{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T11:05:17Z","timestamp":1783940717028,"version":"3.55.0"},"reference-count":30,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T00:00:00Z","timestamp":1783641600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computation"],"abstract":"<jats:p>This paper develops and evaluates a predictive analytics framework for influencer marketing return on investment (ROI), integrating hybrid deep learning architectures with trust-aware modelling to address the dual purpose of (a) developing a rigorous evaluation framework for influencer campaign performance and (b) examining the effectiveness of influencer marketing predictors. The concept of influencer marketing has quickly grown to be one of the most effective mediums within the contemporary digital advertising landscape. Due to the growing number of brands dedicating huge amounts of budgets to social media partnerships, the importance of data-driven approaches that can predict the outcomes of campaigns and, consequently, ensure the best possible return on investment (ROI) has become urgent. This paper introduces a machine learning system that can be used to forecast the sales of products promoted by influencer marketing campaigns based on campaign-level features, including type of platform, influencer type, type of campaign, time of the year, number of engagements, estimated reach, and campaign duration. A publicly available influencer marketing ROI dataset was trained and tested on an XGBoost regression model with a coefficient of determination (R2) of 0.95 indicating high predictive power and generalization. The results show that engagement metrics and estimated reach are some of the most impactful factors in sales performance, and additional contextual factors like platform selection, type of campaign, and timing of the year also moderate results. In addition to predictive modelling, this paper explains how artificial intelligence (AI) can be strategically integrated throughout the influencer marketing lifecycle. With the inclusion of AI-based analytics, marketers will be able to leverage their intuitive decision-making processes with quantifiable and replicable measures and approaches that can lead to true consumer trust and lasting brand resonance. The framework proposed can provide practitioners and researchers with a scalable basis for implementing intelligent systems in the context of influencer marketing. Recent computer science research further demonstrates that AI-driven frameworks spanning generative content modelling, AI-powered CRM architectures for understanding consumer preferences on social media, and parasocial-trust models of influencer engagement provide strong methodological complements to the predictive approach developed here, while governance and project management considerations for deploying such systems are increasingly addressed in the literature. Concurrently, a growing body of influencer marketing research examines how platform affordances shape information-seeking and trust, how influencer attributes and social satisfaction mediate purchase intention, how influencer marketing drives sustainable consumption, and how social media measurably shapes health-related behaviours all of which motivate the predictive and trust-modelling objectives of this work.<\/jats:p>","DOI":"10.3390\/computation14070157","type":"journal-article","created":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T15:13:36Z","timestamp":1783696416000},"page":"157","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Project Management-Driven Predictive Analytics in Influencer Marketing: A Hybrid Deep Learning Approach for Maximizing Return on Investment"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-6155-7895","authenticated-orcid":false,"given":"Md Ariful","family":"Alam","sequence":"first","affiliation":[{"name":"School of Business, International American University, 3440 Wilshire Blvd STE 1000, Los Angeles, CA 90010, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-2809-1326","authenticated-orcid":false,"given":"Shazib Ahmed","family":"Tanvir","sequence":"additional","affiliation":[{"name":"Business School, University of Colorado Denver, 1201 Larimer St, Denver, CO 80204, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-5384-2575","authenticated-orcid":false,"given":"Arafat","family":"Rohan","sequence":"additional","affiliation":[{"name":"School of Business, International American University, 3440 Wilshire Blvd STE 1000, Los Angeles, CA 90010, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0235-2870","authenticated-orcid":false,"given":"Khandakar Rabbi","family":"Ahmed","sequence":"additional","affiliation":[{"name":"Miyan Research Institute, International University of Business Agriculture and Technology, Dhaka 1230, Bangladesh"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-5710-9233","authenticated-orcid":false,"given":"Areyfin Mohammed","family":"Yoshi","sequence":"additional","affiliation":[{"name":"Department of Management, International