El Outsourcing en la dinámica de sistemas hacia mercados extranjeros

Este trabajo recopila literatura académica relevante sobre estrategias de entrada y metodologías para la toma de decisión sobre la contratación de servicios de Outsourcing para el caso de empresas que planean expandirse hacia mercados extranjeros. La manera en que una empresa planifica su entrada a un mercado extranjero, y realiza la consideración y evaluación de información relevante y el diseño de la estrategia, determina el éxito o no de la misma. De otro lado, las metodologías consideradas se concentran en el nivel estratégico de la pirámide organizacional. Se parte de métodos simples para llegar a aquellos basados en la Teoría de Decisión Multicriterio, tanto individuales como híbridos. Finalmente, se presenta la Dinámica de Sistemas como herramienta valiosa en el proceso, por cuanto puede combinarse con métodos multicriterio.

Diseño y Evaluación de intervenciones en organizaciones empresariales desde la dinámica de sistemas – revisión teórica. Sistemas – Revisión Teórica.

Este trabajo tiene como objetivo hacer una revisión teórica desde los inicios de la Teoría General de Sistemas, hasta el desarrollo de la dinámica de sistemas, todo lo que estas dos teorías plantean, además de muchas otras teorías de las cuales estas se encuentran rodeadas y conectadas muy cercanamente, ya que partiendo del planteamiento que hizo el biólogo Ludwig Von Bertalanffy se derivaron diversas corrientes de pensamiento, todas alrededor del enfoque y pensamiento de sistemas, y de la cual se deriva la más importante para nosotros en este trabajo de la cual es padre el Ingeniero Jay Wright Forrester, la Dinámica de Sistemas. Muchas de estas otras teorías tienen como objetivo generar estrategias de cambio en las organizaciones mediante diferentes metodologías, pero todas con el fin de alcanzar un desempeño óptimo en los procesos que son realizados en las organizaciones. Este proyecto es planteado ante la necesidad de tener un amplio conocimiento teórico de todo lo que conllevan los planteamientos de la Dinámica de Sistemas los cuales van de la mano junto con el pensamiento sistémico y el modelamiento organizacional, el cual veremos cómo es desarrollado desde el enfoque de la Dinámica de Sistemas a través de distintos modelos y en la actualidad herramientas informáticas tales como software diseñados exclusivamente para el modelamiento desde la Dinámica de Sistemas.

Análisis de sensibilidad para un modelo de medición de percepción de marca basado en simulación computacional por agentes

Se presenta el análisis de sensibilidad de un modelo de percepción de marca y ajuste de la inversión en marketing desarrollado en el Laboratorio de Simulación de la Universidad del Rosario. Este trabajo de grado consta de una introducción al tema de análisis de sensibilidad y su complementario el análisis de incertidumbre. Se pasa a mostrar ambos análisis usando un ejemplo simple de aplicación del modelo mediante la aplicación exhaustiva y rigurosa de los pasos descritos en la primera parte. Luego se hace una discusión de la problemática de medición de magnitudes que prueba ser el factor más complejo de la aplicación del modelo en el contexto práctico y finalmente se dan conclusiones sobre los resultados de los análisis.

Desarrollo de un estado de la cuestión acerca de las interacciones entre el control de gestión y el aprendizaje organizacional.

Las organizaciones en la actualidad deben encontrar diferentes maneras de sobrevivir en un tiempo de rápida transformación. Uno de los mecanismos usados por las empresas para adaptarse a los cambios organizacionales son los sistemas de control de gestión, que a su vez permiten a las organizaciones hacer un seguimiento a sus procesos, para que la adaptabilidad sea efectiva. Otra variable importante para la adaptación es el aprendizaje organizacional siendo el proceso mediante el cual las organizaciones se adaptan a los cambios del entorno, tanto interno como externo de la compañía. Dado lo anterior, este proyecto se basa en la extracción de documentación soporte valido, que permita explorar las interacciones entre estos dos campos, los sistemas de control de gestión y el aprendizaje organizacional, además, analizar el impacto de estas interacciones en la perdurabilidad organizacional. ​

Modelización bajo el enfoque de dinámica de sistemas de una cadena de abastecimiento para la industria vitivinícola

El proyecto de tesis denominado “Modelización bajo el enfoque de dinámica de sistemas de una cadena de abastecimiento para la industria vitivinícola” busca construir un modelo que aporte una solución óptima al problema logístico encontrado en la cadena de suministro, para que empresas nacionales o internacionales que tengan un funcionamiento similar al del sistema estudiado, puedan tomarlo como ejemplo o referencia. Así mismo, esta investigación pretende encontrar los problemas más frecuentes en cadenas de este tipo con el fin de construir un marco conceptual y teórico fundamentado en la Teoría General de Sistemas (TGS) que genere finalmente un modelo basado en la dinámica de sistemas el cual permitirá a las empresas diseñar y comparar las diferentes intervenciones derivadas del modelo que propicien la generación de capacidades dirigidas al logro de la competitividad de forma perdurable.

