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Quality cost studies present a considerable lack of information on account of the existence of hidden quality costs. As a result, it is necessary to develop instruments that improve the estimations made and favour final data analysis. First, this paper develops an interesting and original tool based on fuzzy logic that will allow any business to improve its estimations of quality costs. This is possible by observing the organisation's position on Crosby's Quality Management Maturity Grid. Finally, data analysis will then take place using both linear and possibilistic regression. The suitability of the latter of these two is demonstrated for quality cost analysis as well as for making predictions. We have made use of a case study as research methodology.

The relation between corporate social responsibility (CSR) and financial performance (FP) has been widely dealt with in specialized literature. This study has two points of interest: first, we develop a new tool which financially quantifies the value contributed to companies that are committed to CSR; then, we make a practical application of this tool through an empirical study focused on Spanish companies. This study is especially innovative because of the fuzzy methodology used and the way it defines CSR through the IQNet SR10 certification of social responsibility systems. In addition, the measurement of CSR through IQNet SR10 certification is a completely new approach to the subject. An interesting conclusion can be drawn from the empirical study: IQNet SR10 CSR certification increases the value of businesses. However, neither size nor the economic sector they belong to influence this relationship significantly. K E Y W O R D Scorporate social responsibility, empirical study, financial performance, fuzzy logic, IQNet SR10

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