Quantity-setting competition under uncertain demand

We consider a quantity-setting duopoly model, and we study the decision to move first or second, by assuming that. the firms produce homogeneous goods and that. there is some demand uncertainty. The competitive phase consists of two periods, and in either period, the firms can make a production decision that is irreversible. As far as the firms are allowed to choose (non-cooperatively) the period they make the decision, we study the circumstances that favour sequential rather than simultaneous decisions.

A Review on the Characterization of Signals and Systems by Power Law Distributions

Power laws, also known as Pareto-like laws or Zipf-like laws, are commonly used to explain a variety of real world distinct phenomena, often described merely by the produced signals. In this paper, we study twelve cases, namely worldwide technological accidents, the annual revenue of America׳s largest private companies, the number of inhabitants in America׳s largest cities, the magnitude of earthquakes with minimum moment magnitude equal to 4, the total burned area in forest fires occurred in Portugal, the net worth of the richer people in America, the frequency of occurrence of words in the novel Ulysses, by James Joyce, the total number of deaths in worldwide terrorist attacks, the number of linking root domains of the top internet domains, the number of linking root domains of the top internet pages, the total number of human victims of tornadoes occurred in the U.S., and the number of inhabitants in the 60 most populated countries. The results demonstrate the emergence of statistical characteristics, very close to a power law behavior. Furthermore, the parametric characterization reveals complex relationships present at higher level of description.

Power Law Behavior and Self-similarity in Modern Industrial Accidents

Advances in technology have produced more and more intricate industrial systems, such as nuclear power plants, chemical centers and petroleum platforms. Such complex plants exhibit multiple interactions among smaller units and human operators, rising potentially disastrous failure, which can propagate across subsystem boundaries. This paper analyzes industrial accident data-series in the perspective of statistical physics and dynamical systems. Global data is collected from the Emergency Events Database (EM-DAT) during the time period from year 1903 up to 2012. The statistical distributions of the number of fatalities caused by industrial accidents reveal Power Law (PL) behavior. We analyze the evolution of the PL parameters over time and observe a remarkable increment in the PL exponent during the last years. PL behavior allows prediction by extrapolation over a wide range of scales. In a complementary line of thought, we compare the data using appropriate indices and use different visualization techniques to correlate and to extract relationships among industrial accident events. This study contributes to better understand the complexity of modern industrial accidents and their ruling principles.

Asymmetric taxation in a competition between nonprofit and for-profit firms

This paper considers a Cournot competition between a nonprofit firm and a for-profit firm in a homogeneous goods market, with uncertain demand. Given an asymmetric tax schedule, we compute explicitly the Bayesian-Nash equilibrium. Furthermore, we analize the effects of the tax rate and the degree of altruistic preference on market equilibrium outcomes.

Quantity competition in a differentiated duopoly

In this paper, we consider a Stackelberg duopoly competition with differentiated goods, linear and symmetric demand and with unknown costs. In our model, the two firms play a non-cooperative game with two stages: in a first stage, firm F 1 chooses the quantity, q 1, that is going to produce; in the second stage, firm F 2 observes the quantity q 1 produced by firm F 1 and chooses its own quantity q 2. Firms choose their output levels in order to maximise their profits. We suppose that each firm has two different technologies, and uses one of them following a certain probability distribution. The use of either one or the other technology affects the unitary production cost. We show that there is exactly one perfect Bayesian equilibrium for this game. We analyse the variations of the expected profits with the parameters of the model, namely with the parameters of the probability distributions, and with the parameters of the demand and differentiation.

Asymmetric dynamic price competition with uncertainty

We consider a dynamic setting-price duopoly model in which a dominant (leader) firm moves first and a subordinate (follower) firm moves second. We suppose that each firm has two different technologies, and uses one of them according to a certain probability distribution. The use of either one or the other technology affects the unitary production cost. We analyse the effect of the production costs uncertainty on the profits of the firms, for different values of the intercept demand parameters.

Cournot duopoly with competition in the R&D expenditures

We present a new R&D investment in a Cournot Duopoly model and we analyze the different possible types of Nash R&D investments. We observe that the new production costs region can be decomposed in three economical regions, depending on the Nash R&D investment, showing the relevance of the use of patents in new technologies.

Cohesive law estimation of adhesive joints in mode II condition

The adhesive bonding technique enables both weight and complexity reduction in structures that require some joining technique to be used on account of fabrication/component shape issues. Because of this, adhesive bonding is also one of the main repair methods for metal and composite structures by the strap and scarf configurations. The availability of strength prediction techniques for adhesive joints is essential for their generalized application and it can rely on different approaches, such as mechanics of materials, conventional fracture mechanics or damage mechanics. These two last techniques depend on the measurement of the fracture toughness (GC) of materials. Within the framework of damage mechanics, a valid option is the use of Cohesive Zone Modelling (CZM) coupled with Finite Element (FE) analyses. In this work, CZM laws for adhesive joints considering three adhesives with varying ductility were estimated. The End-Notched Flexure (ENF) test geometry was selected based on overall test simplicity and results accuracy. The adhesives Araldite® AV138, Araldite® 2015 and Sikaforce® 7752 were studied between high-strength aluminium adherends. Estimation of the CZM laws was carried out by an inverse methodology based on a curve fitting procedure, which enabled a precise estimation of the adhesive joints’ behaviour. The work allowed to conclude that a unique set of shear fracture toughness (GIIC) and shear cohesive strength (ts0) exists for each specimen that accurately reproduces the adhesive layer’ behaviour. With this information, the accurate strength prediction of adhesive joints in shear is made possible by CZM.