Gestión de la cadena de suministros desde la dinámica de sistemas. Aproximación al mejoramiento de la toma de decisiones

El objetivo de este trabajo es hacer un estudio sobre la cadena de suministros en organizaciones empresariales desde la Dinámica de Sistemas y como esta puede aportar al desempeño y el control de las cadenas de suministros. Se buscará Abordar el cocimiento sobre tres perspectivas de Supply Chain y su relación con la dinámica de sistemas. También se buscará identificar los tipos de integración en las actividades de la gestión en la cadena de suministros y sus horizontes de planeación. Por último, se pretende analizar las aplicaciones de Supply Chain Management que se han basado en el uso de la metodología de dinámica de sistemas. Para esto, la investigación empezará por definir la problemática alrededor de unir estas dos áreas y definirá el marco teórico que fundan estas dos disciplinas. Luego se abordará la metodología usada por la Dinámica de Sistemas y los diferentes aspectos de la cadena de suministros. Se Ahondará en el acercamiento de las dos disciplinas y como convergen ayudando la SD a la SCM (Supply Chain Management). En este punto también se describirán los trabajos en los diferentes enfoques que se han hecho a partir de uso de la dinámica de sistemas. Por último, presentaremos las correspondientes conclusiones y comentarios acerca de este campo de investigación y su pertinencia en el campo de la Supply Chain. Esta investigación abarca dos grandes corrientes de pensamiento, una sistémica, a través de la metodología de dinámica de sistemas y la otra, lógico analítica la cual es usada en Supply Chain. Se realizó una revisión de la literatura sobre las aplicaciones de dinámica de sistemas (SD) en el área de Supply Chain, sus puntos en común y se documentaron importantes empleos de esta metodología que se han hecho en la gestión de la cadena de suministros.

Design of a minimum variance multiple input-multiple output neuro self-tuning proportional-integral-derivative controller for non-linear dynamic systems

In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

Experimental design and model construction algorithms for radial basis function networks

New construction algorithms for radial basis function (RBF) network modelling are introduced based on the A-optimality and D-optimality experimental design criteria respectively. We utilize new cost functions, based on experimental design criteria, for model selection that simultaneously optimizes model approximation, parameter variance (A-optimality) or model robustness (D-optimality). The proposed approaches are based on the forward orthogonal least-squares (OLS) algorithm, such that the new A-optimality- and D-optimality-based cost functions are constructed on the basis of an orthogonalization process that gains computational advantages and hence maintains the inherent computational efficiency associated with the conventional forward OLS approach. The proposed approach enhances the very popular forward OLS-algorithm-based RBF model construction method since the resultant RBF models are constructed in a manner that the system dynamics approximation capability, model adequacy and robustness are optimized simultaneously. The numerical examples provided show significant improvement based on the D-optimality design criterion, demonstrating that there is significant room for improvement in modelling via the popular RBF neural network.

e-learning in project management using simulation models: a case study based on the replication of an experiment

Current e-learning systems are increasing their importance in higher education. However, the state of the art of e-learning applications, besides the state of the practice, does not achieve the level of interactivity that current learning theories advocate. In this paper, the possibility of enhancing e-learning systems to achieve deep learning has been studied by replicating an experiment in which students had to learn basic software engineering principles. One group learned these principles using a static approach, while the other group learned the same principles using a system-dynamics-based approach, which provided interactivity and feedback. The results show that, quantitatively, the latter group achieved a better understanding of the principles; furthermore, qualitatively, they enjoyed the learning experience

Vertical and horizontal processes in the global atmosphere and the maximum entropy production conjecture

The objective of this paper is to reconsider the Maximum Entropy Production conjecture (MEP) in the context of a very simple two-dimensional zonal-vertical climate model able to represent the total material entropy production due at the same time to both horizontal and vertical heat fluxes. MEP is applied first to a simple four-box model of climate which accounts for both horizontal and vertical material heat fluxes. It is shown that, under condition of fixed insolation, a MEP solution is found with reasonably realistic temperature and heat fluxes, thus generalising results from independent two-box horizontal or vertical models. It is also shown that the meridional and the vertical entropy production terms are independently involved in the maximisation and thus MEP can be applied to each subsystem with fixed boundary conditions. We then extend the four-box model by increasing its resolution, and compare it with GCM output. A MEP solution is found which is fairly realistic as far as the horizontal large scale organisation of the climate is concerned whereas the vertical structure looks to be unrealistic and presents seriously unstable features. This study suggest that the thermal meridional structure of the atmosphere is predicted fairly well by MEP once the insolation is given but the vertical structure of the atmosphere cannot be predicted satisfactorily by MEP unless constraints are imposed to represent the determination of longwave absorption by water vapour and clouds as a function of the state of the climate. Furthermore an order-of-magnitude estimate of contributions to the material entropy production due to horizontal and vertical processes within the climate system is provided by using two different methods. In both cases we found that approximately 40 mW m−2 K−1 of material entropy production is due to vertical heat transport and 5–7 mW m−2 K−1 to horizontal heat transport

Simulation models in farming systems research : potential and challenges

Integrated simulation models can be useful tools in farming system research. This chapter reviews three commonly used approaches, i.e. linear programming, system dynamics and agent-based models. Applications of each approach are presented and strengths and drawbacks discussed. We argue that, despite some challenges, mainly related to the integration of different approaches, model validation and the representation of human agents, integrated simulation models contribute important insights to the analysis of farming systems. They help unravelling the complex and dynamic interactions and feedbacks among bio-physical, socio-economic, and institutional components across scales and levels in farming systems. In addition, they can provide a platform for integrative research, and can support transdisciplinary research by functioning as learning platforms in participatory processes.

