Improving operational and business performance in the petroleum industry through quality management

Abstract

Purpose

The purpose of this paper is to investigate empirically the effects of quality management practices on operational and business performance.

Design/methodology/approach

A reliable and valid survey instrument was used for data gathering from managers in the petroleum industry. A multiple regression analysis was conducted to determine the effect of quality management practices on operational and business performance.

Findings

The results indicate that top management support, employee training, and employee involvement are significant variables explaining the variability of operational performance. Furthermore, a multiple regression analysis on business performance indicated the significance of top management support on business performance. The study also shows that customer orientation is not a significant predictor of business performance in the petroleum industry. In addition, focus on practices associated with human resource management (employee training and employee involvement) is critical in improving operational performance.

Research limitations/implications

Managers in the oil and gas industry need to emphasize practices associated with human resource management. Future studies should replicate this study with a larger sample size.

Originality/value

The study contributes to theory validation and development in quality management by investigating the effects of quality management practices on operational and business performance. The paper adds to the body of knowledge in quality management in the international context, specifically in the Middle East. In addition, it advances the literature on the practice of quality management in process industries, such as the petroleum industry.

Citation

Mellat Parast, M., Adams, S.G. and Jones, E.C. (2011), "Improving operational and business performance in the petroleum industry through quality management", International Journal of Quality & Reliability Management, Vol. 28 No. 4, pp. 426-450. https://doi.org/10.1108/02656711111121825