Masoumeh Amini, Hossein Vakilimofrad and Mohammad Karim Saberi
Information security is a critical issue in all organizations. The success of information security in libraries depends, to a large extent, on the effective behavior of…
Abstract
Purpose
Information security is a critical issue in all organizations. The success of information security in libraries depends, to a large extent, on the effective behavior of administrators, librarians, users and all human staff. Accordingly, this study aims to design a model for identifying human factors affecting information security in libraries.
Design/methodology/approach
This study is applied in terms of research objectives and is a survey in terms of data collection. Moreover, it goes under the rubric of structural equation modeling in terms of the relationship between variables. The statistical population consisted of 100 managers and librarians of academic and public libraries of Hamadan in Iran. A questionnaire was used for data collection. The face and content validity of the questionnaire were examined using the expert’s opinions in the field of Iranian libraries. Also, the reliability of the questionnaire was calculated through Cronbach’s alpha coefficient. Data were analyzed using SPSS 16 and Smart PLS 2.
Findings
The results showed that among the components of information security, the highest score was designated to self-esteem (4.11 ± 0.57) and level of skill (4.07 ± 0.59), whereas the lowest score belonged to the level of education (3.51 ± 0.74). Ranking human factors affecting information security showed that experience with Rank 1 had the most impact, whereas the level of skill with Rank 6 had the least impact on information security.
Originality/value
In this study, for the first time, a model was designed and tested for human factors affecting information security in libraries. Information security professionals, librarians and library and information science researchers can exploit this model in the future.
Details
Keywords
Nasim Ansari, Hossein Vakilimofrad, Muharram Mansoorizadeh and Mohamad Reza Amiri
This study aims to analyze and predict a user’s behavior and create recommender systems in libraries and information centers, using data mining techniques.
Abstract
Purpose
This study aims to analyze and predict a user’s behavior and create recommender systems in libraries and information centers, using data mining techniques.
Design/methodology/approach
The present study is an analytical survey study of cross-sectional type. The required data for this study were collected from the transactions of the users of libraries and information centers in Hamadan University of Medical Sciences. Using data mining techniques, the existing patterns were investigated, and users’ loan transactions were analyzed.
Findings
The findings showed that the association rules with the degree of confidence above 0.50 were able to determine user access patterns. Furthermore, among the decision tree algorithms, the C.05 predicted the loan period, referrals and users’ delay with the highest accuracy (i.e. 90.1). The other findings on feedforward neural network with R = 0.99 showed that the predicted results of neural network computation were very close to the real situation and had a proper estimation of user’s delay prediction. Finally, the clustering technique with the k-means algorithm predicted users’ behavior model regarding their loyalty.
Practical implications
The results of this study can lead to providing effective services and improve the quality of interaction between librarians and users and provide a good opportunity for managers to align supply of information resources with the real needs of users.
Originality/value
The results of the study showed that various data mining techniques are applicable with high efficiency and accuracy in analyzing library and information centers data and can be used to predict a user’s behavior and create recommendation systems.