{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T14:43:48Z","timestamp":1783608228385,"version":"3.55.0"},"reference-count":84,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2024,6,18]],"date-time":"2024-06-18T00:00:00Z","timestamp":1718668800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Science Fund","award":["BG05M2OP001-1.002-0002"],"award-info":[{"award-number":["BG05M2OP001-1.002-0002"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Social media marketing has become a crucial component of contemporary business strategies, significantly influencing brand visibility, customer engagement, and sales growth. The aim of this study is to investigate and determine the key factors guiding customer attitudes towards social media influencers, and, on that basis, to explore their effects on purchase intentions regarding advertised products or services. A total of 376 filled-in questionnaires from an online survey were analysed. The main characteristics of digital influencers\u2019 behaviour that affect consumer perceptions have been systematized and categorized through a combination of both traditional and advanced data analysis methods. Structural equation modelling (SEM), machine learning and multi-criteria decision-making (MCDM) methods were selected to uncover the hidden dependencies between variables from the perspective of social media users. The developed models elucidate the underlying relationships that shape the acceptance mechanism of influencers\u2019 messages. The obtained results provide specific recommendations for stakeholders across the social media marketing value chain. Marketers can make informed decisions and optimize influencer marketing strategies to enhance user experience and increase conversion rates. Working collaboratively, marketers and influencers can create impactful and successful marketing campaigns that resonate with the target audience and drive meaningful results. Customers benefit from more tailored and engaging influencer content that aligns with their interests and preferences, fostering a stronger connection with brands and potentially affecting their purchase decisions. As the perception of customer satisfaction is an individual and evolving process, stakeholders should organize regular evaluations of influencer marketing data and explore the possibilities to ensure the continuous improvement of this e-marketing channel.<\/jats:p>","DOI":"10.3390\/info15060359","type":"journal-article","created":{"date-parts":[[2024,6,19]],"date-time":"2024-06-19T04:21:28Z","timestamp":1718770888000},"page":"359","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":39,"title":["Social Media Influencers: Customer Attitudes and Impact on Purchase Behaviour"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7504-8576","authenticated-orcid":false,"given":"Galina","family":"Ilieva","sequence":"first","affiliation":[{"name":"Department of Management and Quantitative Methods in Economics, University of Plovdiv Paisii Hilendarski, 4000 Plovdiv, Bulgaria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5877-3098","authenticated-orcid":false,"given":"Tania","family":"Yankova","sequence":"additional","affiliation":[{"name":"Department of Management and Quantitative Methods in Economics, University of Plovdiv Paisii Hilendarski, 4000 Plovdiv, Bulgaria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8683-051X","authenticated-orcid":false,"given":"Margarita","family":"Ruseva","sequence":"additional","affiliation":[{"name":"Department of Management and Quantitative Methods in Economics, University of Plovdiv Paisii Hilendarski, 4000 Plovdiv, Bulgaria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4912-5720","authenticated-orcid":false,"given":"Yulia","family":"Dzhabarova","sequence":"additional","affiliation":[{"name":"Department of Marketing and International Economic Relations, University of Plovdiv Paisii Hilendarski, 4000 Plovdiv, Bulgaria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1703-412X","authenticated-orcid":false,"given":"Stanislava","family":"Klisarova-Belcheva","sequence":"additional","affiliation":[{"name":"Department of Management and Quantitative Methods in Economics, University of Plovdiv Paisii Hilendarski, 4000 Plovdiv, Bulgaria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8129-5650","authenticated-orcid":false,"given":"Marin","family":"Bratkov","sequence":"additional","affiliation":[{"name":"Department of Marketing and International Economic Relations, University of Plovdiv Paisii Hilendarski, 4000 Plovdiv, Bulgaria"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,6,18]]},"reference":[{"key":"ref_1","unstructured":"Kotler, P., Kartajaya, H., and Setiawan, I. 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