Nasser Sanoubar; Saeid Bazmohammadi
Abstract
Analyzing corporate social responsibility (CSR) is a multi-criteria problem. This paper firstly introduces gray relation and entropy weighting methods in order to find a solution to analyze and rank corporations from this point of view. The proposed technique that conducted through combining these two ...
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Analyzing corporate social responsibility (CSR) is a multi-criteria problem. This paper firstly introduces gray relation and entropy weighting methods in order to find a solution to analyze and rank corporations from this point of view. The proposed technique that conducted through combining these two methods, will become more reliable decision making criterion. Furthermore, since in literature there are different dimensions suggested for CSR, entropy method is used to determine the relative importance of each dimension. Awareness-raising questionnaire prepared by the social responsibility unit of European Commission was used to measure corporate responsibility. By applying these methods, 10 active pharmaceutical material and products manufacturing corporations were investigated and in terms of paying attention to social responsibilities, Pars Daro corporation placed first. This technique not only helps corporations to diagnose their weaknesses and strengths, but also helps them to know their position against competitors and make better decisions to promote corporate rank in social responsibility.
Jamshid Salehi sadaghiani; Yasser Sobhani Fard; Maryam Akhavan Kharazian
Volume 5, Issue 14 , December 2006, , Pages 111-130
Abstract
The researches show that the implementation of Just-In-Time isn't unique in all situations. The implementation of this system may be differed in different companies, regions or countries and the some components that are needed to situations may be isn't vital in other situations. The purpose ...
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The researches show that the implementation of Just-In-Time isn't unique in all situations. The implementation of this system may be differed in different companies, regions or countries and the some components that are needed to situations may be isn't vital in other situations. The purpose of this study is to identify elements and components that are critical to lust-In-Time success. This articles goal is proposing a method for this notification in lust-In-Time implementation by using antropy, TOPSIS and Pareto techniques. In this method we use TOPSIS and Pareto techniques for setting a priority and then selection of component and use entropy method for giving coefficient to TOPSIS matrix. At the end, in this case 5 components from 11 possible components in this system to implement in these companies have extracted.