American University, 3440 Wilshire Blvd STE 1000, Los Angeles, CA 90010, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-0168-8752","authenticated-orcid":false,"given":"Belal","family":"Hossain","sequence":"additional","affiliation":[{"name":"School of Business, International American University, 3440 Wilshire Blvd STE 1000, Los Angeles, CA 90010, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-6099-2035","authenticated-orcid":false,"given":"Rakibul","family":"Islam","sequence":"additional","affiliation":[{"name":"School of Business, International American University, 3440 Wilshire Blvd STE 1000, Los Angeles, CA 90010, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2541040","DOI":"10.1080\/23311975.2025.2541040","article-title":"Influencer credibility and consumer behavior: The mediating role of self-brand congruity and moderating role of involvement","volume":"12","author":"Dhaigude","year":"2025","journal-title":"Cogent Bus. Manag."},{"key":"ref_2","unstructured":"Stiles, G. (2026, April 26). Beyond Vanity Metrics: How to Measure True ROI in Influencer Marketing. Available online: https:\/\/www.algorithm.agency\/blog\/beyond-vanity-metrics-how-to-measure-true-roi-in-influencer-marketing."},{"key":"ref_3","first-page":"704","article-title":"Predicting Customer Retention using XGBoost and Balancing Methods","volume":"11","author":"Faris","year":"2020","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Choi, J.A., and Ku, C.S. (2024, January 16\u201318). Examining Platform Strategy for Influencer Marketing Using Text Mining. Proceedings of the 2024 IEEE\/ACIS 9th International Conference on Big Data, Cloud Computing, and Data Science (BCD), Kitakyushu, Japan.","DOI":"10.1109\/BCD61269.2024.10743091"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Chakranarayan, V., Hussain, F., Jaber, F.A., Shaker, R.J., and Rizwan, A. (2025). Safeguarding Brand and Platform Credibility Through AI-Based Multi-Model Fake Profile Detection. Future Internet, 17.","DOI":"10.3390\/fi17090391"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1007\/s11747-024-01052-7","article-title":"Influencer marketing effectiveness: A meta-analytic review","volume":"53","author":"Pan","year":"2025","journal-title":"J. Acad. Mark. Sci."},{"key":"ref_7","unstructured":"Kanuri, V.K., Chen, Y., and Sridhar, S. (2026, April 26). Timing Is Everything: A Scheduled Plan for Your Social Media Presence. Available online: https:\/\/kellercenter.hankamer.baylor.edu\/news\/story\/2020\/timing-everything-scheduled-plan-your-social-media-presence."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1007\/s13278-021-00772-w","article-title":"Cross-platform comparison of framed topics in Twitter and Weibo: Machine learning approaches to social media text mining","volume":"11","author":"Yang","year":"2021","journal-title":"Soc. Netw. Anal. Min."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"183","DOI":"10.34293\/management.v11iiS1-Jan.7163","article-title":"Influencer Marketing Unveiled: A Conceptual Exploration of Emotional Marketing, Consumer Connections, and Future AI Trends","volume":"11","author":"Gaur","year":"2024","journal-title":"Shanlax Int. J. Manag."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"81","DOI":"10.53623\/jdmc.v3i2.350","article-title":"The Role of Influencer Marketing in Building Authentic Brand Relationships Online","volume":"3","author":"Okonkwo","year":"2023","journal-title":"J. Digit. Mark. Commun."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"18860","DOI":"10.1038\/s41598-025-03336-6","article-title":"Empirical Analysis of Influencer Attributes and Social Satisfaction Effects on Purchase Intentions in Chinese Social Media","volume":"15","author":"Yao","year":"2025","journal-title":"Sci. Rep."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"114991","DOI":"10.1016\/j.jbusres.2024.114991","article-title":"Predictors of Social Media Influencer Marketing Effectiveness: A Comprehensive Literature Review and Meta-Analysis","volume":"186","author":"Krause","year":"2025","journal-title":"J. Bus. Res."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Wu, M.H. (2026). How Influencer Attractiveness and Expertise Shape Consumer Responses Through Parasocial Interaction and Trust. Computers, 15.","DOI":"10.3390\/computers15040250"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1108\/JEBDE-09-2024-0034","article-title":"How Influencer Marketing Affect Sustainable Consumer Behaviour? Systematic Review, Integrative Framework and Future Research Agenda","volume":"5","author":"Kilumile","year":"2025","journal-title":"J. Electron. Bus. Digit. Econ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"29","DOI":"10.51768\/dbr.v26i2.262202503","article-title":"Leveraging AI in Influencer Marketing: Opportunities and Ethical Challenges for Brands","volume":"26","author":"Jain","year":"2025","journal-title":"Delhi Bus. Rev."