Calls for papers

 

International Journal of Data Analysis Techniques and Strategies

 

Special Issue on: "Business Intelligence Applications to Decision-Making"

Guest Editor:
Dr. Rashmi Malhotra, Saint Joseph’s University, USA

Organisations use business intelligence (BI) techniques to enhance decision-making, improve or re-engineer business processes, cut costs and identify new business opportunities. Typically, BI mainly refers to computer-based techniques used to identify, extract and analyse business data to support superior business decision-making. Business intelligence includes set of applications to collect, store and analyse raw data to enable managers to make sound decisions in a business enterprise.

BI is a growing discipline that includes several activities related to decision-making such as querying, data mining, online analytical processing, forecasting, benchmarking and predictive analytics, to name a few. Business intelligence is an umbrella term that refers to the technologies that support better management of an enterprise through informed decision-making. BI is not just reporting. It offers an analytical, predictive view of an organisation using its enterprise architecture platform to allow managers to compete and survive in the modern business environment.

It’s only recently that organisations have started to include business intelligence as an integral part of their mission and to devise BI strategies at the enterprise-wide level. As a result, there is a great demand for research focused on the use and application of BI techniques that go beyond traditional reporting and modelling tools.

This special issue addresses the latest research in the area of business intelligence to benefit researchers and managers alike by publishing any efforts to

1. illustrate new trends in BI applications that go far beyond traditional decision support applications
2. support better decision-making that involves more than reporting or sets of tools to glean data from corporate databases to incorporate business analytics.

The papers in this issue aim to represent the latest research ideas in the area of BI to provide performance metrics, tools and techniques for enterprise management.

We welcome theoretical and empirical papers, and interesting case studies that are within the scope of the issue. The issue will contain invited papers and papers submitted directly as per the instructions below. If the number of accepted papers is more than that needed for the special issue, some papers will appear in a regular issue of IJDATS.

Subject Coverage
Topics of interest include but are not limited to:

• Artificial intelligence applications to business decision-making, such as neural networks, genetic algorithms, fuzzy systems and swarm intelligence
• Benchmarking
• Data mining
• Enterprise performance management
• Knowledge discovery and management systems
• Online analytical processing
• Predictive analysis
• Text mining

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 was not originally copyrighted and if it has been completely re-written).

All papers are refereed through a peer review process. A guide for authors, sample copies and other relevant information for submitting papers are available on the Author Guidelines page.

Important Dates

Submission due date of full paper: 31 August, 2012 (extended)

Feedback from referees: 5 September, 2012

Submission due date of revised paper: 30 September, 2012

Notification of acceptance: 1 November, 2012

Submission of final revised paper: 25 November, 2012