Risk Assessment of Professional Expertise of Human Resources at Digital Libraries of State Universities in Tehran According to ISO 31000 Standard

Risk assessment according to ISO 31000 standard is a systematic and logical process that includes identification, analysis and measurement. The risk identification process involves determining the type and source of potential risks. Risk analysis involves determining the estimated level of risks in terms of indices such as the probability and potential consequences of the risk. The measurement involves comparing the estimated levels of risks with respect to the analysis criteria and eventually the risk ranking. The present study aims to assess (identify, analyze and measure) the risks of professional expertise of human resources at digital libraries according to ISO 31000 standard. The present research is an applied nature and to implement it, survey and analytic methods have been applied with Shannon Entropy to weight risks and fuzzy TOPSIS to evaluate them. Primarily the most important risks were identified using the relevant resources and the results of previous researches, a process which led to the formulation of a questionnaire consisting of 38 items. First the demographic characteristics were described and the central statistical indices (mean and median) as well as the dispersion index (standard deviation) were examined. Next, using the weighted average index to the criteria defined by Shannon's entropy method and their application in TOPSIS software, positive and negative ideal options were determined. In the risk assessment stage, risks were prioritized by comparing the distance of each one from the positive and negative ideal options. The content validity and reliability equals 0.955 according to Cronbach's alpha test. 18 professional expertise risks were identified. Risk of having the necessary knowledge about semantic web languages and tools with the minimum distance from the positive ideal point by the value (0.0103) and the maximum distance from the negative ideal point by the value (0.104), and the maximum coefficient close to (0.9103) ranked first. It means that this risk has the closest distance to the ideal positive point and is the most important.Risk of employees' ability to provide digital reference services ranked 18th with the minimum distance from the negative ideal (0.0114) and the maximum distance from the positive ideal (0/1043), and the minimum proximity coefficient (0.0982). That is, it has the maximum distance from the positive ideal option and is the least important. Among the 18 risks of professional expertise of human resources at digital libraries identified, the risk of "having the necessary knowledge about semantic web languages ​​and tools" is the first priority. This reveals that the human resources of academic digital libraries are not in a good position in terms of up-to-date knowledge and modern information technologies and the semantic web that underlies ontologies and linked data, etc.