Developing Ad Impact Assessment Models Using Pre/Post-Survey Data Analytics
Keywords:
advertising effectiveness, pre/post survey, data analytics, causal inference, consumer behavior, machine learningAbstract
This paper presents a comprehensive study on developing advanced advertising impact assessment models leveraging pre- and post-survey data analytics. Advertising effectiveness measurement remains crucial for optimizing marketing investments, yet conventional methods often fail to capture nuanced consumer behavior shifts. Our proposed framework integrates statistical, machine learning, and causal inference approaches to analyze survey data collected before and after ad exposure. This approach enables deeper understanding of consumer perception changes, purchase intent, and brand awareness, supported by large-scale empirical validation. Results demonstrate improved accuracy and interpretability over traditional models, offering practical implications for marketing professionals and researchers. Future directions include integrating multi-modal data sources and real-time adaptive assessment mechanisms.
Downloads
References
V. Kumar and S. Gupta, “Conceptualizing the Evolution and Future of Advertising,” J Advert, vol. 45, no. 3, pp. 302–317, Jul. 2016, doi: 10.1080/00913367.2016.1199335;PAGE:STRING:ARTICLE/CHAPTER.
J. O. Basiru, C. L. Ejiofor, E. C. Onukwulu, and R. U. Attah, “Financial Management Strategies in Emerging Markets: A Review of Theoretical Models and Practical Applications,” Magna Scientia Advanced Research and Reviews, vol. 7, no. 2, pp. 123–140, 2023.
J. I. Oteri, E. C. Onukwulu, I. Ogwe, C. P. M. Ewimemu, I. Ebeh, and A. Sobowale, “Dynamic Pricing Models for Logistics Product Management: Balancing Cost Efficiency and Market Demands,” International Journal of Multidisciplinary Research and Growth Evaluation, vol. 4, 2023.
A. Odeshina, O. Reis, F. Okpeke, V. Attipoe, and O. Orieno, “Leveraging Big Data Analytics for Market Forecasting and Investment Strategy in Digital Finance,” International Journal of Social Science Exceptional Research, vol. 3, pp. 325–333, 2024, [Online]. Available: https://www.researchgate.net/publication/391835563
D. C. Ayodeji, I. Oyeyipo, M. O. Nwaozomudoh, N. J. Isibor, and E. Obianuju, “Modeling the Future of Finance: Digital Transformation, Fintech Innovations, Market Adaptation, and Strategic Growth,” World Journal of Innovation and Modern Technology, vol. 8, no. 6, 2024.
A. I. Afolabi, N. Chukwurah, and O. A. Abieba, “Harnessing machine learning techniques for driving sustainable economic growth and market efficiency,” International Journal of Multidisciplinary Research and Growth Evaluation, vol. 6, no. 2, pp. 277–283, 2025, doi: https://doi.org/10.54660/IJMRGE.2025.6.2.277-283.
B. A. Mayienga, V. Attipoe, I. Oyeyipo, D. C. Ayodeji, N. J. Isibor, and E. Alonge, “Studying the transformation of consumer retail experience through virtual reality technologies,” Gulf Journal of Advance Business Research, vol. 2, no. 6, pp. 506–518, 2024.
O. A. Agboola, E. Ogbuefi, A. A. Abayomi, J. C. Ogeawuchi, O. E. Akpe, and S. Owoade, “Systematic Review of AI-Driven Data Integration for Enabling Smarter E-Commerce Analytics and Consumer Insights,” International Journal of Advanced Multidisciplinary Research and Studies, vol. 3, no. 6, pp. 1573–1581, 2023, [Online]. Available: https://www.multiresearchjournal.com/arclist/list-2023.3.6/id-4245
S. V. S. Pakhomov, P. D. Thuras, R. Finzel, J. Eppel, and M. Kotlyar, “Using consumer-wearable technology for remote assessment of physiological response to stress in the naturalistic environment,” PLoS One, vol. 15, no. 3, p. e0229942, 2020, doi: 10.1371/JOURNAL.PONE.0229942.
A. C. Mgbame, O. E. Akpe, A. A. Abayomi, E. Ogbuefi, and O. O. Adeyelu, “Building data-driven resilience in small businesses: A framework for operational intelligence,” Iconic Research and Engineering Journals, vol. 5, no. 9, pp. 695–712, 2022, [Online]. Available: https://www.irejournals.com/paper-details/1708219
Nnenna Ijeoma Okeke, Olufunke Anne Alabi, Abbey Ngochindo Igwe, Onyeka Chrisanctus Ofodile, and Chikezie Paul-Mikki Ewim, “AI in customer feedback integration: A data-driven framework for enhancing business strategy,” World Journal of Advanced Research and Reviews, vol. 24, no. 1, pp. 2036–2052, Oct. 2024, doi: 10.30574/wjarr.2024.24.1.3207.
