Handbook of Research on Intelligent Techniques and Modeling Applications in Marketing Analytics Front Cover

Handbook of Research on Intelligent Techniques and Modeling Applications in Marketing Analytics

Description

“This book features innovative research and implementation practices of analytics in marketing research, highlighting various techniques in acquiring and deciphering marketing data”–

Table of Contents

Section 1: Consumer Analytics: Fuzzy Applications
Chapter 1: A New Perspective on RFM Analysis
Chapter 2: A Novel Approach to Segmentation Using Customer Locations Data and Intelligent Techniques
Chapter 3: Fuzzy Clustering
Chapter 4: An Analysis of the Interactions among the Enablers of Information Communication Technology in Humanitarian Supply Chain Management

Section 2: Computational Intelligence: Business Analytics
Chapter 5: Auto Associative Extreme Learning Machine Based Hybrids for Data Imputation
Chapter 6: Multi-Criteria Decision Making in Marketing by Using Fuzzy Rough Set
Chapter 7: Fuzzy Multi-Objective Association Rule Mining Using Evolutionary Computation
Chapter 8: Improved Seating Plans for Movie Theatre to Improve Revenue

Section 3: Consumer Analytics: Multi-Criteria (MCDM) Applications and Sentiment Analysis
Chapter 9: Applications of the Stochastic Multicriteria Acceptability Analysis Method for Consumer Preference Study
Chapter 10: Modeling Consumer Opinion Using RIDIT and Grey Relational Analysis
Chapter 11: Sentiment Analysis as a Tool to Understand the Cultural Relationship between Consumer and Brand
Chapter 12: Improving Customer Experience Using Sentiment Analysis in E-Commerce

Section 4: Marketing Analytics: Digital Market Place
Chapter 13: Adoption of Online Marketing for Service SMEs with Multi-Criteria Decision-Making Approach
Chapter 14: E-Retailing from Past to Future
Chapter 15: Fuzzy Time Series
Chapter 16: Understand the Frequency of Application Usage by Smartphone Users

Section 5: Advanced Modelling Applications: Business Analytics
Chapter 17: Car Safety
Chapter 18: Banking Credit Scoring Assessment Using Predictive K-Nearest Neighbour (PKNN) Classifier
Chapter 19: Prediction of the Quality of Fresh Water in a Basin
Chapter 20: Operating Commodities Market by Automated Traders

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