Investigating the impact of hard total quality management practices on operational performance in manufacturing organizations

Abstract

PurposeThe purpose of this paper is to investigate the impact of hard total quality management (TQM) practices on operational performance dimensions in manufacturing organizations.Design/methodology/approachThe study was designed in the Jordanian manufacturing sector. Organizations that are familiar with hard TQM practices specifically that had already implemented ISO 9001 certificate were randomly surveyed through structured questionnaire, yielded a sample of 40 responding organizations. Principal component factor analysis was used to analyze hard TQM practices implementation and organizations operational performance dimensions. As a result, specific hard TQM practices and operational performance dimensions were extracted. The hard TQM practices that significantly influence operational performance dimensions were tested using simple and multiple linear regression analysis.FindingsThe research findings showed that hard TQM practices in manufacturing sector include; continuous improvement, statistical process control (SPC), process management and quality tools and techniques. Meanwhile, operational performance dimensions include; quality and inventory management performance. Also, the findings showed that continuous improvement and SPC practices play a major role in obtaining the desired results of operational performance.Research limitations/implicationsThree limitations can be identified in this research, using subjective measures of TQM practices and operational performance, low response rate and using a sample of organizations from various industries. This paper can help Jordanian manufacturing organizations to foster proper practices and make the right decisions related to operational performance.Originality/valueThis study describes a reliable hard TQM model that can be used by manufacturing organizations to improve their operational performance. Also, the results of this study contribute to prior literature and recommend some best practices for manufacturing organizations.