Inferring causal interpretations of change-readiness using causal-models:a knowledge-based perspective
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Other TitlesCommunications in Computer and Information Science Book Series
AbstractThe ability to understand the conditions in which humans make causal judgements continues to arouse debate from cognitive science, philosophy, and even the domain of computer science. While for most organisations, change is a necessary impetus to sustainability, it is difficult to directly infer cause and affect relationships on human readiness without understanding how humans arrive causal inferences during a complex change situation. To explore the causal interpretations of human readiness-for change the research applies the systems thinking approach, utilising causal models to analyse the cause and effect of human readiness. The research contributes to a knowledge-based perspective examining the various factors effecting readiness-feedback, and how readiness-for change knowledge is received, and processed. The paper demonstrates the application of causal models to interpret the role of human readiness through a case study on the infectious outbreak of Clostridium Difficile (C. difficile). Then we propose a theory of readiness-for change through the lenses of Systems Thinking into a Knowledge Based Reasoning Framework.
CitationPatel S, Samara K, Patel D (2011) 'Inferring causal interpretations of change-readiness using causal-models:a knowledge-based perspective', in Gusev M, Mitrevski P (ed(s).). Communications in Computer and Information Science Book Series , ICT Innovations 2010 edn, : Springer, Berlin, Heidelberg pp.27-39.
PublisherSpringer, Berlin, Heidelberg