Scientific and Techniques of Information Management
Year:2022 | Volume:7 | Issue:4|Papers Count:11

Concurrent with the rapid development of digitalization in various fields, the signs of entering the age of virtual life have become more manifest. The advent of social networks, spaces mixed with virtual reality and the strong tendency of citizens to communicate with the new space, and the unprecedented acceptance of communications and relationships in this space, has necessitated the digital transformation. Although the term of Digital has been designated as an adjective for transformation, digital transformation is not limited to the digitalization directive or process. Digital transformation is the process of transitioning traditional entities based on communication, relationships, and the physical ecosystem into a world based on non-physical occasions and entities. Knowledge management is one of the most important facilitators of change. The knowledge nature of digital transformation and its highly dynamic and variable features require changes in attitudes and the facilitation of knowledge management. For this reason, transformational knowledge management can be suggested as a suitable solution. In this paper, an attempt has been made to briefly explain the formation process and the distinctive features of transformational knowledge management called Knowledge Management 4. 0.

Purpose: Data Quality plays a vital role in the performance and success of an organization and can be compared to oxygen for human beings. Therefore, maintaining data quality helps organizations in low operating costs and increment in revenue. If data has not been offered on time and adequate to each department’, s quality expectation, such organization may not be able to make successful decisions. First step of data quality enhancement is the acquaintance of data quality dimensions. Identifying and grouping various dimensions of data quality allow experts to use data quality enhancement tools and methods on information improvement processes. Methodology: The present study is applied in terms of purpose and analytical-survey research. In this paper, to enhance the level of data quality of university portals, users' requirements (voices) of a university portal have been prioritized using several data quality-related questionnaires by combining Kano & AHP techniques. A designed matrix of a 4-step QFD has been formed, which started with the users' requirements and ended with design methodologies. Findings: As a result of combining Kano & AHP techniques, basic requirements have higher priority than others. It has been defined in this paper that entering data in various formats is the most important users' requirement. Based on QFD analysis, XML & HTML are more proper and useful in comparison to other platforms and programming languages to improve the level of data quality and fulfill users' requirements. In addition, flexibility could be the most important Engineering Characteristics parameter in designing a portal. HVR software can perform a reliable and secure platform to prepare rapid and optimized data integration. Conclusion: The Quality Function Deployment method could be an appropriate solution to solve problems regarding data quality in the condition that it consists of programming to the designing process.

Purpose: This study was carried out to identify and rank factors affecting the success of knowledge management implementation in the gas organization of Khuzestan Province by the Analytical Hierarchy Process Method. Methodology: The research method was descriptive-exploratory. The statistical population included all managers and senior experts of Khuzestan Gas Company, 35 of whom were selected by snowball sampling. The data gathering tool was a researcher-made questionnaire. The face validity of the questionnaire was confirmed by the professors and managers of Khuzestan Gas Company. Cronbach's alpha method was used to determine its reliability, which was estimated at 0. 877 and 0. 892. In this study, SPSS and Expert Choice software were used to analyze data from descriptive and inferential statistics. Findings: Based on the Delphi technique, 6 factors and 33 important factors were identified. The results of the analytical hierarchy process show that in terms of importance, management and leadership factors, information technology, organizational culture, organizational structure, human resource management, and processes and activities factors were ranked first to sixth. Conclusion: According to the results of this study, we can use the decision model derived from identifying and ranking of factors affecting the success of knowledge management implementation in the gas organization of Khuzestan Province by Analytical Hierarchy Process Method to improve and enhance the competitive position of the company. According to the findings obtained from the priority of agents, creation, and development of technological infrastructure, application of knowledge-based strategy in formulating company plans and providing appropriate information systems for storage, transfer, and exchange of knowledge, the rule of creative and critical thinking in culture, engagement, development of social relations between working and business communities as well as informal relations among company employees to increase satisfaction and motivation of knowledge transfer and other knowledge management processes to improve and enhance the company's competitive position in knowledge management development can be implemented and run.

Purpose: The present study aimed to investigate the relationships between information systems and organizational structure elements (centralization, complexity, and formalization) as well as the effect of e-literacy on the use of information systems. Methodology: The present study was descriptive-correlational and survey. The statistical population consisted of Zahedan Governorate experts. Therefore, the research data was collected using a researcher-made questionnaire containing 28 questions in three sections that consist of reviewing the status of e-literacy, reviewing the use of information systems, and reviewing the status of structural elements of the organization. 90 copies of questionnaires were distributed in person among the population members after confirmation of content, convergent, and divergent validity and the reliability of the questionnaire by a group of experts. Data analysis was done by structural equation modeling and SMART PLS 3. 0 software. Findings: The research results indicated that there were positive and significant relationships between the information system and employees' e-literacy. So that the higher the level of e-literacy of the employees of the organization, the more they will use the information systems in the organization. Furthermore, there were negative and significant relationships between using information systems in organizations and formalization and complexity, so that by using information systems in the organization, we will see a decrease in the level of formality and complexity. While there was a significant positive relationship between the use of information systems and centralization in organizations. So that with the use of information systems, the level of centralization will increase. Conclusion: According to the research findings, we can be sure of the use of information systems in the organization by hiring employees with high information literacy or holding training courses by using different methods of e-learning, mobile learning, and face-to-face learning to develop staff information literacy. So we can ensure the actual use of information systems in the organization,as a result, it will lead to less formalization as well as more complexity and higher centralization in the organization.