Steering without Circe : attending to reinforcing loops in social systems

Relating system dynamics to the broad systems movement, the key notion is that reinforcing loops deserve no less attention than balancing loops. Three specific propositions follow. First, since reinforcing loops arise in surprising places, investigations of complex systems must consider their possible existence and potential impact. Second, because the strength of reinforcing loops can be misinferred - we include an example from the field of servomechanisms - computer simulation can be essential. Be it project management, corporate growth or inventory oscillation, simulation helps to assess consequences of reinforcing loops and options for interventions. Third, in social systems the consequences of reinforcing loops are not inevitable. Examples concerning globalization illustrate how difficult it might be to challenge such assumptions. However, system dynamics and ideas from contemporary social theory help to show that even the most complex social systems are, in principle, subject to human influence. In conclusion, by employing these ideas, by attending to reinforcing as well as balancing loops, system dynamics work can improve the understanding of social systems and illuminate our choices when attempting to steer them.

Scenario and modelling uncertainty in global mean temperature change derived from emission-driven global climate models

We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission-driven rather than concentration-driven perturbed parameter ensemble of a global climate model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration-driven simulations (with 10–90th percentile ranges of 1.7 K for the aggressive mitigation scenario, up to 3.9 K for the high-end, business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 K (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission-driven experiments, they do not change existing expectations (based on previous concentration-driven experiments) on the timescales over which different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in the case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration scenarios used to drive GCM ensembles, lies towards the lower end of our simulated distribution. This design decision (a legacy of previous assessments) is likely to lead concentration-driven experiments to under-sample strong feedback responses in future projections. Our ensemble of emission-driven simulations span the global temperature response of the CMIP5 emission-driven simulations, except at the low end. Combinations of low climate sensitivity and low carbon cycle feedbacks lead to a number of CMIP5 responses to lie below our ensemble range. The ensemble simulates a number of high-end responses which lie above the CMIP5 carbon cycle range. These high-end simulations can be linked to sampling a number of stronger carbon cycle feedbacks and to sampling climate sensitivities above 4.5 K. This latter aspect highlights the priority in identifying real-world climate-sensitivity constraints which, if achieved, would lead to reductions on the upper bound of projected global mean temperature change. The ensembles of simulations presented here provides a framework to explore relationships between present-day observables and future changes, while the large spread of future-projected changes highlights the ongoing need for such work.

Effect of disease-selective predation on prey infected by contact and external sources

We propose and analyze a simple mathematical model for susceptible prey (S)–infected prey (I)–predator (P) interaction, where the susceptible prey population (S) is infected directly from external sources as well as through contact with infected class (I) and the predator completely avoids consuming the infected prey. The model is analyzed to obtain different thresholds of the key parameters under which the system exhibits stability around the biologically feasible equilibria. Through numerical simulations we display the effects of external infection and the infection through contact on the system dynamics in the absence as well as in the presence of the predator. We compare the system dynamics when infection occurs only through contact, with that when it occurs through contact and external sources. Our analysis demonstrates that under a disease-selective predation, stability and oscillations of the system is determined by two key parameters: the external infection rate and the force of infection through contact. Due to the introduction of external infection, the predator and the prey population show limit-cycle oscillations over a range parametric values. We suggest that while predicting the dynamics of such an eco-epidemiological system, the modes of infection and the infection rates might be carefully investigated.

An interdisciplinary modelling approach asessing the cost-effectiveness of agri-environmental measures on reducing nutrient concentration to WFD thresholds under climate change: the case of the Louros catchment

The application of the Water Framework Directive (WFD) in the European Union (EU) targets certain threshold levels for the concentration of various nutrients, nitrogen and phosphorous being the most important. In the EU, agri-environmental measures constitute a significant component of Pillar 2—Rural Development Policies in both financial and regulatory terms. Environmental measures also are linked to Pillar 1 payments through cross-compliance and the greening proposals. This paper drawing from work carried out in the REFRESH FP7 project aims to show how an INtegrated CAtchment model of plant/soil system dynamics and instream biogeochemical and hydrological dynamics can be used to assess the cost-effectiveness of agri-environmental measures in relation to nutrient concentration targets set by the WFD, especially in the presence of important habitats. We present the procedures (methodological steps, challenges and problems) for assessing the cost-effectiveness of agri-environmental measures at the baseline situation, and climate and land use change scenarios. Furthermore, we present results of an application of this methodology to the Louros watershed in Greece and discuss the likely uses and future extensions of the modelling approach. Finally, we attempt to reveal the importance of this methodology for designing and incorporating alternative environmental practices in Pillar 1 and 2 measures.