The Effect of Organizational Communication Media on Organizational Culture and Performance: An Agent-Based Simulation Model

This paper examines the mutual relationship between the communication richness of media used for conducting organizational communication and organizational culture. The richness of the media influences how well the organization might maintain its culture. On the other hand, a strong organizational culture allows a more effective use of the media by providing members with some of the necessary common ground to better understand the information exchanged. These relationships are investigated using an agent-based simulation model (ABM). Our ABM incorporates many partial theories into a coherent and fully defined model, which helps formalize and integrate those theories. Our model allows us to analyze non-linearities and interaction effects, which are difficult to investigate using other techniques. Additionally, the ABM allows us to investigate the dynamics of the phenomenon and generate hypotheses that could then be tested using empirical studies. Given the substantial resources necessary to conduct empirical studies, we think that the present ABM is valuable in helping guide data collection efforts. In this paper, we present results that show that organizational culture can influence the effectiveness of the media used for organizational communication and that a high media richness can help maintain and stabilize a culture. The effect of media richness on organizational culture depends on the initial strength of the culture. In general, for a given richness of the media, an initially strong culture stabilizes faster and becomes stronger through time than an initially weak culture. Additionally, the model suggests that a stable network of contacts among agents fosters a high achievement of organizational tasks. Conversely, when agents are forced to establish contacts with agents outside the usual network for doing their work, the accomplishment of tasks decreases.     

Mathematical Modeling and Analysis of an Epidemic Model with Quarantine, Latent and Media Coverage

Epidemic models are very important in today''s analysis of diseases. In this paper, we propose and analyze an epidemic model incorporating quarantine, latent, media coverage and time delay. We analyze the local stability of either the disease-free and endemic equilibrium in terms of the basic reproduction number $\mathcal{R}_{0}$ as a threshold parameter. We prove that if $\mathcal{R}_{0}<1,$ the time delay in media coverage can not affect the stability of the disease-free equilibrium and if $\mathcal{R}_{0}>1$, the model has at least one positive endemic equilibrium, the stability will be affected by the time delay and some conditions for Hopf bifurcation around infected equilibrium to occur are obtained by using the time delay as a bifurcation parameter. We illustrate our results by some numerical simulations such that we show that a proper application of quarantine plays a critical role in the clearance of the disease, and therefore a direct contact between people plays a critical role in the transmission of the disease.     

Individual behavior and macro social properties. An agent-based model

The paper aims at presenting an agent-based modeling exercise to illustrate how small differences in the cognitive properties of agents can generate very different macro social properties. We argue that it is not necessary to assume highly complicated cognitive architectures to introduce cognitive properties that matter for computational social science purposes. Our model is based on different simulation settings characterized by a gradual sophistication of behavior of agents, from simple heuristics to macro-micro feedback and other second-order properties. Agents are localized in a spatial interaction context. They have an individual task but are influenced by a collective coordination problem. The simulation results show that agents can generate efficiency at a macro level particularly when socio-cognitive sophistication of their behavior increases.

Experimentation and Learning in Repeated Cooperation

We study an agency model, in which the principal has only incomplete information about the agent's preferences, in a dynamic setting. Through repeated interaction with the agent, the principal learns about the agent's preferences and can thus adjust the inventive system. In a dynamic computational model, we compare different learning strategies of the principal when facing different types of agents. The results indicate that better learning of preferences can improve the situation of both parties, but the learning process is rather sensitive to random disturbances.     

Determination of heat transfer properties of media with a single-needle probe

Needle probes with a line heater inside are often used in studying the heat transfer properties of loose rocks. The key problem of contact methods of measuring thermal properties of various media consists in finding thermal contact resistance at the probe/medium interface which must be taken into account in determining the thermal diffusivity of the medium. We describe a mathematical model of heating of a long needle probe in the medium under study, taking into account dimensions and thermal properties of the needle source and assuming that thermal contact between the source and the medium is not ideal. Based on the proposed model, we formulate and solve the inverse problem of finding the thermal diffusivity coefficient of the medium and the heat exchange coefficient at the probe/medium interface. The purpose of the article is to create methodology for determining thermal properties of various media in the field.     

