دانلود رایگان مقاله تدوین تئوری برای برآوردن الزامات علم سیستم

Abstract

Just as Lee, Briggs, and Dennis (2014) showed that a rigorous conception of “explanation” leads to requirements for a positivist theory to satisfy, and just as Lee and Hovorka (2015) showed that a rigorous conception of “interpretation” leads to requirements for an interpretive theory to satisfy, we show that a rigorous conception of “systems” leads to certain requirements for a systems theory to satisfy. We apply basics of systems science in general, as well as basics of Luhmann's (Luhmann, 1995; Moeller, 2006) systems perspective in particular. We illustrate these basics with empirical material from a case about the role of information technology in anti-money laundering. The example demonstrates that research in information systems, which has been informed by positivism, interpretivism, and design, can be additionally and beneficially informed by systems science — which, ironically, has been largely absent in information “systems” research.

6. Discussion and conclusion

As mentioned earlier, systems science is not so much an empirical science about phenomena in nature or society as it is an approach that empirical sciences (including IS research) can incorporate. The creation of systems theory itself has involved, among other things, a gradual evolutionary process of incorporating concepts from a multiplicity of scientific fields into a highly abstract lexicon; this convergence towards theoretical abstraction has been a long and bottom-to-top process of synthesis. The goal that systems theory itself has been seeking has been one of reaching the highest levels of abstraction possible. Of course, this was not for the mere sake of abstraction itself, but a reflection of the need to tackle phenomena of greater complexity (e.g. social phenomena). Furthermore, the benefits that systems theory can provide to the field of information systems are not only restricted to a theoretical level but extend to a practical one as well, particularly when it comes to academia-industry interactions. Systems theory can facilitate communication between academia and industry that is far better than what structuration theory – to bring up just one example – could achieve. The success of Soft Systems Methodology (attributed mainly to Checkland and Scholes (1990) is a testament to the possibility of delivering industry relevance through systems concepts. A reason that systems theory can bring additional value for interactions between academics and practitioners pertains to the following: as the development of systems theory was fuelled by many different disciplines in order to assist the synthesis that it promised, its lexicon evolved to include such inter-disciplinarity. As a result, systems theory can be more easily understood by different fields as it transcends physics, chemistry, computer science, biology, sociology, politics, art, economics, and other disciplines. By lending itself to being stated in lay terms more readily than do other theoretical approaches, systems theory can be communicated back to IS practitioners. That is of particular significance for the IS community within which individuals with different scientific backgrounds find their home for research and/or practice