A Holistic Approach to Quality Management on the Performance of Manufacturing Firms

Quality management is a type of management philosophy characterized by its principles, practices and techniques. Quality management emphasizes issues such as continuous improvement, increased employee involvement, teamwork, process orientation, competitive benchmarking, committed leadership, and accurate and consistent measurement of results. The role of quality management practices in gaining the competitive advantage of manufacturing firms is significant. Therefore the purpose of this study is to investigate the role of quality management practices on the manufacturing firms' performance with a holistic approach. The population of this study includes manufacturing firms in Tehran and the sample size is 245 people. Structural Equation Modelling was used to test the hypothesized relationship between quality management practices and manufacturing firms' performance. The hypotheses of this study include two general categories of a) relationships between quality management practices with each other (19 hypotheses) and b) relationships between quality management practices with performance (5 hypotheses). Out of 19 hypotheses in Section A, 18 hypotheses were confirmed. This means that there is a positive and significant relationship between the variables of leadership style, quality policy, quality control department, training, customer focus, supplier quality management, quality information and analysis. All the hypotheses of Section B were also confirmed. This means that the variables of employee relations and process management have a positive and significant effect on the performance of manufacturing and non-manufacturing sectors. In general, quality management practices affect the performance of production and non-production sectors through influencing the variables of employee relations and process management. Also, the demographic variables of gender, age, education, years of service, job position, and industry type have an effect on some of the eleven study variables.