Business analytics: an application focus
Material type:
TextPublication details: New Delhi PHI Learning Pvt. Ltd. 2022 Description: xiv, 238 pISBN: 9788120348196Subject(s): Business planning | Business--Decision making | Commercial statistics | Industrial management--Statistical methods | Strategic planningDDC classification: 658.15 Summary: Business Analytics refers to various categories of analytical approaches for modelling different business situations and arriving at solutions and strategies for optimal decision-making in marketing, finance, operations, organizational behaviour and other managerial processes. Thus, Business Analytics today refers to different approaches for modelling and arriving at assessing and predicting risk, predicting market preferences, project feasibility, customer segmentation, inherent and underlying dimensions in consumer preferences, factors leading to probability of purchase, preferred segments in financial and credit card industry, probability of attrition in large organizations, etc.
The myriad of modelling and other analytical approaches which constitute Business Analytical applications in Indian Industry today include predominantly:
• Determining which attributes in a product are considered significant by the market and which are found to be significantly satisfactory—Gap Analysis.
• Analytical Modelling by Factor and Cluster Analysis.
• Analytical Modelling by Logistics Regression and Discriminant Analysis.
• Segmentation of primary target market by Heuristic Modelling such as RFM (recency, frequency, monetary) analysis.
• Segmentation of target market based on large databases using Decision Tree approaches such as CHAID (Chi-square Automatic Interaction Detection) and other Classification and Regression Trees.
• Determining Linkages between unobserved constructs such as customer satisfaction and factors leading to it, using Structural Equation Modelling (SEM).
• Determining relative preferences in consumer perceptions by Conjoint Analysis.
In this book, the author has discussed these analytical approaches following a classroom teaching format, drawing from her extensive teaching experience spanning over 30 years. The book first discusses all important concepts and then case studies are discussed which emulate real-life managerial situations.
This textbook is designed to serve the needs of management students for a course in Business Analytics.
| Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|---|
Book
|
Indian Institute of Management LRC General Stacks | Marketing | 658.15 RAO (Browse shelf(Opens below)) | 1 | Available | 004119 |
Table of content
1. Gap Analysis
2. Factor Analysis
3. Concepts of Cluster Analysis
4. Linear Discriminant Analysis
5. Logistics Regression
6. Predictive Modelling and RFM Analysis
7. Decision Tree Approach with CHAID
8. Structural Equation Modelling
9. Conjoint Analysis
Case Study I Medical Treatment
Case Study II Brand Loyalty of Sport Drinks in Italian Market
Case Study III Conjoint Analysis Application on Credit Card Industry
Index
Business Analytics refers to various categories of analytical approaches for modelling different business situations and arriving at solutions and strategies for optimal decision-making in marketing, finance, operations, organizational behaviour and other managerial processes. Thus, Business Analytics today refers to different approaches for modelling and arriving at assessing and predicting risk, predicting market preferences, project feasibility, customer segmentation, inherent and underlying dimensions in consumer preferences, factors leading to probability of purchase, preferred segments in financial and credit card industry, probability of attrition in large organizations, etc.
The myriad of modelling and other analytical approaches which constitute Business Analytical applications in Indian Industry today include predominantly:
• Determining which attributes in a product are considered significant by the market and which are found to be significantly satisfactory—Gap Analysis.
• Analytical Modelling by Factor and Cluster Analysis.
• Analytical Modelling by Logistics Regression and Discriminant Analysis.
• Segmentation of primary target market by Heuristic Modelling such as RFM (recency, frequency, monetary) analysis.
• Segmentation of target market based on large databases using Decision Tree approaches such as CHAID (Chi-square Automatic Interaction Detection) and other Classification and Regression Trees.
• Determining Linkages between unobserved constructs such as customer satisfaction and factors leading to it, using Structural Equation Modelling (SEM).
• Determining relative preferences in consumer perceptions by Conjoint Analysis.
In this book, the author has discussed these analytical approaches following a classroom teaching format, drawing from her extensive teaching experience spanning over 30 years. The book first discusses all important concepts and then case studies are discussed which emulate real-life managerial situations.
This textbook is designed to serve the needs of management students for a course in Business Analytics.
There are no comments on this title.