E. C. Chianumba, N. Ikhalea, A. Y. Mustapha, A. Y. Forkuo, and D. Osamika, “Framework for using behavioral science and public health data to address healthcare inequality and vaccine hesitancy,” Journal of Frontiers in Multidisciplinary Research, vol. 4, no. 1, pp. 183–187, 2023.
Y. G. Hassan, A. Collins, G. O. Babatunde, A. A. Alabi, and S. D. Mustapha, “Holistic software solutions for securing Iot ecosystems against data theft and network-based cyber threats,” Gulf Journal of Advance Business Research, vol. 3, no. 1, pp. 252–261, Jan. 2025, doi: 10.51594/GJABR.V3I1.77.
W. O. Owobu, O. A. Abieba, P. Gbenle, J. P. Onoja, A. I. Daraojimba, and A. H. Adepoju, “Conceptual Framework for Deploying Data Loss Prevention and Cloud Access Controls in Multi-Layered Security Environments,” 2022.
A. A. Abayomi, B. C. Ubanadu, A. I. Daraojimba, O. A. Agboola, E. Ogbuefi, and S. Owoade, “A conceptual framework for real-time data analytics and decision-making in cloud-optimized business intelligence systems,” Iconic Research and Engineering Journals, vol. 5, no. 9, pp. 713–722, 2022, [Online]. Available: https://www.irejournals.com/paper-details/1708317
M. R. Shafie, H. Khosravi, S. Farhadpour, S. Das, and I. Ahmed, “A cluster-based human resources analytics for predicting employee turnover using optimized Artificial Neural Networks and data augmentation,” Decision Analytics Journal, vol. 11, p. 100461, Jun. 2024, doi: 10.1016/J.DAJOUR.2024.100461.
F. U. Ojika, W. O. Owobu, O. A. Abieba, O. J. Esan, B. C. Ubamadu, and A. I. Daraojimba, “Transforming Cloud Computing Education: Leveraging AI and Data Science for Enhanced Access and Collaboration in Academic Environments,” 2023.
A. A. Abayomi, J. C. Ogeawuchi, O. E. Akpe, and O. A. Agboola, “Systematic Review of Scalable CRM Data Migration Frameworks in Financial Institutions Undergoing Digital Transformation,” International Journal of Multidisciplinary Research and Growth Evaluation, vol. 3, no. 1, pp. 1093–1098, 2022, doi: 10.54660/.ijmrge.2022.3.1.1093-1098.
E. Ogbuefi, A. C. Mgbame, O. E. Akpe, A. A. Abayomi, and O. O. Adeyelu, “Data literacy and BI tool adoption among small business owners in rural markets,” International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 9, no. 4, pp. 537–563, 2023, doi: 10.32628/IJSRCSIT.
E. Ogbuefi, A. C. Mgbame, O. E. Akpe, A. A. Abayomi, and O. O. Adeyelu, “Data democratization: Making advanced analytics accessible for micro and small enterprises,” International Journal of Management and Organizational Research, vol. 1, no. 1, pp. 199–212, 2022, doi: 10.54660/IJMOR.2022.1.1.199-212.
K. L. Keller, “Unlocking the Power of Integrated Marketing Communications: How Integrated Is Your IMC Program?,” J Advert, vol. 45, no. 3, pp. 286–301, Jul. 2016, doi: 10.1080/00913367.2016.1204967.
R. E. Dosumu, O. O. George, and C. O. Makata, “Optimizing media investment and compliance monitoring: A conceptual framework for risk-resilient advertising strategy,” Journal of Frontiers in Multidisciplinary Research, vol. 5, no. 1, pp. 106–111, 2024, doi: 10.54660/.IJFMR.2024.5.1.106-111.
H. Lee and C. H. Cho, “Digital advertising: present and future prospects,” Int J Advert, vol. 39, no. 3, pp. 332–341, Apr. 2020, doi: 10.1080/02650487.2019.1642015.
“Conceptualizing the Evolution and Future of Advertising: Journal of Advertising: Vol 45, No 3.” Accessed: Jun. 01, 2025. [Online]. Available: https://www.tandfonline.com/doi/abs/10.1080/00913367.2016.1199335?casa_token=BMYTs1jKGF0AAAAA:PsybFxx0CBT0kHBgAR8ArG8-DBm7oUPKlXIB6dW5JBSPexr3txOSo6lkHqB_my9Ut2-6dpKSZ4kL
E. O. Alonge, N. L. Eyo-Udo, B. C. Ubamadu, A. I. Daraojimba, and E. D. Balogun, “Real-Time Data Analytics for Enhancing Supply Chain Efficiency,” vol. 3, 2023.
