Many works in the literature are in favour of the universality of power-laws. However, more recently, a significant amount of research has exposed more subtle details about this subject. In this paper we present two generalisations that aim to solve these possible antagonistic conceptions in a mathematical framework. The first generalisation allows us to show that a vast range of power-laws can be produced through multiplicative process (for example through a single positive feedback mechanism). The second generalisation shows, by solving Lambert's transcendental equations, that the space of solutions where the Pareto distribution is equal to the distribution produced by the power multiplicative transformation (for a number of input distributions) is infinite.

Rankings compare the performance of organizations. In many cases, rankings provide a good assessment of successful or-ganizations. However, rankings often generate controversy and debate since they support the making decisions. A ranking is a weighted linear combination of indicators, and the weights assigned to each of the indicators can lead to different rank orders. In most cases, rankings are used as a tool to support making decisions, such as resource allocation; therefore, these decisions can be affected by the assignment of such weights. In this article, we analyze the behavior of a ranking and the weights; simulations are used to calculate the change in the order of the equally weighted ranking and of the randomly weighted ranking. In this regard, we present a discussion and ranking design alternatives.