Knowledge Extraction
Elham Samadi; Hasanali Bakhtiyar Nasrabadi; Zohreh Saadatmand
Abstract
This research aims to analyze the intellectual education of Avicenna (Ibn Sina) and discover practical knowledge. The purpose of text mining in historical records is to identify relationships within existing data and extract knowledge from them. When the existing data are structured, it is easy to use ...
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This research aims to analyze the intellectual education of Avicenna (Ibn Sina) and discover practical knowledge. The purpose of text mining in historical records is to identify relationships within existing data and extract knowledge from them. When the existing data are structured, it is easy to use data mining methods to extract knowledge from them. In relation to the research topic, the method employed in this study is text mining analysis, making this research exploratory. The TF-IDF weighting method is used in this research. Considering the high dimensionality of the data, where the number of features is much greater than the number of vulnerable samples, linear Support Vector Machine (SVM) is a more suitable choice for these tests. Various implementations of this algorithm are available. In this research, LibLinear SVM, which is one of the most suitable implementations, has been used. First, the conceptual texts of Ibn Sina's thought were analyzed by understanding the contexts of existence, knowledge, man, and values. Subsequently, a list of educational requirements was deduced using concepts and categories. Finally, models for the construction of cognitive perception and an educational model were proposed. It can be said that the ideal human being, according to the teachings of Sinai, is someone who, through their scientific perspective related to their existence, knowledge, and values, can attain proper intellectual development and happiness derived from understanding the truths of the universe. This individual can acquire intellectual knowledge, enhance their power of critical thinking and reasoning, and ultimately achieve perfection.
Data mining
Ali Esmaili; Hoshang Taghizadeh; Naser Faqhi Farhamand
Abstract
This research aims to study the data-driven model of gas consumption management, with a focus on addressing unauthorized use through the analysis of information systems. Research was conducted using a metasynthesis approach and technique in the field of gas consumption management and mathematical programming ...
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This research aims to study the data-driven model of gas consumption management, with a focus on addressing unauthorized use through the analysis of information systems. Research was conducted using a metasynthesis approach and technique in the field of gas consumption management and mathematical programming with genetic algorithms. ATLAS.ti software was used for analysis. The influencing factors related to a specific period of time were examined and searched for in this research. Internal and external sources from the years 2006 to 2023 were analyzed. 27 studies were selected based on the Critical Appraisal Skills Programme (CASP) technique. In the continuation of mathematical modeling using MATLAB software, the simulation was conducted to compare the performance of three proposed algorithms. Based on the results obtained from the meta-combination technique, the main categories include the use of renewable energy, gas consumption management, shortcomings, obstacles, data-driven solutions, consequences of gas consumption management, and economic growth. All three models also demonstrated the basis for optimal gas consumption and the reduction of unauthorized consumption. The utilization of data analysis can enhance system efficiency, pinpoint weaknesses and losses, boost productivity, and optimize the utilization of gas energy. Based on the analysis, it was shown that data mining can be very useful in managing gas energy consumption and identifying unauthorized breaches. Overall, simulating gas energy consumption management using a genetic algorithm can provide efficient and effective solutions, handle complex and dynamic scenarios, and offer insights into optimizing gas consumption and energy efficiency.
Big data
Sadegh Tayebi; Alaedin Etemad Ahari; Fariba Hanifi
Abstract
The research aims to apply big data in providing an effective model of education in serving the knowledge workers of the municipality. The research method was integrated research (quantitative and qualitative). The components and dimensions of the subject were examined in the form of documentary studies ...
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The research aims to apply big data in providing an effective model of education in serving the knowledge workers of the municipality. The research method was integrated research (quantitative and qualitative). The components and dimensions of the subject were examined in the form of documentary studies and interviews and identified in the form of educational content with thematic analysis technique. To analyze the qualitative data, the theme analysis method was used using ATLAS TI software, and genetic algorithm and meta-heuristic methods were used in MINITAB software. The research tool (data collection) was the qualitative part of a semi-structured interview with 12 elites, experts, and qualified specialists of Karaj municipality. The sampling method in the qualitative part was non-probability and non-homogeneous purposeful type dependent on the criterion and in the quantitative part, it was simply random. Finally, the proposed model of in-service training for employees was designed and validated. 6 comprehensive themes (planning (comprehensive implementation), learner, teachers, content, educational environment, and infrastructure) were identified in the form of a paradigm model. The results showed that the VIS algorithm had the best performance. Algorithms CNSGA-II and MISA are almost ranked second and have shown almost similar performances. NSGA-II algorithm is ranked next. The NNIA algorithm is in the next position in terms of performance, and the worst performance is assigned to the NRGA algorithm. Organizational innovation based on big data and organizational training improves the performance of knowledge workers and creativity.