O. D. Balogun, A. Y. Mustapha, B. O. Tomoh, O. S. Soyege, and C. N. Nwokedi, “Enhancing Operational Efficiency in Healthcare: The Role of Advanced Data Analytics,” International Journal of Pharma Growth Research Review, vol. 1, no. 6, pp. 33–40, 2024.
E. C. Chianumba, N. Ikhalea, A. Y. Mustapha, A. Y. Forkuo, and D. Osamika, “Developing a predictive model for healthcare compliance, risk management, and fraud detection using data analytics,” International Journal of Social Science Exceptional Research, vol. 1, no. 1, pp. 232–238, 2022.
O. Ogunwole, E. C. Onukwulu, M. O. Joel, and A. I. Ibeh, “Data-Driven Decision-Making in Corporate Finance: A Review of Predictive Analytics in Profitability and Risk Management,” Iconic Research and Engineering Journals, vol. 7, no. 11, 2024.
O. M. Oluoha, A. Odeshina, O. Reis, F. Okpeke, V. Attipoe, and O. Orieno, “Optimizing Business Decision-Making with Advanced Data Analytics Techniques,” Iconic Research and Engineering Journals, vol. 6, no. 5, pp. 184–203, 2022, [Online]. Available: https://www.irejournals.com/paper-details/1703887
J. O. Ojadi, C. Odionu, E. Onukwulu, and O. A. Owulade, “Big Data Analytics and AI for Optimizing Supply Chain Sustainability and Reducing Greenhouse Gas Emissions in Logistics and Transportation,” International Journal of Multidisciplinary Research and Growth Evaluation, vol. 5, 2024.
O. Ogunwole, E. C. Onukwulu, M. O. Joel, E. M. Adaga, and A. I. Ibeh, “Modernizing Legacy Systems: A Scalable Approach to Next-Generation Data Architectures and Seamless Integration,” International Journal of Multidisciplinary Research and Growth Evaluation, vol. 4, 2023.
T. Akindahunsi, O. Olulaja, O. Ajayi, I. P. Onyenegecha, U. Hanson, and B. Fadojutimi, “Analytical tools in diseases epidemiology and surveillance: A review of literature,” International Journal of Applied Research, vol. 10, no. 9, pp. 155–161, Jan. 2024, doi: 10.22271/allresearch.2024.v10.i9c.12018.
A. Jindal, M. Singh, and N. Kumar, “Consumption-aware data analytical demand response scheme for peak load reduction in smart grid,” IEEE Transactions on Industrial Electronics, vol. 65, no. 11, pp. 8993–9004, Nov. 2018, doi: 10.1109/TIE.2018.2813990.
“Ajiga: AI-powered HR analytics: Transforming workforce... - Google Scholar.” Accessed: May 11, 2025. [Online]. Available: https://scholar.google.com/scholar?cluster=8169453348357691513&hl=en&oi=scholarr
E. C. Onukwulu, J. E. Fiemotongha, A. N. Igwe, and C. P. M. Ewim, “The Strategic Influence of Geopolitical Events on Crude Oil Pricing: An Analytical Approach for Global Traders,” International Journal of Management and Organizational Research, vol. 1, no. 1, pp. 58–74, 2023.
C. Lou and S. Yuan, “Influencer Marketing: How Message Value and Credibility Affect Consumer Trust of Branded Content on Social Media,” Journal of Interactive Advertising, vol. 19, no. 1, pp. 58–73, Jan. 2019, doi: 10.1080/15252019.2018.1533501.
D. Nyangoma, E. M. Adaga, N. J. Sam-Bulya, and G. O. Achumie, “Designing quality control and compliance models for customer-centric service industries: A process-driven approach,” Journal of Frontiers in Multidisciplinary Research, vol. 5, no. 1, pp. 133–140, 2024, doi: 10.54660/.IJFMR.2024.5.1.133-140.
Nnenna Ijeoma Okeke, Olufunke Anne Alabi, Abbey Ngochindo Igwe, Onyeka Chrisanctus Ofodile, and Chikezie Paul-Mikki Ewim, “Customer journey mapping framework for SMES: Enhancing customer satisfaction and business growth,” World Journal of Advanced Research and Reviews, vol. 24, no. 1, pp. 2004–2018, Oct. 2024, doi: 10.30574/wjarr.2024.24.1.3206.
S. C. Boerman, S. Kruikemeier, and F. J. Zuiderveen Borgesius, “Online Behavioral Advertising: A Literature Review and Research Agenda,” J Advert, vol. 46, no. 3, pp. 363–376, Jul. 2017, doi: 10.1080/00913367.2017.1339368.
