Middle East and North Africa (MENA) countries present a banking industry that is well-known for regulatory and cultural heterogeneity, besides ownership, origin, and type diversity. This paper explores these issues by developing a Dynamic Network DEA model in order to handle the underlying relationships among major accounting and financial indicators.Firstly, a relational model encompassing major profit sheet, balance sheet, and financial health indicators is presented under a dynamic network structure. Subsequently, the dynamic effect of carry-over indicators is incorporated into it so that efficiency scores can be properly computed for these three substructures. The impact of contextual variables related to bank ownership, its type, and whether or not it has undergone a previous merger and acquisition process is tested by means of a stochastic non-linear model solved by differential evolution, which combines bootstrapped Simplex, Tobit, Beta, and Simar and Wilson truncated regression results. The results reveal that bank type, origin, and ownership impact efficiency levels differently in terms of profit sheet, balance sheet, and financial health indicators, although the impact of culture and regulatory barriers seem to prevail at the country level.Abstract: Middle East and North Africa (MENA) countries present a banking industry that is well-known for regulatory and cultural heterogeneity, besides ownership, origin, and type diversity. This paper explores these issues by developing a Dynamic Network DEA model in order to handle the underlying relationships among major accounting and financial indicators. Firstly, a relational model encompassing major profit sheet, balance sheet, and financial health indicators is presented under a dynamic network structure. Subsequently, the dynamic effect of carry-over indicators is incorporated into it so that efficiency scores can be properly computed for these three substructures. The impact of contextual variables related to bank ownership, its type, and whether or not it has undergone a previous merger and acquisition process is tested by means of a stochastic non-linear model solved by differential evolution, which combines bootstrapped Simplex, Tobit, Beta, and Simar and Wilson truncated regression results. The results reveal that bank type, origin, and ownership impact efficiency levels differently in terms of profit sheet, balance sheet, and financial health indicators, although the impact of culture and regulatory barriers seem to prevail at the country level.

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An evaluation model of competitive and innovative tourism practices in Portugal based on information entropy is proposed. The relative evolution of each criterion/construct is explored in the light of its predictability/randomness in Portuguese companies by calculating and analysing the information entropy of different perceptions on competitive and innovative tourism practices. This article presents a novel approach by using information entropy to handle probabilistically different competitive and innovative practice weights computed by alternative models such as (a) the Fuzzy Rasch model that combines the item response theory and the fuzzy set theory, (b) the fuzzy analytic hierarchy process (AHP) model and (c) the crisp AHP model based on eight different judgment scales on the relative evolution of each criterion/construct. The results show that the total information entropy suggests a strong heterogeneity in Portuguese companies in terms of innovation for competitiveness. They also reveal a significant relationship between innovative tourism practices and tourism competitiveness models.

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