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Disruptive Innovation Strategy Effects on Hard-Disk Maker Population: A System Dynamics Study

Disruptive Innovation Strategy Effects on Hard-Disk Maker Population: A System Dynamics Study

Nicholas C. Georgantzas, Evangelos Katsamakas
Copyright: © 2007 |Volume: 20 |Issue: 2 |Pages: 18
ISSN: 1040-1628|EISSN: 1533-7979|ISSN: 1040-1628|EISBN13: 9781615200085|EISSN: 1533-7979|DOI: 10.4018/irmj.2007040106
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MLA

Georgantzas, Nicholas C., and Evangelos Katsamakas. "Disruptive Innovation Strategy Effects on Hard-Disk Maker Population: A System Dynamics Study." IRMJ vol.20, no.2 2007: pp.90-107. http://doi.org/10.4018/irmj.2007040106

APA

Georgantzas, N. C. & Katsamakas, E. (2007). Disruptive Innovation Strategy Effects on Hard-Disk Maker Population: A System Dynamics Study. Information Resources Management Journal (IRMJ), 20(2), 90-107. http://doi.org/10.4018/irmj.2007040106

Chicago

Georgantzas, Nicholas C., and Evangelos Katsamakas. "Disruptive Innovation Strategy Effects on Hard-Disk Maker Population: A System Dynamics Study," Information Resources Management Journal (IRMJ) 20, no.2: 90-107. http://doi.org/10.4018/irmj.2007040106

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Abstract

To encourage premium-quality information systems (IS) research in areas where dynamic complexity rules, this article combines disruptive innovation strategy (DIS) theory with the system dynamics (SD) modeling method. It presents a computer simulation model of the hard disk (HD) maker population overshoot and collapse dynamics. Data from the HD maker industry help calibrate the parameters of the SD model and replicate the HD makers’ overshoot and collapse dynamics, which DIS allegedly caused from 1973 through 1993. SD model analysis entails articulating exactly how the structure of feedback relations among variables in a system determines its performance through time. The analysis of the HD maker population model shows that, over five distinct time phases, four different feedback loops might have been most prominent in generating the HD maker population dynamics. The article shows the benefits of using SD modeling software, such as iThink®, and SD model analysis software, such as Digest®. The latter helps detect exactly how changes in loop polarity and prominence determine system performance through time. Strategic scenarios computed with the model also show the relevance of using SD for IS research and practice.

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