Modeling short- and long-term dynamics in the commercialization of technical advances in IT producing industries

Abstract

Manufacturing industries in the IT sector, which are characterized by very low inertia, rapid technological change, and swift technological obsolescence, are a vivid example of how the rapid and effective commercialization of technical advances is critical to the success of high‐technology industries. Radical or breakthrough technologies have both short‐ and long‐term impacts. This paper argues that classical technology diffusion modeling approaches fail to give a fully dynamic picture of technology adoption in an industry, and do not adequately capture dynamic transients caused by short‐term trends and the effect of individual technical changes. It then demonstrates the usefulness of the system dynamics approach in modeling the long‐term system behavior of the commercialization process arising from the dynamic transients caused by short‐term trends and rare events in IT producing industries. Capturing such dynamic transients is critically important because the commercialization process is ultimately shaped by individual decision‐makers making the strategic investment decisions within an industry operating in a particular short‐term context. Copyright © 1999 John Wiley & Sons, Ltd.

A dynamic forecasting model for nursing manpower requirements in the medical service industry

“…The model integrates dynamic characteristics of feedback structures, time lags, and economic conditions. The SD model could provide more reliable forecasts for short to mid-term periods than a statistical model, and thus lead to better decisions (Pardue et al 1999). In addition, the SD model can provide a means of understanding the causes of industry behavior, which leads to better policy establishment (Lyneis 2000).…”

Using System Dynamics to assess the impact of RFID technology on retail operations

“…SD lets understand the overall dynamics of the system, the influence of the various variables to the problem at issue, to support decision making, and test policies through simulations of various case-scenarios. SD has been largely used in production and operations management to explore inventory capacity and instability (Croson and Donohue 2005;Anderson et al 2005, White 1999), as well as to investigate the effects of new technologies on business strategies (Winch 1997;Lyneis 1998;Pardue et al 1999;Disney, Naim and Potter 2004).…”

Information systems research with system dynamics

“…• Groupware-facilitated learning in consulting (Rich, 1998) • Groupware use (Bordetsky and Mark, 2000) • Maintaining mutual knowledge in geographically dispersed virtual teams (Cramton, 2001) • Open online collaboration (Diker, 2003) • ERP implementation critical success factors (Akkermans and van Helden, 2002) • IS investment appraisal (Kennedy, 2001(Kennedy, , 2002 • Business planning for network services (Dutta, 2001a) • Diffusion of data warehouse (Quaddus and Intrapairot, 2001) • Healthcare delivery and services (Tan et al, 2005) • Information security (Xu and Lee, 2003;Torres and Sarriegui, 2004;Sveen et al, 2007;Melara et al, 2003) • IS and knowledge processes in networks (Katsamakas, 2007) • IS outsourcing decision process (McCray and • IT project justification in e-business environments (Dutta and Roy, 2004a) • Knowledge management (Garud and Kumaraswamy, 2005) • Value of information in a business firm (Clark and Augustine, 1992) • Business performance impact of poor IS integration (Georgantzas and Katsamakas, 2008) • Application service provisioning (Currie et al, 2007) • Commercialization process in IT industries (Pardue et al, 1999) • Disruptive innovation in IT markets • E-commerce strategies in small-medium firms (Bianchi and Bivona, 2002) • Information privacy policies in health insurance markets (Thatcher and Clemons, 2000) • IS, information sharing and value chain (Croson and Donohue, 2005;Agarwal et al, 2006;Janamanchi and Burns, 2007) • Limits to growth in electronic commerce (Oliva et al, 2003) • Offshore outsourcing growth (Dutta and Roy, 2005) • Peer-to-peer networks and e-commerce (Pavlov and Saeed, 2004) work at the Center of Technology in Government (University at Albany), they show the roles that trust, knowledge sharing and facilitative artifacts play in the requirements analysis process as different organizations collaborate in a development project.…”