The Role of Complex Systems in Predictive Analytics for E-Commerce Innovations in Business Management

This review explores the incorporation of complex systems theory into predictive analytics in the e-commerce sector, particularly emphasizing recent advancements in business management. By analyzing the intersection of these two domains, the review emphasizes the potential of complex systems models—including agent-based modeling and network theory—to improve the precision and efficacy of predictive analytics. It will provide a comprehensive overview of the applications of emergent predictive analytics techniques and tools, including real-time data analysis and machine learning, in inventory optimization, dynamic pricing, and personalization of customer experiences. In addition, this review will suggest future research directions to advance the discipline and address the technical, ethical, and practical challenges encountered during this integration phase.

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Publication Details

Journal
Systems
Published
2024-10-05
DOI
https://doi.org/10.3390/systems12100415
Citations
14
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
7.40
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article

The Role of Complex Systems in Predictive Analytics for E-Commerce Innovations in Business Management

Mitra Madanchian
14 citations
Systems
Big Data and Business Intelligence
7.40
article

The Role of Complex Systems in Predictive Analytics for E-Commerce Innovations in Business Management

Mitra Madanchian
article en
14 citations

Abstract

This review explores the incorporation of complex systems theory into predictive analytics in the e-commerce sector, particularly emphasizing recent advancements in business management. By analyzing the intersection of these two domains, the review emphasizes the potential of complex systems models—including agent-based modeling and network theory—to improve the precision and efficacy of predictive analytics. It will provide a comprehensive overview of the applications of emergent predictive analytics techniques and tools, including real-time data analysis and machine learning, in inventory optimization, dynamic pricing, and personalization of customer experiences. In addition, this review will suggest future research directions to advance the discipline and address the technical, ethical, and practical challenges encountered during this integration phase.

SystemsVol. 12(10)
University Canada West (CA)
Industry, innovation and infrastructure
Openalex Percentile: Top 3%
Big Data and Business Intelligence
7.40
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