B. M. Fennis and W. Stroebe, “The Psychology of Advertising,” The Psychology of Advertising, Oct. 2020, doi: 10.4324/9780429326981.
J. R. Rossiter and L. Percy, “Methodological Guidelines for Advertising Research,” J Advert, vol. 46, no. 1, pp. 71–82, Jan. 2017, doi: 10.1080/00913367.2016.1182088;WEBSITE:WEBSITE:TFOPB;PAGEGROUP:STRING:PUBLICATION.
O. Awoyemi, F. A. Atobatele, and C. A. Okonkwo, “Teaching Conflict Resolution and Corporate Social Responsibility (CSR) in High Schools: Preparing Students for Socially Responsible Leadership,” International Journal of Social Science Exceptional Research, 2024.
F. A. Atobatele and C. A. Okonkwo, “International Journal of Social Science Exceptional Research,” International Journal of Social Science Exceptional Research, 2024.
L. Phillips, C. Dowling, K. Shaffer, N. Hodas, and S. Volkova, “Using Social Media to Predict the Future: A Systematic Literature Review,” Jun. 2017, Accessed: May 11, 2025. [Online]. Available: https://arxiv.org/pdf/1706.06134
O. T. Akintayo, F. A. Atobatele, and P. D. Mouboua, “Navigating Multilingual Identities: The Role of Languages in Shaping Social Belonging and Political Participation,” International Journal of Applied Research in Social Sciences, vol. 6, no. 5, pp. 828–843, 2024.
O. T. Akintayo, F. A. Atobatele, and P. D. Mouboua, “The Dynamics of Language Shifts in Migrant Communities: Implications for Social Integration and Cultural Preservation,” International Journal of Applied Research in Social Sciences, vol. 6, no. 5, pp. 844–860, 2024.
Patricia Diane Mouboua, Fadeke Adeola Atobatele, and Olateju Temitope Akintayo, “Multilingual education and social equity: A comparative study of integration policies in multicultural societies,” GSC Advanced Research and Reviews, vol. 19, no. 2, pp. 032–042, May 2024, doi: 10.30574/gscarr.2024.19.2.0165.
O. Awoyemi, F. A. Atobatele, and C. A. Okonkwo, “Personalized Learning in High School Social Studies: Addressing Diverse Student Needs in the Classroom,” Journal of Frontiers in Multidisciplinary Research, vol. 5, no. 1, pp. 176–183, 2024.
P. D. Mouboua, F. A. Atobatele, and O. T. Akintayo, “Multilingual Education and Social Equity: A Comparative Study of Integration Policies in Multicultural Societies,” GSC Advanced Research and Reviews, vol. 19, no. 2, pp. 32–42, 2024.
R. Angell, M. Gorton, J. Sauer, P. Bottomley, and J. White, “Don’t Distract Me When I’m Media Multitasking: Toward a Theory for Raising Advertising Recall and Recognition,” J Advert, vol. 45, no. 2, pp. 198–210, Apr. 2016, doi: 10.1080/00913367.2015.1130665.
N. A. Nabout and S. Ada, “Overcoming Quality Issues in Digital Display Advertising Using Digital Dashboards,” The Routledge Companion to Strategic Marketing, pp. 449–465, Oct. 2020, doi: 10.4324/9781351038669-34/OVERCOMING-QUALITY-ISSUES-DIGITAL-DISPLAY-ADVERTISING-USING-DIGITAL-DASHBOARDS-NADIA-ABOU-NABOUT-S.
O. M. Oluoha, A. Odeshina, O. Reis, F. Okpeke, V. Attipoe, and O. Orieno, “Development of a Compliance-Driven Identity Governance Model for Enhancing Enterprise Information Security,” Iconic Research and Engineering Journals, vol. 4, no. 11, pp. 310–324, 2021, [Online]. Available: https://www.irejournals.com/paper-details/1702715
A. Odeshina, O. Reis, F. Okpeke, V. Attipoe, and O. Orieno, “AI-Enabled Framework for Zero Trust Architecture and Continuous Access Governance in Security-Sensitive Organizations,” International Journal of Social Science Exceptional Research, vol. 3, pp. 343–364, 2024, [Online]. Available: https://www.researchgate.net/publication/391835475
E. C. Onukwulu, M. O. Agho, N. L. Eyo-Udo, A. K. Sule, and C. Azubuike, “Advances in Blockchain Integration for Transparent Renewable Energy Supply Chains,” International Journal of Research and Innovation in Applied Science, vol. 9, no. 12, 2024.
