This paper investigates the effects of social media on entrepreneurial opportunity recognition. Combining the internal and external approaches of opportunity recognition, the study analyzes how social media influences the entrepreneurs in discovering new entrepreneurial opportunities. Structural equation modeling was used in this study, using the variance-based partial least squares (PLS)–structural equation modeling (SEM), on a sample of 354 entrepreneurs. We concluded that social media directly and positively influences entrepreneurial opportunity recognition while entrepreneurial alertness (internal approach) and social networks (external approach) partially mediates its indirect effects on entrepreneurial opportunity recognition. The study contributes to the existing literature by bringing new insights into the entrepreneurial opportunity recognition process by focusing on a poorly represented factor in the literature, social media.

This paper reports a new methodology and results on the forecast of the numerical value of the fat tail(s) in asset returns distributions using the irrational fractional Brownian motion model. Optimal model parameter values are obtained from fits to consecutive daily 2-year period returns of S&P500 index over [1950–2016], generating 33-time series estimations. Through an econometric model, the kurtosis of returns distributions is modelled as a function of these parameters. Subsequently an auto-regressive analysis on these parameters advances the modelling and forecasting of kurtosis and returns distributions, providing the accurate shape of returns distributions and measurement of Value at Risk.

In Italy, the elections occur often, indeed almost every year the citizens are involved in a democratic choice for deciding leaders of different administrative entities. Sometimes the citizens are called to vote for filling more than one office in more than one administrative body. This phenomenon has occurred 35 times after 1948; it creates the peculiar condition of having the same sample of people expressing decisions on political bases at the same time. Therefore, the Italian contemporaneous ballots constitute the occasion to measure coherence and chaos in the way of expressing political opinion. In this paper, we address all the Italian elections that occurred between 1948 and 2018. We collect the number of votes per party at each administrative level and we treat each election as a manifestation of a complex system. Then, we use the Shannon entropy and the Gini Index to study the degree of disorder manifested during different types of elections at the municipality level. A particular focus is devoted to the contemporaneous elections. Such cases implicate different disorder dynamics in the contemporaneous ballots, when different administrative level are involved. Furthermore, some features that characterize different entropic regimes have emerged.

This paper identifies the salient factors that characterize the inequality income distribution for Romania. Data analysis is rigorously carried out using sophisticated techniques borrowed from classical statistics (Theil). Decomposition of the inequalities measured by the Theil index is also performed. This study relies on an exhaustive (11.1 million records for 2014) data-set for total personal gross income of Romanian citizens.

An innovative extension of the geometric Brownian motion model is developed by incorporating a weighting factor and a stochastic function modeled as a mixture of power and trigonometric functions. Simulations based on this modified Brownian motion model, with optimal weighting factors selected by goodness-of-fit tests, substantially outperform the basic geometric Brownian motion model in terms of fitting the returns distribution of historic data price indices. Furthermore, we attempt to provide an interpretation of the additional stochastic term in relation to irrational behavior in financial markets and outline the importance of this novel model.