The paper introduces a new concept of social entropy and a new concept of social order, both based on the normative framework of society. From these two concepts, typologies (logical and historical) of societies are inferred and examined in their basic features. To these ends, some well-known concepts such as entropy, order, system, network, synergy, norm, autopoieticity, fetality, and complexity are revisited and placed into an integrated framework. The core body of this paper addresses the structure and the mechanism of social entropy, understood as an institutionally working counterpart of social order. Finally, this paper concludes that social entropy is an artefact, like society itself, and acts through people’s behavior.

In this article, we propose a test of the dynamics of stock market indexes typical of the US and EU capital markets in order to determine which of the two fundamental hypotheses, efficient market hypothesis (EMH) or fractal market hypothesis (FMH), best describes market behavior. The article’s major goal is to show how to appropriately model return distributions for financial market indexes, specifically which geometric Brownian motion (GBM) and geometric fractional Brownian motion (GFBM) dynamic equations best define the evolution of the S&P 500 and Stoxx Europe 600 stock indexes. Daily stock index data were acquired from the Thomson Reuters Eikon database during a ten-year period, from January 2011 to December 2020. The main contribution of this work is determining whether these markets are efficient (as defined by the EMH), in which case the appropriate stock indexes dynamic equation is the GBM, or fractal (as described by the FMH), in which case the appropriate stock indexes dynamic equation is the GFBM. In this paper, we consider two methods for calculating the Hurst exponent: the rescaled range method (RS) and the periodogram method (PE). To determine which of the dynamics (GBM, GFBM) is more appropriate, we employed the mean absolute percentage error (MAPE) method. The simulation results demonstrate that the GFBM is better suited for forecasting stock market indexes than the GBM when the analyzed markets display fractality. However, while these findings cannot be generalized, they are verisimilar.

The most known and used abstract model of the financial market is based on the concept of the informational efficiency (EMH) of that market. The paper proposes an alternative which could be named the behavioural efficiency of the financial market, which is based on the behavioural entropy instead of the informational entropy. More specifically, the paper supports the idea that, in the financial market, the only measure (if any) of the entropy is the available behaviours indicated by the implicit information. Therefore, the behavioural entropy is linked to the concept of behavioural efficiency. The paper argues that, in fact, in the financial markets, there is not a (real) informational efficiency, but there exists a behavioural efficiency instead. The proposal is based both on a new typology of information in the financial market (which provides the concept of implicit information—that is, that information ”translated” by the economic agents from observing the actual behaviours) and on a non-linear (more exactly, a logistic) curve linking the behavioural entropy to the behavioural efficiency of the financial markets. Finally, the paper proposes a synergic overcoming of both EMH and AMH based on the new concept of behavioural entropy in the financial market.

The study intends to deliver a logical analysis of the well-known (and too much used) model of rationality named homo œconomicus. To this end, it is put into evidence the reductionism of the model (more, its cartesianism and mechanicism), by logically assessing the basic principle and the axioms and, also, the relaxations introduced over time. The paper gets the conclusion that economists tried successively to save the homo œconomicus model over time, but all these attempts did nothing but block the developments of the economic theory. Finally, the research organizes into a diachronic matrix the different ways in which economists actualized the genuine model in order to put it in line with the actual behaviour of the economic subject.

This paper presents a new methodology entitled AVTRIZ by its author, which allows technical, economic and managerial innovation based on the forecasting approach, while operating inside various systems. As the foundation of the new methodology, a classical method was chosen, well-known and widely applied that is the Method of Value Analysis and Engineering, a domain where the author has previous concerns. Starting from the fact that this method is deficient in terms of generating improvement solutions, the author searched and identified a method of current interest and global opportunity that is the TRIZ method [1], which is a method of wide debate, very controversial in terms of its adaptability from the technical to the business and management domains. On the other hand, TRIZ is deficient in terms of checking the solutions, a fact which can be successfully compensated by the Value Analysis Engineering method. Based on the above-mentioned approach, the research activities carried out by the author have brought in a new methodology, which is structured on 3 steps, 8 stages and 30 phases, based on the method of Value Analysis and Engineering, while also applying the TRIZ method.