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- Type:
- Document
- Date Created:
- 2006 July 23-2006 July 27
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- f9377a3ac7b50b1fca5e04fb6d679ec2, 23d738ba88f8333bc39725f9cb5bd0b8, and 32937c7b43e3e015509bb71fd40d2054
- Description:
- Phantom orders arise in real supply chains when suppliers are unable to fill orders on time. Customers respond to product shortages by increasing orders and ordering through different channels in an attempt to gain a larger share of the shrinking production pie. Suppliers, often unaware of the underlying demand, respond by increasing output. As allocations increase customers cancel their phantom orders, leaving suppliers and distributors with large surplus stocks. As the title indicates, such behavior can be rational, as multiple customers compete for limited supply. Here we examine the behavior of subjects in the beer distribution game for evidence of phantom ordering. Phantom ordering is never a rational response to shortage in the experiment because there is only one customer for each supplier, no randomness, no production capacity limit, and, in this implementation, customer demand is constant and publicly announced to all players. Yet we find that a significant minority exhibits phantom ordering. We speculate that the urge to hoard evolved early in human history as a locally rational response to scarce resources, and that the brain center responsible for the hoarding response is likely to be distinct from the loci of economic decision making.
-
- Type:
- Document
- Date Created:
- 2006 July 23-2006 July 27
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- f9377a3ac7b50b1fca5e04fb6d679ec2, 23d738ba88f8333bc39725f9cb5bd0b8, and 32937c7b43e3e015509bb71fd40d2054
- Description:
- Systems thinking and system dynamics are widely used methodologies for studying and managing complex systems. A two-way interaction between a persons mental model and an explicit representation of that model leads to an improved understanding of the system. However, the effect of these techniques on a persons dynamic decision-making abilities is yet not fully known. To explore this relationship, an experimental study was conducted. Results show that most participants initially had poor understanding of basic dynamic situations. However, the completeness and accuracy of their mental models improved considerably with system interventions. Specifically participants ability to discern between stocks and flows, identify causal relationships and feedback improved by around 27% after a systems thinking intervention. These abilities further increased by around 4% after participants underwent a system dynamics intervention. Interestingly, in complex tasks that required an in-depth analysis, systems thinking hardly made any positive effect on participants decision-making. However, for the same situation, participants mental models improved by 8-50% after system dynamics intervention. The results of this study confirm with the results of some of the previous studies done in this area and provide a deeper insight on the impact of systems thinking and system dynamics on dynamic decision-making
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- Type:
- Document
- Date Created:
- 2006 July 23-2006 July 27
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- f9377a3ac7b50b1fca5e04fb6d679ec2, 23d738ba88f8333bc39725f9cb5bd0b8, and 32937c7b43e3e015509bb71fd40d2054
- Description:
- This research deals with alternative modeling approaches to multiple agent dynamics. Models of a supply chain system are constructed to make comparisons about the capabilities of aggregated (System Dynamics) and disaggregated (Agent-Based) modeling approaches, based on a query to answer questions such as Can aggregated, macro-level modeling capture the dynamics of micro-level, agent-based modeling? In what specific cases? Effects of several factors, including inventory positions, price, shadow orders, loyalty, safety stocks, and ordering policies are analyzed. It is shown that there are factors, effects of which can be captured by System Dynamics at an aggregate level; however it is also observed that System Dynamics may miss the dynamics at more detailed level resulting from the emerging heterogeneity among individual agent behaviors in these cases. There are also cases where System Dynamics cannot capture the dynamics generated by ABM, even at an aggregate level. Regarding the supply chain dynamics, it is shown that when agents try to act rationally, emergent system behavior may become destructive. Loyalty and reliable safety stocks are proposed as strategies against oscillations in the supply chain.
-
- Type:
- Document
- Date Created:
- 2006 July 23-2006 July 27
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- f9377a3ac7b50b1fca5e04fb6d679ec2, 23d738ba88f8333bc39725f9cb5bd0b8, and 32937c7b43e3e015509bb71fd40d2054
- Description:
- This paper shows how a system dynamics model can be used to identify policy alternatives and scenarios for a policy space in a natural hazard policy analysis. In this paper, I will present a system dynamics model of the problems faced by decision-makers in a community that experiences flooding. While current policy analysis for hazard mitigation focuses on benefit-cost analysis, I argue that system dynamics can be used to improve the policy analysis and compliment the traditional approach. In this paper, I present a system dynamics model and policy space to illustrate the effectiveness of system dynamics in two respects. First, a system dynamics model designed with a policy space in mind provides the policy analyst with a map that effectively identifies policy levers and scenarios in the system. Second, by linking structure with behavior in the policy space, the policy analyst can quickly compare the model behavior of several key indicators over multiple scenarios. The policy space constructed from the system dynamics model identifies both qualitative and quantitative differences in policies. Including a system dynamics model in a policy analysis provides a deeper understanding of the causal structures, which compliments the traditional benefit-cost approaches and improves the overall quality of the analysis. Key words: policy analysis, natural hazard, flood, mitigation, extreme event, public administration, disaster management, agenda setting
-
- Type:
- Document
- Date Created:
- 2006 July 23-2006 July 27
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- f9377a3ac7b50b1fca5e04fb6d679ec2, 23d738ba88f8333bc39725f9cb5bd0b8, and 32937c7b43e3e015509bb71fd40d2054
- Description:
- This paper describes the outcome of a research project undertaken for the government of the State of Sarawak in E. Malaysia. A system dynamics model was constructed so as to inform the States future economic and social planning to 2020. Positive engagement with State government officials at the highest levels was a feature of the successful completion of the work. A flexible policy evaluation tool for use in their macro-economic planning is now available to be used by those officers who were exposed to several training sessions in system dynamics modelling.
