EMPLOYING COGNITIVE BIAS IN KNOWLEDGE RISK MANAGEMENT: AN ANALYTICAL STUDY OF THE OPINIONS OF A SAMPLE OF WORKERS IN AL-DIWANIYAH GENERAL HOSPITAL
Keywords:
cognitive bias, knowledge risk management, jumping on conclusionsAbstract
The purpose of this research is to explore the relationship between cognitive bias in its various dimensions (jumping on conclusions, inflexibility of thinking, external attribution, attention to threats, social cognitive problems, subjective cognitive problems, safe behaviors) and managing knowledge risks(KRM) represented by its dimensions (human risks, technological risks, operational risk). Much has been written about knowledge risk management and the analytical methods that can be measured. The need for accurate and timely risk mitigation has accelerated with the pace of new and replacement programmes. And part of the process that needs to be updated is that risk has to be seen as a feature of the systems, just like cost, schedule, technical compliance and so on. It is imperative that knowledge systems engineers in contemporary organizations develop and follow a knowledge risk management plan in the early stages of any project. It is also important to know the impact of cognitive bias on the knowledge risk management process. This research confirms that most knowledge risk management programs fail to be as effective as they can be due to a number of motives that are often overlooked, such as cognitive bias with the scarcity of addressing the issue of cognitive bias. When asked, most knowledge theorists claim that they have no bias. They insist that they only use logic, reasoning and mathematics to make decisions. Data were collected and reviewed for this research. The health sector workers in Employees in the upper and middle management in AlDiwaniyah General Hospital were selected as a community for this research, amounting to (200) workers. The questionnaire was used as a tool for collecting data from the surveyed sample, and a set of statistical methods were used in data analysis and statistical programs such as (SPSS V.27) and a program (AMOS V.26). The results of the analysis showed that cognitive biases have an impact on knowledge risk management. Knowing these biases and their potential impact on the project will lead to better risk management. It also came out with a set of practical recommendations that are beneficial to the research community
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