<p>This thesis consists of four self-contained essays in economics. <i>Tournaments and unfair treatment</i>. This paper introduces the negative feelings associated with the perception of being unfairly treated into a tournament model and examines the impact of these perceptions on workers’ efforts and their willingness to work overtime. The effect of unfair treatment on workers’ behavior is ambiguous in the model in that two countervailing effects arise: a negative impulsive effect and a positive strategic effect. The impulsive effect implies that workers react to the perception of being unfairly treated by reducing their level of effort. The strategic effect implies that workers raise this level in order to improve their career opportunities and thereby avoid feeling even more unfairly treated in the future. An empirical test of the model using survey data from a Swedish municipal utility shows that the overall effect is negative. This suggests that employers should consider the negative impulsive effect of unfair treatment on effort and overtime in designing contracts and determining on promotions.<i> </i></p><p><i>Late careers in Sweden between 1970 and 2000</i>. In this essay Swedish workers’ late careers between 1970 and 2000 are studied. The aim is to examine older workers’ career patterns and whether they have changed during this period. For example, is there a difference in career mobility or labor market exiting between cohorts? What affects the late career, and does this differ between cohorts? The analysis shows that between 1970 and 2000 the late careers of Swedish workers comprised of few job changes and consisted more of “trying to keep the job you had in your mid-fifties” than of climbing up the promotion ladder. There are no cohort differences in this pattern. Also a large fraction of the older workers exited the labor market before the normal retirement age of 65. During the 1970s and first part of the 1980s, 56 percent of the older workers made an early exit and the average drop-out age was 63. During the late 1980s and the 1990s the share of old workers who made an early exit had risen to 76 percent and the average drop-out age had dropped to 61.5. Different factors have affected the probabilities of an early exit between 1970 and 2000. For example, skills did affect the risk of exiting the labor market during the 1970s and up to the mid-1980s, but not in the late 1980s or the 1990s. During the first period old workers in the lowest occupations or with the lowest level of education were more likely to exit the labor market than more highly skilled workers. In the second period old workers at all levels of skill had the same probability of leaving the labor market.<i> </i></p><p><i>The growth and survival of establishments: does gender segregation matter?</i> We empirically examine the employment dynamics that arise in Becker’s (1957) model of labor market discrimination. According to the model, firms that employ a large fraction of women will be relatively more profitable due to lower wage costs, and thus enjoy a greater probability of surviving and growing by underselling other firms in the competitive product market. In order to test these implications, we use a unique Swedish matched employer-employee data set. We find that female-dominated establishments do not enjoy any greater probability of surviving and do not grow faster than other establishments. Additionally, we find that integrated establishments, in terms of gender, age and education levels, are more successful than other establishments. Thus, attempts by legislators to integrate firms along all dimensions of diversity may have positive effects on the growth and survival of firms. </p><p><i>Risk and overconfidence – Gender differences in financial decision-making as revealed in the TV game-show Jeopardy.</i> We have used unique data from the Swedish version of the TV-show <i>Jeopardy</i> to uncover gender differences in financial decision-making by looking at the contestants’ final wagering strategies. After ruling out empirical best-responses, which do appear in Jeopardy in the US, a simple model is derived to show that risk preferences, the subjective and objective probabilities of answering correctly (individual and group competence), determine wagering strategies. The empirical model shows that, on average, women adopt more conservative and diversified strategies, while men’s strategies aim for the greatest gains. Further, women’s strategies are more responsive to the competence measures, which suggests that they are less overconfident. Together these traits make women more successful players. These results are in line with earlier findings on gender and financial trading.</p>

