Management and Educational Perspective

Abstract The present study aimed to examine the effects of ecosystem development, motivation, network orientation, and the redesign of think tanks’ roles on performance management based on think-tank networks, considering the roles of network cohesion and implementation facilitation.This study was applied in terms of its purpose and employed a mixed-methods design (qualitative–quantitative) in terms of its implementation. The statistical population in the qualitative phase consisted of 19 faculty members, managers, and experts in public administration and performance management, who were selected through purposive sampling. In the quantitative phase, the statistical population comprised 173 employees working in governmental think tanks in Tehran, who were selected using simple random sampling.Data were collected through semi-structured interviews in the qualitative phase and questionnaires in the quantitative phase. For data analysis, the grounded theory approach was applied in the qualitative phase, whereas SmartPLS software was used in the quantitative phase. During the qualitative stage, 540 initial codes were extracted using the grounded theory method. These codes were subsequently categorized into 122 indicators, 32 components, and ultimately 13 dimensions.The findings revealed that the development of the think-tank network ecosystem exerted the strongest effect on network-based performance management, whereas orientation toward a network-based approach exhibited the weakest effect. Maintaining network cohesion played a mediating role in the relationships of role redesign and network orientation with network-based performance management. Moreover, facilitating the establishment of think-tank networks had a moderating effect on the relationships between ecosystem development and network orientation, on the one hand, and performance management, on the other hand.

Abstract The present study aimed to identify the factors affecting educational productivity in primary schools in Fars Province. In terms of purpose, this research was applied, and in terms of nature, it was descriptive; it was conducted using a mixed-methods approach (qualitative and quantitative). In the qualitative section, the statistical population consisted of 12 experts in primary education from the Ministry of Education, as well as university professors in educational management, who were selected through purposive sampling. In the quantitative section, the population included principals, assistant principals, and teachers of primary schools in Fars Province, of whom 380 individuals were considered as the sample. First, 10 counties were selected through random cluster sampling, and then the questionnaires were distributed and collected through convenience sampling. The data collection instruments consisted of semi-structured interviews in the qualitative section and a researcher-made questionnaire in the quantitative section. For data analysis, the Delphi method and SPSS version 23 and LISREL software were used. The findings showed that 38 sub-factors, within the categories of macro-level policymaking, educational planning, evaluation and supervision of productivity levels, organizational knowledge management, creativity and innovation, individual motivation, knowledge enhancement, organizational incentives, and staff training and development, affect the educational productivity of primary schools in Fars Province. It can be stated that coherent planning, increasing training courses, creating motivation among teachers, and implementing field evaluation and supervision can contribute to the improvement of educational productivity in primary schools in Fars Province.

Abstract The purpose of this research is to prioritize the antecedent factors influencing the role of artificial intelligence (AI) in human resource development. In terms of objective, the study is developmental; in terms of nature, it is descriptive; and regarding the data type, it is quantitative. The research population consists of 11 experts in human resource management, information technology, AI, and organizational management, selected through purposive sampling, with data collection continuing until theoretical saturation was reached. Data were gathered using a researcher-made Fuzzy Delphi questionnaire, developed based on a literature review and expert interviews. The Fuzzy Delphi method was employed for data analysis and was implemented in three rounds to identify, screen, and prioritize the antecedents. The identified antecedent factors include technical and infrastructural factors, human and organizational readiness, managerial and procedural dimensions, environmental conditions, and ethical and legal considerations. The findings revealed that “technological infrastructure and system integration” achieved the highest priority among the antecedents with a defuzzified value of 4.965, followed by “human and organizational readiness” (4.965) and “process organization and procedural factors” (4.114). Technological awareness, organizational culture, and data mining capability were also identified as influential antecedent dimensions. In contrast, “external conditions and environmental factors” received the lowest priority with a defuzzified value of 3.280.

