Modelling knowledge in SD organisational interventions may become a puzzling task because of difficulties in achieving a common shared view among business key-actors about the impact of Intellectual Capital (IC) investments on future company performance.
Such difficulties are not only related to the intangible nature of IC, but also to the indirect role of knowledge in affecting performance drivers and outcomes. This phenomenon is particularly relevant in service businesses, where intangibles account for a high percentage of total assets.
In order to overcome such problems, a conceptual framework has been developed by the authors to build a generic SD model aimed to support business decision makers in IC planning, with particular regard to service firms.
Such model has provided the basis for developing two ILEs focused on a telecom mobile service provider and an insurance company. The first application was related to an education project, while the second one was linked to a consulting assignment.
The use of a conceptual framework as a basis to build an ILE has proved to be a successful strategy in order to better communicate business key-actors the potential of SD in modelling and assessing IC policies.
Main key-issues underlying model development and the ILEs application are discussed in the paper, and most significant outcomes from simulations are commented.
The phenomenon of dwarf or stunted small and micro firms (in Italian nanismo aziendale) is recognised in the small business literature. These are firms that have survived through many years, maybe many generations, providing their owners with acceptable returns and lifestyles, but have remained very small. They might therefore represent potential lost opportunities for owners and, given the importance of the SME sector, local employment and economies. A system dynamics model replicating the basic no-growth, cyclical behaviour attributed to stunted SMEs is firstly analysed. Alternative policies arising from different entrepreneurial views and aimed at changing behaviour to one of stability or steady growth, are then tested and analysed. In this relatively simple form, the model does link behaviours to system structure and could support individual entrepreneurs in understanding the reasons for dwarfism in their firm and the potential for unleashing growth. It could also form the basis for a more detailed model to support the identification and evaluation of strategic alternatives in individual firms.
The complexity and characteristics of the pharmaceutical firm present an intriguing context for underlying information management issues during clinical trials for new drug development. This paper reports on the evaluation and performance of MIS for information management in clinical trials in new drug development. The main objective of the study is to examine the economic and business impacts of automating that process, to enhance our understanding of informational stakes involved, using a system dynamics (SD) model. The SD method is enriched in this paper with other conceptual frameworks such as Alters (2001) Work Centered Analysis (WCA) and the Balanced Scorecard (BSC) (Kaplan and Norton, 2001). Results of the simulations for alternative sensitivity analyses on errors rates in data transmissions, that is, on alternative error-rate specifications, do not necessarily influence project delay, but rather work intensity. A discussion details the usefulness of enriching the SD modeling process with alternative conceptual frameworks in the problem definition in such complex settings.
The negligent upkeep of many abandoned industrial sites (brownfields) throughout the twentieth century has had grave impacts on the urban landscape of American and European cities. In recent years, brownfield redevelopment has come to be viewed as a strategy for sustainable land use and urban revitalization. This study assesses the feasibility of the construction of a dynamic simulation model of urban brownfield redevelopment. Literature surrounding brownfield redevelopment is reviewed and used to construct a dynamic hypothesis of brownfield redevelopment as it relates to site liability, economic viability, and availability of redevelopment funding. Finally, an initial system dynamics model of the brownfield redevelopment process is constructed. This quantitative analysis is performed using the 2003 US Conference of Mayors brownfield survey, which serves as a dataset on brownfield distribution and average site size. We conclude with suggestions for the extension of the model to capture spatial feedback in order to assess redevelopment effects on the surrounding matrix of urban land-uses.
Recently, an invasive Asian beetle known as the Emerald Ash Borer (EAB) (Agrilus planipennis Coleoptera: Buprestidae) has emerged as a threat to Ash trees in the Midwestern United States and Canada (McCullough and Katovich 2004). Significant infestations in Michigan and nearby areas have all but doomed nearly one billion native ash trees. This paper presents an argument for the establishment of a widely accessible knowledgebase of information on the EABs spread capabilities. We argue that spatial dynamic modeling stands as a flexible and powerful decision support system platform. We present initial simulations of EAB spread scenarios constructed using tree information and land use data collected for DuPage County, IL, an uninfected suburban county in the Chicago metropolitan area. These simulations test policies focused on impeding the costly spread of the beetle. This analysis also presents a framework for further studies assessing the economic impacts on municipalities and counties due to tree removal costs and aesthetic damage. Our work points to human driven movement as the major vector for EAB spread throughout our study area. Here, the focus falls on the ability of state and county implemented firewood quarantines to act as effective policies for slowing EAB spread.
Project-based professional service organisations supply their services as tailored or one-off projects for specific clients. The particular form of their organisation, the character of their relationships with their clients necessary to deliver highly customised projects and the non-routine, creative nature of the work come together in a way which makes the management of these service firms particularly demanding. A common challenge is fluctuation in the workload. While this is partly influenced by changes in demand, the external environment does not provide a comprehensive explanation and the interaction between business processes and project processes needs to be examined. In providing a generic explanation of the causes of workload fluctuation as well as an assessment of different bidding strategies based on a system dynamics model, this paper aims to help to advance the theoretical understanding of the project-based professional service organisation and ultimately to help to provide tools for its managers.
The importance of management flight simulators for learning has been already tested and documented. Single player simulation games are usually utilised, but a multiplayer simulation game adds direct competition to the existing problems (delays, nonlinearities and feedbacks). An asymmetric game also introduces bounded rationality and the dynamics of the information flow within the team. A network team game finally allows for the analysis of cooperation dynamics (by letting the users play against each other: against an unpredictable competitor, with no pre-defined strategy). This paper presents an asymmetric multiplayer network game that is considered to be easy to play and understand. The main advantage of the ILE here introduced is the facilitation of the analysis of: learning and decision making processes, cooperation and competition dynamics.
Our objective is to conduct simulations with economic environmental model. We list the important and causal relationships among the levels and trace the feedback loop structures. In describing an economic and environmental model we focus on the relations among income, consumption, emission, and damage. This paper yields insight into maximization of welfare. Next, we present the simulation runs of the model, conducted with the help of existing system dynamics modeling tools.
System Dynamics (SD) is a special type of simulation modeling where
output validity refers to validating the patterns of dynamic behaviors, such
as oscillations, growth or decline. The developers and users of these
models (the decision makers and people affected by decisions based on
such models) are all rightly concerned with whether a model and its
results are valid. Structural model validity and validation have long been
recognized as one of the main issues in system dynamics. This concern
is addressed through pattern recognition and testing in this paper.
Another issue in dynamic simulation methodology is parameter
calibration; assuming that the structure of simulation model constructed
by the user is valid. Parameter calibration is the minimization of an error
function which is a measure of the correspondence between numerically
calculated output patterns and the respective real behavior patterns. We
offer a software that does automated parameter calibration with respect to
a given (desired) dynamic pattern. This particular feature can also be
used in policy improvement design.
Natural gas for automotive purposes is an appealing alternative: curbing local and global pollution and dependence on foreign oil are among the most remarkable advantages. The other side of the coin implies building and maintaining an on purpose network entailing financial requirements. The final aim of this work is to compare its advantages with economic rationale.
A system dynamics model is built and taken as reference for all quantitative assertions. It contains data referring to two scenarios: business as usual versus expansion. The model treats separately global and local emissions and infrastructure needs. Quantitative results are the basis for the final assessment, that is grounded on the externalities theory. By analyzing the scenarios gap numerous remarks follow.
Regarding global emissions, beneficial effects seem modest. Local emissions would either decrease or not vary depending on the pollutant. Avoided externalities estimates exceed infrastructure financial requirements. Natural gas is a suitable answer in tackling some issues related to the road transport industry.