This thesis consists of four self-contained essays in economics. Tournaments and unfair treatment. This paper introduces the negative feelings associated with the perception of being unfairly treated into a tournament model and examines the impact of these perceptions on workers’ efforts and their willingness to work overtime. The effect of unfair treatment on workers’ behavior is ambiguous in the model in that two countervailing effects arise: a negative impulsive effect and a positive strategic effect. The impulsive effect implies that workers react to the perception of being unfairly treated by reducing their level of effort. The strategic effect implies that workers raise this level in order to improve their career opportunities and thereby avoid feeling even more unfairly treated in the future. An empirical test of the model using survey data from a Swedish municipal utility shows that the overall effect is negative. This suggests that employers should consider the negative impulsive effect of unfair treatment on effort and overtime in designing contracts and determining on promotions. Late careers in Sweden between 1970 and 2000. In this essay Swedish workers’ late careers between 1970 and 2000 are studied. The aim is to examine older workers’ career patterns and whether they have changed during this period. For example, is there a difference in career mobility or labor market exiting between cohorts? What affects the late career, and does this differ between cohorts? The analysis shows that between 1970 and 2000 the late careers of Swedish workers comprised of few job changes and consisted more of “trying to keep the job you had in your mid-fifties” than of climbing up the promotion ladder. There are no cohort differences in this pattern. Also a large fraction of the older workers exited the labor market before the normal retirement age of 65. During the 1970s and first part of the 1980s, 56 percent of the older workers made an early exit and the average drop-out age was 63. During the late 1980s and the 1990s the share of old workers who made an early exit had risen to 76 percent and the average drop-out age had dropped to 61.5. Different factors have affected the probabilities of an early exit between 1970 and 2000. For example, skills did affect the risk of exiting the labor market during the 1970s and up to the mid-1980s, but not in the late 1980s or the 1990s. During the first period old workers in the lowest occupations or with the lowest level of education were more likely to exit the labor market than more highly skilled workers. In the second period old workers at all levels of skill had the same probability of leaving the labor market. The growth and survival of establishments: does gender segregation matter? We empirically examine the employment dynamics that arise in Becker’s (1957) model of labor market discrimination. According to the model, firms that employ a large fraction of women will be relatively more profitable due to lower wage costs, and thus enjoy a greater probability of surviving and growing by underselling other firms in the competitive product market. In order to test these implications, we use a unique Swedish matched employer-employee data set. We find that female-dominated establishments do not enjoy any greater probability of surviving and do not grow faster than other establishments. Additionally, we find that integrated establishments, in terms of gender, age and education levels, are more successful than other establishments. Thus, attempts by legislators to integrate firms along all dimensions of diversity may have positive effects on the growth and survival of firms. Risk and overconfidence – Gender differences in financial decision-making as revealed in the TV game-show Jeopardy. We have used unique data from the Swedish version of the TV-show Jeopardy to uncover gender differences in financial decision-making by looking at the contestants’ final wagering strategies. After ruling out empirical best-responses, which do appear in Jeopardy in the US, a simple model is derived to show that risk preferences, the subjective and objective probabilities of answering correctly (individual and group competence), determine wagering strategies. The empirical model shows that, on average, women adopt more conservative and diversified strategies, while men’s strategies aim for the greatest gains. Further, women’s strategies are more responsive to the competence measures, which suggests that they are less overconfident. Together these traits make women more successful players. These results are in line with earlier findings on gender and financial trading.

After globalized division of labor, the upstream and downstream in industry have become more valued. Designing, advertising, and marketing are exactly the focus of cultural creative industries. The destruction of environment that comes with economic development also forces Chinese government to consider the environmental issue and transformation in industries: developing cultural creative industry to enhance the profit, which ensures sustainable development in economy. This study focus on how cultural creative industrial parks help the expansion of cultural creative industries in Shanghai. ¡§Tianzifang,¡¨ ¡§M50,¡¨ ¡§Red Town,¡¨ and "Bridge 8" are for example in terms of how cultural creative industrial parks ¡§innovate¡¨ and improve cultural productivity in Shanghai, helping the sustained and stable development in the industry. With the history of concession, Shanghai is the gateway to China. Researches show that this fusion of Chinese and Western culture is open, diverse and tolerant. The establishment of Shanghai cultural creative industrial parks builds the platform for exchange and interaction among culture, industry, and consumers. The parks are also capable of revitalizing the uniqueness in Shanghai culture, creating employment, and cultivating the cultural creative markets. The parks are customer-oriented at present, highlighting the hardware and entertainment venues, which disappoints the cultural creative workers. As the core of creative industries is in creative work, improving the working environment and meeting satisfaction of the enterprises and workers will be the matter in the future.