-
- Type:
- Document
- Date Created:
- 2006 July 23-2006 July 27
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- f9377a3ac7b50b1fca5e04fb6d679ec2, 23d738ba88f8333bc39725f9cb5bd0b8, and 32937c7b43e3e015509bb71fd40d2054
- Description:
- The organization can be a potential resource for encouraging innovation in a company. In its turn, innovation changes the organization. In this paper we will endeavour to study and understand the network of mutual determination of the couple which we will call: Organization - innovating Process. We will therefore analyze the organizational elements which increase creative effervescence. System dynamics enables us to understand, over periods of time, how the process of innovation is created as well as how it can disappear. Indeed, it is in the duration and lifecycle of the organization that one can observe the collaborative forces which create the conditions for innovation. We wish to show that the changes of an organization's state and the properties which result from this exacerbate or on the contrary inhibit innovation. Innovation is a process which begins with the identification and acquisition of knowledge and ends with transferring and implementing this knowledge into organizational initiatives. We will highlight the principal feedback loops and propose a model showing the behaviours and the counter-intuitive effects resulting from interactions between variables. We based our research on a study carried out in a company. Our model can be used to teach the dynamics of organizational innovation
-
- Type:
- Document
- Date Created:
- 2006 July 23-2006 July 27
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- f9377a3ac7b50b1fca5e04fb6d679ec2, 23d738ba88f8333bc39725f9cb5bd0b8, and 32937c7b43e3e015509bb71fd40d2054
- Description:
- Hydrogen fuel cells are increasingly seen as the propulsion technology of the future for road transport. However, despite the potential of this technology to reduce the environmental impact of road transport and to improve energy efficiency, both technical and economic barriers need to be overcome for these technologies to be successfully introduced in mass markets. At Imperial College we are currently undertaking an analysis of the possible future dynamics of the PEM fuel cell market for road transport in Europe. This study is part of an EC-funded, Integrated Project involving 18 partners from both industry and academia; this allows extensive interaction with key market players of particular relevance to the dynamics under study. This paper presents results of work in progress, which involves the development and use of a simulation model as well as a dedicated group learning session with project partners.
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- Type:
- Document
- Date Created:
- 2006 July 23-2006 July 27
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- f9377a3ac7b50b1fca5e04fb6d679ec2, 23d738ba88f8333bc39725f9cb5bd0b8, and 32937c7b43e3e015509bb71fd40d2054
- Description:
- The present research shows through computer simulations the dynamic positive interconnections among Knowledge, Capabilities, Dynamic Capabilities, Entrepreneurial Performance and Trans-generational Value in family business. In addition, interesting results and new insights will come out introducing Family Inertia in the model (as a function of Paternalism) which negatively influences the creation of capabilities and dynamic capabilities, with some exceptions. Keywords: Knowledge, Absorptive Capacity, Capabilities, Dynamic Capabilities, Trans-generational Value, Paternalism, Family Inertia, Family business
-
- Type:
- Document
- Date Created:
- 2006 July 23-2006 July 27
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- f9377a3ac7b50b1fca5e04fb6d679ec2, 23d738ba88f8333bc39725f9cb5bd0b8, and 32937c7b43e3e015509bb71fd40d2054
- Description:
- The innovation management is the key activity for enterprises and it plays a significant role in pursuing core competence and sustainable profit. To achieve high performance, enterprises no longer merely rest on technology innovation but call for innovation synergy between both technology and non-technology elements including organization, strategy, culture, market, etc. The All Element Innovation (AEI), one aspect of TIM theory, aims at providing facilitating method for encouraging and regulating innovation of all synergic elements. In this paper, the system dynamics model of AEI is established to study the impact of the portfolio of innovation elements on enterprises innovation performance. By simulation and policy analysis of the SD model, the interaction and dynamic characteristics of AEI is successfully worked out. The simulating results indicate that, for single element, culture and strategy influence the performance most significantly. In addition, the portfolio of culture and strategy, strategy and organization have the most profound effect on performance. Furthermore, we discover that the innovation performance with multiple coordinated elements is obviously higher than that with single or a few elements, thus confirming that heightened performance depends on synergic innovation process with multiple innovation elements involved.
-
- Type:
- Document
- Date Created:
- 2006 July 23-2006 July 27
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- f9377a3ac7b50b1fca5e04fb6d679ec2, 23d738ba88f8333bc39725f9cb5bd0b8, and 32937c7b43e3e015509bb71fd40d2054
- Description:
- System dynamics may amplify A/LM (Asset/Liability Management) methodology capability to being risk oriented. Conceptual issues assigned to A/LM variables are described and a dynamic A/LM approach based on SD principles and risk factors in pension funds is examined. Risks must be defined in tangible operational terms. Pension Funds need to produce a high-income return to correspond to actuarial expectations and to pay benefits of different kinds. Its non-financial nature of the underlying assets and long-term liabilities dictates the nature of risk management processes and approaches that a pension fund must take. In a changing and complex environment, the wealth of the organization need a management of its investment assets with better tools than the static mean-variance analysis. ALM provides many advantages this way. Finally, since the decisions under uncertainties become complex specially because of the low comprehension of the long term best interests of the system as a whole, System dynamics methods may provide an holistic overview to the analysis of ALM results. The combination may improve the managers hability to explicit tacit knowledge, understand complexity and design better operating policies enhancing, this way, the discussions and learning about businesses strategies.