International Journal of Knowledge Processing Studies

Abstract This research aims to identify the function of social entrepreneurship knowledge in realizing sustainable development of northern Iranian villages. In this research, using the opinions of experts, indicators, components, and dimensions were identified explanatorily. Regarding the method of extracting these indicators, it should be noted that this was done by examining the existing theoretical foundations and implementing the interview text using the Brown and Clark theme analysis method in ATLAS TI software. In this regard, interviews were conducted until theoretical saturation with 20 urban planning and rural management experts, then the interview text was analyzed using coding. Thematic analysis was based on 6 level two constructive themes, 24 level one constructive themes, and 72 primary themes. The constructive themes include economic themes, social themes, cultural themes, environmental themes, institutional and governance themes, and technological and innovative themes. Achieving sustainable development in the villages of northern Iran requires a combination of production optimization, increasing the added value of products, financial management, activity substitution, reducing economic risk, multidisciplinary entrepreneurship, local cooperation networks, trust, social groups and associations, education and skills training, access to resources, economic independence, and participation in local decision-making. These components reinforce each other, and only with a comprehensive and coordinated approach can sustainable, resilient, and inclusive development be achieved. When the local community is empowered, participatory, and has mutual trust, and resources and opportunities are managed in a fair and sustainable manner, the path to sustainable development is paved and people's lives improve in the short and long term.

Abstract Sustainable development represents a new perspective on the relationship between humans, nature, and society, aiming to meet present needs without limiting the ability of future generations. This study seeks to design and explain a cultural model of environmental protection within the framework of sustainable development in the National Environmental Organization. The research is applied in purpose and exploratory in method, employing both qualitative and quantitative (mixed) approaches through grounded theory and exploratory factor analysis. Data collection relied on semi-structured interviews with 12 experts, including university professors, managers in environmental fields, and representatives of organizations, municipalities, and NGOs. Analysis followed grounded theory procedures—open, axial, and selective coding—resulting in 15 categories within a paradigm model. These included causal conditions (ecological, social, economic, ethical, and political necessities), the central phenomenon (cultural model of environmental protection), enabling conditions (sustainability culture, governance, and leadership), intervening conditions (cognitive, attitudinal, socio-cultural, political, economic, and infrastructural factors), strategies (cultural transformation, behavioral innovation, and sustainability strategies), and consequences (environmental and socio-political outcomes). In the quantitative phase, the statistical population extended to managers and staff of the National Environmental Organization. Data from exploratory factor analysis were processed using SPSS26, confirming validity and reliability of the questionnaire as factor loadings exceeded 0.3 and significance coefficients surpassed 1.96. Furthermore, structural equation modeling via AMOS confirmed the strength of relationships among model components, validating the proposed framework

Abstract The study aimed to develop a model of employee disengagement in Iranian government organizations. The research was applied in purpose, descriptive-analytical in nature, and conducted using a sequential mixed-method design. This study proposes a Non-Participation Model for employees in Iranian government organizations. Using Theme Analysis and Fuzzy DEMATEL the study identifies the main psychological, managerial, and cultural factors leading to employee disengagement and explains how these factors interact to create non-participation. In the qualitative phase, effective dimensions and components of disengagement were identified through semi-structured interviews with experts, and data were analyzed using thematic analysis and coding techniques. A researcher-developed questionnaire was administered, and data were analyzed using the fuzzy DEMATEL technique to determine cause–effect relationships and the degree of influence among components. Sampling was non-probability and continued until theoretical saturation. The quantitative phase involved academic experts in human resources and executive experts (senior and middle managers, supervisors) with a minimum of five years of experience in government organizations, selected through purposive non-probability sampling. Findings revealed a disengagement model based on six overarching dimensions and 26 components. The dimensions included: (1) lack of attention to optimal use of human resources (6 components), (2) neglect of cooperation and interactions (3), (3) lack of patronage and support (4), (4) neglect of a critical and empathetic culture (2), (5) lack of attention to employees’ psychological needs (5), and (6) weak guidance and leadership (6). The study further prioritized sub-criteria and outlined their interrelations, offering practical recommendations for government organizations.

Abstract The aim of the research is to design a knowledge model for accounting fraud detection based on digital innovations with a focus on human-technology interaction in organizations. The increasing spread of digital innovations and the increasing complexity of financial processes have fundamentally changed the nature of accounting fraud in organizations and challenged the effectiveness of traditional fraud detection approaches. In such circumstances, relying solely on technological tools or human judgments alone is not sufficient to detect fraud in a timely and effective manner, but the synergy of human knowledge and the capacities of digital technologies has become doubly important. The structural interaction analysis method of MICMAC software was used in information processing. Based on the results obtained, 10 criteria (big data analytics, fraud machine learning, audit artificial intelligence, smart transaction tracking, encryption and transparency, financial process automation, hidden behavioral data mining, digital anomaly detection, financial blockchain platform, and continuous real-time monitoring) were categorized into 7 levels. This approach, by creating synergy between the professional knowledge of accountants and auditors, the analytical capabilities of smart technologies, and organizational knowledge sharing and learning platforms, enables more timely and accurate identification of fraud patterns. The results of such a model can lead to improved financial transparency, strengthened stakeholder trust, improved supervisory decision-making, and organizations moving toward predictive and knowledge-based control systems; which will ultimately play an important role in improving the economic health and financial governance of organizations.

Abstract To lag behind other competitors in a competitive environment, organizations are forced to use and implement the empowerment of their employees. Accordingly, the present study was conducted with the aim of identifying the themes of self-disabling and empowerment of managers at the University of Medical Sciences with a qualitative strategy. The research method was content analysis based on the Clarck and Braun (2006) model. The data collection tool was a semi-structured and in-depth interview that was analyzed using open and axial coding. The research population was 15 experts (managers, employees, elites and qualified specialists of Iranian government organizations) who reached saturation level. The research findings show that the two models of self-disabling and empowerment of managers clearly explain their behavioral, emotional and mental structures and have different individual, organizational and social consequences. Also, the use of metaheuristic algorithms provides the possibility of optimizing decision-making, scheduling activities, and resource allocation. Therefore, it can be concluded that explaining and comparing the role of empowering and self-disabling managers in government organizations is not only important from a theoretical and psychological point of view, but can also lead to the design of practical models to improve the efficiency, motivation, and mental health of employees in the country's administrative system.