-------- Forwarded Message -------- Subject: [AISWorld] 1st CFP: Book: Handbook of Research on Foundations and Applications of Intelligent Business Analytics Date: Thu, 25 Mar 2021 10:53:15 +1100 From: Zhaohao Sun zhaohao.sun@gmail.com To: aisworld@lists.aisnet.org CC: Maria Rohde mrohde@igi-global.com

1ST CALL FOR BOOK CHAPTERS

BOOK: Handbook of Research on Foundations and Applications of Intelligent Business Analytics EDITED BY PROF. DR. ZHAOHAO SUN AND PROF. DR. ZHIYOU WU TO BE PUBLISHED BY IGI Global, USA

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Introduction

We are living in the age of big data, analytics and artificial intelligence (AI). Intelligent business analytics as the integration of big data, analytics , and artificial intelligence for business has drawn increasing attention in academia and industries. Intelligent business analytics mainly includes intelligent business analytics systems, intelligent business analytics platform, intelligent business analytics services, intelligent business process analytics, intelligent human resource analytics, intelligent marketing analytics, business analytics intelligence, intelligent business analytics tools, advanced intelligent business analytics, intelligent customer analytics, intelligent traffic analytics, intelligent data analytics, intelligent health analytics, intelligent big data analytics and more. Intelligent business analytics is still an emerging discipline in academia although artificial intelligence (AI) and business analytics have become a hotspot in academia and industries. The following are still big research issues for developing intelligent business analytics based on our preliminary analysis: What is intelligent business analytics? What is the fundamental of intelligent business analytics? How can incorporate the latest intelligent techniques into business analytics applications? What are the applications of intelligent business analytics? What are the impacts of intelligent business analytics on intelligent business and business decision making?

Objective of the book

This book addresses the above-mentioned research issues by investigating into foundations, technologies, and applications of intelligent business analytics. This book is the first book on "Intelligent business analytics" that focuses on intelligent business, intelligent business analytics, intelligent analytics including intelligent big data analytics in the age of big data, analytics, and artificial intelligence. This book is the first book to reveal the cutting-edge theoretical foundations, technologies, methodologies, and applications of intelligent business analytics in an integrated way. This is also the first book demonstrating that intelligent business analytics is at the center of intelligent business, intelligent decision making, intelligent management, digital transformation, governance, and services in the digital age.

Target audience

This book?s primary aim is to convey the theoretical foundations, technologies, thoughts, and methods of intelligent business analytics with applications to scientists, engineers, educators and university students, business, service, and management professionals, policy-makers, decision-makers, and others who have an interest in big data, intelligent business, intelligent management, intelligent business analytics, AI, digital transformation, SMACS (service, mobile, analytics, cloud, social) business and intelligence, service, and data science. Primary audiences for this book are undergraduate, postgraduate students, and a variety of professionals in the fields of big data, analytics, intelligent business and management, data science, information science and technology, knowledge technology and engineering, intelligence science, AI, ICT, computing, commerce, business, services, management, and government. The variety of readers in the fields of government, consulting, marketing, business, and trade, as well as the readers from all the social strata, can also be benefited from this book to improve understanding of the cutting-edge theory, technologies, methodologies, and applications of intelligent business analytics in the digital age.

Recommended topics include, but are not limited to, the following

We seek book chapters with original research that promotes theoretical and technical research as well as emerging applications of intelligent business analytics. Submissions that cross multiple disciplines such as management, service, business, AI, intelligent systems, computer science, data science, optimization, statistics, information systems, decision sciences, and industries to develop theory and provide technologies and applications that could move theory and practice forward in intelligent business analytics, are especially encouraged.

Topics of Interest

Topics of contributions to this book include four parts: foundations, technologies, applications and emerging technologies and applications of intelligent business analytics.