Knowledge Extraction
Mohammad Hossein Rahmati; Farshid Namamian; Seyed Reza Hasani; Afshin Baghfalaki
Abstract
Brand resilience knowledge helps companies maintain customer trust and strengthen relationships through proper planning and strategies. This research was conducted to model brand resilience in Iran's handwoven carpet industry using background knowledge and data mining in critical conditions. In brand ...
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Brand resilience knowledge helps companies maintain customer trust and strengthen relationships through proper planning and strategies. This research was conducted to model brand resilience in Iran's handwoven carpet industry using background knowledge and data mining in critical conditions. In brand resilience, knowledge analysis is considered highly significant for identifying key factors and effective patterns. This mixed research has been done based on qualitative data techniques in NVIVO software and quantitative data mining method in MATLAB software. 12 people were selected purposefully from carpet industry experts. Interviews were analyzed, coded, according to Strauss and Corbin method, and compared with the data mining method of the trained model and the MLP method. Based on the proposed model, 6 categories, 15 core codes, and 41 primary codes were identified. The proposed model could predict 98% brand resilience in crisis conditions. This model can help brands to maintain their business interests and implement appropriate strategies for active development, internal resistance, creative support, and production under sanctions. Furthermore, this model can help brands strengthen their capabilities and brand value, and identity in critical situations.
Knowledge management
Alireza Mandegari; Sina Nematizadeh; Abbas Heidari
Abstract
Due to the increasing exchange of information and data through the use of cell phones, this research aims to design a data-driven model of mobile marketing in Iran. The focus is on decision-making information related to purchasing behavior. By studying customers' decision-making information, businesses ...
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Due to the increasing exchange of information and data through the use of cell phones, this research aims to design a data-driven model of mobile marketing in Iran. The focus is on decision-making information related to purchasing behavior. By studying customers' decision-making information, businesses can collectively form antecedents that enable them to predict customers' behaviors and reactions. A mixed exploratory methodology (qualitative-quantitative) was used to collect and analyze the research data. For this purpose, the qualitative phase utilized the theme analysis method, while the quantitative phase employed the fuzzy Delphi and fuzzy hierarchical analysis methods.Therefore, it was determined that the mobile marketing model, based on decision-making information on purchasing behavior, includes 98 indicators, 18 components, and four general categories (dimensions) of influencing factors. These categories are decision-making styles, individual factors, social factors, and technical factors.The results of the quantitative phase showed that the most important factors in decision-making, from the customer's perspective, were sensitivity to the price and value of goods, social pressures, user concerns and worries, and utilitarian factors related to the message. Mobile marketing can be effective among Iranian users and consumers when it aligns with the various aspects of consumer purchasing behavior decision-making information and enhances perceptions. It instilled a desire in people to prioritize safety and usefulness in their field.
Knowledge management
Abdolhamid Sharafi; Malike Beheshtifar; Mohamad Ziaaddini
Abstract
The main purpose of this study is to develop a model of strategic unlearning of sharing knowledge in Iranian state-owned banks. This qualitative study is developmental in terms of purpose. In the first part of this research, the content related to the concepts of unlearning and strategy were extracted ...
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The main purpose of this study is to develop a model of strategic unlearning of sharing knowledge in Iranian state-owned banks. This qualitative study is developmental in terms of purpose. In the first part of this research, the content related to the concepts of unlearning and strategy were extracted from library sources. The second part refers to the interview process with 21 managers, executives, and experts conducted in the winter of 2021. The statistical population of the research includes experts from the university department who have published at least two articles in the field of unlearning and related research plans. Furthermore, the executive team comprises individuals with a university degree and a minimum of 4 years of work experience in the field of banking education. Judgmental sampling was implemented based on the opinions of professors and experts in this field and continued until theoretical saturation was achieved. The interviews were then analyzed using Atlas.ti 8 software. Findings identified 11 components, 18 indicators, and 76 selected codes. The results also indicated that some components, such as employee development, management, economics, knowledge management, education, organizational structure, legal aspects, marketing strategies, cultural factors, consolidation, rigidity, and unlearning, are essential in the strategic unlearning process of Iranian state-owned banks.
