Nonlinear Dynamics Psychology and Life Sciences最新文献

The classic paper 'A Garbage Can Model of Organizational Choice' by Cohen, March and Olsen (1972) both heralded a significant expansion of the study of organizational decision making to non-industrial settings, in particular universities, and served as a very early example of reproducible computational research, incorporating a Fortran 66 program in its appendix to permit others to reproduce their results and run further examples. In this work my extensive attempts to perfectly reproduce the original results show the inherent challenge of reproducing computational research in the presence of ever-changing computing platforms and technology. Indeed, exact values could not be reproduced in this study, nor any other published study, because of hypersensitivity. Despite this, additional statistics allowed by modern computer capabilities almost completely agree with the qualitative observations and conclusions in the original work. Finally, in light of the need for high precision, it will be worthwhile to retest and reevaluate later studies of the internal dynamics of the model that faulted the code for behavior at odds with the theory.

Since the pioneering work of Herbert A. Simon, bounded rationality (BR) constitutes a viable alternative to utility maximization in settings characterized by uncertainty about the possible emergence of novel events, missing information, and limitations to human reasoning. Because of its realism, BR gained consensus in organization and management studies. However, BR is a theory of individual decision-making. Substantial extensions are required in order to turn it into a tool to analyze collective decision processes. Following an intuition by the late Simon himself, we submit that organizations channel information flows in ways that alleviate human BR. Thus, analysis and reconstruction of their structure as well as differential degrees and qualities of individual BR within organizations is key to extend this concept to collective decision-making. In this special issue we collected contributions where instances of BR couple with interaction structures to yield collective behavior. Tools range from mathematical models to experimental settings to computational models, testifying to the value of multiple approaches and perspectives.

Smith's (1962) demonstration that prices and allocations quickly converge to the competitive equilibrium in the continuous double auction (CDA) remains one of the most important results in experimental economics. Market experiments and exchange models have added considerably to our knowledge of how markets reach equilibrium, and how they respond to disruptions. Perhaps the best-known model of exchange in CDA market experiments is the random behavior 'zero-intelligence' (ZI) model by Gode and Sunder (1993). They argue that the CDA generates efficient allocations and 'convergence of transaction prices to the proximity of the theoretical equilibrium price,' provided only that agents meet their budget constraints. We demonstrate that prices do not converge in their simulations. Their budget constraint requires that a buyer's currency never exceeds her commodity value, which is an unnatural restriction. Their conclusion that market efficiency results from the structure of the CDA independent of traders' profit seeking behavior rests on their claim that the constraints that they impose are a part of the market institution. We show that actually they impose individual rationality. Misinterpretation of this behavioral constraint has led to unproductive debate on market adjustment processes.

We consider a stylized model of competition between two firms who provide a local service, for instance coffee-shops or hamburger chains. These firms are characterised by their quality of service, with one firm being high quality and the other being low quality. Quality impacts both the fixed and variable costs of the firms. The firms compete for customers in two areas, which are characterised by a different customer density. Firms decide in which area(s) to locate, and what price to charge. A firm entering both areas must charge the same price in both, i.e., price-discrimination is not allowed. We analyse the impact of cost levels and quality and density differences on the resulting market structure, prices, profits, customer surplus and social welfare. We show how the balance between fixed and variable cost determine the competitive conditions ranging from highly competitive markets to local monopolies under the same regulatory environment. Furthermore, in some areas with multiple equilibria the profitability of the firms is highly dependent on which of the possible equilibria is realised. The results can help explain some of the patterns observed in the location of chain outlets.

Change is ubiquitous in the study of organizations. Organizational change is characterized by multiple perspectives, both conceptually and methodologically. Computational modeling efforts are not the exception. In this work, we aim to provide an analysis of computational modeling approaches to organizational change. For that, we first review published works that directly connect to developing knowledge in organizational change from a computational lens. Second, we offer an account of unexplored topics in computational organizational change. Last, we highlight the potentialities of computer simulation models based on agent interactions in regard to how they could contribute to the understanding of central issues in this organizational research subfield.

Since its inception the science of physiology, like many other non-physical disciplines, has been guided in its development by the mechanical models of physics. That strategy has proven to be extraordinarily successful, even surviving the introduction of fractals into the modeling strategy. That is until quite recently. The true complexity of physiologic networks has been revealed with the development and implementation of ever more sensitive sensors and mathematically sophisticated data processing techniques. These developments have led to a divergence of the modeling strategies appropriate for the physical sciences from those for the life sciences. Therefore, we review how far the fractal concept has taken us into the non-mechanical interpretation of physiology. What emerges in this brief review of fractal physiology is the increasing importance of criticality, the cooperative nature of networks in physiologic behavior, and the importance of the fractional calculus in characterizing the dynamics of living systems. We draw some further inferences from the review and speculate as to what research directions might be most productive for continuing future success.