Multiscale decision-making: Bridging organizational scales in systems with distributed decision-makers

Decision-making in organizations is complex due to interdependencies among decision-makers (agents) within and across organizational hierarchies. We propose a multiscale decision-making model that captures and analyzes multiscale agent interactions in large, distributed decision-making systems. In general, multiscale systems exhibit phenomena that are coupled through various temporal, spatial and organizational scales. Our model focuses on the organizational scale and provides analytic, closed-form solutions which enable agents across all organizational scales to select a best course of action. By setting an optimal intensity level for agent interactions, an organizational designer can align the choices of self-interested agents with the overall goals of the organization. Moreover, our results demonstrate when local and aggregate information exchange is sufficient for system-wide optimal decision-making. We motivate the model and illustrate its capabilities using a manufacturing enterprise example.     

Optimal vaccine distribution in a spatiotemporal epidemic model with an application to rabies and raccoons

We formulate an S-I-R (Susceptible, Infected, Immune) spatiotemporal epidemic model as a system of coupled parabolic partial differential equations with no-flux boundary conditions. Immunity is gained through vaccination with the vaccine distribution considered a control variable. The objective is to characterize an optimal control, a vaccine program which minimizes the number of infected individuals and the costs associated with vaccination over a finite space and time domain. We prove existence of solutions to the state system and existence of an optimal control, as well as derive corresponding sensitivity and adjoint equations. Techniques of optimal control theory are then employed to obtain the optimal control characterization in terms of state and adjoint functions. To illustrate solutions, parameter values are chosen to model the spread of rabies in raccoons. Optimal distributions of oral rabies vaccine baits for homogeneous and heterogeneous spatial domains are compared. Numerical results reveal that natural land features affecting raccoon movement and the relocation of raccoons by humans can considerably alter the design of a cost-effective vaccination regime. We show that the use of optimal control theory in mathematical models can yield immediate insight as to when, where, and what degree control measures should be implemented.     

Free mobility and taste-homogeneity of jurisdiction structures

We consider a population of agents distributed on the unit interval. Agents form jurisdictions in order to provide a public facility and share its costs equally. This creates an incentive to form large entities. Individuals also incur a transportation cost depending on their location and that of the facility which makes small jurisdictions advantageous. We consider a fairly general class of distributions of agents and generalize previous versions of this model by allowing for non-linear transportation costs. We show that, in general, jurisdictions are not necessarily homogeneous. However, they are if facilities are always intraterritory and transportation costs are superadditive. Superadditivity can be weakened to strictly increasing and strictly concave when agents are uniformly distributed.     

Hertzian contact problem: Numerical reduction and volumetric modification

A technique for the analytical formulation and numerical implementation of an elastic contact model for rigid bodies in the framework of the Hertzian contact problem is described. The normal elastic force and the semiaxes of the contact area are computed so that the problem is sequentially reduced to a scalar transcendental equation depending on complete elliptic integrals of the first and second kinds. Based on the classical solution to the Hertzian contact problem, an invariant volumetric force function is proposed that depends on the geometric characteristics of interpenetration of two undeformed bodies. The normal forces computed using the force function agree with results obtained previously for non-Hertzian contact of elastic bodies. As an example, a ball bearing is used to compare the contact dynamics of elastic bodies simulated in the classical Hertzian model and its volumetric modification.     

基于多技能多渠道变成本的物流联络中心排班

物流联络中心的人力成本随着坐席拥有的技能、服务渠道的多少以及服务时段的不同而不同,对人员进行合理班次设计以节省人力成本尤为必要。考虑现实联络中心工作时间的连续与中断、技能组和渠道组的匹配等,提出采用分阶段法优化班次。首先给出不考虑时间中断的坐席的排班模型A,求得排班方案;接下来,在此基础上将中断时间约束加入,建立模型B,求得班次覆盖矩阵;最后加入排班调整约束,建立模型C,对多技能组中各渠道组进行调整,给出最符合实际情况的最优排班调整方案。数值实验结合物流企业实例和各方案的比较,验证了模型的有效性。该方法为联络中心排班提供了新思路,对其它服务行业的排班也具有一定的参考价值。     

A differential variational inequality in the study of contact problems with wear

We start with a mathematical model which describes the sliding contact of a viscoelastic body with a moving foundation. The contact is frictional and the wear of the contact surfaces is taken into account. We prove that this model leads to a differential variational inequality in which the unknowns are the displacement field and the wear function. Then, inspired by this model, we consider a general differential variational inequality in reflexive Banach spaces, governed by four parameters. We prove the unique solvability of the inequality as well as the continuous dependence of its solution with respect to the parameters. The proofs are based on arguments of monotonicity, compactness, convex analysis and lower semicontinuity. Then, we apply these abstract results to the mathematical model of contact for which we deduce the existence of a unique solution as well as the existence of optimal control for an associate optimal control problem. We also present the corresponding mechanical interpretations.     

