نشریه مدیریت اطلاعات
سال هشتم شماره 2 (پیاپی 15، پاییز و زمستان 1401)

Due to the limited power of human perception of the outside world and also the power of comprehensive and deep reasoning, he faces uncertainty and uncertainty. Multi-criteria decision-making methods, including methods to increase confidence and reduce uncertainty due to judgment Decision makers and comprehensiveness of information. One of the indicators calculated in the decision matrix in conditions of uncertainty is the minimum regret index. The purpose of this study is to identify options with the least regret in selecting faculty members. Therefore, using the variables obtained from the previous literature and the opinion of experts in the field of study, an expert system was designed to assist in decision-making in attracting faculty members.The results of the analysis indicated that the options of academic record, ethics (communication skills), teaching ability (ability to express and convey content) and decision-making skills are indicators that have the least risk of being considered in the scientific selection of individuals. According to the results of this research and the designed expert system can be used to help decision-making in attracting faculty members of universities by reducing time, increasing the quality and accuracy of decision-making.

Today, data generation through smart equipment, including mobile phones, has faced a significant growth, and clustering is one of the most widely used knowledge discovery techniques in big data. Density-based clustering (DBSCAN) is one of the most efficient clustering algorithms in data mining, and despite having advantages, it also has problems, such as the difficulty in determining the input parameters, as well as not being able to detect clusters. with different densities. In the proposed algorithm of this article, it is inspired by the K-DBSCAN algorithm in grouping large data with the aim of reducing the clustering execution time.In addition, by using K-Means and H-DBSCAN algorithms, different densities of the data set were identified and an Eps radius was determined for each density, and then, the proposed density-based clustering algorithm was developed with parameters The matching is applied to the data, and in fact, the innovation of this article is the use of K Means clustering and the estimation of different densities in the DBSCAN clustering method. The proposed algorithm has been compared with the simple DBSCAN clustering algorithm and two developed K-DBSCAN and H-DBSCAN algorithms on four standard data sets: Image segmentation, Pendigit, Letters and Shuttle control. The results show that the proposed algorithm is superior to other algorithms when both time and accuracy are criteria in clustering.

This research aims to create a data warehouse (Admitted to store and organize Documents) with data management Approach, strategic assessment of the views of senior managers, IT managers and heads of departments of the National Library and Archives of the Islamic Republic of Iran. This is a type of research, and application of research methods, descriptive. The study population consisted of 30 patients (10 senior managers, 10 IT managers and 10 heads of groups), the National Library and Archives Organization of the Islamic Republic of Iran and are 50 National Library and Archives of Iran’s users has been selected sampling method. Data is based on a Likert questionnaire has been developed. Validity and content validity and reliability with Cranach’s alpha coefficients of the views of senior managers by 82%, IT managers perspective with 74% and heads of groups perspective with 78% is estimated. Results indicate that the position of senior managers with an average of 5.35, IT managers with an average of 57.8 and heads of each class with the mean average 39.7 To create a data warehouse with the National Library and Archives of Iran's strategic management processes is positive. Structural communication between senior managers and IT managers plays an important role in implementing the data warehouse of the National Library and Archives of Iran. It is essential that the directors of the National Library and Archives of the Islamic Republic of Iran to establish strategic data warehouse management approach and systematic actions necessary to comply with the principles and practice of the organization needs to take action. Creating data warehousing should be consistent with the organization's strategic management processes, missions, vision, and core objectives. It must also consider the long-term goals of the organization.

The main aim of this research is to study the scientific activity of the authors of highly-cited articles in the iMetrics field in the ResearcGate scientific social network and its impact on the scientometric indicators in the Google Scholar citation database. This study is a basic and applied research. The research community consists of the authors of the highly-cited articles in the field of iMetrics, indexed at the Scopus database in 2010-2019. In the first step of this research, all articles published in two core journals in the field of imetrics, namely Scientometrics and Journal of informetrics in the period under study are extracted from Scopus database.The extracted articles have been sorted in descending order based on the number of citations and the top 200 articles have been selected as the sample for review in terms of citation rate. The authors of these articles, who are members of the ResearchGate social network and also have profiles on Google Scholar, were then identified. Then, in the second step of the research, the relationship between the alternative metrics of the authors of the ResearchGate and the productivity indicators of these authors in the Google Scholar system was examined. The findings showed that due to the low correlation coefficient between the variables, there is not much relationship between the alternative measures of ResearchGate member authors and the H-index as well as the i10 index of the same authors in Google Scholar. In general, it can be said that although ResearchGate and other scientific social networks increase research communication and sharing of scientific products, this issue can be effective in the quantity of research outputs and increasing the visibility of scientific products, but to determine the actual usefulness of these media in practice , can be analyzed analytically by conducting separate researches in other thematic fields and on a wider scale.

