With increasingly volatile oil prices, unprecedented US dependence on imported petroleum, and growing environmental concerns, the creation of economically sustainable markets for alternative fuel vehicles (AFVs) is vital. However most efforts to supplant the current transportation system have failed or had limited success. The diffusion of AFVs is complex, being both enabled and constrained by powerful positive feedbacks arising from scale and scope economies, experience curves, network effects and complementary assets. While such feedbacks are sometimes discussed, dominant mental models among both policy makers and academics may underestimate the strength of these feedbacks and the fact that they also operate to advantage the current dominant technology. The result has been a series of overly-optimistic forecasts for the extent and speed of diffusion for AFVs and EDVs, and insufficient investment in standards and policies to help such vehicles over the tipping point to self-sustained adoption. We describe a model we have developed a suite of behavioral dynamic, spatially disaggregated models with a broad scope and its key actors. We demonstrate, through various thought experiments, that higher oil prices, while important in speeding EDV adoption, are less effective than many expect, due to a range of compensating feedbacks that enable internal combustion-gasoline technology to adapt.
This paper examines challenges and opportunities for policy actions that transform healthy living behaviour. We examine how policies and other decisions, made by various types of actors (i.e. consumers, industry, agriculture, government, NGOs, and global institutions) evolve as they interact and collectively shape nutritious food markets over time. Such a transformation is characterized by multiple feedbacks and long-term delays, and involving disjointed public and private level interactions, produces counterintuitive behaviour. To develop an in-depth understanding of the major challenges and identify high-leverage strategies in transitioning away from low nutrition / high motivational (LN-HM)-based food system we have developed a behavioral dynamic model with a broad scope. Key actors in the models include consumers, producers, and policy-makers. In this paper we describe the model and carry out simulation experiments designed to examine barriers to self-sustaining market shifts between supply and demand factors. Collective action among producers to improve nutrition, while important in achieving nutritional change, builds up slow and is failure prone, due to a range of compensating supply and demand feedbacks. We analyze and discuss the role of cross-product category substitution, the contextual role of consumer switching dynamics, and a variety of initiatives, including those oriented around marketing and R&D. We conclude by discussing the importance of coordination and commitment across actors and model extensions.
Language dynamics in multi-language societies is a growing field of study. Most extant research focuses on the dynamics of language death in multilingual societies. However, empirically, languages form more complex patterns, including survival in local clusters. This paper lays the foundation for a model to explain the process by which dominated languages sustain themselves. The key mechanism we explore in this paper is the social-network effect that affects single or multiple language adoption. In particular we hypothesize an important role of bilangualism. To analyze this we extend existing, stylized, models that predict one single dominant language. We simulate the competition of two language groups who interact through a bilingual population. We include factors such as language status and ease of learning. The model is tested against the empirical case of Quebec from 1931 to 2006. We explore the importance of bilingual parents raising their children as bilinguals or unilinguals according to the relative attractiveness of each language. We find that this factor, while not critical in explaining qualitative patterns, is instrumental to replicate more accurate patterns. We conclude by developing a hypothesis of how spatial disaggregation of the network effects may explain the local cluster survival of dominated languages.
The stock management (SM) problem is of high relevance for a broad range of decision makers in society, business, and personal affairs. Although in some areas highly sophisticated models and control concepts have been developed, human stock management performance is lamentable. One recent explanation for this failure is offered by a stream of research, which finds evidence for widespread and persistent deficits in understanding how flows accumulate in stocks. This misunderstanding of accumulation (MoA) is proven even among well-educated adults. This research uses laboratory experiments to test the hypothesis that the better people understand accumulation, the higher is their performance in SM tasks. Correlation and univariate regression analysis show that MoA indeed contributes to explaining performance differences in stock management. However, the effect is moderate and vanishes almost completely when intelligence and economic knowledge are included as control variables in a multiple regression model. The value of this paper lies in explicitly testing the relation of MoA and SM, whose existence is widely taken for granted. Future research could explore a broader set of control variables and should increase the number of cases to allow for advanced theory testing using, for example, structural equation modelling.
This paper presents findings from the use of a simulation learning environment to teach college students about principles of accumulation. The simulation package is part of an ongoing study testing the utility of systems simulations for teaching students about the complex systems relationships in environmental studies and science. We have conducted paired experiments over the past five semesters in a team-taught, college-level Introduction to Environmental Science course using system dynamics simulations. We have progressively refined the systems learning objectives, simulations, and assessments. The focus that has emerged from this research is the need for building systems understanding about the dynamics of accumulations. While most students are able to define and identify everyday examples of accumulations, they have difficulty understanding relationships between flows and accumulations in any but the simplest cases. The pattern-matching tendency is strong. In this paper we present a simulation developed specifically to address simple issues of accumulation and discuss lessons we have learned about best practices for discovery learning in this setting.
This poster presents a web-based simulation learning environment for facilitating discovery learning about accumulations. It was designed to complement an Introduction to Environmental Science course at the college level, but will eventually be available as a stand-alone package. The primary learning objective is to develop the users understanding of the relationship between inflows, outflows, and accumulations, as well as the effect of changes in inflow and outflow rates. Results from the use of this simulation in freshman Environmental Science classes will be presented in another paper. Here we describe the domain and discovery learning objectives, storyboard, and interpretive scaffolding of the simulation learning package, and present insights from user feedback on the design. We plan to have a demonstration version of the simulation available at the conference.
Joining the European Union big opportunities in the international markets have opened for Latvia. Paper purpose is to investigate influence of international integration processes on development of economy of Latvia. Latvia's incoming in EU increased the amount of received means from structural and cohesion funds, removed the trading barriers, increases foreign investments, reduced unemployment and increased labor migration. In the paper the system dynamics model, which describes integration of the Latvian economy into EU, is developed. In the model international financial flows connected with Latvia and EU; import, its relation to internal producing; and migration processes are considered. Model functioning is measured considering various scenarios of situation development. The developed model can be used not only in the analysis of Latvias economic integration in the EU, but on its basis it is possible to create models of regional cohesion in Europe.
This paper explores the dynamics of energy reduction policy setting for data centers in the face of new metrics and related regulation. With these new metrics there is a potential for management to establish policies that achieve the specific metric target while sub-optimizing the total energy reduction opportunity. This paper will address the question of whether new insight can be gained by using a system dynamics approach versus static return on investment forecasting. The first part of this paper will describe the unique dynamics of energy consumption in a data center and the application of one particular metric used to indicate energy consumption efficiency. The second part of this paper proposes a model that represents the interconnected behavior of data center energy consumption and metric based policy implementation. This approach is compared to static methods and the insights gained from taking a systems approach.