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1080\/15252019.2024.2313721","article-title":"Artificial Intelligence in Influencer Marketing: A Mixed-Method Comparison of Human and Virtual Influencers on Instagram","volume":"24","author":"Looi","year":"2024","journal-title":"J. Interact. Advert."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Jayasingh, S., Sivakumar, A., and Vanathaiyan, A.A. (2025). Artificial Intelligence Influencers\u2019 Credibility Effect on Consumer Engagement and Purchase Intention. J. Theor. Appl. Electron. Commer. Res., 20.","DOI":"10.3390\/jtaer20010017"},{"key":"ref_18","first-page":"1194","article-title":"The effectiveness of influencer marketing in the age of AI","volume":"4","author":"Ramachandran","year":"2024","journal-title":"J. Inform. Educ. Res."},{"key":"ref_19","first-page":"4563","article-title":"AI-driven influence: Transforming brand engagement and trust in the digital age","volume":"70","author":"Wah","year":"2025","journal-title":"Chin. Sci. Bull. (Kexue Tongbao)"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Sowndharya, S., and Hariharan, R. (2025, January 3\u20135). Advanced Machine Learning Algorithms: A Big Data Approach to Predictive Analytics in Business Marketing. Proceedings of the 2025 4th International Conference on Innovative Mechanisms for Industry Applications (ICIMIA), Tirupur, India.","DOI":"10.1109\/ICIMIA67127.2025.11200955"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Samanta, P., Amir, M., Bagga, S., Dubey, B., Khulbe, M., and Gupta, R. (2025, January 13\u201314). Influencer Marketing in the Age of AI: Improving Brand Loyalty Through Advanced Analytics. Proceedings of the 2025 International Conference on Intelligent Control, Computing and Communications (IC3), Mathura, India.","DOI":"10.1109\/IC363308.2025.10956901"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Patil, S.M., Kharat, A.M., Jain, S., Tripathi, V.V.R., Bisen, G.K., and Joshi, A. (2024, January 9\u201310). Investigating the Influence and Function of Artificial Intelligence in Contemporary Marketing Management: Marketing in the AI Era. Proceedings of the 2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI), Chennai, India.","DOI":"10.1109\/ACCAI61061.2024.10602227"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Al-Hashemi, S.K.A., Al Husaini, M.A.S., Al Husaini, Y.N., AL Kishri, W.A., and Abdulghafor, R. (2025, January 22\u201324). Digital Marketing Platform Connecting Businesses with Influencers and Marketing Agencies using Machine Learning. Proceedings of the 2025 International Conference on Computer and Applications (ICCA), Manama, Bahrain.","DOI":"10.1109\/ICCA66035.2025.11430807"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Islam, T., Miron, A., Nandy, M., Choudrie, J., Liu, X., and Li, Y. (2024). Transforming Digital Marketing with Generative AI. Computers, 13.","DOI":"10.3390\/computers13070168"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Aldhamiri, A. (2026). AI-Driven CRM Architecture for Managing Large-Scale Fragrance Sample Requests and Understanding Customer Preferences on Social Media. Computers, 15.","DOI":"10.3390\/computers15040252"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Adamantiadou, D., and Tsironis, L. (2025). Leveraging Artificial Intelligence in Project Management: A Systematic Review of Applications, Challenges, and Future Directions. Computers, 14.","DOI":"10.37766\/inplasy2025.1.0041"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1057\/s41599-025-04882-0","article-title":"Information Seeking and Affective Relationship Building in Influencer Marketing: The Role of Social Media Affordances","volume":"12","author":"Wang","year":"2025","journal-title":"Humanit. Soc. Sci. Commun."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1038\/s41405-026-00417-0","article-title":"A Tool to Measure the Influence of Social Media on Health Behaviors: An Exploratory Study","volume":"12","author":"Rethaber","year":"2026","journal-title":"BDJ Open"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Hananto, A., and Veza, I. (2025). Governance Framework for Intelligent Digital Twin Systems in Battery Storage: Aligning Standards, Market Incentives, and Cybersecurity for Decision Support of Digital Twin in BESS. Computers, 14.","DOI":"10.3390\/computers14090365"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Mikkilineni, R., and Kelly, W. (2026). The Missing Layer in Modern IT: Governance of Commitments, Not Just Compute and Data. Computers, 15.","DOI":"10.20944\/preprints202603.0413.v1"}],"container-title":["Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2079-3197\/14\/7\/157\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T10:12:56Z","timestamp":1783937576000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2079-3197\/14\/7\/157"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,10]]},"references-count":30,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2026,7]]}},"alternative-id":["computation14070157"],"URL":"https:\/\/doi.org\/10.3390\/computation14070157","relation":{},"ISSN":["2079-3197"],"issn-type":[{"value":"2079-3197","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,10]]}}}