Integrating Artificial Intelligence into Product Roadmapping: A Study of Predictive Analytics Adoption Among U.S. E-Commerce Firms

References

[1] Chen, L., & Zhang, M. (2021). Artificial intelligence in strategic planning: A systematic review and research agenda. Strategic Management Journal, 42(8), 1454-1477. https://doi.org/10.1002/smj.3265

[2] Kumar, S., Peterson, R., & Williams, A. (2020). Machine learning applications in retail demand forecasting: A comprehensive analysis. Journal of Business Research, 108, 85-97. https://doi.org/10.1016/j.jbusres.2019.10.032

[3] Martinez, C., & Johnson, D. (2021). Personalization systems in e-commerce: Performance impacts and implementation strategies. Information Systems Research, 32(3), 891-908. https://doi.org/10.1287/isre.2021.0998

[4] Patel, N., Kumar, V., & Smith, R. (2022). Digital transformation in retail: AI adoption patterns and performance outcomes. Harvard Business Review, 100(4), 78-87.

[5] Rodriguez, M., Thompson, K., & Lee, S. (2021). Predictive analytics in supply chain management: Evidence from e-commerce firms. Production and Operations Management, 30(7), 2234-2251. https://doi.org/10.1111/poms.13385

[6] Teece, D. J. (2018). Business models and dynamic capabilities. Long Range Planning, 51(1), 40-49. https://doi.org/10.1016/j.lrp.2017.06.007

[7] Thompson, J. (2022). Organizational factors in AI implementation: A multi-industry study. MIT Sloan Management Review, 63(2), 45-52.

[8] U.S. Census Bureau. (2022). Quarterly retail e-commerce sales: 4th quarter 2021. U.S. Department of Commerce. https://www.census.gov/retail/mrts/www/data/pdf/ec_current.pdf

[9] Williams, P., Davis, K., & Anderson, L. (2022). Barriers to AI adoption in medium-sized enterprises: An empirical investigation. MIS Quarterly, 46(2), 687-712. https://doi.org/10.25300/MISQ/2022/15834

[10] Wilson, R., Brown, T., & Garcia, M. (2021). Customer analytics and business performance: A meta-analysis of e-commerce studies. Journal of Marketing Analytics, 9(3), 156-172. https://doi.org/10.1057/s41270-021-00108-9

[11] Young, S., Clark, B., & Taylor, H. (2022). Technology infrastructure and AI success: Lessons from retail implementations. Information Technology & Management, 23(2), 89-105. https://doi.org/10.1007/s10799-021-00341-2

[12] Zhang, Q., Miller, A., & Foster, J. (2021). Change management in AI implementations: Critical success factors. Organizational Dynamics, 50(4), 100-115. https://doi.org/10.1016/j.orgdyn.2021.100847

[13] Corresponding Author: Dr. [Author Name] Department of Management Information Systems [University Name] Email: [email]

[14] Received: March 15, 2022; Revised: June 8, 2022; Accepted: August 12, 2022

@article{1710172,
      author = {Omon ENI, Arun K Menon},
      title = {Integrating Artificial Intelligence into Product Roadmapping: A Study of Predictive Analytics Adoption Among U.S. E-Commerce Firms},
      journal = {Iconic Research And Engineering Journals},
      year = {2022},
      volume = {6},
      number = {3},
      pages = {312-321},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1710172.pdf},
      abstract = {This study examines the integration of artificial intelligence (AI) and predictive analytics into product roadmapping processes among medium-to-large U.S. e-commerce companies. Through a mixed-methods approach involving surveys of 284 companies and in-depth interviews with 47 executives, this research investigates how AI adoption in product planning affects return on investment (ROI) and customer retention metrics. The findings reveal that companies implementing AI-driven predictive analytics in their product roadmapping processes achieved an average ROI improvement of 23.4% and customer retention increases of 18.7% over traditional methods. However, adoption barriers including data quality concerns, organizational resistance, and technical infrastructure limitations persist across the sector. This research contributes to the growing body of knowledge on AI implementation in strategic business processes and provides actionable insights for e-commerce executives considering AI integration.},
      keywords = {Artificial Intelligence, Product Roadmapping, E-commerce, Predictive Analytics, Customer Retention, ROI},
      month = {September},
  }