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Social Media have been gaining in popularity worldwide over the last years at an increasingly growing rate. The introduction of social media in companies enables a new method of communication among colleagues and with customers. Although social media are in the top of the agenda for many companies to date, there seems to be very limited understanding of the usage of social media for work purposes. In this study, we investigate whether employees make use of social media for work purposes, what values increase this usage, and if that usage is related with their performance. Responses from 1799 employees in the insurance industry were used to examine the impact of social media on work. Results confirmed that in the case of social media for work, employees make extended use of them no matter their age. We found also that both utilitarian and hedonic values influence employees to use more social media for their work, at least in the insurance sector. Last but not least, this study confirms that there is an important relation between the use of social media and the work performance.

In this paper, an innovative fuzzy approach for ranking alternatives in multiple attribute decision making problems based on TOPSIS is presented in-depth and studied through simulation comparison with the original method. The TOPSIS method provides the principle of compromise that the chosen alternative should have the shortest distance from the ideal solution and, simultaneously, the farthest distance from the negative ideal solution. However, the TOPSIS method does not always produce results in harmony with this principle due to an oversimplified definition of its aggregation function which does not grasp the contradictory nature of the principle's formulation. Our approach addresses this issue through the introduction of a fuzzy set representation of the closeness to the ideal and to the negative ideal solution for the definition of the aggregation function which is modeled as the membership function of the intersection of two fuzzy sets. This model enables a parameterization of the method according to the risk attitude of the decision maker. Thus, a class of methods is formulated whose different instances correspond to different risk attitudes of the decision makers. In order to define some clear advises for decision makers facilitating a proper parameterization of the method, a comparative analysis of the proposed class of methods with the original TOPSIS method is performed according to well defined simulation techniques. The results of the simulation experiment show on the one hand that there is no direct correspondence between the proposed class of methods and TOPSIS, and on the other hand that it is adequate to distinguish three instances that correspond respectively to risk-averse, risk-neutral and risk-seeking decision makers. Finally, a numerical example pertaining to the problem of service provider selection is presented to illustrate the application of the proposed class of methods and its functioning.