"This book explores the possibilities and advantages created by fuzzy methods through the presentation of thorough research and case studies"--Provided by publisher.

"This book explores the possibilities and advantages created by fuzzy methods through the presentation of thorough research and case studies"--Provided by publisher.

"This book explores the possibilities and advantages created by fuzzy methods through the presentation of thorough research and case studies"--Provided by publisher.

This book introduces a fuzzy classification approach, which combines relational databases with fuzzy logic for more effective and powerful customer relationship management (CRM). It shows the benefits of a fuzzy classification in contrast to the traditional sharp evaluation of customers for the acquisition, retention and recovery of customers in online shops. The book starts with a presentation of the basic concepts, fuzzy set theory and the combination of relational databases and fuzzy classification. In its second part, it focuses on the customer perspective, detailing the central concepts of CRM, its theoretical constructs and aspects of analytical, operational and collaborative CRM. It juxtaposes fuzzy and sharp customer classes and shows the implications for customer positioning, mass customization, personalization, customer assessment and controlling. Finally, the book presents the application and implementation of the concepts in online shops. A detailed case study presents the application and a separate chapter introduces the fuzzy Classification Query Language (fCQL) toolkit for implementing these concepts. In its appendix the book lists the fuzzy set operators and the query language’s grammar.

To enhance marketing analytics, approximate and inductive reasoning can be applied to handle uncertainty in individual marketing models. This book demonstrates the use of fuzzy logic for classification and segmentation in marketing campaigns. Based on practical experience as a data analyst and on theoretical studies as a researcher, the author explains fuzzy classification, inductive logic and the concept of likelihood and introduces a blend of Bayesian and Fuzzy Set approaches, allowing reasonings on fuzzy sets that are derived by inductive logic. By application of this theory, the book guides the reader towards a gradual segmentation of customers which can enhance return on targeted marketing campaigns. The algorithms presented can be used for visualization, selection and prediction. The book shows how fuzzy logic can complement customer analytics by introducing fuzzy target groups. This book is for researchers, analytics professionals, data miners and students interested in fuzzy classification for marketing analytics.

This book presents recently developed intelligent techniques with applications and theory in the area of engineering management. The involved applications of intelligent techniques such as neural networks, fuzzy sets, Tabu search, genetic algorithms, etc. will be useful for engineering managers, postgraduate students, researchers, and lecturers. The book has been written considering the contents of a classical engineering management book but intelligent techniques are used for handling the engineering management problem areas. This comprehensive characteristics of the book makes it an excellent reference for the solution of complex problems of engineering management. The authors of the chapters are well-known researchers with their previous works in the area of engineering management.

This volume advocates accurate case outcome prediction that does not rely on symmetric modeling. To that end, it provides theory construction and testing applications in several sub-disciplines of business and the social sciences to illustrate how to move away from symmetric theory construction. Each chapter constructs case outcome theory and includes empirical analysis of outcomes. Chapter 1 provides a foundation of symmetric variable directional-relationship theory construction and null hypothesis significance testing versus asymmetric case outcome theory construction and somewhat precise outcome testing, while Chapters 2–6 investigate these principles through a range of applications. This volume will be very useful to researchers and professionals in manufacturing, service, consulting, management, marketing, organizational studies, and more. It will also be an excellent resource for advanced statistics students in building and testing case outcome models. Data sets are included so that readers can replicate findings presented in each chapter, and grow to present and test additional theories.