Effectiveness of Total Quality Management and Product Quality Implementation in Improving Company Operational Performance
Contributors
Dewi Nuraini
Keywords
Proceeding
Track
General Track
License
Copyright (c) 2026 International Seminar and Conference on Management, Research, and Transformation (I-SMART)

This work is licensed under a Creative Commons Attribution 4.0 International License.
Abstract
This research aims to assess how effectively Total Quality Management (TQM) and product quality contribute to enhancing a company's operational performance. A quantitative method was employed using a structured questionnaire distributed to respondents involved in production and operational activities. The collected data were processed using multiple linear regression in SPSS, alongside classical assumption testsnormality, multicollinearity, and heteroscedasticityto ensure that the model met statistical requirements before hypothesis analysis. The findings reveal that TQM significantly and positively influences operational performance, as indicated by a significance level below 0.05 and a positive partial R² showing improvements in productivity and efficiency. Product quality likewise demonstrates a positive and significant effect, confirmed by its regression coefficient and its role in maintaining operational consistency, reducing defects, and supporting stable performance. Together, both variables account for a considerable portion of the variability in operational performance, as reflected in the overall R² value, reinforcing the strong link between quality-oriented management practices and operational outcomes.The results emphasize that combining TQM principlescustomer orientation, continuous improvement, and employee participationwith product quality enhancement forms an essential approach to achieving sustainable operational excellence. This study provides practical insights for companies in formulating integrated quality strategies and offers empirical evidence that can guide future research examining other factors influencing operational performance across different industrial contexts.