Based on the publications [P1–P6], the cumulative dissertation at hand addresses quite diverse aspects of non-equilibrium behavior in isolated quantum systems. The works presented in publications [P1, P2] concern the issue of finding generally valid upper bounds on equilibration times, which ensure the eventual occurrence of equilibration in isolated quantum systems. Recently, a particularly compelling bound for physically relevant observables has been proposed. Said bound is examined analytically as well as numerically. It is found that the bound fails to give meaningful results in a number of standard physical scenarios. Continuing, publication [P4] examines a particular integral fluctuation theorem (IFT) for the total entropy production of a small system coupled to a substantially larger but finite bath. While said IFT is known to hold for canonical states, it is shown to be valid for microcanonical and even pure energy eigenstates as well by invoking the physically natural conditions of “stiffness” and “smoothness” of transition probabilities. The validity of the IFT and the existence of stiffness and smoothness are numerically investigated for various lattice models. Furthermore, this dissertation puts emphasis on the issue of the route to equilibrium, i.e., to explain the omnipresence of certain relaxation dynamics in nature, while other, more exotic relaxation patterns are practically never observed, even though they are a priori not disfavored by the microscopic laws of motion. Regarding this question, the existence of stability in a larger class of dynamics consisting of exponentially damped oscillations is corroborated in publication [P6]. In the same vein, existing theories on the ubiquity of certain dynamics are numerically scrutinized in publication [P3]. Finally, in publication [P5], the recently proposed “universal operator growth hypothesis”, which characterizes the complexity growth of operators during unitary time evolution, is numerically probed for various spin-based systems in the thermodynamic limit. The hypothesis is found to be valid within the limits of the numerical approach.

In the context of evolutionary robotics and neurorobotics, artificial neural networks, used as controllers for animats, are examined to identify principles of neuro-control, network organization, the interaction between body and control, and other likewise properties. Before such an examination can take place, suitable neuro-controllers have to be identified. A promising and widely used technique to search for such networks are evolutionary algorithms specifically adapted for neural networks. These allow the search for neuro-controllers with various network topologies directly on physically grounded (simulated) animats. This neuro-evolution approach works well for small neuro-controllers and has lead to interesting results. However, due to the exponentially increasing search space with respect to the number of involved neurons, this approach does not scale well with larger networks. This scaling problem makes it difficult to find non-trivial, larger networks, that show interesting properties. In the context of this thesis, networks of this class are called mid-scale networks, having between 50 and 500 neurons. Searching for networks of this class involves very large search spaces, including all possible synaptic connections between the neurons, the bias terms of the neurons and (optionally) parameters of the neuron model, such as the transfer function, activation function or parameters of learning rules. In this domain, most evolutionary algorithms are not able to find suitable, non-trivial neuro-controllers in feasible time. To cope with this problem and to shift the frontier for evolvable network topologies a bit further, a novel evolutionary method has been developed in this thesis: the Interactively Constrained Neuro-Evolution method (ICONE). A way to approach the problem of increasing search spaces is the introduction of measures that reduce and restrict the search space back to a feasible domain. With ICONE, this restriction is realized with a unified, extensible and highly adaptable concept: Instead of evolving networks freely, networks are evolved within specifically designed constraint masks, that define mandatory properties of the evolving networks. These constraint masks are defined primarily using so called functional constraints, that actively modify a neural network to enforce the adherence of all required limitations and assumptions. Consequently, independently of the mutations taking place during evolution, the constraint masks repair and readjust the networks so that constraint violations are not able to evolve. Such functional constraints can be very specific and can enforce various network properties, such as symmetries, structure reuse, connectivity patterns, connectivity density heuristics, synaptic pathways, local processing assemblies, and much more. Constraint masks therefore describe a narrow, user defined subset of the parameter space -- based on domain knowledge and user experience -- that focuses the search on a smaller search space leading to a higher success rate for the evolution. Due to the involved domain knowledge, such evolutions are strongly biased towards specific classes of networks, because only networks within the defined search space can evolve. This, surely, can also be actively used to lead the evolution towards specific solution approaches, allowing the experimenter not only to search for any upcoming solution, but also to confirm assumptions about possible solutions. This makes it easier to investigate specific neuro-control principles, because the experimenter can systematically search for networks implementing the desired principles, simply by using suitable constraints to enforce them. Constraint masks in ICONE are built up by functional constraints working on so called neuro-modules. These modules are used to structure the networks, to define the scope for constraints and to simplify the reuse of (evolved) neural structures. The concept of functional, constrained neuro-modules allows a simple and flexible way to construct constraint masks and to inherit constraints when neuro-modules are reused or shared. A final cornerstone of the ICONE method is the interactive control of the evolution process, that allows the adaptation of the evolution parameters and the constraint masks to guide evolution towards promising domains and to counteract undesired developments. Due to the constraint masks, this interactive guidance is more effective than the adaptation of the evolution parameters alone, so that the identification of promising search space regions becomes easier. This thesis describes the ICONE method in detail and shows several applications of the method and the involved features. The examples demonstrate that the method can be used effectively for problems in the domain of mid-scale networks. Hereby, as effects of the constraint masks and the herewith reduced complexity of the networks, the results are -- despite their size -- often easy to comprehend, well analyzable and easy to reuse. Another benefit of constraint masks is the ability to deliberately search for very specific network configurations, which allows the effective and systematic exploration of distinct variations for an evolution experiment, simply by changing the constraint masks over the course of multiple evolution runs. The ICONE method therefore is a promising novel evolution method to tackle the problem of evolving mid-scale networks, pushing the frontier of evolvable networks a bit further. This allows for novel evolution experiments in the domain of neurorobotics and evolutionary robotics and may possibly lead to new insights into neuro-dynamical principles of animat control.

