In this paper, key elements about the Fourth Industrial Revolution are set under examination. Concerns, challenges, and opportunities related to the Industry 4.0 are analyzed, and specific policies to deal with the challenges and take advantage from the opportunities are proposed. Other issues that are set under consideration in this paper are the rate at which the human labor is threatened by the technological achievements, the main factors that increase workers' exposure to the risk of automation, the jobs that are more at risk due to automation, and the basic factors that make political intervention necessary in order to deal with the unpredictable consequences of the technological progress such as the threat of a nuclear disaster and a possible income and social inequality gap widening. Finally, a special reference is done for the case of Greece.

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Purpose – The purpose of this paper is to report new original evidence on optimal holding periods and optimal asset allocations (Benartzi and Thaler, 1995). Design/methodology/approach – The authors employ a number of different value functions, a recent dataset, different markets, and varying investment horizons. Findings – The authors report original evidence across markets and over-time, employing different value functions and varying investment horizons. The results results indicate that, during the past decades, the optimal holding period (seven months during the whole period and four/five months during crises) is not affected by the value function employed, is in accordance with the Myopic Loss Aversion hypothesis, is consistent across markets, but is sensitive to economic crises and shorter to that reported in Benartzi and Thaler (12 months). The optimal asset allocation is also different to that of Benartzi and Thaler during crises periods and/or assuming value functions with probability distortion. Originality/value – The paper employs a number of different value functions, with and without probability distortion; it compares investor behavior in three important international markets (USA, UK, Germany); as a further robustness test the authors use various investment horizons.

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The main aim of this paper is to empirically evaluate the role of three significant factors of the Prospect Theory: the S-shaped value function, the loss aversion, and the distortion of probability, in decision making. In order to do this, a general behavioral reward-risk model is firstly setup and an empirical evaluation about the role of each of these factor, separately and in interaction, on the optimal solutions of the problem follows. For the analysis, well known US equity portfolios consisting by stocks listed in NYSE, AMEX, and NASDAQ formed on investment style are employed. The findings indicate that agents differentiate their behavior according to their type of preferences and their loss aversion level but they seem to always prefer high positively skewed assets such as small and value stocks. The attractiveness of positively skewed assets is re-enforced when probability distortion is introduced in the model. The introduction of probability distortion also affects the optimal perspective values of the problem increasing significantly their magnitude. After that, results show that as loss aversion increases agents tend to follow more conservative strategies, with and without probability distortion, while the value functional form has also its role in the model; bounded value functions as the negative exponential function drives agents to more conservative behaviors while unbounded value functions as the piecewise power function give the incentive to agents to undertake great risks and follow more aggressive strategies. The examination of the interaction of these factors indicate that the combination of an unbounded value functional form with a large loss aversion index may reduce agents' aggressiveness and limit (but not alter) the value functional form effect on optimal solutions.