PurposeThe purpose of this paper is to propose a model for analysing the influence of costs of quality.Design/methodology/approachA model is designed by using a causal loop diagram and is analysed through a system dynamics approach. The model simulation is prepared by Vensim software.FindingsPrevention and appraisal costs are the two effective cost factors. The model represented in this paper reveals that prevention costs have the most effect on total cost of quality and especially external failure costs. Hence, in order to achieve the customer expected quality level, prevention and appraisal costs should be considered.Research limitations/implicationsCalculating and measuring non‐conformance costs is very difficult in organizations and some errors and mistakes may happen.Practical implicationsA system dynamics approach can analyse and measure the amount of prevention cost effects on cost of quality in different organizations.Originality/valueThe proposed methodology demonstrates the use of an innovative approach in developing a cost of quality concept and constructing a practical framework for system dynamics in a real case.

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Despite considerable efforts to give diversity to world's energy supply portfolio, oil still has a significant share among energy carriers and plays a major role in economy of countries. Regarding dependency of Iran's economy on revenues of crude oil exports, investigations on the dynamics of crude oil production rate (considering the factors such as technological, economic, political, etc.) are of high importance for the country. In this paper, factors influencing the Iran's crude oil production peak are investigated by system dynamics approach. Through results obtained by the model it is shown how different factors, within causal relationships, affect the occurrence time and the volume of produced oil at its peak. The model is also used to evaluate different scenarios on oil price, geological uncertainty, production depletion, and foreign investment level in the country. Moreover, it can be used to simulate behavior of main variables in the industry under different policy options. The model predicts that the peak will occur sometime between 2035 and 2042 with various production volumes in different scenarios. The developed model can help practitioners, especially policy makers, in the oil sector to gain a systemic and comprehensive insight of influencing factors and the relationships which cause occurrence of Iran's crude oil peak. Investments in all exploration and production sectors, which depend on the oil prices, might be the most crucial variable on the future of the industry and its success to help the developing country achieve its goals.

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