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LAP Lambert Academic Publishing Mitigating Information Security Risks during Operation Transition: Model and Data

Name: Mitigating Information Security Risks during Operation Transition: Model and Data
Brand: LAP Lambert Academic Publishing
Price: 67.0 GBP
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Description

Information security is becoming increasingly critical as computers and the internet have become the information infrastructure of our society and of most business organizations, including those in hazardous industries. Previous research mostly focused on technology measures. Recently, research on human factors and management factors has emerged. In this study, we investigate information security issues from management using system dynamics. The model-building process employs an iterative approach with model-based interventions (include group model-building workshops, model formulation interviews, and model validation interviews) and model development. A series of increasingly more detailed models are created in stages. Given the validated model, we tested various scenarios to search policies for a safe, fast and successful operation transition. Tradeoffs, such as those between fast transition and high security risk and between short-term and long-term benefits are identified. Being aware of such tradeoffs prevents the management from pursuing one target without considering other side effects. About the Author Qian Ying is an assistant professor in Shanghai University, school of management, information management department. She obtained her Ph.D. in 2010 from University of Bergen, where she also got her master degree in 2004. In her Ph.D. study, she participated in a research project in University of Agder. Her Bachelor degree was from Fudan University.

Product Specifications

Brand: LAP Lambert Academic Publishing
Format: paperback
ASIN: 3847311816
Category: Books > Subjects > Business, Finance & Law > E-Commerce > E-commerce
Domain: Amazon UK
Release Date: 25 December 2012
Listed Since: 12 February 2013

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LAP Lambert Academic Publishing Mitigating Information Security Risks during Operation Transition: Model and Data

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