Abstract The purpose of this study is to identify and prioritize multidimensional strategies for sustaining the job motivation of primary school teachers (an integrated study). This research is applied in terms of its purpose, mixed‑method (qualitative–quantitative) in terms of implementation, and exploratory with a convergent mixed‑methods design in terms of data collection.The qualitative population consisted of 20 teachers, school principals, and educational experts in Ilam, selected through purposive sampling based on the principle of theoretical saturation. The quantitative population included 500 primary school teachers in Ilam, from which a sample size of 217 participants was determined using Cochran’s formula.Data were collected through semi‑structured interviews and a researcher‑developed questionnaire. In the qualitative phase, thematic analysis and MAXQDA 2020 software were employed, while in the quantitative phase, the Friedman test and PLS software were used.The analysis resulted in the identification of 62 basic themes and 17 organizing themes related to strategies for maintaining primary school teachers’ job motivation, which were subsequently categorized into 10 overarching themes. The findings indicate that organizational–social support and positive interactions with students exert the strongest influence on sustaining teachers’ job motivation. Moreover, significant differences were found in the prioritization of strategies based on teachers’ educational level and years of service.Overall, the results highlight the necessity of paying attention to the human, social, and meaning‑related dimensions of the teaching profession alongside structural and material factors, and can serve as a foundation for designing effective supportive policies and programs in the primary education system.

Abstract This study utilized semi-structured interviews with experts in higher education and human resource management, which were analyzed using thematic analysis. In the quantitative phase, the extracted indicators were validated and refined through the Fuzzy Delphi Method (FDM) to ensure content validity and consensus among experts. Finally, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique was employed for structural analysis and prioritization, identifying the causal relationships among the model’s dimensions and ranking the variables based on their prominence and net influence. Thematic analysis led to the identification of 289 initial codes, 63 sub-themes, and 19 basic themes, which were ultimately categorized into 9 main dimensions. These dimensions include: Human Resource Recruitment and Onboarding, Human Resource Development and Empowerment, Career and Human Capital Management, Performance Management and Intelligent Decision-Making, Governance and Organizational Structure, Organizational Culture and Social Capital, Environmental Interactions and Social Responsibility, Digital Transformation and Smart HR, and Data-Driven and HR Information Management. The Fuzzy Delphi results confirmed the optimal content validity of all indicators. Furthermore, the DEMATEL findings revealed that seven dimensions were classified as “causal/driving” factors, whereas “Career and Human Capital Management” and “Performance Management and Intelligent Decision-Making” were categorized as “effect/dependent” factors. The findings indicate that achieving the transformation goals of the higher education system requires an integrated approach to human capital development, digital transformation, data-driven management, and environmental interactions. The proposed model can serve as a strategic framework for policymaking, planning, and decision-making by higher education managers to enhance human resource effectiveness.

Abstract The present study aims to reconfigure the human resource development model based on dynamic capabilities in public organizations, with a focus on the Agricultural Bank of Iran. In terms of purpose, this research is applied, and in terms of its research paradigm, it is qualitative. The study population consisted of 16 experts in banking, human resource management, and academia. Sampling began purposively and continued until theoretical data saturation was achieved. Data were collected through semi-structured interviews. The interview data were analyzed using thematic analysis with the assistance of MAXQDA software. To assess coding reliability and ensure interpretive validity, Cohen’s kappa coefficient was calculated at 0.845, indicating excellent and reliable agreement among coders.An in-depth analysis of the interviews led to the identification and development of a thematic network comprising five global themes (main dimensions), 15 organizing themes (components), and 81 basic themes (indicators). The identified global themes included: “dynamic learning and innovation creation,” “agile and transformative reconfiguration,” “structural coordination and integration,” “empowering and future-oriented human resource management,” and “dynamic leadership and strategic decision-making.”The findings indicate that human resource development based on dynamic capabilities is the outcome of effective interactions between environmental drivers and internal strategic capacities. Its realization requires a fundamental transition from traditional and static human resource functions toward a learning-oriented, agile, data-driven, and transformative system.

