A novel archetype, abstracted from published work and supported by anecdotal analogies is proposed. Its novelty is evidenced by a comparison with the 'Relative Control' archetype from Wolstenholme's classification. The significant difference is the erasure of the system boundary from 'Relative Control'. The effect is to bring the dynamics entirely within the system thereby creating a 'political' archetype: a structure internalizing the struggle between two opposed policies.
How can we build dynamic models to effectively inform our research? The System Dynamics method offers established practices and principles to enable us to do so. This boot camp is directed to expose PhD students to the (iterative) SD modeling process.
The workshop consists of two parts. In the first part participants will engage in the process of model building from a case and getting some basic insights. Issues that will be discussed include problem definition, model boundary, scope/level of aggregation, generating insights from modeling, as well as challenging the research question.
The second part of the boot camp will address actual issues from participants research based on the important themes discussed in the first section. For this we ask participants to submit a one/two page summary of their current research, comprising: abstract, research questions, motivation for model and two or three main issues. We encourage submitting models in whatever stage of progress. The summaries should be in at latest on Monday of the conference (though earlier is strongly suggested!). The case material will be available upfront so that the participants read the case before hand.
Note: this workshop does not involve one-on-one coaching that the modeling assistance workshop offers, nor has it the conference setup of the PhD colloquium. These sessions are complementary to each other and participants are encouraged to participate in all of them.
Product development (PD) is a crucial capability for firms in competitive markets. Building on case studies of software development constructed from fieldwork at a large firm, this paper explores the interaction among the different stages of the PD process, the underlying architecture of the product, and the products in the field. The study corroborates the dynamics of tipping into firefighting (Repenning 2001) that follows quality-productivity tradeoffs under pressure. Moreover, we introduce the concept of the adaptation trap, where intendedly functional adaptation of workload can overload the PD organization and force it into firefighting because there is a delay in seeing the additional resource need from the field and underlying code-base. Finally, the study highlights the importance of architecture and underlying product-base in platform-based product development, through their impact on quality of new models under development, as well as resource requirements for bug-fixing. Put together, these dynamics elucidate some of the reasons why PD capability is hard to build and how it erodes. Consequently, we offer hypotheses on the characteristics of the PD process that increase its strategic significance and discuss some practical challenges in the face of these dynamics.
This paper provides an example of a system dynamics model that incorporates soft variables. The model examines the challenges that a superpower faces while maintaining its position in the global economic system. The effects on aggregate welfare of the population at home and abroad, as well as, issues of sustaining authority in the long run are explored through experimentation with a computer model. This theory is an extension of the framework developed by Saeed(1990), which was used to understand political instability and the failure of the government to stay committed to welfare agendas in the
developing countries. The present model captures the interaction between several institutional actors involved with the economic and the governance systems. They include the public, the authoritarian regime, the reformist movements that seek change within the existing framework, and the dissident movements that turn to violent methods.
This paper reports an action research study in which we applied Edgar Scheins process consultation approach to a cross-functional problem in a large academic teaching hospital. The project task force was charged with investigating a hypothesized effect of poor lab turnaround time on the risk of probable discharges being postponed until the following day, thereby increasing average length of stay and associated hospital operating costs. The tools we used at different stages of our process included group facilitation, interviews, process flowcharts, systems thinking with causal loop diagrams, and what-if analysis with a system dynamics simulation model. Through facilitation of the task forces work, we were able to reorient each constituent groups perspective from a parochial to a systemic view, greatly improving the task forces functioning and chances for successful sustainable improvement.
Empirical evidence suggests that people perform poorly in dynamic tasks. The thesis of this article is that dynamic decision performance can be improved by helping people to develop more accurate mental models of the task stems through training with debriefing supported computer simulation-based interactive learning environments (CSBILEs). I report a laboratory experiment in which subjects managed a dynamic task by playing the role of fishing fleet managers. One group of participants used a CSBILE with debriefing, whereas another group used the same CSBILE but without debriefing. A comprehensive model consisting of four evaluation criteria is developed and used: task performance, structural knowledge, heuristics, and cognitive effort. It is found that debriefing was effective on all four criteria; debriefing improves task performance, helps the user learn more about the decision domain, develop heuristics, and expend less cognitive effort in dynamic decision making.
Boston's residential real estate market has seen dramatic growth in recent years. Prices have doubled and then doubled again. No one knows how long this will last. Is it a "bubble"? If so, when will it burst? Is it still safe to invest? Is it time to move? Fine questions for owners and speculators--but the consequences of the continuing boom are disastrous for those of lesser means working in Boston. Boston's Mayor Menino has made his Affordable Housing initiative a top priority. Understanding the dynamics driving the market and the success or failure for these initiatives could be a key enabler of robust public strategies. The dynamics displayed and described in this session were developed on a pro bono basis working with Boston's Department of Neighborhood Development at the request of Mayor Menino. Extensions of this work with the Mayor's office and additional housing agencies are underway.
As self-described educators, in our formal instruction of students and teachers and our more recent outreach to a wider array of clients, we have focused on systematically using the full range of system dynamics tools to become, and assist our clients to become, better thinkers and modelers. In a conscious effort to build that capacity through collaborative problem solving, we have devised a ladder of engagement. It is a structure and sequence of activities supporting a powerful and integrated process by which continuously better questions allow us to: (1) probe progressively more deeply into describing the behavior of the system (a rung of KNOWLEDGE); (2) identify the systems features (feedback loops and delays) controlling its behaviors (UNDERSTANDING); and (3) locate and evaluate leverage points in the system where intervention can effectively and efficiently affect its behavior (INFLUENCE). In addition to the ladder's hierarchical structure, at each rung or level the process explicitly incorporates feedbacks designed to develop an iterative learning process that continually reinforces the linking of answers to better questions and the parleying of ones facility within a limited sphere of interest into broader abilities and motivations to pursue more diverse challenges and enduring and generic problems.
Worldwide competition is evolutionary and dynamic; therefore it is necessary that countries not only think in terms of immediate cost but that they foment the necessary conditions under which their companies or new companies can develop competitive advantages based on the innovation.
According to this, it is important that countries like México foment the creation and the development of new industries in the biotechnological cluster, in order to develop new areas in which we could be competitive.
This paper is about the design of a model that could help us to evaluate de viability of the development of a biotechnology cluster in Mexico.
Keywords: biotechnology, cluster development, Innovation