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Business Analytics
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Business Analytics
Solving Business Problems With R



January 2024 | 344 pages | SAGE Publications, Inc
Businesses typically encounter problems first and then seek out analytical methods to help in decision making. Business Analytics: Solving Business Problems with R by Arul Mishra and Himanshu Mishra offers practical, data-driven solutions for today's dynamic business environment. This text helps students see the real-world potential of analytical methods to help meet their business challenges by demonstrating the application of crucial methods. These methods are cutting edge, including neural nets, natural language processing, and boosted decision trees. Applications throughout the book, including pricing models, social sentiment analysis, and branding show students how to use these analytical methods in real business settings, including Frito-Lay, Netflix, and Zappos. Step-by-step R code with commentary gives readers the tools to adapt each method to their business settings. The book offers comprehensive coverage across diverse business domains, including finance, marketing, human resources, operations, and accounting. Finally, an entire chapter explores equity and fairness in analytical methods, as well as the techniques that can be used to mitigate biases and enhance equity in the results.

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Part 1. Business Environment Analytics
 
Chapter 1: The external environment of a business
 
Chapter 2: Monitoring the Macroeconomic Environment
 
Chapter 3: Monitoring the Competitive Environment using Principal Component Analysis
 
Chapter 4: Monitoring the Social Environment using Text Analysis
 
Part 2. Marketing Analytics
 
Chapter 5: Market Segmentation using Clustering Algorithms
 
Chapter 6: Predicting Price with Neural Nets
 
Chapter 7: Advertising and Branding with A/B Testing
 
Chapter 8: Customer Analytics using Neural Nets
 
Part 3. Financial and Accounting Analytics
 
Chapter 9: Loan Charge-off Prediction using an Explainable Model
 
Chapter 10: Analyzing Financial Performance with LASSO
 
Chapter 11: Forensic Accounting using Outlier Detection Algorithms
 
Part 4. Operations and Supply Chain Analytics
 
Chapter 12: Predicting Decision Uncertainty using Random Forests
 
Chapter 13: Predicting Employee Satisfaction using Boosted Decision Trees
 
Chapter 14: New Product Development with A/B Testing
 
Part 5. Business Ethics and Analytics
 
Chapter 15: Fairness in Business Analytics
 
Part 6. Technical Appendix

I could not access the book. It is shown in the cart, but I cannot do anything about it. So, no chance to review the book. Your system seems to have a problem.

Professor Dohoon Kim
Management, Kyung Hee University - Yongin
January 16, 2025
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