Call for Chapters: Data-Driven Intelligent Business Sustainability


Sonia Singh, Toss Global Management, United Arab Emirates
S. Suman Rajest, Bharath Institute of Higher Education and Research, India
Slim Hadoussa, Brest Business School France, France
Ahmed J. Obaid, University of Kufa, Iraq
R. Regin , SRM Institute of Science and Technology, India

Call for Chapters

Proposals Submission Deadline: May 17, 2023
Full Chapters Due: July 30, 2023
Submission Date: July 30, 2023


This book series aims to provide an in-depth examination of the impact that data-driven decision making is having on the ability to achieve long-term commercial and economic success. In order to be considered for inclusion in this proposed book series, research must be novel, with the goal of providing new insights through methodologically sound and evidence-based analysis. Recent years have seen a meteoric rise in data-driven decision making, powered by advances in our capacity to collect and interpret information on a scale previously unimaginable. One of the greatest problems in today's technical and business climate is maintaining a healthy firm that can develop and continue to provide cutting-edge goods and services to the public and boost economic growth. Researchers are asked to solve the topic of how to ensure the long-term success of organisations by using evidence-based decision making in this book series. When it comes to deploying and utilising critical technology, we zero in on how firms do so in order to maximise their impact.

Numerous significant technologies have dramatically altered the ways in which businesses are operated. Blockchain, the Internet of Things (IoT), and artificial intelligence (AI) are just a few examples of such technologies. How businesses make decisions, interact with clients, and introduce new offerings is now being influenced by cutting-edge tech. The foundation for the connection between organisations and their many stakeholders has shifted thanks to the emergence of new tools and techniques including chatbots, virtual assistants, m-commerce, virtual teams, and interactions via the metaverse. The rapid pace of digitization has created new risks for businesses, particularly in the form of cybersecurity threats, and the usage of artificial intelligence has introduced new ethical questions and conundrums. Therefore, it is essential to create plans for long-term company expansion. This book series seeks contributions to modern machine learning methods, causal inference, and other data-driven approaches that might help businesses make better managerial decisions.


The purpose of this book series is to provide a comprehensive analysis of how data-driven decision making is influencing the prospects for sustainable commercial and economic growth. Novel research with the intent of elucidating fresh perspectives through methodically sound and evidence-based analysis is required for consideration for inclusion in this proposed book series. Data-driven decision making has skyrocketed in popularity in recent years, thanks to technological advancements that have allowed us to collect and analyse data on an unprecedented scale. Today's technological and business environment makes it difficult to sustain a thriving corporation that can innovate, grow, and supply the market with cutting-edge products and services that stimulate the economy. The problem has been posed to the research community.

Target Audience

This book aims to give opportunities for academicians, Scientists, Research Scholars, Professors, Graduates, undergraduates, and students of the Department of Computer Science and Engineering and contains transdisciplinary advancements in Long-Term Business Success in Data-Driven Decision Making.

The topics are crafted in such a way as to cover all the areas of Long-Term Business Success in Data-Driven Decision Making that require AI for further development. Some of the topics which contain algorithms and techniques are explained with the help of source code developed by the chapter contributors. This book encompasses the readiness and needs for advancements in managing yet another pandemic in the future.

This results in the self-sustainability goals in Long-Term Business Success in Data-Driven Decision Making across the globe. Most of the technologies addressed in this book are added with a concept of encapsulation to obtain a cookbook for anyone who needs to reskill or upskill themselves in order to contribute to an advancement in the field. This book benefits students, professionals, and anyone from any background to learn about Artificial and Long-Term Business Success in Data-Driven Decision Making. We trust this book is instructive yet much more than it is provocative and moves, driving per user to examine different inquiries, applications, and potential arrangements in making sheltered and secure plans for all researchers worldwide. This book Chapter inspires young scholars to learn about newly created avenues of research at an international academic forum.

Recommended Topics

• Chapter 1: New tech for enterprises and pricing optimization
• Chapter 2: Big data and metaverse models
• Chapter 3: Fighting digital economy's evil
• Chapter 4: Data-driven strategy ethics
• Chapter 5: Data-driven case studies on managing digitalization
• Chapter 6: Business usage of new technology' social
• Chapter 7: Blockchain, big data, and cryptocurrency markets
• Chapter 8: IoT-based business models and channel optimization
• Chapter 9: Explainable business artificial intelligence
• Chapter 10: Blockchain-based apps and omnichannel promotions
• Chapter 11: Big data and social welfare and environmental implications
• Chapter 12: Climate change-focused apps
• Chapter 13: Data-driven work-future management
• Chapter 14: Data-driven cybersecurity management
• Chapter 15: Metaverse data-driven decision-making
• Chapter 16: Big data-driven business decision models
• Chapter 17: Big data and finance and developing sustainably
• Chapter 18: Large-scale optimization and company performance
• Chapter 19: Big data analytics for product development
• Chapter 20: Competence, performance, and big data analytics
• Chapter 21: Big data analytics in HR management
• Chapter 22: Circular economy requires big data analytics
• Chapter 23: Big data analytics for business stakeholders
• Chapter 24: Business stakeholders' big data analytics value
• Chapter 25: Big data analytics metrics to financial performance

Submission Procedure

Researchers and practitioners are invited to submit on or before May 17, 2023, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by May 31, 2023 about the status of their proposals and sent chapter guidelines.Full chapters are expected to be submitted by July 30, 2023, and all interested authors must consult the guidelines for manuscript submissions at prior to submission. All submitted chapters will be reviewed on a double-blind review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Data-Driven Intelligent Business Sustainability. All manuscripts are accepted based on a double-blind peer review editorial process.

All proposals should be submitted through the eEditorial Discovery® online submission manager.


This book is scheduled to be published by IGI Global (formerly Idea Group Inc.), an international academic publisher of the "Information Science Reference" (formerly Idea Group Reference), "Medical Information Science Reference," "Business Science Reference," and "Engineering Science Reference" imprints. IGI Global specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit This publication is anticipated to be released in 2024.

Important Dates

May 17, 2023: Proposal Submission Deadline
May 31, 2023: Notification of Acceptance
July 30, 2023: Full Chapter Submission
September 12, 2023: Review Results Returned
October 24, 2023: Final Acceptance Notification
November 7, 2023: Final Chapter Submission


Sonia Singh
Toss Global Management

S. Suman Rajest
Bharath Institute of Higher Education and Research

Slim Hadoussa
Brest Business School France

Ahmed J. Obaid
University of Kufa

Regin R
SRM Institute of Science and Technology


Business and Management; Computer Science and Information Technology; Education; Environmental, Agricultural, and Physical Sciences; Library and Information Science; Medical, Healthcare, and Life Sciences; Media and Communications; Security and Forensics; Government and Law; Social Sciences and Humanities; Science and Engineering
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