G. O. Osho, “Building Scalable Blockchain Applications: A Framework for Leveraging Solidity and AWS Lambda in Real-World Asset Tokenization,” Unknown Journal, 2020.
J. O. Omisola, E. A. Etukudoh, O. K. Okenwa, and G. I. Tokunbo, “Geosteering Real-Time Geosteering Optimization Using Deep Learning Algorithms Integration of Deep Reinforcement Learning in Real-time Well Trajectory Adjustment to Maximize,” Unknown Journal, 2020.
J. O. Omisola, E. A. Etukudoh, O. K. Okenwa, and G. I. Tokunbo, “Pore-Scale Modeling of CO2-Brine-Rock Interactions in Carbonate Reservoirs: Numerical and Experimental Evaluation of Geochemical and Geomechanical Changes Occurring During,” Unknown Journal, 2025.
W. Liang, “Data Characterization and Anomaly Detection for HPC Datacenters Using Machine Learning,” 2726.
B. Adebisi, E. Aigbedion, O. B. Ayorinde, and E. C. Onukwulu, “A Conceptual Model for Predictive Asset Integrity Management Using Data Analytics to Enhance Maintenance and Reliability in Oil & Gas Operations,” International Journal of Multidisciplinary Research and Growth Evaluation, vol. 2, 2021.
J. O. Ojadi, E. C. Onukwulu, C. Somtochukwu, and C. S. Odionu, “Natural Language Processing for Climate Change Policy Analysis and Public Sentiment Prediction: A Data-Driven Approach to Sustainable Decision-Making,” Iconic Research and Engineering Journals, vol. 7, no. 3, pp. 732–751, 2023.
A. Farooq, A. B. N. Abbey, and E. C. Onukwulu, “Inventory Optimization and Sustainability in Retail: A Conceptual Approach to Data-Driven Resource Management,” International Journal of Multidisciplinary Research and Growth Evaluation, vol. 5, 2024.
H. Zhou, C. Taber, S. Arcona, and Y. Li, “Difference-in-Differences Method in Comparative Effectiveness Research: Utility with Unbalanced Groups,” Appl Health Econ Health Policy, vol. 14, no. 4, pp. 419–429, Aug. 2016, doi: 10.1007/S40258-016-0249-Y/TABLES/5.
J. B. Dimick and A. M. Ryan, “Methods for evaluating changes in health care policy: the difference-in-differences approach,” JAMA, vol. 312, no. 22, pp. 2401–2402, Dec. 2014, doi: 10.1001/jama.2014.16153.
A. Odeshina, O. Reis, F. Okpeke, V. Attipoe, and O. Orieno, “Developing Compliance-Oriented Social Media Risk Management Models to Combat Identity Fraud and Cyber Threats,” International Journal of Multidisciplinary Research and Growth Evaluation, vol. 4, pp. 1055–1073, 2023, [Online]. Available: https://www.researchgate.net/publication/390723496
J. O. Basiru, C. L. Ejiofor, E. C. Onukwulu, and R. U. Attah, “Sustainable Procurement in Multinational Corporations: A Conceptual Framework for Aligning Business and Environmental Goals,” International Journal of Multidisciplinary Research and Growth Evaluation, vol. 4, 2023.
P. I. Egbumokei, I. N. Dienagha, W. N. Digitemie, E. C. Onukwulu, and O. T. Oladipo, “The Role of Digital Transformation in Enhancing Sustainability in Oil and Gas Business Operations,” International Journal of Multidisciplinary Research and Growth Evaluation, vol. 5, 2024.
X. Li, W. R. Hartmann, and T. Amano, “Preference Externality Estimators: A Comparison of Border Approaches and IVs,” Manage Sci, vol. 70, no. 11, Nov. 2024, doi: 10.1287/MNSC.2023.4977/ASSET/IMAGES/LARGE/MNSC.2023.4977F6.JPEG.
G. Y. Gu, “Technology and Disintermediation in Online Marketplaces,” Manage Sci, Nov. 2024, doi: 10.1287/MNSC.2021.02736.
V. Allan et al., “Propensity score matching and inverse probability of treatment weighting to address confounding by indication in comparative effectiveness research of oral anticoagulants,” J Comp Eff Res, vol. 9, no. 9, pp. 603–614, Jun. 2020, doi: 10.2217/CER-2020-0013/ASSET/81A4421F-4C18-489A-9961-0DB2D7BAFEAB/ASSETS/IMAGES/LARGE/FIGURE1.JPG.