Knowledge management
Mohammad Hassanzadeh; Samaneh Rahimian
Abstract
The success of organizations depends more on knowledge assets than physical assets. Knowledge management transforms the organization into a knowledge-based organization, thus institutionalizing the importance of knowledge in all the organization's processes. This research investigates the role of knowledge ...
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The success of organizations depends more on knowledge assets than physical assets. Knowledge management transforms the organization into a knowledge-based organization, thus institutionalizing the importance of knowledge in all the organization's processes. This research investigates the role of knowledge management in improving the performance of the Tehran Municipality. In this way, according to the organizational scale of Tehran municipality, which has organizational levels including line and staff (22 urban areas, affiliated organizations and companies, specialized vice-chancellors) in its strategic and functional areas. Therefore, qualitative data were collected using the available information and documents related to establishing knowledge management and descriptive strategy, Then quantitative data was collected using questionnaire tools and survey strategy. By using the method of thematic analysis, 13 upstream documents of Iran's administrative system and ten management standards and frameworks were reviewed and analyzed for the necessity of implementing knowledge management solutions therefore the infrastructures for establishing knowledge management in the Tehran municipality were identified. Based on the results, the components of upstream documents affecting the establishment of knowledge management in Tehran Municipality are communication, knowledge-based governance, technology, knowledge creation, futurology, culture, human resources, organizational processes, and knowledge processes. Also, knowledge management barriers are divided into eight sections: technological barriers, cultural barriers, management barriers, organizational/structural barriers, human barriers, content barriers, implementation barriers, and legal barriers.
Knowledge Extraction
Zahra Sadafi Tehrani; Masoumeh Al-Sadat Abtahi; Ezatollah Naderi; Maryam Saif Naraghi Saif Naraghi
Abstract
The purpose of the study is to analyze the sixth grade textbooks for the application of financial knowledge from the point of view of the professors of the financial management department of public and private universities. The research method is descriptive-analytical. The statistical population of ...
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The purpose of the study is to analyze the sixth grade textbooks for the application of financial knowledge from the point of view of the professors of the financial management department of public and private universities. The research method is descriptive-analytical. The statistical population of all professors of the financial management department of public and private universities with more than 10 years of experience in Tehran province is determined to be around 322 people. A researcher-made questionnaire was used to collect data. This tool is a combination of the financial knowledge tests of the National Council of Economic Education of America and the national standards for personal finance of the Jumpstart model and adapted to the conditions of Iranian students. Professors, experts of the Department of Economics of Islamic Azad University in Tehran and experts of the Education Organization have confirmed the validity of the questionnaire and its reliability has been confirmed by calculating Cronbach's alpha of 0.894. Text mining methods (mean, percentage and frequency) and inferential statistics have been used to review and analyze the data. The results of the research show that the educational goals of the framework of the personal finance book, the framework of content and learning experiences, the framework of organizing teaching-learning experiences and the design of the evaluation framework of learning experiences in the application of financial knowledge in sixth grade textbooks are effective from the point of view of financial experts and experts.
Knowledge management
Shahram Bakhshi hajikhajeloo; Yousef Namvar; Nasibeh Pourasghar
Abstract
The current research was conducted to design a model to identify the effective organizational factors for tacit knowledge management in Iran's Social Security Organization. The method and tools of data collection were obtained through field methods such as interviews and questionnaires. The statistical ...
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The current research was conducted to design a model to identify the effective organizational factors for tacit knowledge management in Iran's Social Security Organization. The method and tools of data collection were obtained through field methods such as interviews and questionnaires. The statistical population in the qualitative phase included managers and experts from the general departments of the Deputy of Management Development and Human Resources of the Social Security Organization. The sampling method in the qualitative phase was purposive and snowball. Based on the principle of theoretical saturation, a sample size of 15 interviews was chosen for the semi-structured interviews. To validate qualitative findings, four criteria of validity, generalizability, reliability, and verifiability were used. To assess the validity of the findings, content validity was employed. The process of data analysis was conducted using the open, axial, and selective coding methods in the MAXQDA. The statistical population in the quantitative part of the research was 360 managers and expert experts in 7 specialized vice offices of the organization's headquarters, and according to the table of Karjesi and Morgan (1970), the number of quantitative study samples was 186 people selected by simple random method. In the inferential statistics section, quantitative content analysis of the structural equation modeling method was used. Finally, the model of effective organizational factors on tacit knowledge management in the social security organization was confirmed. It is necessary to pay attention to the institutionalization of effective factors in tacit knowledge management by considering the designed model.
