A Survey on the Effect of Quality Management on Performance Indicators (Case Study: Dashtestan Cement Industries)

Subject Areas : Industrial Management

Mehran Sadeghi ¹ , Ali Givechian ² , Sara Bazyari ³

1 - M.A in Industrial Management, Persian Gulf University of Bushehr, Bushehr, Iran
2 - M.A. In industrial management, Persian Gulf University of Bushehr, Bushehr, Iran
3 - M.A. In Food Science Engineering, Islamic Azad University, Science and Research Branch

Received: 2018-01-08 Accepted : 2018-01-08 Published : 2013-08-23

Keywords:

Abstract :

The past decade has seen many firms focusing on quality management as an essential activity for improving profit, market share, and competitiveness. The goal of this research is to determine the usage amount of quality management principles and activities, and their effects on each other and on performance indicators (personnel performance & operational performance) in Dshtestan cement industries located in the Bushehr province. Statistical population of this research includes all employees in Dshtestan cement industries. The SPSS is used for statistical analysis of gathered data to test the hypotheses, and LISREL software is used for testing the research model of Structural Equation Modeling Technique. Research findings illustrate that between quality management activities, teamwork has the greatest effect on continues improvement. Also, close relationships between teamwork and personnel performance, and between customer focus and operational performance are stronger than other relationships. The research results also tell us that some acts must be done to increase team & group participation, and it is necessary to pay attention to internal and external customers -inside of results and goods- to improve performance indicators. 

References:

1. 
   

   1-Akao,Y., & Shigeru, M. (1994). QFD: The Customer-driven approach to quality planning and development, APO.

   
   

   2- Badri, M. A. (2001). A Combined AHP-GP Model for Quality Control System. International Journal of Production Economics, 27-40.

   
   

   3-Chan, L. K., & Ming, L. (1998). Prioritizing the technical measures in Quality function deployment, Quality Engineering.

   
   

   4- Danaeifard, H., & Alvani, M. (2004). Quantitative research methodology in management: a comprehensive approach, Safaar Press.

   
   

   5- Dagdeviren, M., Yavuz, S., & Kilinc, N. (2009). Weapon Selection Using AHP and TOPSIS Method Under Fuzzy Environment. Journal of Expert Systems with applications, 8143-8151.

   
   

   6- Dong, E., & Lee, T. K., & Arditi, D. (2009). Automated stochastic quality function deployment system for measuring the quality performance of design/build contractors.

   
   

   7- Lee, D. E., & Arditi, D. (2006). Total  Quality  Performance  of D/B Firms Using Quality Function Deployment, Journal of Construction Engineering and Management.

   
   

   8- Momeni, M. (2006). Modern Topics in Operations Research. Tehran University Press.

   
   

   9- Naderi, E., & Seyfenaraghi, M. (1992). Research and evaluation methods in humanities, Badr press.

   
   

   10-Terninko, John. (1996). QFD: Customer driven product design, Prentice Hall.

   
   

   11- Saaty, Y. L. (1980). The Analytic Hierarchy Process. New York: McGraw-Hill

   
   

   12- Wang, J. J., & Yang, D. L. (2007). Using a Hybrid Multi Criteria Decision Aid Method for Information Systems Outsourcing. Journal of Computer and Operation Research, 34, 3691-3700

   
   

   13-Yi, K., & Juan, Y., & Horng, P. (2009).  Housing refurbishment contractor's selection based on a hybrid fuzzy-QFD approach Elsevier.

   
   

   14- Yi, Q., & Yang, S., & Qing, W. (2003). A fuzzy quality function deployment system for buildable design decision-makings, Elsevier.