A meta-analysis of quality measures in manufacturing system

Purpose - The manufacturing community has embraced the concept of total quality management (TQM) but little research has been published on how each aspect of quality is measured. This paper provides a deeper understanding of current quality measures and recommendations for appropriate TQM practices. This article adopts meta-analysis approach to study issues concerning reliability of TQM measures and find consensus on the relationship between TQM practices and organizational performance across studies. The research findings and managerial implications are discussed.Design methodology approach - A meta-analysis approach was used to study 421 items relating to TQM practices in 50 refereed articles.Findings - Items were categorized according to Malcolm Baldrige National Quality Award (MBNQA) categories. A total of 77 items were not matched and eliminated. Findings reveal that the mean value of reliability coefficients (α) is 0.84 in TQM research compared to 0.77 in marketing and 0.81 in MIS. The mean values of α are significantly different across studies based on years and nations. The mean values of α from the nations of North America, South America, Africa, and Asia are significantly higher than those of Europe and Australia. Top management support shows the highest mean effect size of the relationship between TQM practices and organizational performance compared to other relationships.Originality value - Meta-analysis is used to enhance the understanding, applicability, and generalizability of a comparable research with diverse results. It does not require the original data. Using data from already published TQM research, meta-analysis can be used to improve the understanding of current TQM issues manufacturing firms are facing.