INTRODUCING A THEORETIC MODEL AND AN EMPIRIC NORM FOR INFORMATION RISK MANAGEMENT IN DECISION MAKING

Nowadays computer mediated communication (CMC) and the high volume of computed and stored information is getting a business on its own. Information is collected, aggregated, analyzed and used to create real business advantage and value but also risks within companies and also outside on the markets in a high volume. On the other hand, single individuals still need to deal and interpret this sheer mass of increasing information continuously. The change in information management and handling triggers the ongoing changes in decision makings on the operational level as well as on the strategic level. Information is a good sold itself and triggered an own industry of information brokerage. It opens the question of trust and correctness into the information itself but also into the information source and opens a complete new, not modelled yet discipline of Information Risk Management. Currently no model exists in science to measure Information Risk Management where as there is a highly increasing demand to measure case-based applicability and success of Information Risk-Management (IRM) activities in a broader context. The authors propose a new model for IRM and derive a qualitative prove of variables/measure and a quantitative empiric-norm as a base for further perception comparison with specifically targeted groups.