System Dynamics to Understand Public Information Technology

System Dynamics to Understand Public Information Technology

Luis Felipe Luna-Reyes (Universidad de las Américas-Puebla, Mexico)
Copyright: © 2008 |Pages: 17
DOI: 10.4018/978-1-59904-857-4.ch045
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Abstract

Information technology development and implementation have been recognized as forms of organizational change (Doherty & King, 2003; Orlikowski, 2000). Public-sector organizations are interested in this process of change because of the expected benefits of using IT, such as cost savings, improved service quality, increased accountability, and public participation (Gil-Garcia & Helbig, 2006). However, IT fails to deliver the anticipated payback in many projects (Jackson, 1997; Keil, Cule, Lyytinen, & Schmidt, 1998). Some of such failures are the result of our lack of understanding about the relationships among IT components and organizational factors involved in the implementation process, producing mismatches or unintended consequences in the process: “[t]he computer hardware may perform correctly, and the software may satisfy its specification; but the results are not what was intended, and may be disastrous” (Jackson, 1997, p. 5).

Key Terms in this Chapter

Feedback Loop: A feedback loop is a closed path of causal relations among variables. Feedback loops usually represent the process of monitoring the state of the system, the effects of decisions in the system state, and future decisions.

Problem Conceptualization: This is the stage in the modeling process where the modeler focuses on understanding the problematic behavior over time and the important feedback processes associated with it.

Model Validation: This consists of a series of activities to build confidence in a system-dynamics model as a useful policy tool in a specific context.

Simulation Model: Simulation models are formal representations of a portion of reality. Simulation models allow managers to share and test assumptions about problem causes and solutions.

Reference Mode: The reference mode is a historical or hypothesized dynamic characterization of a problem. These behaviors are the guiding principle for the system-dynamics modeling process.

Model Formulation: This is the stage in the modeling process where the modeler creates a mathematical representation of a conceptual model.

Mental Model: Mental models are representations of reality built in people’s minds. These models are based on arrangements of assumptions, judgments, and values. A main weakness of mental models is that people’s assumptions and judgments change over time and are applied in inconsistent ways when building explanations of the world.

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