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. Samia Chehbi-Gamoura, Prof. Ridha Derrouiche and Prof. Yuan Yao, Strasbourg University, France


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

In management, the key use of BDA by organisations is to acquire significant information that allows them to better assess, forecast and discover unknown patterns, and to then improve their competitiveness. Indeed, advanced analytics approaches in BDA are changing the way the management of several processes is performed. This change is affecting 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 that representes the "next big thing" in management. Scholars have gone so far as to suggest that BDA is the "next management revolution", and it is thus generating significant attention from both practitioners and academics.

These changes offer new openings and business opportunities, but also raise unexpected new challenges for creating new business models and altering existing operations. Actually, big data projects have become demanding tasks for enterprises, and require expert skills in customised business processes. Furthermore, multiple surveys have divulged that today only 48 percent of big data initiatives have accomplished assessable outcomes. It’s clear that companies are facing major challenges when it comes to deploying their BDA approaches.

Beyond considering the return on an investment in getting value from BDA, businesses are also concentrating on how this new generation of analytics might be applied to get the most significant insights in management. Given the size and complexity of the range covering analytic approaches - including artificial intelligence, machine learning, business intelligence and data mining - that can 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 invites 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 decision making, improved intra-and inter-organisational performance, and competitive advantage. In addition, it will provide an opportunity for academics to investigate how different advanced analytics approaches can be applied to emerging challenges in management in 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 in 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 in the era of big data
  • Data mining in the era of big data
  • Changes 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 system changes 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 in the era of big data
  • Collaborative external tools for 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 resource 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: 30 September, 2019

Notification to authors: 30 December, 2019

Final versions due by: 15 April, 2020