Part I. Foundations of intelligent analytics

Topics: fundamental concepts and theories, models/architectures, frameworks/mechanisms or foundations for developing, operating, evaluating, managing, and regulating intelligent analytics and intelligent business analytics. The following topics might include, but not limited to. 1. Intelligent business analytics as a science 2. A unified theoretical foundation of intelligent business analytics 3. Frameworks and mechanisms for intelligent business analytics 4. Business Intelligence, big data intelligence 5. Business analytics intelligence 6. Intelligent business analytics for big data, information, knowledge, intelligence, and wisdom processing 7. Intelligent business analytics ecosystems 8. Intelligent business analytics for automated decision making. 9. Intelligent business analytics and intelligent analytics 10. Computational foundations of intelligent business analytics 11. New computational models for big data analytics 12. Mathematical fundamentals of intelligent business analytics 13. Mathematical theory of intelligent analytics 14. Fuzzy logic approach to intelligent business analytics 15. ICT fundamentals for analytics 16. Business models for intelligent analytics 17. Real-time algorithms for intelligent business analytics 18. Intelligent business analytics thinking 19. Computing thinking for intelligent analytics 20. Business processes flow-oriented intelligent analytics 21. Big data science 22. Data preparation and data visualization 23. Machine learning and deep learning for intelligent business analytics 24. Data and text mining for intelligent business analytics 25. Intelligent warehouses, intelligent mining, intelligent statistical modelling 26. Data visualization for intelligent business analytics 27. Intelligent visualization of data, models, and insights 28. Statistical modelling for intelligent business analytics 29. Intelligent reporting 30. Optimization for big data, information, knowledge, intelligence, and wisdom 31. AI, Ethic AI, Explainable AI, and responsible AI for business analytics process

Part II. Technologies for intelligent analytics

Topics: Tools and technologies for developing, operating, evaluating, managing, and regulating intelligent analytics and intelligent business analytics might include the following topics of interest, but not limited to.

1. Intelligent business analytics as a technology 2. Intelligent technology, computational technology, web technology, Internet technology, social networking technology, cloud technology, big data technology, IoT, and IoE (the Internet of everything) technology for business analytics 3. Intelligent business analytics systems 4. Intelligent business analytics services 5. Intelligent business analytics management 6. Intelligent enterprise analytics 7. Intelligent services analytics 8. Intelligent data visualization techniques for business analytics 9. Intelligent techniques for enterprise analytics and services analytics. 10. Business processes flow-oriented intelligent analytics 11. Rule-based systems 12. Neural networks 13. Fuzzy logic 14. Expert systems 15. Intelligent agents and multi-agent systems 16. Cased-based reasoning 17. Genetic algorithms 18. Data mining algorithms 19. Intelligent user interfaces 20. Knowledge management 21. Intelligent big data/information/knowledge technologies 22. Intelligent service technologies 23. Social networking technologies 24. Intelligent decision technologies 25. Cloud computing, IoT, and IoE 26. Intelligent business and management technologies 27. Intelligent analytics for Micro, Small & Medium Enterprises (MSMEs) 28. Optimization techniques for intelligent business analytics 29. Machine-to-machine communication.

Part III. Applications of intelligent analytics Topics: Real-world applications and case studies for using foundations and technologies in Part I, II in various domains such as digital transformation, blockchain, 5G systems, SMACS business and services, intelligent drones, healthcare, smart cities, financial services, legal services, healthcare services, educational services, and military services taking into account intelligent descriptive, diagnostic, predictive and prescriptive analytics. The following topics might include, but not limited to. 1. Intelligent business analytics-based innovation and entrepreneurship 2. Intelligent analytics in business ecosystems 3. Intelligent business analytics with public and open data 4. Intelligent business analytics for market innovation 5. Intelligent business analytics for e-business 6. Intelligent business analytics for cloud computing 7. Intelligent business analytics for IoT and IoE 8. Intelligent business analytics for blockchain 9. Intelligent business analytics for 5G applications 10. Intelligent business analytics for business decision making 11. Intelligent healthcare analytics 12. Analytic flow-oriented business solutions 13. Intelligent business analytics for business model innovation 14. Big data analytics economics and business analytics economics 15. Intelligent business analytics for location intelligence 16. Big data management and intelligent business analytics 17. Marketing analytics, healthcare analytics, management analytics and HR analytics 18. Intelligent analytics in banking industry 19. Intelligent analytics in social networking services 20. Intelligent analytics for big data, information, knowledge, and wisdom 21. Cybersecurity and privacy in intelligent business analytics. 22. Intelligent analytics for management 23. Intelligent analytics for risk management 24. Organization analytics 25. Intelligent analytics-driven decision making 26. Analytics centric business and enterprise innovations 27. SME oriented intelligent business analytics 28. Academic analytics, teaching analytics, and learning analytics 29. Smart AI, intelligent business analytics adoption studies 30. Ethical issues related to intelligent business analytics 31. Risks in adoption and deployment of business analytics and enterprise analytics. 32. Challenges, trends, and controversies of intelligent analytics and business analytics Part IV. Emerging technologies and applications for intelligent business analytics Topics: Emerging cutting-edge technologies, methodologies, and applications for intelligent business analytics. The following topics of interest might also include, but not limited to.

