887 resultados para Problem Behavior Theory
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Using data from 65,485 Chinese private small and medium-sized enterprises over the period 2000-2006, we examine the extent to which firms can improve access to debt by adopting strategies aimed at building social capital, namely entertaining and gift giving to others in their social network, and obtaining political affiliation. We find that although entertainment and gift-giving expenditure leads to higher levels of total and short-term debt, it does not enable firms to obtain greater long-term debt. In contrast, we demonstrate that obtaining political affiliation allows firms greater access to long-term debt.
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Even simple hybrid systems like the classic bouncing ball can exhibit Zeno behaviors. The existence of this type of behavior has so far forced simulators to either ignore some events or risk looping indefinitely. This in turn forces modelers to either insert ad hoc restrictions to circumvent Zeno behavior or to abandon hybrid modeling. To address this problem, we take a fresh look at event detection and localization. A key insight that emerges from this investigation is that an enclosure for a given time interval can be valid independently of the occurrence of a given event. Such an event can then even occur an unbounded number of times, thus making it possible to handle certain types of Zeno behavior.
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Purpose – To propose and investigate a stable numerical procedure for the reconstruction of the velocity of a viscous incompressible fluid flow in linear hydrodynamics from knowledge of the velocity and fluid stress force given on a part of the boundary of a bounded domain. Design/methodology/approach – Earlier works have involved the similar problem but for stationary case (time-independent fluid flow). Extending these ideas a procedure is proposed and investigated also for the time-dependent case. Findings – The paper finds a novel variation method for the Cauchy problem. It proves convergence and also proposes a new boundary element method. Research limitations/implications – The fluid flow domain is limited to annular domains; this restriction can be removed undertaking analyses in appropriate weighted spaces to incorporate singularities that can occur on general bounded domains. Future work involves numerical investigations and also to consider Oseen type flow. A challenging problem is to consider non-linear Navier-Stokes equation. Practical implications – Fluid flow problems where data are known only on a part of the boundary occur in a range of engineering situations such as colloidal suspension and swimming of microorganisms. For example, the solution domain can be the region between to spheres where only the outer sphere is accessible for measurements. Originality/value – A novel variational method for the Cauchy problem is proposed which preserves the unsteady Stokes operator, convergence is proved and using recent for the fundamental solution for unsteady Stokes system, a new boundary element method for this system is also proposed.
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We use the self-concept based theory of leadership and social exchange theory to hypothesize processes linking transformational leadership to follower performance outcomes. Specifically, we hypothesize that (a) transformational leadership relates to followers' work engagement both directly and indirectly through their psychological states, (b) work engagement relates to innovative behavior, (c) innovative behavior relates to task performance, and (d) the work engagement–innovative behavior relationship is moderated by leader–member exchange. Results from a test of these relationships in a sample of employees of a large telecommunication company in China largely support our hypothesized model.
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We analyze the steady-state propagation of optical pulses in fiber transmission systems with lumped nonlinear optical devices (NODs) placed periodically in the line. For the first time to our knowledge, a theoretical model is developed to describe the transmission regime with a quasilinear pulse evolution along the transmission line and the point action of NODs. We formulate the mapping problem for pulse propagation in a unit cell of the line and show that in the particular application to nonlinear optical loop mirrors, the steady-state pulse characteristics predicted by the theory accurately reproduce the results of direct numerical simulations. © 2005 Springer Science+Business Media, Inc.
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If history matters for organization theory, then we need greater reflexivity regarding the epistemological problem of representing the past; otherwise, history might be seen as merely a repository of ready-made data. To facilitate this reflexivity, we set out three epistemological dualisms derived from historical theory to explain the relationship between history and organization theory: (1) in the dualism of explanation, historians are preoccupied with narrative construction, whereas organization theorists subordinate narrative to analysis; (2) in the dualism of evidence, historians use verifiable documentary sources, whereas organization theorists prefer constructed data; and (3) in the dualism of temporality, historians construct their own periodization, whereas organization theorists treat time as constant for chronology. These three dualisms underpin our explication of four alternative research strategies for organizational history: corporate history, consisting of a holistic, objectivist narrative of a corporate entity; analytically structured history, narrating theoretically conceptualized structures and events; serial history, using replicable techniques to analyze repeatable facts; and ethnographic history, reading documentary sources "against the grain." Ultimately, we argue that our epistemological dualisms will enable organization theorists to justify their theoretical stance in relation to a range of strategies in organizational history, including narratives constructed from documentary sources found in organizational archives. Copyright of the Academy of Management, all rights reserved.
