Enhancing Service Quality: A Total Quality Management Approach in a South African Company

A. S. Mncube, N. Sukdeo, S. C. Mukwakungu, C. Mbohwa

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper examines key factors for effective Total Quality Management (TQM) implementation in service industries and investigates the resulting benefits. Utilizing a mixed-methods approach, data were collected via questionnaires and interviews with top management, supervisors, employees, and customers of a South African service company. Results show that most TQM principles were practiced in the organization, but full benefits were not realized due to limited top management commitment and low staff awareness of TQM principles. Recommendations include consistent customer feedback collection, clear communication of short- and long-term objectives to employees, and provision of necessary training resources. Implementing these suggestions will enable the company and other organizations (both service and manufacturing) to fully benefit from TQM and maintain a competitive edge in the market.

Original languageEnglish
Title of host publication2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1768-1772
Number of pages5
ISBN (Electronic)9798350323153
DOIs
Publication statusPublished - 2023
Event2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023 - Singapore, Singapore
Duration: 18 Dec 202321 Dec 2023

Publication series

Name2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023

Conference

Conference2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023
Country/TerritorySingapore
CitySingapore
Period18/12/2321/12/23

Keywords

  • Customer satisfaction
  • Service Quality
  • Service industry
  • Total Quality Management

ASJC Scopus subject areas

  • Artificial Intelligence
  • Decision Sciences (miscellaneous)
  • Statistics, Probability and Uncertainty
  • Industrial and Manufacturing Engineering
  • Modeling and Simulation
  • Strategy and Management

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