Purpose: The main purpose of this article is to analyze the data of the Tehran Municipality websites and provide data mining solutions for managers' decisions. Methodology: This research is fundamental and in terms of nature, it can be considered analytical. The data collection method was the field. The statistical population was selected from 220 domains of Tehran Municipality and for analysis, data mining techniques were used to discover the appropriate decision model of city managers. The source of data collection was web analytics and tools used by Google Analytics. Findings: The accuracy of the LSTM deep neural network is 99. 84%. Network accuracy is 99. 90%, the call is equal to 99. 63%, the error is equal to 0. 16%, MSM standard is equal to 0. 003. The accuracy of the DBScan method with other basic methods for analyzing the data of Tehran Municipality websites is 99. 84%, the deep learning method is 99. 25%, the nearest neighbor method is 99. 81% and the decision tree method is equal to 99. 8%. With these interpretations, the rate of improvement of the accuracy of the DBScan method in comparison with the deep learning methods is equal to 0. 59%. Conclusion: Finally, by simulating the DBScan method to identify and analyze the data of Tehran Municipality websites and provide data mining solutions for managers' decisions, it was observed that the proposed method provides suggestions to managers to improve site visits and The performance of the municipality is significantly effective.

Purpose: Due to the digital revolution and increasing development of ICTs, and the entrance of national as well as international organizations to such an arena, the foundation of transparency is formed through virtual environments including organizational websites. As a result of the importance of this subject, i. e. transparency, and also, the undeniable role of human rights international organizations, the present research aims to explain and evaluate the transparency status of websites at these organizations. Methodology: To do this, firstly, the research population consisting of 11 human rights international organizations was selected. A questionnaire revolving around 3 main dimensions (access to information, contribution to/engagement in decision making, and access to outputs) was developed and utilized, and then, the gathered data were analyzed. Findings: Based on the analysis of collected data, UNESCO (with 100 percent coverage of transparency items) and HRWF (with 40 percent coverage of transparency items) were the best and the worst performers, respectively. Moreover, the three organizations "International Labor Organization", "World Health Organization", and "United Nations Children's Fund" (joint second rank with 97. 5 percent coverage of transparency items), "Civil Rights Defenders" (third rank with 92. 5 percent coverage of transparency items), "Anti-Slavery International" (fourth rank with 90 percent coverage of transparency items), "United Nations" (fifth rank with 87. 5 percent coverage of transparency items), FIAN (sixth rank with 75 percent coverage of transparency items), "Amnesty International" (seventh rank with 72. 5 percent coverage of transparency items), and "Center for Economic and Social Rights" (eighth rank with 67. 5 percent coverage of transparency items) were identified. Conclusion: Finally, the overall performance of the international organizations of human rights was evaluated as acceptable. Regardless of the current situation, in line with much more performance and so better transparency, some recommendations revolving around the three main dimensions (i. e., access to information, contribution to/engagement in decision making, and access to outputs) were emphasized.

Purpose: With the beginning of the third millennium, the role of human resources has become more and more important, to the point that some consider it the only factor in gaining a sustainable competitive advantage. This is especially true in knowledge-based businesses. As a result, for a knowledge-based company, human capital is the most important asset, and the better the quality of this asset, the more likely it is that the business will survive, succeed, and thrive. One of the indicators of the desirability of human resources is the discussion of human resource agility. According to these materials, the present study was conducted to investigate the mediating role of knowledge absorption capacity in the impact of innovation culture on human resource agility among all employees of Zahedan Science and Technology Park in Sistan and Baluchestan province. Methodology: This is applied research that has been done by the descriptive correlational method. Data collection tools are standard questionnaires whose reliability was assessed using Cronbach's alpha test and their validity was assessed using content validity. The statistical population includes all members of Zahedan Science and Technology Park companies. The sample size was determined using the Jersey and Morgan table, up to 130 people by simple random sampling. To confirm or refute the hypotheses, the structural equation modeling method was used with the help of Smart-PLS software. Findings: The findings showed that the culture of innovation has a positive and significant effect on the capacity to absorb knowledge and agility of human resources and also the capacity to absorb knowledge on the agility of human resources. In addition, the mediating role of knowledge absorption capacity in the impact of innovation culture on human resource agility has been confirmed. Conclusion: According to the results of the research, the culture of innovation has a significant effect on the capacity to absorb knowledge and human resource agility in science and technology park companies. Therefore, managers of science and technology parks should take action to strengthen this culture by making structural changes and supporting creative ideas and laws. According to the research results and the importance of innovation and innovation culture, suggestions in the field of managerial and structural changes in science and technology parks in Zahedan such as changes in the external environment of the organization, institutionalizing trust among employees, commitment to change among employees, support Creative ideas, few rules, extensive informal communication, face-to-face communication.

