IRANIAN JOURNAL OF INFORMATION MANAGEMENT
Year:2018 | Volume:4 | Issue:1 (6) |Papers Count:7

Regarding the complexity of IT service management (ITSM), the purpose of this study is to provide a mathematical model for evaluating and selecting ITSM solution. Through this research, a new classification of functional and non-functional requirements as well as a fuzzy multi-objective model is presented. The functional requirements derived from the ITIL processes generally include: strategic requirements, design, transfer, operation, and continuous service improvement. In addition, three requirements for availability, capacity and occurrence were carefully examined. a total of 64 criteria for assessing ITSM systems are provided. The developed models with fuzzy approach also include 5 objective and 7 constraints that were implemented with fuzzy multi-objective Technics. The proposed model was used to evaluate and select the software in the IT service provider company. The proposed model not only helps the organization to choose the best supplier, but also helps identify the supplier's weaknesses, reduce decision-making time, and increase the accuracy and ease of decision-making. The results of the methods that used to solved the model show that the MOPSO algorithm has the best result than the other three ones. Respectively NSGA2, Goal programming and epsilon constraint were ranked in the following order.

In recent years, the rate of academic misconduct and consequently, the number of retracted articles in many countries has increased. Because the phenomenon of retraction often occurs in prestigious international journals and after the publication of paper, an article may retract many years later. In order to study retracted articles, the amount of post retraction citation is a most important subject in the scientific relationship and citation behavior of researchers in different areas. The purpose of present study is to compare the world's retracted articles with regard to the amount of prior to retraction citations and post retraction citations by fields and countries. This is an applied research and has been conducted using scientometric methods and descriptive-analytical approach. Statistical population is all retracted articles of world in the fields of humanities, medical sciences, engineering science and pure science which have been indexed by WoS from 1970 to 2017. All articles reviewed in Microsoft Excel for the citation status. Research findings indicate that in all four areas, articles have also been cited after retraction. Except engineering field, which has received a high percentage of prior to retraction citations, other fields had a high percentage of post retraction citations. Among the countries with the most retracted articles in WoS, all citations received by the United States, Iran and Sweden were post retraction citations. In fact this study is a policy research related to citation behavior of researchers of different fields in the world and can play an important role in determining the scientific luck of articles after retraction in different scientific disciplines. In the field of scientific misconduct and retracted articles, there has been no research on the comparative study of the citation of these papers in various sciences.

Presently, due to cellular or mobile networks development, using modern methods and systems for management, monitoring and maintenance of such networks are essential. The study will propose a new method for fault monitoring of the mobile network which works based on fuzzy inference. Nowadays, the researchers have suggested several different models for this field one of which is known as the model of maintenance based on “ fuzzy inference system” developed based on fuzzy logic using fuzzy control technique and belongs to the expert-based systems category. In the proposed method, the alarm rate is considered as the basis for fault detection in the network links. According to the received alarms and considering the possibility of fault occurrence, the membership functions and fuzzy rules base are designed in the FIS system. The fuzzy inference engine is of Mamdani-type function. In the suggested FIS system, the alarms are put into the system as truth values and are compared in the fuzzy inference engine and the resulting fuzzy output received at the last step shall be defuzzified. In this way, the faults in the respective link will be monitored. This method has led to service quality improvement and besides its innovation aspect it is efficient for all different fields.

Customer lifetime value (CLV) is an invaluable metric which plays a pivotal role in assessing the future worth of the customers and the profitability of them. To elaborate upon, CLV is an index so as to evaluate the potential as well as the practical worth of a wide variety of customers. So, it seems obvious that estimation of this metric in different cooperation, especially IT ones, can cause the organizations to identify the behaving trend of their customers so that the organizations can forecast their future purchase as well as the customers’ loyalty to their cooperation. Therefore, in this paper, we present a model in order to estimate the CLV in an IT cooperation. Hence, in the first step, we explain the concept of CLV metric, and its role in today’ s customer analysis. Then, the next step has to do with presenting the RFM method and its parameters for assessing the CLV index. Our proposed case study is included 182 data of customers in an IT cooperation, which we used ordered logistic regression so as to analyze. In the experimental results section, our proposed method applying to this specific cooperation data demonstrates a better performance both in accuracy and precision in comparison with the popular methods.

Research trend analysis for a specific research area (through different time frames) can lead to a better understanding for researchers in that area, and for policy makers in research for contributing in assigning research funds and policies. An important and practical approach to analyzing research trends is to study and review research data and publications using scientometrics and research document processing. In this research, we have proposed a text mining approach for analysing research publications in a specific area, in order to analyze and identify important research topics. In this paper, we propose a method to analysis a scientific trend. The proposed approach is based on clustering keywords through a new co-occurrence matrix. A new metric is also adopted to identify centrality and density (maturity) of a specific research area and identify keywords and contributory topics. For achieving this, we proposed a trend analysis method using co-word matrix with and for deeper analysis we use clustering and strategic diagram with propose indices. In order to test and evaluate the proposed method, we use comparative evaluation method. In addition, for more analysis, we have selected research publications in a specific period of time (2012-2016) in Mechanical Engineering, which are extracted from WoS (Web of Sciences) database. We have applied the proposed metrics to evaluate research trends and identify contributory areas and topics in the selected documents. The comparative evaluation shows an improvement in proposed trend analysis method.

Performance evaluation is a semi-structured issue; therefore, an intelligent decision support system can help decision makers in the Ministry of Science, Research and Technology, as well as, managers of the research institutes to better evaluate the performance, by providing the required knowledge and appropriate evaluation models. Conducting a requirements analysis process in the early stages of the development of a decision support system can guarantee the better performance of this system. The existing information system for evaluating the performance of research institutes affiliated to the Ministry of Science, Research and Technology does not allow for a proper decision on the evaluation and prediction of the performance of these institutes. Although iterative non-linear process model is suitable for analysing the requirements of an information system, it does not consider any risk assessment. In this research, an adjusted iterative non-linear process model was proposed for requirements analysis and risk assessment. To validate this process model, it was implemented through consensus methods such as Delphi and Brainstorming for requirements analysis and risk assessment of an intelligent decision support system suitable for performance evaluation. The calculation of means and standard deviations of successive rounds of Delphi showed that different stakeholders reached a consensus on the main functional and non-functional requirements of the intelligent decision support system. In addition, the risks of the new system were identified.

The purpose of this quantitative research, conducted in a survey methodology, is to examine the role of the validity for domestic political news on sharing this news in cyberspace in the youth community. The statistical population is youth in North and South of Tehran. Sampling method was simple random and multiple cluster. 400 people were selected. data were collected via questionnaire with five levels of Likert scale. The independent variable is validity, which is based on Philip Meyer's validity indicators, including reliability, accuracy, unbiased, completeness and disinterested indicators. These indices According to accreditation of news to audience can influence on domestic political news sharing in the youth community. Based on the results of research, there is a significant and positive correlation between credit for domestic political news among youth and news sharing in cyberspace. According to the results of the research, based on the five indicators of the validity of the news, more than half of the sample members believe that domestic political news has a lack of reliability, accuracy, unbiased, completeness, disinterested, which makes it do not share the news in cyberspace.