Abstract The present study aims to develop a qualitative model of the interactions and outcomes of artificial intelligence-based human resource management (AI-HRM). In terms of purpose, the research is exploratory, and in terms of implementation, it adopts a qualitative approach. The study population consisted of 18 university scholars, managers, and human resource management experts who were selected through purposive sampling. Data were collected using semi-structured interviews and analyzed through thematic analysis. The findings led to the identification of 183 codes, categorized into 28 basic themes and 27 organizing themes. The results indicated that AI-based human resource management comprises four principal dimensions: interactive algorithms in the interview screening process, including the interactive enhancement of interviews, intelligent matching of applicants with organizational competencies, and interactive analysis of résumé data; dynamic performance appraisal, including interactive evaluation of work quality, interactive prediction of long-term performance, and automated continuous feedback; employee interaction with the learning and development system, including interactive career path recommendation, adaptive learning content, and soft-skills simulation; and interactive human resource planning systems, including workforce estimation, turnover intention prediction, and improvement of HR processes. These four dimensions directly affect three major outcomes: operational productivity, with emphasis on automating administrative decrees and reducing leave-processing time; improvement in HR decision-making, with emphasis on the unbiased standardization of interviews and monitoring of behavioral data; and human resource value creation, with emphasis on shared value creation and alignment with strategic objectives.

Abstract The purpose of this study is to examine the effect of organizational justice on organizational commitment and deviant behavior among organizational employees. In terms of purpose, the study is applied, and in terms of method, it is descriptive-survey research. The statistical population consisted of 346 employees of Bank Mellat in Tehran Province, who were selected through stratified random sampling. A questionnaire was used as the data collection instrument. Data were analyzed using SmartPLS software.The findings indicate that interpersonal justice has a significant negative relationship with unlawful behavior, such that higher perceptions of respect and fair interpersonal treatment lead to a reduction in violations. In addition, procedural justice is positively and significantly related to interpersonal justice, and both distributive and procedural justice have a direct and positive relationship with affective commitment. On the other hand, although unlawful behavior showed a direct and significant relationship with negative behavior, no significant relationship was found between unlawful behavior and affective or normative commitment. In contrast, negative behavior had a significant negative relationship with both affective and normative commitment. These findings suggest that while organizational commitment can act as a deterrent to everyday negative behaviors, unlawful behaviors may be influenced by factors other than commitment, such as structural monitoring mechanisms.In conclusion, enhancing employees’ perceptions of justice in its distributive, procedural, and interpersonal dimensions is an effective strategy for increasing affective commitment and reducing deviant behaviors in service organizations such as banks. Managers should therefore focus on improving process transparency and the quality of human interactions in order to foster constructive behaviors.

Abstract The aim of this study is to explain and design a model linking three-level organizational learning and the crisis management cycle in in-service training with a focus on organizational resilience. Considering its objective, the research is applied, and in terms of implementation, it is qualitative and based on thematic analysis. The statistical population of the study consisted of 22 experts and specialists in the fields of educational management, organizational learning, and crisis management. The sampling method was purposive and snowball sampling. The data collection instrument was a semi-structured interview. Data analysis was conducted using thematic analysis, including open and axial coding, with the assistance of ATLAS.ti software. The findings showed that the reconfiguration of in-service training can be explained in three phases: preparedness, control, and learning. Specifically, identifying weak signals through new technologies in the preparedness phase, transforming field knowledge into training scenarios in the control phase, and decentralized management combined with a shared organizational language play key roles in strengthening learning and preventing organizational forgetting. The results indicate that existing in-service training programs, due to their emphasis on superficial learning, are not sufficiently effective in crisis conditions. To enhance organizational sustainability, these programs must move toward deep, experience-based, and scenario-based learning. Achieving this requires a managerial shift toward future-oriented approaches and the use of modern technologies in human capital management.