On Effective Models of Porous Stratified Media with a Sliding Contact Between Layers

In order to study wave propagation in porous layered media with a sliding contact between the elastic phases on the interfaces, effective models of these media are investigated. For these models, the front sets of four waves excited by point sources are established and formulas for the wave velocities along the axes are derived. The methods of constructing the front sets applied in this paper allow one to point out special features of these front sets such as loops and juts. The particular case where all of the layers are identical and a sliding contact occurs between layers is also considered. Bibliography: 8 titles.     

On the predictive capabilities of a multiphase SPH model for hydrodynamic spreading dynamics

We assess the predictive capabilities of a multiphase Smoothed-Particle Hydrodynamics (SPH) model to simulate two-phase flow processes that are decisively governed by the dynamics of hydrodynamically moving contact lines. The spreading of a liquid droplet on a completely wettable, smooth and flat substrate serves as prototype validation problem. Our simulation results reproduce the main features of hydrodynamic spreading in the quasi-static limit, i. e. when the balance of viscous and capillary forces near the contact line governs the dynamics. The exponential spreading rate is consistent with Tanner's law. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Analysis and control of stationary inclusions in contact mechanics

We start with a mathematical model which describes the frictionless contact of an elastic body with an obstacle and prove that it leads to a stationary inclusion for the strain field. Then, inspired by this contact model, we consider a general stationary inclusion in a real Hilbert space, governed by three parameters. We prove the unique solvability of the inclusion as well as the continuous dependence of its solution with respect to the parameters. We use these results in the study of an associated optimal control problem for which we prove existence and convergence results. The proofs are based on arguments of monotonicity, compactness, convex analysis and lower semicontinuity. Then, we apply these abstract results to the mathematical model of contact and provide the corresponding mechanical interpretations.     

Optimal control of information epidemics modeled as Maki Thompson rumors

We model the spread of information in a homogeneously mixed population using the Maki Thompson rumor model. We formulate an optimal control problem, from the perspective of single campaigner, to maximize the spread of information when the campaign budget is fixed. Control signals, such as advertising in the mass media, attempt to convert ignorants and stiflers into spreaders. We show the existence of a solution to the optimal control problem when the campaigning incurs non-linear costs under the isoperimetric budget constraint. The solution employs Pontryagin’s Minimum Principle and a modified version of forward backward sweep technique for numerical computation to accommodate the isoperimetric budget constraint. The techniques developed in this paper are general and can be applied to similar optimal control problems in other areas.We have allowed the spreading rate of the information epidemic to vary over the campaign duration to model practical situations when the interest level of the population in the subject of the campaign changes with time. The shape of the optimal control signal is studied for different model parameters and spreading rate profiles. We have also studied the variation of the optimal campaigning costs with respect to various model parameters. Results indicate that, for some model parameters, significant improvements can be achieved by the optimal strategy compared to the static control strategy. The static strategy respects the same budget constraint as the optimal strategy and has a constant value throughout the campaign horizon. This work finds application in election and social awareness campaigns, product advertising, movie promotion and crowdfunding campaigns.     

SDML: A Multi-Agent Language for Organizational Modelling

A programming language which is optimized for modelling multi-agent interaction within articulated social structures such as organizations is described with several examples of its functionality. The language is SDML, a strictly declarative modelling language which has object-oriented features and corresponds to a fragment of strongly grounded autoepistemic logic. The virtues of SDML include the ease of building complex models and the facility for representing agents flexibly as models of cognition as well as modularity and code reusability. Two representations of cognitive agents within organizational structures are reported and a Soar-to-SDML compiler is described. One of the agent representations is a declarative implementation of a Soar agent taken from the Radar-Soar model of Ye and Carley (1995). The Ye-Carley results are replicated but the declarative SDML implementation is shown to be much less computationally expensive than the more procedural Soar implementation. As a result, it appears that SDML supports more elaborate representations of agent cognition together with more detailed articulation of organizational structure than we have seen in computational organization theory. Moreover, by representing Soar-cognitive agents declaratively within SDML, that implementation of the Ye-Carley specification is necessarily consistent and sound with respect to the formal logic to which SDML corresponds.     

