International Journal of Knowledge Processing Studies
Volume:3 Issue: 4, Autumn 2023

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.

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.

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.

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.

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.

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.

This paper aims to generate a genealogy of Digital Transformation employing visualization techniques of scientific documents which will contribute theoretically to the research field and practically to the business. To reach the genealogy, three relations including ancestors, fathers, and descendants were defined. The ancestors and fathers were respectively determined by Reference Publication Year Spectroscopy (RPYS) and Citation analysis. Identification of the descendants was done through the bibliographic coupling of the documents published in the last two years. Visualization of the ancestors, fathers, and descendants was respectively done via fathers’ reference co-citation analysis, citation analysis on documents, and clustering of the bibliographic couplings using VosViewer. The analysis of each cluster identifies the topics of each relation of the genealogy. The analysis of the ancestors showed that the ancestors have studied theoretical foundations in digital transformation to a great extent. according to the clusters obtained for the fathers, Business models, Strategy and Innovation, Industry 4.0, and Servitization were the dominant topics of this relation. The identified topical clusters of descendants contained Digital Transformation Nature, the Influence of Digitalization on Business, Industry 4.0 and Sustainability, Digital Twins, and other Technologies in Industry 4.0, Digital Transformation, and Medicine, and Digital Transformation, Smart City, and The Effect on Financial and Economic Services showing the focus of latest research in specific technologies and innovation. The generated genealogy can be used to anticipate future trends and measures to be taken by businesses to realize digital transformation.

This research aimed to create new knowledge on supply chain performance management in private banks., It was performed in two phases using a thematic analysis under the qualitative methodology and the correlational analysis technique using structural equation modeling in the quantitative part. The data was obtained from in-depth and semi-structured interviews with 12 managers of five private banks in Iran, based on purposeful sampling and continued until reaching theoretical saturation. The statistical population in the quantitative part included all 235 managers of Mellat Bank's branches, from which 144 were selected by simple random sampling. A researcher-made questionnaire was used to collect the data for the first part. The validity was assessed by factor analysis of the extracted components. A reliability value of 0.7 was obtained using Cronbach's alpha. The factor load of causal factors on the main category was 0.53, contextual factors on strategies were 0.54, intervening factors on strategies were 0.37, the main category on strategies was 0.47, and finally, the factor load of strategies on consequences was 0.71. A performance measurement system is a framework for measuring supply chain performance. To create knowledge in the supply chain based on research findings, one must first know what knowledge is important to maintain and how it can be maintained effectively.

The current research aims to study the effectiveness of artificial intelligence (AI) on sustainable and intelligent supply chain management in the food industry of East Azarbaijan province. The use of intelligent technologies and sustainability components based on organizational knowledge in the product supply chain not only improves the information level of the supply chain but also reduces the risk of product security problems, especially perishable products, by controlling the supply chain. Also, when a product security problem occurs, companies can help solve this problem through intelligentization and knowledge management. In this research, by comparing the regression rate, which is closer to the desired number of one, and the MSE rate of the obtained error value, which is very close to zero, in the best case, the results related to one hidden layer and two neurons were selected. Then, by calculating the sum of the weights of each layer and normalizing the weights, the importance of each input layer was determined. The research results showed that the order of importance of the independent variables in the neural network structure model is cultural factors, economic factors, environmental factors, and social factors. measures to be taken by businesses to realize digital transformation.

This research is done in a mixed way (thematic analysis and data mining). In the first step, based on the qualitative method of thematic analysis, the effective factors of knowledge-based career path planning with a high-performance approach and data processing approach are identified. The investigated population is the managers and decision-makers of Zone Ten of Iran's gas transmission operations. 10 people were purposefully selected and interviewed. These people had more than 10 years of work experience in this organization. Using the six-step coding method, the interviews were entered into the MAXQDA software, and the effective factors on career path planning with a high-performance approach based on organizational knowledge were identified. Data was collected in SPSS format and used as input in WEKA software. The path of career development in this research was determined based on the dimensions of individual factors, organizational factors, empowerment strategies, management strategy, culture-building strategies, process development, and management processes. The operationalization of these factors in data mining showed that the situation of the predicted career path has significant differences from the reality of the organization. This procedure can be improved by periodic knowledge extraction and long-term performance evaluation. The obtained results showed that the knowledge-oriented career path emphasizes the empowerment of employees in a specialty. The level of knowledge participation of employees does not only mean that the employee shows useful behaviors for the organization within the organization, but also includes the attitude of people towards the company and recognizing their existential value in the company.

The availability of social capital is a valuable resource that supports employees in performing activities in organizations. Social capital has a close interaction with knowledge. The current research aimed at investigating the dynamics of the social capital database to gain economic, social, cultural, and environmental knowledge of the industrial development of Kangan City using a quantitative approach and a survey method. The data collection tool was a questionnaire. The statistical population was all the citizens of Kangan City over 25, 400 were selected as a sample and studied using the multi-stage cluster sampling method. The data were analyzed on two descriptive and inferential levels in SPSS software. The results show that the average of the social-environmental behavior variable is higher than the average and the average of the change in the consumption of cultural goods is lower than the average. Based on this, it can be said that the impact of industrial development on social-environmental behaviors and social capital (including the dimension of social trust) has been positive and the consumption of cultural goods has had no effect, or to be more precise, it has had a negative effect. Holding scientific meetings in order to increase social trust in the industrial area is one of the practical suggestions of this research, also culturalization of knowledge sharing and use of existing databases will strengthen social capital and create a competitive advantage of knowledge creation in the long term.

Numerous studies have shown that the quality of teacher's performance is a very important factor in determining the learning outcomes and achievements of the educational system. This research was conducted through qualitative text analysis using the pertinent research projects, scientific documents and formal educational, documents at national and international levels, as well as the related literature with the aim of identifying and explaining the role of professional competencies of special education teachers and trainers with a focus on students with intellectual disabilities. The results of the analysis have been presented in the form of a set of competencies required by teachers and trainers of intellectually disabled students, which include components such as positive and supportive interaction and creating hope in children, control of emotions and stress, attitude and skills for facilitation of affairs, ability in cultivating creativity, intelligent behavior with scientific vision and cultural awareness, designing empowerment activities and timely intervention programs, enriching, adapting and strengthening content and learning environment, as well as teaching skills needed for effective communication, problem-solving, safety, and health, and defending their individual and social rights. The presented arguments can be used in the field of educational policy-making, evaluation of professional competence, and empowerment of teachers and trainers in general and special education, as well as in the design and development of curricula for students with intellectual disabilities.