Potential Data Collections Methods for System Dynamics Modelling: A Brief Overview
System Dynamics (SD) modelling is a highly complex process. Although the SD methodology has been discussed extensively in most breakthroughs and present literature, discussions on data collection methods for SD modelling are not explained in details in most studies. To date, comprehensive descriptio...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
The Science and Information (SAI) Organization Limited
2021
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/32021/1/Potential%20Data%20Collections%20Methods%20for%20System.pdf http://umpir.ump.edu.my/id/eprint/32021/ https://dx.doi.org/10.14569/IJACSA.2021.0120332 https://dx.doi.org/10.14569/IJACSA.2021.0120332 |
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| Institution: | Universiti Malaysia Pahang |
| Language: | English |
| Summary: | System Dynamics (SD) modelling is a highly complex process. Although the SD methodology has been discussed extensively in most breakthroughs and present literature, discussions on data collection methods for SD modelling are not explained in details in most studies. To date, comprehensive descriptions of knowledge extraction for SD modelling is still scarce in the literature either. In an attempt to fill in the gap, three primary groups of data sources proposed by Forrester: (1) mental database, (2) written database and (3) numerical database, were reviewed, including the potential data collections methods for each database by taking into account the advancement of current computer and information technology. The contributions of this paper come in three folds. First, this paper highlights the potential data sources that deserved to be acknowledged and reflected in the SD domain. Second, this paper provides insights into the appropriate mix and match of data collection methods for SD development. Third, this paper provides a practical synthesis of potential data sources and their suitability according to the SD modelling stage, which can serve as modelling practice guidelines. |
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