We discuss a computational model that describes stabilization of percept choices under intermittent viewing of an ambiguous visual stimulus at long stimulus intervals. Let T_off and T_on be the time that the stimulus is off and on, respectively. The behavior was studied by direct numerical simulation in a grid of (T_off, T_on) values in a 2007 paper of Noest, van Ee, Nijs, and van Wezel. They found that both alternating and repetitive sequences of percepts can appear stably, sometimes even for the same values of T_off and T_on. Longer T_off, however, always leads to a situation where, after transients, only repetitive sequences of percepts exist. We incorporate T_off and T_on explicitly as bifurcation parameters of an extended mathematical model of the perceptual choices. We elucidate the bifurcations of periodic orbits responsible for switching between alternating and repetitive sequences. We show that the stability borders of the alternating and repeating sequences in the (T_off, T_on) -parameter plane consist of curves of limit point and period-doubling bifurcations of periodic orbits. The stability regions overlap, resulting in a wedge with bistability of both sequences. We conclude by comparing our modeling results with the experimental results obtained by Noest, van Ee, Nijs, and van Wezel.

Gaze behavior represents a complex phenomenon in social inter-action. We focus here on dyadic face-to-face interaction during naturally occurring verbal exchanges, where shared attention can be operationalized by joint gazes and eye contact. A multi-step methodology for the analysis of eye synchrony is presented, exemplified by a single case. The dynamics of face-to-face interaction allows estimating the degree of interlocutors' synchrony. While there is growing evidence for interpersonal synchrony of various behavioral and physiological signals, eye synchrony has not yet been studied outside the laboratory. The method presented is based on time series of gaze behavior acquired by mobile eye tracking devices. We applied windowed cross-correlations to the data and used surrogate testing to attain effect sizes even for single interactions (Surrogate Synchrony, SUSY). SUSY thus integrates nomo-thetic with idiographic research goals: The nomothetic interest is to test hypotheses that gaze behavior may be generally synchronized and linked with psychological variables. The idiographic aspect is that effect sizes can be determined even in single-case studies owing to the surrogate analyses, which supports qualitative research. Results of the exemplary dataset suggested that proof-of-concept of this approach was attained. We describe what prerequisites are needed of a setting and technical setup for use in future studies of psychotherapy, counseling, negotiations, or work-related interactions.

The present study explores the role of convergent and divergent thinking in learning sciences from the nonlinear dynamical system (NDS) perspective. The participants (N=375) were fifth and sixth graders, aged 11-12, who were taking an introductory course in science. Students' understanding of physical phenomena, such as melting, boiling and evaporation was investigated as a function of four neo-Piagetian constructs via the difference-equation cusp catastrophe model. The nonlinear models where logical thinking acted as the asymmetry factor and field dependence/ independence, convergent thinking and divergent thinking acted as bifurcation factors, were superior, explaining 43-44% of the variance, whereas their linear alternatives explained 0-18%. Empirical evidence regarding the role of the above neo-Piagetian constructs at these early ages is reported for the first time and contributes to theory development within the NDS framework. Further, discussion about the significance of the findings is provided.

To further the understanding of how to build or reduce synchrony in a work team, we examined two principles for defining the optimal condition to produce or limit synchrony: (a) the empath-driver ratio (relative strength of the stronger influencer compared to the receptive strength of any member in the group), and (b) the balance between autocorrelated autonomic arousal (degree to which members' signals are independent of other group members) and the degree of influence that transfers from each group member to other group members. In study 1, we employed a series of computational simulations designed to manipulate the four variables. The results indicated that there is a four-way balance between driver strength, empath strength, autocorrelational and transfer effects among team members. The relationship between the synchronization coefficient and the empath-driver ratio was moderated by whether the group adopted a network structure for group problem solving or command-and-control. In study 2 we analyzed autonomic arousal (electrodermal response) in four teams of five participants playing a first-person shooter computer game. The correlation between the synchronization coefficient and the empath-driver ratio was 0.280 (p < .001) based on 64 pairs of observations. The relationship was moderated by both the network structure and the statistical model that one adopted to analyze dyadic relationships within the group. The implications of these relationships for a growing theory of team synchrony are discussed.