Abstract The aim of the present study is to analyze theories related to the management of large classes and to present an optimal model with a fuzzy approach. This research is of applied research type in terms of purpose and nature and mixed (qualitative-quantitative) in terms of implementation. In the first part of the study, in order to develop a comprehensive model of analyzing theories related to the management of large classes, the method of comparative content analysis was used to review domestic and foreign studies over the past two decades. The samples were selected purposefully and based on theoretical saturation, and the intra-subject agreement rate was 0.92. The data were processed and analyzed using the content analysis method. In the second part of the study, which is a survey, the mathematical modeling method (fuzzy expert system) was used to present the optimal combination of model dimensions so that large classes can be managed more effectively and optimally. The results of this study showed that the proposed model of large class management, by emphasizing key factors such as creating a supportive environment, positive and constructive interactions, shaping a self-regulatory environment, developing metacognitive skills, goal setting, and accountability, can help create more effective and sustainable learning environments. The findings of this study can be used as a guide for educational policies and designing classroom management improvement programs, and in particular, help teachers and educational administrators to effectively implement appropriate strategies for optimal management of large classes.

Abstract The aim of this study is to develop a model of ingratiation using Fairclough’s Critical Discourse Analysis approach. In terms of purpose, the study is applied-developmental; in terms of data collection, it is descriptive; and regarding the nature of the data, it is qualitative. The statistical population consisted of 20 specialists and experts familiar with organizational behavior issues in a large mining and industrial company. Snowball sampling was employed, and sampling continued until theoretical saturation was achieved. Data were collected through semi-structured interviews. MAXQDA 2020 software was used for data analysis. Using Fairclough’s Critical Discourse Analysis method, 81 discourse codes with 116 frequencies were extracted and classified into 5 main categories, including discursive duality, discursive labeling, verbal strategies, linguistic metaphors, and lexical manipulation. In addition, 131 descriptive codes with 228 frequencies were identified and categorized into 9 main categories, including managers’ reactions, structural and discursive inequality, organizational context, verbal strategies, resistance to ingratiation, causes and drivers of ingratiation, benefits and rewards of ingratiation, organizational consequences, and the reproduction of ingratiation. The findings showed that the most important causes of ingratiation included ambiguity in evaluation criteria (5 frequencies), centralized power structure (4 frequencies), structural insecurity (3 frequencies), and fear of weakened position (3 frequencies). The dominant verbal strategies included voluntary self-censorship (3), resistant silence (3), reality softening (3), and unquestioning approval (3). The main consequences were perceived injustice (5), filtering of real information (4), weakening of horizontal and vertical trust (4), and fatigue and demotivation among staff (4).

Abstract The present study aims to examine the dimensions and components of managers’ meritophobia model (case study: public and private organizations in the city of Kerman). In terms of purpose, this research is applied-developmental, and in terms of methodology, it was conducted qualitatively using thematic analysis. The statistical population consisted of 20 managers from public and private organizations in Kerman. Participants were selected through purposive sampling based on the criterion of having at least 10 years of managerial experience in public and private organizations and full familiarity with this field. Semi-structured interviews with participants continued until theoretical saturation was reached.The data collection tool consisted of two parts: review and exploration of the research literature in the library section, and semi-structured interviews in the field section. Data were analyzed using thematic analysis (basic, organizing, and overarching themes), and the process of coding and textual analysis of the interviews was carried out using MAXQDA 2018 qualitative data analysis software.The findings of the study showed that the adaptive model of managers’ meritophobia in public and private organizations in Kerman includes the following dimensions: individual-personality factors (fear of losing power, ضعف اعتماد به نفس مدیریتی مدیریتی / low managerial self-confidence, superiority complex, and narrow-mindedness); structural-process factors (lack of a succession planning system, weak performance evaluation system, absence of a clear career path, and lack of a talent bank); cultural-environmental factors (relationship-oriented culture, administrative politicization, nepotism, and weak laws); and anti-merit methods and behaviors (organizational exclusion, marginalization, discrediting, and delaying/blocking).

