I introduce a model of corporate voting. I characterize the shareholder majority rule as the unique corporate voting rule that satisfies four axioms: anonymity, neutrality, share monotonicity, and merger, a property that requires consistency in election outcomes following stock-for-stock mergers. JEL classification: D71, D72, K22

A median of a k-tuple =(x1; : : : ; xk) of elements of a 0nite metric space (X; d) is an element x for which ∑k i=1 d(x; xi) is minimum. The function m with domain the set of all k-tuples with k ¿ 0 and de0ned by m( ) = {x: x is a median of } is called the median function on X . Continuing with the program of characterizing m on various metric spaces, this paper presents a characterization of t...

In this paper, we first review existing fuzzy extensions of the dominance-based rough set approach (DRSA), and advance theory considering additional properties. Moreover, examine application Ordered Weighted Average (OWA) operators to DRSA. OWA have shown a lot potential in handling outliers noisy data decision tables, when they are combined with indiscernibility-based (IRSA). We theoretical pr...

Social media are an essential source of meaningful data that can be used in different tasks such as sentiment analysis and emotion recognition. Mostly, these solved with deep learning methods. Due to the fuzzy nature textual data, we consider using classification methods based on rough sets.Specifically, develop approach for SemEval-2018 detection task, nearest neighbour (FRNN) classifier enhan...

The OWA operators gained interest among researchers as they provide a continuum of aggregation operators able to cover the whole range of compensation between the minimum and the maximum. In some circumstances, it is useful to consider a wider range of values, extending below the minimum and over the maximum. ST-OWA are able to surpass the boundaries of variation of ordinary compensatory operat...

We introduce a new aggregation operator called the heavy ordered weighted averaging – weighted averaging (HOWAWA) operator. It is a new aggregation operator that uses the weighted average and the ordered weighted average in the same formulation and considering the degree of importance that each concept has in the analysis. Moreover, by using heavy aggregations, we are allowing the weighting vec...

We develop a new model for decision making under risk environment and under uncertainty. We introduce a new aggregation operator that unifies the probabilities and the ordered weighted averaging (OWA) operator in the same formulation. We call it the probabilistic ordered weighted averaging (POWA) operator. This aggregation operator provides a more complete representation of the decision problem...