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Dear Colleagues
We would like to invite you to submit your work for possible
publication in the special issue for Journal of Business Research
(3* ABS) - Using Big Data and Artificial Intelligence in Business
to Impact Global Challenges
Deadline: 30th April 2019
Guest Editors:
Zahir Irani - Professor and Dean of Faculty, University of
Bradford, UK.
Peter E.D Love - John Curtin Distinguished Professor, Curtin
University, Australia.
Muhammad M. Kamal - Senior Lecturer, Brunel University London, UK.
Introduction:
Decision-making that leads to the allocation of competitively
sought resources for exploration, discovery, building or testing
of ideas is informed by data that when structured creates
information. However, the harvesting of more data from multiple
sources, coined as big data or huge data has led to challenges of
how best to interrogate and meaningfully manage often benign data
to support improved decision-making for greater impact. The
databases continuously storing the large amounts of data will
eventually become larger and larger over time and applying big
data analysis (BDA) approaches will be inevitable (Sivarajah et
al., 2017). BDA is the collection of data and technology that
accesses, integrates, and reports all available data by filtering,
correlating, and reporting insights not attainable with past data
technologies (APICS 2012) is seen as supporting more robust
decision-making.
A normative definition by International Data Corporation (IDC) -
2011, Big Data technologies1 describe a new generation of
technologies and architectures, designed to economically extract
value from very large volumes of a wide variety of data, by
enabling high velocity capture, discovery, and/or analysis. Not
surprisingly, academic and practitioner-based research continues
to explore the potential of Big Data. Added to this potential,
advances in Artificial Intelligence (AI) coming from the computer
science community and a burgeoning demand for skilled
professionals with creative minds, is seeing Big Data being
combined with Artificial Intelligence and reaching new heights of
discovery. Such a powerful combination is leading to new insights
in trending and prediction modelling using sophisticated machine
learning whether in finance (for market predictions), HR (for
workforce planning), Manufacturing (for predictive capacity
planning), Health (disease profiling) or Marketing (for consumer
behaviour modelling and consumption trending).
In the context of Technology and Organisational Resource
Management, Big Data and Business Analytics has the potential to
facilitate more sophisticated data-driven decision-making for
real-time business processes and new ways to organise and manage
data (including examining and processing data so that hidden
underlying patterns area revealed). We see this topic as being
topical to both public and private sector organisations and being
explored quantitatively and through mixed methods. The recent
successes in the area of Artificial Intelligence (with most
successful method - machine learning) are based on the rapid
processing of large amounts of data through BDA (Leonard, 2017;
Hernándeza et al., 2018). Nevertheless, Big Data and Artificial
Intelligence is still emerging with a potential impact considered
limitless (only by imagination). However, such impact is not
limited to commercial endeavours alone. The United Nations led the
world in identifying global challenges, which progressed from the
millennium development goals.
These new global challenges provide an opportunity for mankind
(including womankind) to unit around a common sense of challenge,
which will improve the world we all live-in and, share. This
Special Issue seeks to bring together normative applied research
that has a real impact on any of the UN Sustainable Development
Goals; where this impact is made possible using Big Data and
Artificial Intelligence. Clear alignment or association to with
the UN Sustainable Development Goals will need to be carefully
articulated in the submission along with the impact or
implications presented in the conclusions.
Special Issue Objective:
The proposed special issue seeks to present novel solutions to
improving the quality of life, for all. This special issue will
share related practical experience or insights to benefit society
and will provide clear evidence that Big Data and AI are playing
an ever-increasing role in improving the world we live in. The
Guest Editors seek scholarly research from the academic and
practitioner communities to look at how value can be created or
co-created with society for the benefit of society. The results
will in turn reveal the implications of Big Data and Artificial
Intelligence on progressing the UN Sustainable Development Goals.
Proposed Topics:
The topics to be discussed in this special issue include but are
not limited to the following:
ˇ Problem solving UN Sustainable Development Goals through BDA
and/or AI techniques.
ˇ Big Data analytics-enabled in innovation and creativity in
Business.
ˇ Big Data and AI to identify and manage complex business
decision-making.
ˇ Using Big Data in education and across Government.
ˇ Evaluating facilitators and inhibitors of Big Data
Analytics/Artificial Intelligence adoption.
ˇ In-depth and longitudinal case studies on Big Data initiatives
for enhancing Health and Wellbeing when set within UN Sustainable
Development Goals.
ˇ Application of Big Data Analytics for global business, trade and
development.
ˇ Privacy and trust issues in Big Data Analytics.
ˇ Influencing community practice through Social Media, Cloud
Computing and Big Data Analytics.
ˇ The dark sides of Big Data and Artificial Intelligence.
ˇ Approaches to leverage Big Data and AI to support
decision-making.
ˇ The unintended or unanticipated consequences of using Big Data
and Artificial Intelligence on impacting global challenges.
Submitting authors are advised to note that this is not a call for
Operational Research papers that will be desk rejected.
Manuscripts should apply the general author guidelines of the
Journal of Business Research (JBR)
(
https://www.elsevier.com/journals/journal-of-business-research/0148-2963/guide-for-authors).
Manuscripts should not have been previously published or be under
consideration by other journals and must explicitly state what is
unique and valuable about the paper within the context of
exploring Global Challenges.
Authors are asked to select 'Big Data and AI' as the submission
special issue.
All submissions should be through the official portal
(
https://www.journals.elsevier.com/journal-of-business-research)
when the initial screening will commence. For any queries
regarding submission, please contact
JBR@bradford.ac.uk<mailto:JBR@bradford.ac.uk>
All papers will be screened by at least two guest editors (and
desk rejected if not deemed suitable) before then being sent to at
least two referees. Papers will undergo multiple rounds of
revision, as necessary and in line with the customary practice and
standards of JBR. There is no guarantee of publication.
References:
APICS (2012). APICS 2012 Big Data Insights and Innovations
Executive Summary.
Hernándeza, Á.B., Perez, M.S., Gupta, S., Muntés-Mulero, V.
(2018). Using machine learning to optimize parallelism in big data
applications, Future Generation Computer Systems, 86,1076-1092.
Leonard, F. (2017). Big Data and Artificial Intelligence,
Intellectual Property Journal, 9(3), 288-298.
Nadkarni, A. and Vesset, D. (2016). Worldwide Big Data Technology
and Services Forecast, 2016-2020, International Data Corporation,
IDC.
Sivarajah, U., Kamal, M.M., Irani, Z. and Weerakkody, V. (2017).
Critical Analysis of Big Data Challenges and Analytical Methods,
Journal of Business Research, 70, 263-286.
Kind Regards
Kamal
Dr Muhammad Mustafa Kamal (BBA, MCS, OCP 'DBA', MSc DCS, PhD,
FHEA)
Director of Undergraduate Studies
Director of Alumni
UG Business and Management - General Pathway Leader
Senior Lecturer in Operations and Supply Chain Management
T: +44 (0) 1895 267728 | F: +44 (0) 1895 269775 | Twitter:
@muhammadmkamal
Office: Room 217, 2nd Floor, Eastern Gateway Building
Brunel University London
Brunel Business School
Brunel University London, Uxbridge, UB8 3PH, United Kingdom
T +44(0)1895 274000
www.brunel.ac.uk<http://www.brunel.ac.uk/>
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