Knowledge management
Yalda Saremi; Mohammad Aghaei; Mohammad Rahim Esfid; Tahmoures Hasangholipour; Manouchehr Ansari
Abstract
Due to the spread of activities in the virtual world and on the Internet, the marketing and advertising method has completely changed and is moving from traditional marketing to digital marketing. In this regard, one of the most important benefits that businesses can create in the digital space is to ...
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Due to the spread of activities in the virtual world and on the Internet, the marketing and advertising method has completely changed and is moving from traditional marketing to digital marketing. In this regard, one of the most important benefits that businesses can create in the digital space is to increase engagement with customers. This research was conducted with the aim of presenting a digital marketing model with a customer participation approach with intervening role of knowledge management. This research is of mixed type (qualitative-quantitative) and in terms of fundamental-applied purpose, and in terms of the nature and form of implementation, it was done in an exploratory-descriptive manner. In the qualitative part, the statistical population includes all CEOs as well as managers of related units (marketing, research and development, business development) who are active in different industries, and sampling was done using the snowball method, and finally with 16 saturated interviews. There was a comment. The data collection tool included a semi-structured interview, and the Foundation's data theory method and MAXQDA software was used to analyze the specialized interviews. In a small part, they form also, for the survey in the quantitative part, experts, employees and customers are also included in the statistical population, and sampling was done using the accessible and random method, and 384 people were selected using the Cochran formula.
Knowledge Extraction
Manya Sadat Hashemian; Javad Rezaian; Amir Gholam Abri
Abstract
The aim of the current research was to provide an intelligent model of the green supply chain of pharmaceutical products with the overlap of common customers. This research applies simulation to the proposed model of a pharmaceutical supply chain with smart and green conditions. The society under investigation ...
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The aim of the current research was to provide an intelligent model of the green supply chain of pharmaceutical products with the overlap of common customers. This research applies simulation to the proposed model of a pharmaceutical supply chain with smart and green conditions. The society under investigation is the environment of pharmaceutical companies, with its specific assumptions and goals. This model is simulated in the GMAS software environment. The problem was examined from two perspectives: simultaneous production (coordination of drugs) and cooperative planning (coordination of suppliers). Additionally, in order to address the issue of vehicle routing under real conditions of limited capacity for delivery vehicles, the expiration date of the drug and time windows in orders were taken into consideration. The objective was to allocate orders to vehicles in a way that minimizes the total delivery time and reduces the amount of carbon dioxide produced. Based on the obtained results, this multi-objective model aims to improve the performance of the pharmaceutical distribution network by addressing three main complexities: economic, environmental, and social. This approach provides a comprehensive and balanced solution for designing the drug distribution network. Its goal is to preserve the environment, improve social conditions, and maximize economic profit.
Knowledge Extraction
Fatemeh Baratloo
Abstract
The purpose of this study is to identify the thematic trends of scientific publications in the fields of humanities and social sciences, considering the impact of Covid-19. The study utilizes a descriptive approach with a scientometric and content analysis method, incorporating co-word analysis and social ...
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The purpose of this study is to identify the thematic trends of scientific publications in the fields of humanities and social sciences, considering the impact of Covid-19. The study utilizes a descriptive approach with a scientometric and content analysis method, incorporating co-word analysis and social network analysis techniques. The research population comprises Covid-19 studies in the fields of humanities and social sciences in the Web of Science, conducted between 2019 and 2021, involving the top countries in three prominent continents. CiteSpace, Bibexcel, and Gephi software were used to analyze the data, while VOSviewer software was utilized to visualize the intellectual structure. The analysis reveals that religion, spirituality, public health, religiosity, mental health, epidemics, depression, crisis, social media, anxiety, and ethics are significant keywords in research within the humanities and social sciences. Additionally, thematic overlap is observed in the clusters of "China and Spain" and "India, Turkey, Britain, Italy, United States, Canada, and Brazil," with a greater accumulation of clusters in the studies of Turkey, Canada, and Brazil. In addition, it can be said that the focus of studies in the Americas is more on social sciences than on studies in the other two continents.
