[AISWorld] CFP for Journal of Business Research - Using Big Data and Artificial Intelligence in Business to Impact Global Challenges

[Muhammad Kamal]

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:


·         Problem solving UN Sustainable Development Goals through BDA and/or AI techniques.

·         Big Data analytics-enabled in innovation and creativity in Business.

·         Big Data and AI to identify and manage complex business decision-making.

·         Using Big Data in education and across Government.

·         Evaluating facilitators and inhibitors of Big Data Analytics/Artificial Intelligence adoption.

·         In-depth and longitudinal case studies on Big Data initiatives for enhancing Health and Wellbeing when set within UN Sustainable Development Goals.

·         Application of Big Data Analytics for global business, trade and development.

·         Privacy and trust issues in Big Data Analytics.

·         Influencing community practice through Social Media, Cloud Computing and Big Data Analytics.

·         The dark sides of Big Data and Artificial Intelligence.

·         Approaches to leverage Big Data and AI to support decision-making.

·         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 at bradford.ac.uk<mailto:JBR at 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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