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Existing studies on the role of switching costs (SC) as moderator of the relationship between satisfaction and repurchase behavior are inconclusive. We attempt to explain these inconclusive findings by synthesizing an amplifying and a lock-in effect, and hypothesize a nonlinear moderating effect. In Study 1 (a main study and three replications), we find strong evidence for an inverted u-shaped moderating effect of overall SC. Our results suggest that satisfaction is a particularly important predictor of repurchase behavior in situations characterized by medium-levels of SC. Based on Prospect Theory, Study 2 (a main study and one replication) reveals that this inverted u-shaped moderating effect of SC is stronger for positive (relational and financial) SC than for negative (procedural) SC. We conclude with recommendations for satisfaction management of different customer segments, and describe possibilities to influence customer switching costs in various industries. © 2014 New York University.
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Optimal stochastic controller pushes the closed-loop behavior as close as possible to the desired one. The fully probabilistic design (FPD) uses probabilistic description of the desired closed loop and minimizes Kullback-Leibler divergence of the closed-loop description to the desired one. Practical exploitation of the fully probabilistic design control theory continues to be hindered by the computational complexities involved in numerically solving the associated stochastic dynamic programming problem. In particular very hard multivariate integration and an approximate interpolation of the involved multivariate functions. This paper proposes a new fully probabilistic contro algorithm that uses the adaptive critic methods to circumvent the need for explicitly evaluating the optimal value function, thereby dramatically reducing computational requirements. This is a main contribution of this short paper.
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The summary of automata theory ontology is presented in the paper. It is based on the following dependences: a type of an automaton – the language accepted by the automaton – applications. The given ontology does not claim to be exhaustive as automata theory is very extensive and it is a complicated problem to survey all its aspects within one article. Only the main properties of automata and their applications are considered.
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This paper is a survey of our recent results on the bispectral problem. We describe a new method for constructing bispectral algebras of any rank and illustrate the method by a series of new examples as well as by all previously known ones. Next we exhibit a close connection of the bispectral problem to the representation theory of W1+∞–algerba. This connection allows us to explain and generalise to any rank the result of Magri and Zubelli on the symmetries of the manifold of the bispectral operators of rank and order two.
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This paper considers the problem of concept generalization in decision-making systems where such features of real-world databases as large size, incompleteness and inconsistence of the stored information are taken into account. The methods of the rough set theory (like lower and upper approximations, positive regions and reducts) are used for the solving of this problem. The new discretization algorithm of the continuous attributes is proposed. It essentially increases an overall performance of generalization algorithms and can be applied to processing of real value attributes in large data tables. Also the search algorithm of the significant attributes combined with a stage of discretization is developed. It allows avoiding splitting of continuous domains of insignificant attributes into intervals.
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In the specific area of software engineering (SE) for self-adaptive systems (SASs) there is a growing research awareness about the synergy between SE and artificial intelligence (AI). However, just few significant results have been published so far. In this paper, we propose a novel and formal Bayesian definition of surprise as the basis for quantitative analysis to measure degrees of uncertainty and deviations of self-adaptive systems from normal behavior. A surprise measures how observed data affects the models or assumptions of the world during runtime. The key idea is that a "surprising" event can be defined as one that causes a large divergence between the belief distributions prior to and posterior to the event occurring. In such a case the system may decide either to adapt accordingly or to flag that an abnormal situation is happening. In this paper, we discuss possible applications of Bayesian theory of surprise for the case of self-adaptive systems using Bayesian dynamic decision networks. Copyright © 2014 ACM.
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The usual assumption that the processing times of the operations are known in advance is the strictest one in scheduling theory. This assumption essentially restricts practical aspects of deterministic scheduling theory since it is not valid for the most processes arising in practice. The paper is devoted to a stability analysis of an optimal schedule, which may help to extend the significance of scheduling theory for decision-making in the real-world applications. The term stability is generally used for the phase of an algorithm, at which an optimal solution of a problem has already been found, and additional calculations are performed in order to study how solution optimality depends on variation of the numerical input data.
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Mathematics Subject Classification: 26A33, 74B20, 74D10, 74L15