An approach to modeling of a problem based on the state at a fixed point in time. A variety of mathematical approaches exist with different properties. For example, empirical or statistical models use collected data to create a view of the problem, whereas stochastic models reason about uncertainty in the problem.
Published in Chapter:
Developing a Dynamic View of Broadband Adoption
Herbert Daly (Brunel University, UK), Adriana Ortiz (TECNUN University of Navarra, Spain), Yogesh K. Dwivedi (Swansea University, UK), Ray J. Paul (Brunel University, UK), Javier Santos (TECNUN University of Navarra, Spain), and Jose M. Sarriegi (TECNUN University of Navarra, Spain)
Copyright: © 2008
|Pages: 15
DOI: 10.4018/978-1-59904-851-2.ch020
Abstract
The widespread domestic use of broadband Internet technology has been recognized to have a positive influence on national economies and improve the life of citizens. Despite substantial investment to develop the infrastructure, many countries have experienced slow adoption rates for broadband. This chapter develops a view of UK broadband adoption using dynamic modeling techniques based on an existing statistical study. The contrasting approaches to modeling are compared. Principles of a dynamic modeling system are introduced and an appropriate form for broadband adoption chosen. The process of building a dynamic model based on an existing static model of broadband adoption is presented. Finally, the new perspective of the dynamic model is explored using the causal loop analysis technique.