A coevolutionary analysis of organisational systems and processes: Quantitative applications to information system dynamics in small entrepreneurial firms

2009 ◽  
Vol 20 (6) ◽  
pp. 762-781 ◽  
Author(s):  
Gavin C. Reid ◽  
Julia A. Smith
Keyword(s):  
Information System ◽  
System Dynamics ◽  
Entrepreneurial Firms

Information System Dynamics: An International Research Programme

Paradigm ◽  
2009 ◽  
Vol 13 (2) ◽  
pp. 64-68
Author(s):  
Ahmed Bounfour ◽  
Surinder Batra
Keyword(s):  
Information System ◽  
System Dynamics ◽  
International Research ◽  
Research Programme

Applying system dynamics approach in software and information system projects: A mapping study

2018 ◽  
Vol 93 ◽  
pp. 58-73 ◽  
Author(s):  
Eduardo Ferreira Franco ◽  
Kechi Hirama ◽  
Marly M. Carvalho
Keyword(s):  
Information System ◽  
System Dynamics ◽  
Mapping Study

scholarly journals Nonequilibrium Information Landscape and Flux, Mutual Information Rate Decomposition and Entropy Production

2017 ◽  
Author(s):  
Qian Zeng ◽  
Jin Wang
Keyword(s):  
Information System ◽  
Mutual Information ◽  
Markov Chains ◽  
System Dynamics ◽  
Entropy Production ◽  
Driving Force ◽  
Detailed Balance ◽  
Information Rate ◽  
Equilibrium Time ◽  
Information Landscape

We explored the dynamics of the two interacting information systems. We show that for the Markovian marginal systems the driving force for information dynamics is determined by both the information landscape and information flux. While the information landscape can be used to construct the driving force to describe the equilibrium time reversible information system dynamics, the information flux can be used to describe the nonequilibrium time-irreversible behaviours of the information system dynamics. The information flux explicitly breaks the detailed balance and is a direct measure of the degree of the nonequilibriumness or time irreversibility. We further demonstrate that the mutual information rate between the two subsystems can be decomposed into the equilibrium time-reversible and nonequilibrium time-irreversible parts respectively. This decomposition of the mutual information rate (MIR) corresponds to the information landscape-flux decomposition explicitly when the two subsystems behave as Markov chains. Finally, we uncover the intimate relationship between the nonequilibrium thermodynamics in terms of the entropy production rates and the time-irreversible part of the mutual information rate. We found that this relationship and MIR decomposition still hold for the more general stationary and ergodic cases. We demonstrate the above features with two examples of the bivariate Markov chains.

The Information System within the Organization

2011 ◽  
pp. 209-225
Author(s):  
Bruce R. Campbell ◽  
G. Mike McGrath
Keyword(s):  
Information System ◽  
Information Systems ◽  
System Dynamics ◽  
Field Study ◽  
Organizational Environment ◽  
Considerable Effort ◽  
Considerable Evidence ◽  
Is Projects

There is considerable evidence that many information systems (IS) projects fail because of organizational, “softer” or “people-related” issues. Considerable effort has been expended in efforts to design improved development methodologies that incorporate these softer aspects. Less attention, however, has been directed towards approaches that increase our understanding of the interaction of the implemented IS with the wider organizational environment. Our thesis is that system dynamics (SD) has much to offer here and, in this chapter, we illustrate the utility of the SD approach in this context through presentation of a field study.

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