A knowledge-based service automation system for service logistics

Chi Fai Cheung, Y. L. Chan, S. K. Kwok, Wing Bun Lee, W. M. Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

25 Citations (Scopus)

Abstract

Purpose - Effective service logistics can lower the cost and increase service value by improving customer satisfaction and loyalty. However, the conventional ways of the service logistics are information driven instead of knowledge-driven which are insufficient to meet the current needs. The purpose of this paper is to present a knowledge-based service automation system (KBSAS) to enhance the competitiveness for manufacturing enterprises in service logistics. Design/methodology/approach - The KBSAS incorporates various artificial intelligence technologies such as case-based reasoning which is used for achieving four perspectives of knowledge acquisition, service logistics, service automation and performance measurement, respectively. Findings - A prototype customer service portal has been built based on the KBSAS and implemented successfully in a semi-conductor equipment manufacturing company. It is verified that the KBSAS provides high quality customer services with fast and efficient customer responses. It also allows the company to capture the valuable experience and tacit knowledge of the staff in performing customer and field services. Practical implications - The KBSAS yields a number of advantages over conventional service logistics which include streamlining the service logistics process; performance measurement; reduction of paper work; the provision of 24 hours worldwide automatic customer service supported by the verified knowledge base established in the date time operations as well as the driving for continuous improvement of customer service quality. Originality/value - The paper presents the development and successful implementation of a KBSAS which allows for the capture of the valuable experience and tacit knowledge of the staff in performing customer and field services.
Original languageEnglish
Pages (from-to)750-771
Number of pages22
JournalJournal of Manufacturing Technology Management
Volume17
Issue number6
DOIs
Publication statusPublished - 7 Aug 2006

Keywords

  • Artificial intelligence
  • Customer relations
  • Customer service management
  • Knowledge management

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Science Applications
  • Strategy and Management
  • Industrial and Manufacturing Engineering

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