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Engineering - Computational Intelligence and Complexity | An Intelligent Customer Complaint Management System with Application to the Transport and Logistics Industry

An Intelligent Customer Complaint Management System with Application to the Transport and Logistics Industry

Series: Springer Theses

Faed, Alireza

2013, XXII, 349 p. 98 illus., 11 illus. in color.

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  • Nominated as an outstanding PhD thesis by Curtin University, Australia
  • Offers a comprehensive survey of the current literature on CRM systems, including the most recent academic research on this topic and its current challenges and gaps
  • Describes a novel intelligent customer relationship management that not only categorizes and analyses customer complaints, but also evaluates customer satisfaction thus helping to convert customer complaints and dissatisfaction into future business development strategies

This thesis addresses the issue of customer complaints in the context of Customer Relationship Management (CRM). Following a comprehensive survey of the current literature on CRM, it describes the development of a new intelligent CRM (I-CRM) framework, which integrates in a single approach different innovative analytical methods. Unlike conventional approaches, this new methodology can handle customer complaints with respect to different variables, thus allowing organizations to find their key customers and key complaints, and to address and provide solutions for their major complaints, hence promoting business development. The  thesis also describes the successful application of the method to a real-world  case: the virtually immeasurable number of complaints from truck drivers at the  port city Fremantle in Western Australia.

Content Level » Research

Keywords » Customer complaint categorization - Customer satisfaction analysis - Intelligent CRM - Logistics Operators - Neuro-Fuzzy Systems - Perceived value and interactivity - Statistical complaint analysis - Text mining analysis

Related subjects » Business Information Systems - Computational Intelligence and Complexity - Production & Process Engineering

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