Quality management and organizational context in selected service industries of China

Xiande Zhao, Cheong Leung Yeung, T. S. Lee

Research output: Journal article publicationJournal articleAcademic researchpeer-review

100 Citations (Scopus)

Abstract

By developing an empirical taxonomy of quality management systems (QMS) in selected service industries in China, we compare the taxonomy of QMS developed in the service industries to that found in previous studies in manufacturing industries. We further investigate contingency relationships between the development of a QMS and its organizational contexts. Based on cluster analyses of quality management practices measured by the Malcolm Baldrige National Quality Award (MBNQA) criteria, we found four patterns of service quality management practices: undeveloped, accommodating, strategic, and soft quality systems. Our research indicates that the type of quality system adopted by an organization is highly associated with organizational contextual factors. Our results indicate that environmental uncertainty shapes the development of a QMS in the early stage, while the perceived importance of quality induces the further development of a QMS to a strategic quality system. The results also show that small service firms that compete locally can achieve very good performance results using a soft quality system, a QMS with no formal process management systems. This research provides empirical evidence on contingent relationships among quality management practices, organizational context, and business performance, thus contributing to contingency theory in quality management.
Original languageEnglish
Pages (from-to)575-587
Number of pages13
JournalJournal of Operations Management
Volume22
Issue number6
DOIs
Publication statusPublished - 1 Dec 2004

Keywords

  • Business results
  • Empirical taxonomy
  • Organizational context
  • Quality management

ASJC Scopus subject areas

  • Computer Science Applications
  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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