Purpose: This study aimed to investigate the role of effort expectancy, social influences, and facilitating conditions in the intention to use information and communication technology with the mediating role of performance expectancy among graduate students of Tabriz University of Medical Sciences. Methodology: The present study is a descriptive-survey correlational study based on the structural equation model in terms of applied purpose and in terms of data collection. The statistical population of the study is all graduate students of Tabriz University of Medical Sciences with a number of 1500 people. The statistical sample of this research is 306 people who have been selected by the stratified random sampling method. The data collection tool is a translation and synthesis of a standard questionnaire based on the use of technology modified by the researcher. The validity of the questionnaire was confirmed based on content validity, face validity, and construct validity (confirmatory factor analysis, CFA) and its reliability coefficient was obtained based on Cronbach's alpha coefficient which is equal to 0. 86. The collected data were analyzed using descriptive statistics (frequency, mean, standard deviation, and Pearson correlation coefficient) and inferential statistics (path analysis of structural equation model) by SPSS and LISREL software. Finding: The results showed that the variables of effort expectancy, social influences, and facilitator conditions with mediating role of performance expectancy have a positive and significant causal effect on the intention to use information and communication technology of Tabriz University of Medical Sciences students with mediating role of performance expectation (p<. 01). Conclusion: The use of information and communication technology in the educational and research goals of students is a good opportunity and it is necessary to consider the attitudes of educational organizations and policy makers based on the results of such research.

Purpose: Information culture is a new concept that shows the organization's orientation towards information, as well as values, norms, and behaviors related to information in the organization. Addressing this concept is especially important in knowledge-based organizations such as universities. The purpose of this research is to introduce a model information culture for governmental universities of Iran. Methodology: The populations were faculty members of governmental universities of Iran. The members of the research sample in the qualitative section were selected by using the purposive sampling method and in the quantitative section by using the random sampling method. In the qualitative section, semi-structured interviews were used to collect data. After analyzing the interviews and coding the data, a conceptual model of the research was designed. Then, to assess the validity of the research model, quantitative data were collected with the help of a researcher-made questionnaire. To evaluate the fitness of the research model, the SEM method (Structural Equation Modeling) was used with the help of LISREL software. Findings: By analyzing qualitative data 57 initial codes were identified for information culture, these codes were categorized in format of 16 subcategories and 4 main categories. Fitting the research model with the SEM method showed, information culture model of governmental universities of Iran has very good fitness. Therefore, to measure information culture in governmental universities of Iran, this model which includes 4 main dimensions information values and norms, optimized use of information and communication technology, information management, and Communications and interactions, can be used. Conclusions: This research, by presenting a model for information culture, provides the possibility of measuring and monitoring information culture in the governmental universities of Iran. In addition, the results of this research can be a base for doing more research and the development of theoretical foundations in this field.

Purpose: Convolutional neural networks, as one of the most important models of deep learning, have gained high accuracy on these issues. In this study, discussion and text analysis at the sentence level and improving the performance of neural networks to detect fake news has been convolution. The network of words for bags of words in the data model so that each word according to the two-dimensional vector space to become matrices. One of the limitations of convolutional networks is that it works at the word level and cannot consider the relationship and distance between sentences. And sentence-level analysis is a major problem in this research. Sentence level analysis is a major problem in this research. In this research, a basic model based on convolutional networks is proposed in which documents are given to the network in the form of 3D tensors to solve the mentioned problem. Considering 3D tensors allows the model to learn the position of words in a sentence and achieve more accurate results in detecting fake news. Methodology: This study is applied research in which about 42, 000 Persian news from different cities of Iran were collected from Twitter and using preprocessing, additional and useless data is deleted and after tagging the deleted texts, the news text is used for the proposed approach using Python software and related libraries. Findings: During testing, some machine learning algorithms had more power in classification problems, but with the changes in the structure of the convolutional network algorithm, better results were obtained than machine learning algorithms and other similar algorithms. Conclusion: Considering 3D tensors allows the model to learn the position of words in a sentence, and this proposed model has gained considerable accuracy compared to the proposed approaches in the literature. The proposed model without adding additional overhead in terms of the number of features and network depth, by changing the input has been able to achieve better and more acceptable results than other approaches in the literature and achieve an accuracy of more than 94%.

Purpose: This study was conducted to provide a social media-based model of the factors affecting the promotion of trust in e-commerce using three-stage grounded theory. Methodology: The statistical community has been purposefully selected and it includes experts and specialists with knowledge and familiarity with the subject of e-commerce and related issues and those involved in its implementation. The research tool was the implementation of interviews in the form of coding and summarizing them and the method of data analysis using coding and categorization of categories and themes using the grounded theory method. Finally, the statements obtained from the interview are categorized by three methods of open, selective, and axial coding. Finally, by examining the causal conditions, background conditions, and intervening conditions, the effective factors in promoting trust in e-commerce were identified. Finding: After analyzing the data based on expert evaluation, it was observed that there is a significant relationship between the reliability of e-business websites and improving customer trust. It was also confirmed that a reputable brand and the transparency of a website have a direct effect on increasing customer trust in the website. Conclusion: The effective supportive role of the government in the development of e-commerce was proven. The results of this research apply to consumers and e-business owners.