The Prediction of Successful Probability of CSR and Sustainable Development Strategy Implementation within "Rosia Montana Project" using Fuzzy Logic
This article aims to develop a methodology to forecast the probability of success regarding to the implementation of the concept of corporate social responsibility (CSR) and of the strategy of sustainable development in a mining company of exploitation of mineral resources. It is well known that in the modern period we are witnessing ever more to increased demands in terms of corporate responsibility towards the environment, in the area which can include economic, social, cultural and ecological environment. As a consequence of this fact, it increases the uncertainty of decisions to be adopted by companies, uncertainty that may arise from several aspects such as incompleteness, inconsistencies or inaccuracies in information or simply due to the subjective nature of human reasoning which often is expressed in words, through linguistic values. Thus, for modeling this vagueness of decision or prediction process there is a particularly effective tool, represented by the fuzzy logic through triangular fuzzy numbers. By multiplying the importance weight of factors that influencing the adoption of CSR and sustainable development policy with values resulting from evaluation of the possibility of successful implementation of this policy with respect to each factor, there it results a probability that suggests us if the action of implementation of CSR and of sustainable development strategy will have the overall expected effect and in the case the result is not properly there it will require remedial measures. The proposed methodology is applied in a case study concerning the Romanian mining company Rosia Montana Gold Corporation (RMGC) from Rosia Montana, Romania and also concerning the community in which it operates.
Year of publication: |
2013
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Authors: | SIRB, Lucian |
Published in: |
Informatica Economica. - Academia de Studii Economice din Bucureşti, ISSN 1453-1305. - Vol. 17.2013, 2, p. 130-147
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Publisher: |
Academia de Studii Economice din Bucureşti |
Subject: | CSR | Sustainable Development | Fuzzy Logic | Prediction |
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