[AISWorld] CFP: Book: Handbook of Research on Foundations and Applications of Intelligent Business Analytics

Sat May 22 02:33:16 EDT 2021

2nd 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

HTTPS://WWW.IGI-GLOBAL.COM/PUBLISH/CALL-FOR-PAPERS/CALL-DETAILS/5211
<https://www.igi-global.com/PUBLISH/CALL-FOR-PAPERS/CALL-DETAILS/5211>
or
http://wikicfp.com/cfp/servlet/event.showcfp?eventid=128907&copyownerid=49462

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 May 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 May 30, 2021 about the status of their proposals and sent
chapter guidelines. Full chapters are expected to be submitted by June 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
- June 21, 2021: 1st proposal submission deadline to the editor (if you
submitted, please ignore this part),
- July 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.

Prof. Dr. Zhaohao Sun, Ph.D. & Prof. Dr. Zhiyou Wu, Ph.D.
Editor of Handbook of Research on Foundations and Applications Intelligent
Business Analytics

Research Centre of Big Data Analytics and Intelligent Systems (BAIS)
Department of Business Studies
PNG University of Technology
Morobe 411, PNG
zhaohao.sun at gmail.com
&
School of Mathematical Sciences
Chongqing Normal University, China
zywu at cqnu.edu.cn

On Fri, May 14, 2021 at 2:39 PM Zhaohao Sun <zhaohao.sun at gmail.com> wrote:

>
> 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
>
> HTTPS://WWW.IGI-GLOBAL.COM/PUBLISH/CALL-FOR-PAPERS/CALL-DETAILS/5211
> <https://www.igi-global.com/PUBLISH/CALL-FOR-PAPERS/CALL-DETAILS/5211>
> or
>
> http://wikicfp.com/cfp/servlet/event.showcfp?eventid=128907&copyownerid=49462
>
> 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 May 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 May 30, 2021 about the status of their proposals and sent
> chapter guidelines. Full chapters are expected to be submitted by June 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
> - May 21, 2021: 1st proposal submission deadline to the editor (if you
> submitted, please ignore this part),
> - June 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.
>
> Prof. Dr. Zhaohao Sun, Ph.D. & Prof. Dr. Zhiyou Wu, Ph.D.
> Editor of Handbook of Research on Foundations and Applications Intelligent
> Business Analytics
>
> Research Centre of Big Data Analytics and Intelligent Systems (BAIS)
> Department of Business Studies
> PNG University of Technology
> Morobe 411, PNG
> zhaohao.sun at gmail.com
> &
> School of Mathematical Sciences
> Chongqing Normal University, China
> zywu at cqnu.edu.cn
>