E. O. Alonge, N. L. Eyo-Udo, B. C. Ubanadu, A. I. Daraojimba, E. D. Balogun, and K. O. Ogunsola, “Enhancing data security with machine learning: A study on fraud detection algorithms,” Journal of Frontiers in Multidisciplinary Research, vol. 2, no. 1, pp. 19–31, 2021, doi: 10.54660/.IJFMR.2021.2.1.19-31.
B. I. Adekunle, E. C. Chukwuma-Eke, E. D. Balogun, and K. O. Ogunsola, “Improving customer retention through machine learning: A predictive approach to churn prevention and engagement strategies,” International Journal of Scientific Research in Computer Science, 2023.
“‘Optimizing Ad Campaigns with Machine Learning: Data-Driven Approaches in Modern Media’. | EBSCOhost.” Accessed: Jun. 01, 2025. [Online]. Available: https://openurl.ebsco.com/EPDB%3Agcd%3A2%3A32770754/detailv2?sid=ebsco%3Aplink%3Ascholar&id=ebsco%3Agcd%3A180730865&crl=c&link_origin=scholar.google.com
A. O. Mbata, O. S. Soyege, C. N. Nwokedi, B. O. Tomoh, and A. Y. Mustapha, “Machine learning for health informatics: An Overview,” 2024.
E. C. Chianumba, N. Ikhalea, A. Y. Mustapha, and A. Y. Forkuo, “A Conceptual Model for Using Machine Learning to Enhance Radiology Diagnostics,” International Journal of Advanced Multidisciplinary Research and Studies, vol. 4, 2024.
J. Ali, R. Khan, N. Ahmad, and I. Maqsood, “Random Forests and Decision Trees,” 2012, Accessed: May 11, 2025. [Online]. Available: www.IJCSI.org
S. S. Roy, R. Chopra, K. C. Lee, C. Spampinato, and B. Mohammadi-Ivatlood, “Random forest, gradient boosted machines and deep neural network for stock price forecasting: A comparative analysis on South Korean companies,” International Journal of Ad Hoc and Ubiquitous Computing, vol. 33, no. 1, pp. 62–71, 2020, doi: 10.1504/IJAHUC.2020.104715;PAGE:STRING:ARTICLE/CHAPTER.
B. I. Adekunle, E. C. Chukwuma-Eke, E. D. Balogun, and K. O. Ogunsola, “Machine learning for automation: Developing data-driven solutions for process optimization and accuracy improvement,” Mach Learn, vol. 2, no. 1, p. 18, 2021.
Chianumba, I. E. C., M. N., F. A. Y., A. Y. Osamika, and D, “Exploring the role of AI and machine learning in improving healthcare diagnostics and personalized medicine,” C., Ikhalea, N., Mustapha, A. Y., Forkuo, A. Y., & Osamika, D. (2023). Exploring the role of AI and machine learning in improving healthcare diagnostics and personalized medicine. Journal of Frontiers in Multidisciplinary Research, vol. 2023), 2023.
E. C. Chianumba, N. Ikhalea, A. Y. Mustapha, A. Y. Forkuo, and D. Osamika, “Exploring the role of AI and machine learning in improving healthcare diagnostics and personalized medicine,” Journal of Frontiers in Multidisciplinary Research, vol. 4, no. 1, pp. 177–182, 2023.
B. I. Adekunle, E. C. Chukwuma-Eke, E. D. Balogun, and K. O. Ogunsola, “A predictive modeling approach to optimizing business operations: A case study on reducing operational inefficiencies through machine learning,” International Journal of Multidisciplinary Research and Growth Evaluation, vol. 2, p. 21, 2021.
O. B. Johnson, J. Olamijuwon, E. Cadet, O. S. Osundare, and Y. W. Weldegeorgise, “Developing real-time monitoring models to enhance operational support and improve incident response times,” International Journal of Engineering Research and Development, vol. 20, no. 11, pp. 1296–1304, 2024.
K. O. Omomo, A. E. Esiri, C. Olisakwe, and Henry, “Hydraulic modeling and real-time optimization of drilling fluids: A future perspective,” Global journal of research in Engineering and Technology, vol. 2, no. 2, pp. 30–38, 2024.
E. Kamau, T. Myllynen, S. D. Mustapha, G. O. Babatunde, and A. A. Alabi, “A Conceptual Model for Real-Time Data Synchronization in Multi-Cloud Environments,” 2024.
A. Odeshina, O. Reis, F. Okpeke, V. Attipoe, O. Orieno, and A. Pub, “Business Intelligence Dashboard Optimization Model for Real-Time Performance Tracking and Forecasting Accuracy,” International Journal of Social Science Exceptional Research, vol. 3, pp. 334–342, 2024, [Online]. Available: https://www.researchgate.net/publication/391835472
O. Ojadi, C. Onukwulu, Odionu, and A. Owulade, “Leveraging IoT and Deep Learning for Real-Time Carbon Footprint Monitoring and Optimization in Smart Cities and Industrial Zones,” Iconic Research and Engineering Journals, vol. 6, no. 11, pp. 946–964, 2023.