Microfoundations for diffusion price processes

We study microeconomic foundations of diffusion processes as models of stock price dynamics. To this end, we develop a microscopic model of a stock market with finitely many heterogeneous economic agents, who trade in continuous time, giving rise to an endogeneous pure-jump process describing the evolution of stock prices over time. When the number of agents in the market is large, we show that the price process can be approximated by a diffusion, with price-dependent drift and volatility coefficients that are determined by small excess demands and trading volume in the microscopic model. We extend the microscopic model further by allowing for non-market interactions between agents, to model herd behavior in the market. In this case, price dynamics can be approximated by a process with stochastic volatility. Finally, we demonstrate how heavy-tailed stock returns emerge when agents have a strong tendency towards herd behavior.     

Additive hazards regression with random effects for clustered failure times

Additive hazards model with random effects is proposed for modelling the correlated failure time data when focus is on comparing the failure times within clusters and on estimating the correlation between failure times from the same cluster, as well as the marginal regression parameters. Our model features that, when marginalized over the random effect variable, it still enjoys the structure of the additive hazards model. We develop the estimating equations for inferring the regression parameters. The proposed estimators are shown to be consistent and asymptotically normal under appropriate regularity conditions. Furthermore, the estimator of the baseline hazards function is proposed and its asymptotic properties are also established. We propose a class of diagnostic methods to assess the overall fitting adequacy of the additive hazards model with random effects. We conduct simulation studies to evaluate the finite sample behaviors of the proposed estimators in various scenarios. Analysis of the Diabetic Retinopathy Study is provided as an illustration for the proposed method.     

Deffuant model with general opinion distributions: First impression and critical confidence bound

In the Deffuant model for social influence, pairs of adjacent agents interact at a constant rate and mix up their opinions (represented by continuous variables) only if the distance between opinions is short according to a threshold. We derive a critical threshold for the Deffuant model on , above which the opinions converge toward the average value of the initial opinion distribution with probability one, provided the initial distribution has a finite second order moment. We demonstrate our theoretical results by performing extensive numerical simulations on some continuous probability distributions including uniform, Beta, power‐law and normal distributions. Noticed is a clear differentiation of convergence rate that unimodal opinions (regardless of being biased or not) achieve consensus much faster than even or polarized opinions. Hereby, the emergence of a single mainstream view is a prominent feature giving rise to fast consensus in public opinion formation and social contagious behavior. Finally, we discuss the Deffuant model on an infinite Cayley tree, through which general network architectures might be factored in. © 2013 Wiley Periodicals, Inc. Complexity 19: 38–49, 2013     

Strong reciprocity, social structure, and the evolution of fair allocations in a simulated ultimatum game

Cooperation has long been an enigma in the life and social sciences. A possible explanation for the phenomenon is the recently developed idea of strong reciprocity in which agents altruistically reward those that cooperate and altruistically punish those that do not. The acts are altruistic in the sense that when agents punish or reward they incur a cost but receive no material benefit. Both experimentalists and modelers have focused primarily on third-party altruistic punishment mechanisms yet rarely discuss how they establish a cost for punishing. In this study I used agent-based modelling to test the ability of altruistic punishment to elicit fair allocations in a simulated ultimatum game. In particular I simulated agents with the ability to punish neighbors whose offers were deemed too low while systematically varying the ratio of costs between punisher and punishee. Despite several studies in which strong reciprocity is shown to induce cooperation, altruistic punishment failed to evolve fair allocations in these simulations. However, outcomes were highly dependant on the spatial structure of agents in the simulations and fair allocations did evolve in a linearly structured population even in the absence of punishment. As the number of immediate neighbors increased, mean offers fell but still remained significantly greater than that predicted by standard economic theory. Only when social structure was removed, and agents could interact with any other agent in the population, did offers in the simulated ultimatum game match theoretical expectations.