In a globally operating company, when a country management team base their opposition to the global product marketing strategy on a System Dynamics simulation tool, the model is definitely to support communication across the management layers in a bottom-up way. To reach out to stakeholders and global management at the HQ, neither of them being familiar with the System Dynamics approach, its not sufficient to provide a technically convincing simulation tool. This paper describes a bottom-up model building initiative and its vital educational component. Building the model with the client had to both grow ownership at the country level, overcome "black-box" attitudes and establish a shared understanding for the approach at the stakeholder level in order to structure the discussion about critical issues beyond trailing market dynamics or covering up by fanciful statistics.
Keywords: Black box, Stakeholder, Ownership
An important class of decision problems involve the selection of a policy in the presence of both uncertainty regarding future eventualities and a system exhibiting complex policy response. Within this paper, we examine the performance benefits of performing strategy selection for such problems using a hybrid modeling approach that combines decision analysis and system dynamics. Within this approach, a modeler uses a decision tree to encapsulate choices, uncertainties, and consequences (the last computed by a system dynamics model). While this hybrid technique offers many additional advantages in terms of expressiveness and the encouragment of systematic investigation of policy space, this paper focuses on the performance gains it provides. In particular, the use of decision trees to represent such decision problems permits the use of dynamic programming, which can dramatically decrease the costs of identifying a preferred policy beyond what is possible by evaluating possible policies in turn. The paper quantifies these performance advantages by means of recurrence relations for arbitrary trees, and derives inductively proven closed-form expressions of performance gain for complete trees. The results suggest that the hybrid method yields speedups exponential in the depth of the tree for both complete and randomly generated trees.
Overreaction to supply shortages can create havoc in supply chains, costing millions of dollars in
excess inventory and manufacturing capacity. In an experiment with the Beer Distribution Game, we
explore overreaction to shortages as a complementary behavioral cause of supply chain instability. As
in previous studies, we find that players ignore the supply line. We find, however, that instead of
overreacting to shortages, players limit the size of their order adjustment while aiming for higher than
necessary inventory level; a policy that is more stable than the linear response suggested in previous
studies. Since an ordering rule that fails to account for the supply line leads to higher than necessary
costs and order amplification, our results suggest that players are not fully rational. However,
evaluating the performance of the estimated policy we find that, given the information cues available,
players show bounded rationality and develop a satisficing replenishment decision rule that minimizes
local cost at the expense of higher upstream cost. We explore the implications of these findings for the
design of information and incentive systems for supply chain management.
In a previous work the philosophical concept of Mechanism was proposed in order to characterize the kind of scientific explanations provided by the system dynamics approach. That earlier paper positioned such idea epistemologically contrasting it with the traditional view used by mainstream management research and developed a different ontological ground based on the structuralist approach of Bertrand Russell. However, it seems to be needed an emphasis on the epistemological nature of the Mechanism thesis because of its common association with reductionism and the view of mechanistic thinking as supposedly opposed to holism and emergentism. This paper constitutes a second part; it underlines the epistemic status of Mechanism which explains why it is in no way opposed to ideas like holism or emergentism, on the contrary it is consistent with such worldviews. Based on this condition the paper explores the repercussions of such characterization for philosophy of science and for system dynamics by developing a research agenda for both fields around this topic.
The Swiss electricity market - as well as the European electricity markets, is now facing a period of fundamental structural changes. Emergent liberalisation is taking place, and nuclear dismantling is being debated. Given this scenario, it is important to evaluate market response to those changes in terms of security of supply and the viability of international exchanges - imports and exports of electricity from and to neighbouring countries. The approach we adopt to analyse various aspects of security of supply in Switzerland differs from the traditional economic methodology which focuses on equilibrium of outcomes as opposed to on how the new situation is reached. We use system dynamics simulation models, which incorporate information feedback and behavioural policies, to study scenarios of the transient period currently faced by the Swiss electricity market.
Many organizations set ambitious schedules for their product development projects to gain competitive advantages. However, ambitious schedules might be the main factor to deteriorate project performance. The features of system dynamics application in project management is discussed and a generic simulation model is built for studying the effects of schedule pressure and providing a helpful tool for project management to understand feedbacks, delays and nonlinear relationships among projects and how project behaviors are driven by project structures. Finally, the future works about this study are discussed.
Abstract: By means of system thinking, the issues of traveling resources, traveling condition and finance in tourism business as well as the interrelations among them were analyzed to search the effective approach to the prosperity of tourism business. The software STELLA is used to build the operation model of tourism business, including the modules of ticket price, the payment of loans and the development and demolishment of resources in order to find out an efficient way to prosper the tourism industry while protecting the environment.
There's no real data for it's just a student's exercise. It mainly analyzes the genegal idea, and every related aspects.
Also, its purpose is to show the importance of system thinking in high school students' studies.
An enterprise model is a computational representation of the structure, activities, processes, information, resources, people, behavior, goals, and constraints of an organization. It can be both descriptive and definitionalspanning the as-is and/or the to-be. The role of an enterprise model is to achieve model-driven enterprise design, analysis, and operation.
Of particular concern is an analysts ability to determine the impact of changes, and/or proposed changes, on each functional component of the enterprise. For example, how would relaxing recruiting standards affect the quality of Sailors throughout the enterprise? What is the attrition impact to the fleet if we shorten or expand time in the delayed entry program?
Upon successful completion, analysts and/or decision-makers will receive an interactive analysis system to facilitate strategic planning. The system will allow component managers to explore the impact that functional policy and resource decisions have across the entire personnel enterprise. The goal is to create a more effective personnel environment through strategic evaluations of potential futures.
The task of finding optimal policies in stochastic dynamic systems is challenging. The theory of stochastic dynamic programming (SDP) is quite complex and the available software packages are not intended for non-specialists. Furthermore, SDP is traditionally limited to quite small and well defined problems. Stochastic optimization in policy space (SOPS) seems to be an attractive alternative, particularly for people with a background in simulation of dynamic systems. However, to date no user friendly software has been available for this method. In this paper we present and demonstrate a new program package for this task. The resulting software allows the user to formulate the model in a well-known simulation program, Powersim Studio 2005. The model is automatically transferred to a standalone program. The SOPS program allows the user to reset model parameters, to specify search criteria, and to study the results of repeated searches for optimal policies. To maximise speed, Monte Carlo simulations utilise C+ code.
Firms often attempt to imitate successful practices of other firms. When implementing new practices, individuals in organizations learn new ways of doing things, develop new skills, and adopt new organizational routines. In the paper, we view implementation as a learning process and apply learning curve theory to the understanding of implementation dynamics. We extend classic learning curve to include a required output level for an individual who must choose between an old and a new way to achieve the output. Doing work the new way builds experience, increasing productivity and thus favoring continued use of the new skill, but this reinforcing process works to favor the new skill only at relatively high levels of productivity. Otherwise, the same process is a vicious cycle, driving out the new skill. We use a system dynamics model to demonstrate a mode of behavior in which learning begins and then stalls and another mode in which the new skill becomes the preferred one. We identify the tipping point between these two modes and characterize the transition problem: Learning by doing is a dynamic process, a transition from use of an old way to a new way that requires accumulating experience beyond a threshold.