brand preference, purchase intention |
Boerman | social capital theory | experiment | disclosure | ad recognition | influencer type | online behavioral intentions parasocial interaction brand recall |
Kay et al. | persuasion knowledge model | experiment | influencer type × sponsorship disclosure | product knowledge, product attractiveness | \ | purchase intention |
Boerman et al. | attribution theory/ multiple inference model | experiment | influencer message | influencer credibility | influencer type | pro-environmental intentions |
Park et al. | cultural meaning transfer model | experiment | influencer type | influencer authenticity, brand authenticity | consumption type | advertising effectiveness |
Pradhan et al. | moral responsibility theory | experiment | brand control | moral emotions | influencer type, relationship strength | brand avoidance |
Giuffredi-Kähr et al. | expectancy disconfirmation theory | experiment | influencer type | persuasion knowledge, trustworthiness of the sponsored post | sponsorship disclosure | brand evaluation, influencer likeability |
Chiu and Ho | attachment theory | experiment | source credibility | emotional attachment | \ | purchase intention |
Pangarkar and Rathee | congruity theory | experiment | influencer type | congruity, influencer credibility | Conspicuity scale | purchase intention |
Hill and Qesja | signaling theory | experiment | influencer type | perceived influencer authenticity | perceived endorser motives | behavioral intentions |
Lee et al. | schema theory/ match-up hypothesis | experiment | endorser–product congruence type, self-expressive product type | \ | advertising skepticism, persuasion knowledge | source credibility, eWOM intention |
Li et al. | \ | experiment | influencer type, mindset | perceived trustworthiness | social tie recommendations | consumer intention to generate WOM |
Rungruangjit and Charoenpornpanichkul | information relevance theory/ observational learning theory | questionnaire | topicality of content, novelty, understandability, reliability, interestingness, authenticity | consumer-influencer engagement | \ | brand evangelism |
Han and Zhang | self-congruity theory/ emotional solidarity theory | questionnaire | self-influencer, congruence, identification with place | emotional solidarity | knowledge | visit intention |
Hernández-Méndez and Baute-Díaz | \ | questionnaire | source credibility, similarity | attitude towards the post, attitude towards the destination | \ | intention to follow, intention to travel |
Berne-Manero and Marzo-Navarro | commitment–trust theory/ attribution theory | questionnaire | pleasantness, credibility, emotions | \ | influencer type | engagement |
Conde and Casais | parasocial interaction theory | questionnaire | influencer type | perception of popularity, prescribed opinion leadership | parasocial relation | intention to adopt recommendations |
Kim and Kim | human brand theory/ attachment theory | questionnaire | homophily, social presence, physical attractiveness | attachment | \ | loyalty to the influencer, advertising perception, advertising credibility, advertising resistance |
Hassanzadeh et al. | social comparison theory | questionnaire | similarity, personality traits | parasocial interaction | \ | opinion leadership |
Muda and Hamzah | social identity theory/ source homophily theory | questionnaire | perceived source homophily | perceived source credibility, attitude toward UGC | \ | e-WOM; purchase intention |
Syrdal et al. | elaboration likelihood model | econometrics | text language, complex words, analytical language, clout language, authentic language, positive emotional language | \ | \ | post engagement |
Li et al. | source credibility theory | econometrics | internet celebrity count, e-shop seller count | internet celebrities’ livestreaming sales | influencer type | E-shop sellers’ livestreaming sales |
Li et al. | influencer–brand fit theory | econometrics | influencer type | \ | product line breadth, product line depth, product type, product price | luxury brand sales |
Holiday et al. | social exchange theory/ emotional contagion theory | machine learning | facial emotion expression | textual emotion content | influencer type, branding of post | consumer engagement |
Panopoulos et al. | influencer theory | mixed (questionnaire, literature review) | environmental concerns, influencer type | ECO labeling; UGC | \ | purchase intention |
Valsesia et al. | social influence theory | mixed (Experiment, econometrics) | following number | perceived autonomy, perceived influence | influencer type | engagement |
Bainotti | conspicuous consumption theory | mixed (machine learning, semi-structured interviews) | \ | \ | \ | \ |
Shen | information adoption model | content analysis | argument quality, source credibility | \ | \ | information adoption |
Alassani and Göretz | two-stage flow theory | content analysis | \ | \ | \ | \ |
Fietkiewicz et al. | content analysis | \ | \ | \ | \ | |
Hudders et al. | Revised Communication Model for Advertising | literature review | \ | \ | \ | \ |
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Chen, J.; Zhang, Y.; Cai, H.; Liu, L.; Liao, M.; Fang, J. A Comprehensive Overview of Micro-Influencer Marketing: Decoding the Current Landscape, Impacts, and Trends. Behav. Sci. 2024, 14, 243. https://doi.org/10.3390/bs14030243
Chen J, Zhang Y, Cai H, Liu L, Liao M, Fang J. A Comprehensive Overview of Micro-Influencer Marketing: Decoding the Current Landscape, Impacts, and Trends. Behavioral Sciences. 2024; 14(3):243. https://doi.org/10.3390/bs14030243
Chicago/Turabian StyleChen, Jie, Yangting Zhang, Han Cai, Lu Liu, Miyan Liao, and Jiaming Fang. 2024. "A Comprehensive Overview of Micro-Influencer Marketing: Decoding the Current Landscape, Impacts, and Trends" Behavioral Sciences 14, no. 3: 243. https://doi.org/10.3390/bs14030243