International Journal of Knowledge Processing Studies

Abstract This research aims to depict the knowledge of social capital based on pathology in the education system using a fuzzy approach. In terms of approach, it is mixed research, and in terms of method, it used theme analysis and fuzzy analysis. The study population was university professors and managers in the general education departments. Through purposeful sampling, based on criteria, the target sample was selected and sampling continued until the theoretical saturation of the data was reached. Therefore, the participants in the research included 12 professors and administrators. The data collection tool in this research is a semi-structured interview. In the fuzzy part, a researcher-made paired questionnaire was also used. In this research, the questionnaire of paired comparisons with a spectrum of 1-9 hours was used. Nvivo software was used in the thematic analysis. In fuzzy analysis, the hierarchical technique was used in MATLAB software. 70 sub-categories and 13 core categories were identified, each of which was located in different classes. Individual factors, structural factors, educational factors, managerial factors, solidarity and cohesion, social and family factors, institutional factors, collaborative factors, educational, cultural, and ideological policies, network relations, job satisfaction, and valuing social status as categories.

Abstract This research aims to provide an information system based on virtual currency data in the banking industry in Iran. Data is one of the most significant assets of the organization. This research is applied in terms of purpose. The population includes university professors in marketing and experts, including managers of the banking industry. Sampling in the qualitative section was done purposefully, and the criteria of expertise were at least a graduate degree and ten-year of relevant work experience. Finally, 20 people were selected as samples. The method used is SWARA's quantitative prioritization method. The index of using virtual currency in Iran's sanctions situation (Q67) with a weight of 0.12 is the first. The index of entrepreneurial acceleration based on the new payment system (Q56) with a weight of 0.11 is the second priority. The index of general uncertainty about the nature of virtual currencies (Q16) with a weight of 0.09 is the third priority. The index of improving communication and interactions between customers and the bank (Q63) with a weight of 0.0859 is the fourth priority. The index of alignment of banking processes with global standards (Q61) with a weight of 0.07 is the fifth priority. Extracting useful information from the database and converting it into actionable results is the main challenge that companies face. Therefore, results show that one of the ways to the success of cryptocurrencies is the use of data-oriented information systems and data mining techniques. The data-oriented information system is one of the recent developments in data management technologies. 

Abstract This research has addressed the modeling of knowledge-based human resource management with a qualitative approach in voluntary organizations. According to the theory of resource-based perspective, human resources can be considered rare and non-repeatable assets that provide a sustainable competitive advantage to the company. The researcher is trying to answer a practical problem and in this regard, to develop practical knowledge and discover new knowledge in voluntary organizations. The method used was theme analysis in NVIVO software. The statistical population consists of experts from voluntary organizations with at least the position of deputy; over 20-year work experience; experience in voluntary activities; at least 45 years old with a doctorate degree or higher. The size of the community of experts was 10 people. The number of samples was determined using the purposive sampling technique. In this research, an 8-dimensional model with 29 indicators was identified. These 8 dimensions are supply, growth and training, motivation, maintenance, human resources infrastructure, consequences, internal environment, and external environment. These 8 criteria indicate that the creation of a suitable structure and organization of human resources causes the employees to move towards their main specialties and consequently increases the organization's productivity. Therefore, by giving importance to human resources, developing and implementing new knowledge strategies, the productivity of knowledge workers, and the use of approaches based on information technology, can improve the knowledge management of human resources.

Abstract This research aims to design a data-oriented strategic training with the future research approach in the automobile industry. The research is applied in terms of its purpose and uses a qualitative approach and thematic analysis method. The data collection tool is semi-structured interviews, and the validity of the questions was obtained using the opinions of experts in the field of human resources in the automotive industry. The statistical population of this research is twenty-seven specialists and experts familiar with education, human resource development, and strategic planning from Saipa Automotive Group companies, who were selected by the snowball method. Next, based on the specified codes, 4 categories were selected, and based on 8 components in the Scenario Wizard software, future research analysis was performed and 3 compatible scenarios were identified. The results of the research show the extraction of 110 primary codes and the statistics of 14 sub-categories and 5 main categories, which include: 1- The core structure category of education, which has 3 sub-categories: organizational structure, systematization, and discipline. 2- The core agility category of education which has 3 sub-categories: transactional, intelligence, creativity and innovation 3- The business-oriented category of education which has 3 sub-categories: business conditions and organizational productivity, beneficiary-oriented 4- The strategy-oriented category of education which has 2 sub-categories: strategy-oriented, foresight and result orientation 5- The central development category of education has two sub-categories: individual development and organizational development. 

Abstract This research aims to use organizational information as an interpretive structural model for the development of knowledge-based capabilities of human resources. This research is mixed and after identifying indicators of the development of human resources capabilities through interviews with experts, they were modeled using the thematic analysis method. The final model was proposed using the quantitative method of interpretive structural modeling with the expert decision-making approach. The statistical population in this research is all the experts of the judicial organizations of Bushehr province, based on the purposive sampling method, 12 people were selected as a sample. MAXQDA software was used in the qualitative analysis. EXCEL software was used in interpretative structural analysis. The studied structures of developing human resources capabilities are employment potentials, specialized potentials, organizational potentials, cognitive characteristics, performance improvement, motivational and emotional characteristics, competitive advantage, productivity capabilities, and psychological characteristics. Based on the proposed model, knowledge organizations, to reduce their organizational challenges, especially in the field of human resources, need an approach to cover them in topics such as recruiting and hiring, salaries and wages, benefits, and rewards, but also at higher levels of human resources such as career path, skills development, training, job enrichment, integrated performance management, employee empowerment, employee relations, psychological well-being, etc. 

Abstract The purpose of this research is to use data mining to detect accounting fraud in the database of stock exchange member companies. The combination of discrete and continuous data has increased the necessity of using data mining and machine learning methods in the field of fraud detection. This research is applied in terms of purpose and descriptive in terms of method. The document review method was used to collect information in the field of literature and research background. The prepared questionnaire includes 7 main indicators consisting of 48 questions for each of the variables. This questionnaire was made available by the researcher to 400 accountants of companies admitted to the Tehran Stock Exchange by sampling method. In order to fit the model, the structural equation method was used in SMARTPLS software. In the data mining section, all IB1, IBK, LWL, KSTAR, and KNN algorithms were used to simulate the proposed model in Rapidminer software. Effectiveness of internal control, compensation system, asymmetry of information, compliance with accounting rules, management ethics, and ethical principles are effective and meaningful on accounting fraud. In evaluating parameters and according to the graphs, the K-STAR algorithm has better performance than other algorithms. The proposed data mining model for financial fraud detection showed that since the amount of data creation in financial companies is increasing day by day with the development of technology, it is possible to provide early detection of fraud by reviewing and analyzing the data.