Special Issue on: The Next ‘Deep’ Thing in X to Z Marketing: An Artificial Intelligence Driven Approach
Historically, marketing departments have relied on data analytics and key performance
indicators to measure their progress towards revenue generation and customer growth targets.
Today, however, such undertakings are challenged by overwhelming amounts of data,
complex environments, increased competitive pressures, and rapidly changing customer
behaviors. At the same time, the explosion in digital technologies has opened unprecedented
opportunities for the mining of new insights into customer needs and behaviors (from
individuals to corporations and governments). Artificial intelligence techniques are tools that can be used to process large data sets and
uncover hidden knowledge, enabling organisations to deliver, in real-time, even more
significant contributions to revenue growth, while strengthening customer relationships in the
process. Although some attempts have already been made to explore the impact of artificial
intelligence on marketing strategies, processes, and practices, more research is needed to
unpack their full potential and implications for practice. Used suitably, such tools, and in
particular ‘deep learning’ models, can become a source of competitive advantage to
understand, anticipate, predict, and act faster than competitors. Among others, they can help
organisations to (a) improve their understanding of their target consumers; (b) know
consumers on a deeper level, (c) understand how the interactions with consumers can be
optimised; (d) foster marketing personalisation for the individual consumer; (e) design products
that meet consumers’ personal needs; and (f) automate simple, yet time-consuming tasks,
boosting productivity. In a nutshell, artificial intelligence has the potential to revolutionise the
activity of marketing.
This Special Issue welcomes original research papers of high quality that focus on novel ways
of using artificial intelligence techniques to derive innovative insights that can streamline
marketing processes and make businesses more effective. Empirical research studies and
interdisciplinary research that addresses challenging and emerging issues in the area of X to
Z MARKETING (e.g. B2B, B2C, C2B, C2C, B2E, B2G etc.) are of considerable interest.
Contributions from both the academic and the practitioner communities are encouraged.
Topics and areas of submission include, but are not limited to:
Forms of Submission
This Special Issue will consist of 1) the best submissions from an open Call for Papers,
selected on a competitive basis; and 2) invited papers that are extended or modified versions
of selected papers accepted at the following venues i) AMCIS2020 - Minitrack 2: Big Data for
Business and Societal Transformation, ii) BAM2020 - Track: e-Business and e-Government,
iii) IFIP WG8.6 Working Conference (Tracks on AI and on Social Media), iv) IEEE CBI2020 –
Track on Information Management
In the latter case, the submission will be a substantial revision of the conference publication
and the authors will be required to submit a letter detailing the difference between their
conference paper and the new version. All submitted papers and invited papers will go through
peer review; if an invited conference paper does not receive a satisfactory review, the paper
will not be considered for the Special Issue.
Submission Instruction
Manuscripts must be submitted in PDF format to the ISF-Springer online submission system
at http://www.editorialmanager.com/isfi/. Paper submissions must conform to the format
guidelines of Information Systems Frontiers available at
http://www.springer.com/business/business+information+systems/journal/10796.
Submissions should be approximately 32 pages double spaced including references.
Important dates
Submission deadline: 30 March 2021
Notification of first-round reviews: 30 May 2021
Revised manuscripts due: 15 July 2021
Notification of second-round reviews: 30 September 2021
Final version due: 15 November 2021
Guest Editors
Vincent Charles, University of Bradford, UK, c.vincent3@bradford.ac.uk
Nripendra P. Rana, University of Bradford, UK, n.p.rana@bradford.ac.uk
Ilias O. Pappas, University of Agder, Norway, ilias.pappas@uia.no
Morten Kamphaug, Digital Executive Advisor, IBM, morten.kamphaug@ibm.com
Keng Siau, Missouri University of Science and Technology, USA, siauk@mst.edu
Kenth Engø-Monsen, Senior Research Scientist, Telenor Research, kenth.engomonsen@telenor.com