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First Published Book

AI in Business Analytics & Decision-Making

The inaugural edited volume published by Jupiter Publications Consortium (JPC).

AI in Business Analytics and Decision-Making Book Cover

This edited scholarly work explores how Artificial Intelligence and Machine Learning reshape enterprise analytics, enabling predictive, prescriptive, and automated decision-making at scale. The volume consolidates foundational theories, applied research, and domain-specific case studies that guide organizational transformation through data-driven intelligence.

AI/ML Business Analytics Decision Intelligence Enterprise Transformation
eISBN978-93-86388-87-2
Book DOI https://doi.org/10.47715/978-93-86388-87-2
VolumeI
EditionFirst
First Published12th November, 2025
AvailabilityOpen Access
Copyright © 2025 Jupiter Publications Consortium
All rights reserved worldwide.
Publisher Jupiter Publications Consortium
22/102, Second Street, Virugambakkam,
Chennai – 600 092, India
Email: director@jpc.in.net
Website: www.jpc.in.net
Editors Prof. (Dr.) S. Mohan Kumar · Prof. (Dr.) G. Balakrishnan · Dr. Joseph Bamidele Awotunde · Prof. (Dr.) K. P. Yadav
Chapter-wise DOI Registry
Ch. 1 DOI Ch. 2 DOI Ch. 3 DOI Ch. 4 DOI Ch. 5 DOI Ch. 6 DOI Ch. 7 DOI
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The Analytics–Personalization Nexus
Current Call for Chapters

The Analytics–Personalization Nexus (Digital Retail)

This volume focuses on the intersection of analytics, personalization, and customer experience in digital retail. Topics include recommender systems, behavioural segmentation, churn prediction, omni-channel engagement, and responsible use of customer data in AI-driven environments.

E-commerce Recommender Systems Customer Loyalty Behavioural Analytics

Editors: Prof. (Dr.) S. Mohan Kumar · Prof. Dr. A. Shajin Nargunam · Dr. A. Hemalatha · Dr. Duraisamy Balaganesh

ISBN: 978-93-XXXX-XXXX

DOI (Volume): 10.xxxx/jpc.retail-personalization

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Active & Upcoming Calls

Calls for Book Chapters

Contribute original research, surveys, case studies, and practice-oriented chapters to our edited books.

AI in Business Analytics & Decision-Making

Chapters on AI/ML-enabled analytics, forecasting, optimization, decision support, and organizational change for data-driven enterprises.

AI/ML Decision Support
View Scope

Analytics–Personalization Nexus

Focused on digital retail, personalization strategies, recommender systems, customer experience design, and loyalty analytics.

Digital Retail Customer Analytics
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Thematic Focus

Research Themes & Application Domains

We welcome contributions from diverse domains where AI, analytics, and digital technologies are shaping decision-making and organizational performance.

Business Intelligence & Dashboards Predictive & Prescriptive Analytics Financial Analytics & FinTech Healthcare & Public Health Analytics Manufacturing & Industry 4.0 Smart Cities & Public Policy Customer Experience & CRM Education Technology & Learning Analytics AI Governance & Ethics

Authors may submit theoretical, empirical, simulation-based, review, or case-study chapters aligned with the scope of each edited book.

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Our editorial process is structured to support authors from initial concept to final publication, ensuring quality, relevance, and visibility for every chapter.

Step 1
Identify your theme and align it with an active call for chapters.
Step 2
Submit an extended abstract or proposal via the Submit Chapter page.
Step 3
Develop the full chapter following our author guidelines and template.
Step 4
Revise based on peer and editorial reviews; finalize for ISBN & DOI-indexed publication.
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Voices from the Community

Scholars on AI & Analytics

“Artificial intelligence is the new electricity.” It is transforming industries and reshaping the way organizations think about data-driven decisions.

Andrew Ng

“The future belongs to those who can turn data into decisions.” Edited books like these play a crucial role in capturing best practices and emerging frameworks.

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“For academicians and practitioners, contributing a chapter is an opportunity to shape how AI and analytics are adopted responsibly across sectors.”

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