-------- Forwarded Message --------
3rd 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
Please also see
https://www.igi-global.com/publish/call-for-papers/call-details/5211
or
http://wikicfp.com/cfp/servlet/event.showcfp?eventid=128907©ownerid=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?
*The objective of the book*
This book addresses the above-mentioned research issues by
investigating
the 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
July 21,
2021, a chapter proposal (Abstract) of 150 to 200 word/s clearly
explaining
the mission and concerns of his or her proposed chapter. Authors
will be
notified by July 26, 2021, about the status of their proposals and
sent
chapter guidelines. Full chapters are expected to be submitted by
August
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
- July 21, 2021: 1st proposal submission deadline to the editor
(if you
submitted, please ignore this part),
- August 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@gmail.com
&
School of Mathematical Sciences
Chongqing Normal University, China
zywu@cqnu.edu.cn
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