G. O. Osho, J. O. Omisola, and J. O. Shiyanbola, “An Integrated AI-Power BI Model for Real-Time Supply Chain Visibility and Forecasting: A Data-Intelligence Approach to Operational Excellence,” Unknown Journal, 2020.
A. A. Abayomi, B. C. Ubanadu, A. I. Daraojimba, O. A. Agboola, and S. Owoade, “A Conceptual Framework for Real-Time Data Analytics and Decision-Making in Cloud-Optimized Healthcare Intelligence Systems,” Healthcare Analytics, vol. 45, no. 45 SP 45–45, 2022, [Online]. Available: https://www.irejournals.com/paper-details/1708317
E. O. Alonge, N. L. Eyo-Udo, B. C. Ubamadu, A. I. Daraojimba, and E. D. Balogun, “Real-Time Data Analytics for Enhancing Supply Chain Efficiency,” vol. 3, 2023.
A. Sharma, N. Patel, and R. Gupta, “Enhancing Personalized Loyalty Programs through Reinforcement Learning and Collaborative Filtering Algorithms,” European Advanced AI Journal, vol. 11, no. 10, Jun. 2022, Accessed: May 15, 2025. [Online]. Available: https://www.eaaij.com/index.php/eaaij/article/view/30
E. O. Alonge, N. L. Eyo-Udo, B. C. Ubanadu, A. I. Daraojimba, and E. D. Balogun, “Real-time data analytics for enhancing supply chain efficiency,” Journal of Supply Chain Management and Analytics, vol. 10, no. 1, pp. 49–60, 2023.
S. Hsu, R. Benton, and R. Gottumukkala, “Real-time flu monitoring system and decision informatics,” Proceedings of the Annual Hawaii International Conference on System Sciences, vol. 2015-March, pp. 2794–2803, Mar. 2015, doi: 10.1109/HICSS.2015.338.
S. Brenner et al., “Design of an impact evaluation using a mixed methods model—an explanatory assessment of the effects of results-based financing mechanisms on maternal healthcare services in Malawi,” BMC Health Serv Res., vol. 14, no. 1, p. 180, Apr. 2014, doi: 10.1186/1472-6963-14-180.
O. M. Oluoha, A. Odeshina, O. Reis, F. Okpeke, V. Attipoe, and O. Orieno, “A Privacy-First Framework for Data Protection and Compliance Assurance in Digital Ecosystems,” Iconic Research and Engineering Journals, vol. 7, no. 4, pp. 620–646, 2023, [Online]. Available: https://www.irejournals.com/paper-details/1705171
L. Cioccolanti et al., “Development of a smart control unit for small-scale concentrated solar combined heat and power systems for residential applications,” e-Prime - Advances in Electrical Engineering, Electronics and Energy, vol. 2, p. 100040, Jan. 2022, doi: 10.1016/J.PRIME.2022.100040.
F. Benaben, W. Mu, N. Boissel-Dallier, A. M. Barthe-Delanoe, S. Zribi, and H. Pingaud, “Supporting interoperability of collaborative networks through engineering of a service-based mediation information system (mise 2.0),” Enterp Inf Syst, vol. 9, pp. 556–582, Aug. 2015, doi: 10.1080/17517575.2014.928949.
Z. Liao, Y. Liu, and Z. Xie, “Optimal Cross-Sectional Regression,” Manage Sci, Nov. 2024, doi: 10.1287/MNSC.2023.4966.
P. Alexopoulos and M. Wallace, “Creating domain-specific semantic lexicons for aspect-based sentiment analysis,” Proceedings - 10th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2015, pp. 71–75, Dec. 2015, doi: 10.1109/SMAP.2015.7370083.
N. J. Isibor, C. Paul-Mikki Ewim, A. I. Ibeh, E. M. Adaga, N. J. Sam-Bulya, and G. O. Achumie, “A Generalizable Social Media Utilization Framework for Entrepreneurs: Enhancing Digital Branding, Customer Engagement, and Growth,” International Journal of Multidisciplinary Research and Growth Evaluation, vol. 2, no. 1, pp. 751–758, 2021, doi: 10.54660/.IJMRGE.2021.2.1.751-758.
O. Uchendu, O. D. Akintayo, and A. O. Dagunduro, “Strengthening Workforce Stability by Mediating Labor Disputes Successfully,” International Journal of Engineering Research and Development, vol. 20, no. 11, pp. 998–1010, 2024.