1. Next-generation big data analytics 2. Next generation of intelligent business analytics 3. Intelligent business analytics for enhancing organization intelligence and market intelligence. 4. Emergent intelligent business analytics technologies 5. Emergent technologies for business analytics intelligence 6. Challenges, opportunities, and implications of intelligent big data analytics 7. Challenges, opportunities, and implications of intelligent enterprise analytics and market analytics 8. Challenges and opportunities for intelligent big information analytics 9. Challenges and opportunities for intelligent big knowledge analytics 10. Challenges and opportunities for intelligent analytics research 11. Challenges, opportunities, and dark-side of intelligent analytics applications 12. Ethic AI, explainable AI, and responsible AI for business analytics 13. Challenges and opportunities for intelligent analytics tools, platforms , and systems 14. Organisational and business innovation from AI and intelligent business analytics 15. Automated analytics process integration. Submission Procedure Researchers and practitioners are invited to submit on or before April 21, 2021, a chapter proposal of 150 to 2,00 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by April 30, 2021 about the status of their proposals and sent chapter guidelines. Full chapters are expected to be submitted by May 19, 2021, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ 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, Handbook of Research on Foundations and Applications of Intelligent Business Analytics. 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 through clicking "Propose a chapter" at https://www.igi-global.com/publish/call-for-papers/call-details/5211. Submission Format and Evaluation Every book chapter submission should consist of 8,000-12,000 words, and be structured into sections including Abstract, Introduction, background (or related work), main sections, future research directions, conclusion, and references. Every book chapter must be submitted in Microsoft? Word and be typewritten in English in APA style based on the "manage source" and "insert citation" function. Every book chapter submission is original. Only ORIGINAL articles will be accepted for publication by IGI-Global. Upon acceptance of your book chapter, you will be required to sign a warranty that your book chapter is original and has NOT been submitted for publication or published elsewhere. All chapter submissions undergo a double-blind peer-review using the eEditorial Discovery? online submission manager. Conditioned accepted chapters will have an additional opportunity for being improved and evaluated. In the second evaluation, a definitive editorial decision among: accepted or rejected will be reported. All of the accepted chapters must be submitted according to the Editorial publishing format rules timely. Instructions for authors can be downloaded at: http://www.igi-global.com/Files/AuthorEditor/guidelinessubmission.pdf. The final chapters are copy edited/proofed by the authors prior to submission, following the IGI Global chapter formatting and submission guidelines. Important Dates - Mar 22, 2021, Release First CFP - Apr 21, 2021: 1st proposal submission deadline to the editor, - May 19, 2021: Submission deadline of the full chapters. - Oct 17, 2021: Review results due to authors - Nov 14, 2021: Revisions due from authors - Nov 28, 2021: Final acceptance/rejection notification due to authors - Dec 12, 2021: All final accepted materials due from authors.

Editors' Information Prof. Dr. Zhaohao Sun, Ph.D. Research Centre of Big Data Analytics and Intelligent Systems (BAIS) Department of Business Studies PNG University of Technology Morobe, PNG zhaohao.sun@gmail.com & Prof. Dr. Zhiyou Wu, Ph.D. School of Mathematical Sciences Chongqing Normal University, China zywu@cqnu.edu.cn

Sun -----------------------

Prof. Dr. Zhaohao Sun, Ph.D.

Director

Research Centre of Big Data Analytics and Intelligent Systems (BAIS)

Department of Business Studies

PNG University of Technology

Private Mail Bag, Lae 411, Morobe, PNG

Phone: +675 473 4406

Email: zhaohao.sun@pnguot.ac.pg zsun@dbs.initech.ac.pg or zhaohao.sun@gmail.com (private)

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