Continuous advances in e-business have put on the agenda of businesses the approaches that lead to value creation and long-term communication with users. Therefore, many IT managers believe that the future of business depends on "user experience management". The main purpose of this study is to explain the behavior of social network users in e-business. In this study, CLEMENTINE software was used to perform data mining based on Bayesian network techniques and artificial neural networks. The data of this research was based on a sample of a thousand documents and reports of Elite online store during the years 1395 to 1400, seasonally. The findings of the present study showed that it was important that based on the initial model and the proposed research, after conducting a qualitative case study in the Elite online store, the final model was developed according to the following variables: "Business users profile" component based on indicators such as: Education Users; Age of users; Users' revenue; Gender of users; Was determined. The component of "managing the behavior of business users" based on indicators such as: the number of likes of business users; Number of business users sharing; Number of comments from business users; Number of business user posts; Was determined. The component of "managing relationships with e-business users" based on indicators such as: user surveys; Customizing products and services; Adherence to the promise with the user; Ways of communicating with the user; Was determined. The component of "business social network management" based on indicators such as: the amount of social media feedback, the quality of content in the CMS; Information on business products and services; Features of a business website in SEO; Was determined.

Performance indicators are a suitable tool for the implementation of infrastructural, research and process-oriented management projects in universities and higher education institutions, as well as the evaluation of these institutions, which can be used to compare the past performance, current and desired status of the institutions with the standards. The purpose of this study is to evaluate the performance of non-governmental research institutions in Iran in the fields of humanities and engineering. This is an applied research that was conducted with a scientometrics approach and based on the evaluation model of the Sanandaj handbook. The research community are non-governmental research institutions that have received permission from the Ministry of Science, Research and Technology. In this study, two institutes from both fields that had better performance among their peers were selected for comprehensive evaluation. In general, the evaluation results showed that the "B" engineering field institute has a good situation compared to the "A" humanities institute. Undoubtedly, the use of short-term, medium-term and long-term strategic plans and the promotion of research activities in the Institute of Engineering have not been without influence. It is necessary for non-governmental research institutions to prepare or revise the strategic plan and annual self-evaluations in accordance with the dimensions and indicators of the Ministry of Science, Research and Technology, to provide the basis for growth and promotion in order to be effective and fulfill their mission in the research field of the country.

In this regard, in this article, by examining and analyzing the lifetime value of customers in the banking industry, a suitable and innovative model has been presented to measure the lifetime value of customers. To achieve this goal, first by reviewing the studies available in the literature, the primary indicators were calculated and by collecting the indicators available in one of the domestic banks, their list was updated. For this purpose, a descriptive and analytical approach was used based on consensus techniques and expert opinion analysis, and primary data was collected through semi-structured interviews with banking industry experts. Then, using the Delphi method, a consensus-building process was carried out among experts to achieve an acceptable and accurate set of indicators for evaluating customer lifetime value based on multiple periods of feedback and modification. The obtained results indicate the approval of a three-part model which is based on past behavior, future behavior and customer loyalty, and for each part of the model, indicators from the literature and the bank database were determined. The designed model leads to the improvement of the information required by the bank's database to better identify and evaluate customers, and with its help, it is possible to identify indicators suitable for measuring customer loyalty and measuring the future value of bank customers. Finally, this paper provides strategies for using customer lifetime value data in profitability management and developing strategies that help improve customer experience and sustainable bank growth. This research not only provides valuable information for researchers and bank managers, but also provides a deeper understanding of the relationship between customer lifetime value and bank customer segmentation.