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Nexera: A Mobile Platform Integrating Instant On-Demand Services and AI-Driven Market Insights

by Shah Farzeen Hossain, Md. Fokhray Hossain, Md. Asif Al Rumel, Md. Abdullah Abu Sayem, Mohammad Samir Hossain, Md. Al-Amin Hossen
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 56
Year of Publication: 2025
Authors: Shah Farzeen Hossain, Md. Fokhray Hossain, Md. Asif Al Rumel, Md. Abdullah Abu Sayem, Mohammad Samir Hossain, Md. Al-Amin Hossen
10.5120/ijca2025925987

Shah Farzeen Hossain, Md. Fokhray Hossain, Md. Asif Al Rumel, Md. Abdullah Abu Sayem, Mohammad Samir Hossain, Md. Al-Amin Hossen . Nexera: A Mobile Platform Integrating Instant On-Demand Services and AI-Driven Market Insights. International Journal of Computer Applications. 187, 56 ( Nov 2025), 55-60. DOI=10.5120/ijca2025925987

@article{ 10.5120/ijca2025925987,
author = { Shah Farzeen Hossain, Md. Fokhray Hossain, Md. Asif Al Rumel, Md. Abdullah Abu Sayem, Mohammad Samir Hossain, Md. Al-Amin Hossen },
title = { Nexera: A Mobile Platform Integrating Instant On-Demand Services and AI-Driven Market Insights },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2025 },
volume = { 187 },
number = { 56 },
month = { Nov },
year = { 2025 },
issn = { 0975-8887 },
pages = { 55-60 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number56/nexera-a-mobile-platform-integrating-instant-on-demand-services-and-ai-driven-market-insights/ },
doi = { 10.5120/ijca2025925987 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-11-18T21:11:06.831572+05:30
%A Shah Farzeen Hossain
%A Md. Fokhray Hossain
%A Md. Asif Al Rumel
%A Md. Abdullah Abu Sayem
%A Mohammad Samir Hossain
%A Md. Al-Amin Hossen
%T Nexera: A Mobile Platform Integrating Instant On-Demand Services and AI-Driven Market Insights
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 56
%P 55-60
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Smart job search systems and mobile applications have significantly improved access to employment opportunities, yet they remain largely constrained to conventional recruitment processes, graduate employability tools, and social networking-based professional systems, leaving a persistent gap between job seekers’ immediate needs for flexible, income-generating tasks and the dynamic requirements of local markets and emerging startups. This study introduces Nexera, a Java-based mobile application designed to provide instant service provision, micro-task employment, and grassroots-level purchase insights powered by AI. Unlike existing systems, Nexera integrates job search with real-time market intelligence, enabling users not only to earn through short-term tasks but also to access supplier data, gain entrepreneurial insights, and transition into sustainable business ownership. By connecting local economic actors with AI-driven insights, Nexera supports both regional micro-earning opportunities and instant access to on-demand workers across a region, supporting global entrepreneurial participation and local-to-global market integration. By combining instant gig opportunities, AI recommendations, and startup dashboards, Nexera contributes to both individual empowerment, local economic development, and the broader processes of globalization.

