Calls for papers


International Journal of Spatio-Temporal Data Science
International Journal of Spatio-Temporal Data Science


Special Issue on: "Big Data Analytics: Applications and Applicability in Management"

Guest Editors:
Prof. Dr. Samia Chehbi-Gamoura, Strasbourg University, France
Prof. Dr. Halil-Ibrahim Koruca, Süleyman Demirel University, Turkey

Big data analytics (BDA) is the new scientific field that gathers all analytic approaches for the processing of the huge amounts of data by extracting hidden insights that could not be attainable with the traditional approaches.

In management, the key use of BDA by organizations is to acquire significant information that allows them to better assess, forecast, discover unknown patterns, and then improve their competitiveness. Indeed, the advanced analytics approaches in BDA are mutating the way, the management of several processes is performed. This mutation is affecting the companies both internally through changing transactional information systems, and externally through integrating new data sources from social media, mobile technologies, Internet of Things (IoT), and so forth. Moreover, BDA is an emerging paradigm as the "next big thing" in management. Scholars have gone so far as suggesting that BDA is the "next management revolution", and thus generating huge attention from both practitioners and academics.

Besides, these mutations hold new openings and business opportunities, but also reveal unexpected new challenges for creating new business models and altering existing operations. Actually, the Big Data projects have become today fastidious task for enterprises and need expertise skills in customized business processes. Furthermore, multiple surveys divulge today that only 48 percent Big Data initiatives had accomplished assessable outcomes. Obviously, the companies are facing major dares, when they come to deploying their BDA approaches.

Beyond considering the return on an investment in catching value from BDA, the businesses are also concentrating on how this new generation of analytics might be applied to get the most significant insights in management. Given the high number and complexity of the range covering analytic approaches including Artificial Intelligence, Machine Learning, Business Intelligence, Data Mining to be applied for prescriptive, predictive, diagnostic, and descriptive business, this task is not slight and may be very challenging.

The objective of this special issue is to fill this knowledge gap. Specifically, this special issue aims to invite scholars and practitioners to look at the ways and means to identify and capture business value from BDA in terms of innovative business models, improved decisions making, improved intra-and inter-organizational performance, and competitive advantage. In addition, it provides an opportunity for academics to investigate on how different advanced analytics approaches can be applied on emerging challenges in management under the era of Big Data.

Subject Coverage
Suitable topics include, but are not limited, to the following:

  • Data Analytics and Data Science
  • Cloud Data Analytics
  • Web Analytics
  • Blockchain and analytics in management
  • Cognitive management
  • Management in Industry 4.0
  • Management in smart manufacturing
  • Proactive and predictive management
  • Collective management under the era of Big Data
  • Strategic management and Big Data Analytics
  • Knowledge management and Big Data Analytics
  • Operational management and Big Data Analytics
  • Supply chain management and Big Data Analytics
  • Business process management and Big Data analytics
  • Business intelligence under the era Big Data
  • Data mining under the era Big Data
  • Mutations in management in the era of Big Data
  • Collaborative management in the era of Big Data
  • Big Data Analytics in accounting operations
  • Big Data analytics and marketing
  • Big Data analytics and sales
  • Big Data analytics and customer management
  • Big Data analytics and supplier management
  • Analytics in business operations
  • Information systems mutations in the era of Big Data analytics
  • Artificial intelligence in management
  • Machine Learning and Deep learning in management
  • Advanced analytics in management
  • Big Data-based analytics
  • Decision-making processes in operations under the era of Big Data
  • Collaborative external tools for the business performance
  • Digital transformation and business process management
  • Knowledge transfer processes and Big Data Analytics
  • Re-shaping business processes through strategic collaborations
  • Cloud Support for Time Series Data Analytics
  • Big data analytics adoption in management
  • Big Data analytics in financial management
  • Big Data analytics in Human Resources management
  • Big Data analytics and manufacturing

Notes for Prospective Authors

Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper has been completely re-written and if appropriate written permissions have been obtained from any copyright holders of the original paper).

All papers are refereed through a peer review process.

All papers must be submitted online. To submit a paper, please read our Submitting articles page.

Important Dates

Manuscripts due by: 31 December, 2020

Notification to authors: 31 March, 2021

Final versions due by: 30 June, 2021