Mobile robots need to move in the real world for the majority of tasks. Their control is often intertwined with the tasks they have to solve. Unforeseen events must have an adequate and prompt reaction, in order to solve the corresponding task satisfactorily. A robust system must be able to respond to a variety of events with specific solutions and strategies to keep the system running. Robot navigation control systems are essential for this. In this thesis we present a robot navigation control system that fulfills these requirements: Move Base Flex. Furthermore, the map representation used to model the environment is essential for path planning. Depending on the representation of the map, path planners can solve problems like simple 2D indoor navigation, but also complex rough terrain outdoor navigation with multiple levels and varying slopes, if the corresponding representation can model them accurately. With Move Base Flex, we present a middle layer navigation framework for navigation control, that is map independent at its core. Based on this, we present the Mesh Navigation Stack to master path planning in complex outdoor environments using a developed mesh map to model surfaces in 3D. Finally, to solve path planning in complex outdoor environments, we have developed and integrated the Continuous Vector Field Planner with the aforementioned solutions and evaluated it on five challenging and complex outdoor datasets in simulation and in the real-world. Beyond that, the corresponding developed software packages are open source available and have been released to easily reproduce the provided scientific results.

The goal of this thesis is to improve our knowledge on energetic particle precipitation into the Earth’s atmosphere from the thermosphere to the surface. The particles origin from the Sun or from temporarily trapped populations inside the magnetosphere. The best documented influence of solar (high-) energetic particles on the atmosphere is the Ozone depletion in high latitudes, attributed to the generation of HOx and NOx by precipitating particles (Crutzen et al., 1975; Solomon et al., 1981; Reid et al., 1991). In addition Callis et al. (1996b, 2001) and Randall et al. (2005, 2006) point out the importance of low-energetic precipitating particles of magnetospheric origin, creating NOx in the lower thermosphere, which may be transported downwards where it also contributes to Ozone depletion. The incoming particle flux is dramatically changing as a function of auroral/geomagnetical activity and in particular during solar particle events. As a result, the degree of ionization and the chemical composition of the atmosphere are substantially affected by the state of the Sun. Therefore the direct energetic or dynamical influences of ions on the upper atmosphere depend on solar variability at different time scales. Influences on chemistry have been considered so far with simplified precipitation patterns, limited energy range and restrictions to certain particle species, see e.g. Jackman et al. (2000); Sinnhuber et al. (2003b, for solar energetic protons and no spatial differentiation), and Callis et al. (1996b, 2001, for magnetospheric electrons only). A comprehensive atmospheric ionization model with spatially resolved particle precipitation including a wide energy range and all main particle species as well as a dynamic magnetosphere was missing. In the scope of this work, a 3-D precipitation model of solar and magnetospheric particles has been developed. Temporal as well as spatial ionization patterns will be discussed. Apart from that, the ionization data are used in different climate models, allowing (a) simulations of NOx and HOx formation and transport, (b) comparisons to incoherent scatter radar measurements and (c) inter-comparison of the chemistry part in different models and comparison of model results to MIPAS observations. In a bigger scope the ionization data may be used to better constrain the natural sources of climate change or consequences for atmospheric dynamics due to local temperature changes by precipitating particles and their implications for chemistry. Thus the influence of precipitating energetic particles on the composition and dynamics of the atmosphere is a challenging issue in climate modeling. The ionization data is available online and can be adopted automatically to any user specific model grid.