References
  1. Baptista, D., Freund, R., & Novella, R. (2024). Job training and search assistance for microwork: Evidence from Haiti. Economics Letters, 244, 111948. https://doi.org/10.1016/j.econlet.2024.111948.
  2. Meccawy, Z., Meccawy, M., Alsobhi, A., 2018. The Graduate Helper: Using a mobile application as a feasible resource for job hunting across Saudi Arabia. International Journal of Interactive Mobile Technologies 12, 152–163.
  3. Ziakis, J., & Vlachopoulou, M. (2023). Artificial intelligence in digital marketing: Insights from a systematic literature review. Information, 14(12), 664. https://doi.org/10.3390/info14120664.
  4. Easak, C., Devigasri, V., 2025. Quick Hire – Web based platform. International Research Journal of Modernization in Engineering, Technology and Science 7. Available at: https://www.irjmets.com/upload_newfiles/irjmets70500301355/paper_file/irjmets70500301355.pdf
  5. Kittur, A., Smus, B., Khamkar, S., Kraut, R.E., 2011. On-the-job learning for micro-task workers. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’11). ACM, Vancouver, Canada, pp. 2739–2748. https://doi.org/10.1145/1978942.1979336
  6. Mirwan, S.H., Ginny, P.L., Darwin, D., Ghazali, R., Lenas, M.N.J., 2023. Using artificial intelligence (AI) in developing marketing strategies. International Journal of Applied Research in Sustainable Science 1, 225–238.
  7. Silva, B.C., Moreira, A.C., 2022. Entrepreneurship and the gig economy: A bibliometric analysis. Cuadernos de Gestión 22, 23–44. https://doi.org/10.5295/cdg.211580am
  8. Han, H.H., Choi, Y.K., Lee, J.H., 2022. Independent workers’ continuous engagement in the gig economy: A meta-analysis. Selangor Business Review 7, 69–84. Available at: https://sbr.journals.unisel.edu.my/ojs/index.php/sbr/article/view/118
  9. Paulino, D., Correia, A., Barroso, J., Paredes, H., 2023. Cognitive personalization for online microtask labor platforms: A systematic literature review. User Modeling and User-Adapted Interaction 34, 617–658. https://doi.org/10.1007/s11257-023-09383-w
  10. Hsieh, J., Zhang, A., Rasetarinera, M., Chou, E., Ngo, D., Lightman, K., Lee, M.K., Zhu, H., 2024. Supporting gig worker needs and advancing policy through worker-centered data-sharing. arXiv preprint arXiv:2412.02973. Available at: https://arxiv.org/abs/2412.02973
  11. Lu, L., Weng, X., Xiao, L., 2024. Service deployment in the on-demand economy: Employees, contractors, or both? arXiv preprint arXiv:2411.06793. Available at: https://arxiv.org/abs/2411.06793
  12. Luo, Q., Tharumarajah, N.A.L., 2025. How flexibility in gig work affects work-life balance: A case study of online service platform industry. International Journal of Public Policy and Administration Research 12, 133–150. https://doi.org/10.18488/74.v12i2.4260
  13. ArticleMarket, 2025. The rise of AI microtasks: How small jobs are creating big opportunities. ArticleMarket. Available at: https://www.articlemarket.org/the-rise-of-ai-microtasks-how-small-jobs-are-creating-big-opportunities/
  14. Fossen, F.M., McLemore, T., Sorgner, A., 2024. Artificial intelligence and entrepreneurship. IZA Discussion Paper No. 17055. Available at: https://docs.iza.org/dp17055.pdf
  15. Reffell, C., 2025. Microtask platforms balance employer and worker perspectives. Crowdsourcing Week. Available at: https://crowdsourcingweek.com/blog/microtask-platforms-balance-employers-and-workers/
  16. Zhang, H., Wang, Y., Lam, H., Wong, Y., Liu, Z., Zhao, X., Wang, Y., Chen, B., Guo, H., Tang, R., 2023. Multi-task deep recommender systems: A survey. arXiv preprint arXiv:2302.03525. Available at: https://arxiv.org/abs/2302.03525
  17. Rajput, S., Mitra, J., Li, E., Callan, J., 2023. Recommender systems with generative retrieval. arXiv preprint arXiv:2305.05065. Available at: https://arxiv.org/abs/2305.05065
  18. Ndolo, D.M., 2023. Job recommendation systems: A literature review. International Journal of Innovative Research in Science, Engineering and Technology 8, 2356–2359. Available at: https://www.researchgate.net/publication/369973770_Job_Recommendation_Systems_A_Literature_Review
  19. Gupta, S.K., Gupta, R.K., Gupta, S.K., 2020. Optimizing microtask assignment on crowdsourcing platforms using worker characteristics. Computers & Industrial Engineering 149, 106806. https://doi.org/10.1016/j.cie.2020.106806
  20. Taylor, L.M., 2020. Microjobs in 2030: A perspective on the future of work. Visionary Innovation Group, Frost & Sullivan, Global, Megatrends report, 7 February 2020. Available at: https://www.frost.com
  21. Research and Markets. (2025). Microtasking market forecasts report 2025–2030. https://www.researchandmarkets.com/report/microtasking.
  22. Birau, R., Chugh, R., & Jain, A. (2024). Artificial intelligence (AI) empowerment in e-commerce. Global Business Review, 25(1), 1–18. https://doi.org/10.1177/09711023241303621
Index Terms

Computer Science
Information Sciences
Mobile Application
Artificial Intelligence
Gig Economy
Entrepreneurship

Keywords

Micro task Part-time job search gig economy AI insights mobile applications grassroots entrepreneurship local purchase intelligence global market integration cross-regional opportunity