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International Journal of Business Analytics (IJBAN) Volume 3, Issue 1

Book Description

The International Journal of Business Analytics (IJBAN) is an indispensable resource for practitioners and academics that work in Business Analytics and related fields. Business Analytics is commonly viewed from three major perspectives: descriptive, predictive, and prescriptive. Business Analytics provides the framework to exploit the synergies among traditionally-diverse topics, such as the fields of data mining, quantitative methods, OR/MS, DSS, and so forth, in a more practical, application-driven format. The journal bridges the gap among different disciplines such as data mining, business process optimization, applied business statistics, and business intelligence/information systems. The journal supports and provides tools to allow companies and organizations to make frequent, faster, smarter, data-driven, and real-time decisions.

This issue contains the following articles:

  • A Prescriptive Stock Market Investment Strategy for the Restaurant Industry using an Artificial Neural Network Methodology
  • An Expanded Assessment of Data Mining Approaches for Analyzing Actuarial Student Success Rate
  • Loss Profit Estimation Using Temporal Association Rule Mining
  • Social Media Mining: A New Framework and Literature Review