D. Ballantyne and R. Aitken, “Branding in B2B markets: Insights from the service-dominant logic of marketing,” Journal of Business and Industrial Marketing, vol. 22, no. 6, pp. 363–371, 2007, doi: 10.1108/08858620710780127.
E. D. Balogun, K. O. Ogunsola, and A. Samuel, “A Risk Intelligence Framework for Detecting and Preventing Financial Fraud in Digital Marketplaces,” ICONIC RESEARCH AND ENGINEERING JOURNALS, vol. 4, no. 08, pp. 134–149, 2021.
O. F. Dudu, O. B. Alao, and E. O. Alonge, “Advancing financial inclusion through digital payment platforms in emerging markets,” Finance & Accounting Research Journal, vol. 6, no. 11, 2024.
J. O. Basiru, C. L. Ejiofor, E. C. Onukwulu, and R. U. Attah, “Adopting Lean Management Principles in Procurement: A Conceptual Model for Improving Cost-Efficiency and Process Flow,” Iconic Research and Engineering Journals, vol. 6, no. 12, pp. 1503–1522, 2023.
J. O. Omisola, P. E. Chima, O. K. Okenwa, and G. I. Tokunbo, “Green Financing and Investment Trends in Sustainable LNG Projects A Comprehensive Review,” Unknown Journal, 2020.
A. Obijuru, J. O. Arowoogun, C. Onwumere, I. P. Odilibe, and E. C. Anyanwu, “Big data analytics in healthcare: a review of recent advances and potential for personalized medicine,” International Medical Science Research Journal, vol. 4, no. 2, pp. 170–182, 2024.
E. C. Chianumba, N. Ikhalea, A. Y. Mustapha, A. Y. Forkuo, and D. Osamika, “Developing a predictive model for healthcare compliance, risk management, and fraud detection using data analytics,” International Journal of Social Science Exceptional Research, vol. 1, no. 1, pp. 232–238, 2022.
S. A. Shah, D. Z. Seker, S. Hameed, and D. Draheim, “The rising role of big data analytics and IoT in disaster management: Recent advances, taxonomy and prospects,” IEEE Access, vol. 7, pp. 54595–54614, 2019, doi: 10.1109/ACCESS.2019.2913340.
I. E. Agbehadji, B. O. Awuzie, A. B. Ngowi, and R. C. Millham, “Review of big data analytics, artificial intelligence and nature-inspired computing models towards accurate detection of COVID-19 pandemic cases and contact tracing,” Int J Environ Res Public Health, vol. 17, no. 15, pp. 1–16, Aug. 2020, doi: 10.3390/IJERPH17155330.
C. A. Mgbame, O. E. Akpe, A. A. Abayomi, E. Ogbuefi, and O. O. Adeyelu, “Building Data-Driven Resilience in Healthcare: A Framework for Operational Intelligence,” Healthcare Analytics, vol. 5, no. 9 SP 45–72 PY 45, [Online]. Available: https://doi.org/10.1016/j.health.2024.100123
O. S. Soyege, C. N. Nwokedi, and O. B. data Balogun AU - Mustapha AY Big data AU - Tomoh BO JO Big data International Journal of AI, “Big data analytics and artificial intelligence in Healthcare: Revolutionizing patient care and clinical outcomes,” vol. 6 PY Big data, 2023.
A. Odeshina, O. Reis, F. Okpeke, V. Attipoe, and O. Orieno, “Leveraging Big Data Analytics for Market Forecasting and Investment Strategy in Digital Finance,” International Journal of Social Science Exceptional Research, vol. 3, pp. 325–333, 2024, [Online]. Available: https://www.researchgate.net/publication/391835563
M. T. Ribeiro, S. Singh, and C. Guestrin, “Model-Agnostic Interpretability of Machine Learning,” Jun. 2016, Accessed: May 15, 2025. [Online]. Available: https://arxiv.org/pdf/1606.05386
D. Nyangoma, E. M. Adaga, N. J. Sam-Bulya, and G. O. Achumie, “A sustainable agribusiness workforce development model: Bridging agricultural innovation and economic empowerment,” International Journal of Management and Organizational Research, vol. 2, no. 1, pp. 274–280, 2023, doi: 10.54660/IJMOR.2023.2.1.274-280.
O. Uchendu, K. O. Omomo, and A. E. Esiri, “Theoretical Insights into Uncertainty Quantification in Reservoir Models: A Bayesian and Stochastic Approach,” International Journal of Engineering Research and Development, vol. 20, no. 11, pp. 987–997, 2024.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 International Journal of Scientific Research in Humanities and Social Sciences
This work is licensed under a Creative Commons Attribution 4.0 International License.