Abstract The present study aims to classify and level the factors influencing organizational commitment based on a spiritual leadership style using the Interpretive Structural Modeling (ISM) method. In terms of purpose, the research is applied-developmental, and regarding data collection, it is descriptive; in terms of implementation, it follows a quantitative approach. The statistical population consisted of 10 managers from Bank Sepah in Kerman province, each with over 20 years of work experience, at least 10 years of managerial experience, and a specialized academic background in management. Participants were selected using purposive sampling. Data were collected through an ISM questionnaire, which was distributed, completed, and analyzed in the field. For the leveling of factors, Interpretive Structural Modeling (ISM) and MICMAC software were utilized. The findings revealed that “Hope” and “Vision” occupy the fourth level, functioning as the foundation of the model and possessing the highest driving power in shaping organizational commitment, acting as a “strategic driver.” “Value Thinking and Perception,” “Sense of Purpose,” and “Meaningfulness” are positioned at the third level, serving as mediating factors. “Spirituality in the Organization,” “Job Characteristics,” “Self-Knowledge,” and “Sincere Behaviors” are located at the second level, also functioning as mediators. Finally, “Environmental Awareness,” “Self-Actualization,” and “Cultural Intelligence” are placed at the first level as the final outcomes of the model.

Abstract The present study aims to design a comprehensive Human Resource Management (HRM) system in the Supreme Audit Court of Iran. In terms of implementation, the research adopted a mixed-methods (qualitative–quantitative) approach using exploratory analyses. The statistical population in the qualitative phase consisted of 12 organizational experts selected through purposive and snowball sampling methods. In the quantitative phase, the population included 210 official employees working at the headquarters of the Supreme Audit Court. Data were collected through semi-structured interviews and questionnaires. Qualitative data were analyzed using coding techniques with MAXQDA 2020 software, while quantitative data were analyzed using SMARTPLS 4 and SPSS 24 software. The findings indicated that the comprehensive HRM system in the Supreme Audit Court comprises four dimensions and 26 components. The four identified dimensions include human resource planning, human resource development, human resource maintenance, and influencing behavioral variables. The planning dimension consists of six components, development includes five components, maintenance comprises four components, and influencing behavioral variables encompass eleven components. The results further revealed that the current human resource conditions in the Supreme Audit Court are not in a favorable state and require immediate attention from senior management.

Abstract The purpose of this study is to model the development of capacities for human capital, organizational culture, and organizational wisdom for banking governance. In terms of purpose, this is an applied study; regarding methodology, it is qualitative, based on an interpretivist paradigm and inductive logic, and is exploratory in nature. The study population consists of 14 senior, middle, and operational managers of Shahr Bank, who were selected using non-probability, purposive sampling. Data collection was conducted through semi-structured interviews, which continued until theoretical saturation was reached. The qualitative data analysis process was carried out using grounded theory and thematic analysis methods.The results of this study indicate that the identified factors include: Ethical Leadership (including exemplary managerial behavior, active listening, and consistency between speech and action); Trust-based Learning Culture (including organizational trust, a spirit of learning, error acceptance, and healthy dialogue); Facilitating and Transparent Governance (including committee structure, staff development reporting, balance between control and agility, targeted human capital development, operational training, succession planning, multidimensional evaluation, and alignment of training with job requirements); Dynamic Organizational Wisdom (including an experience bank, experience sharing, data-driven decision-making, and learning from errors); Conflict-Inducing Factors (including centralization, informal relationships, quantitative-only evaluation, and excessive control); and Convergent Factors (including transparency, trust, targeted training, fair evaluation, as well as continuous dialogue and feedback).

Abstract The aim of this study was to use a document analysis approach in designing a model of employees’ social action. In terms of purpose, the study was applied research; in terms of method, it fell within descriptive studies with a correlational approach; and in terms of implementation, it was qualitative in nature. The statistical population consisted of 11 experts. Data were collected through semi-structured interviews. For data analysis, content analysis and MAXQDA 2020 software were employed.The findings showed that employees’ social action is a multidimensional phenomenon shaped by justice, trust, organizational culture, and organizational identity. Contextual conditions such as organizational structure and culture, the level of autonomy, and communication channels, as well as intervening conditions such as pressures, burnout, and institutional monitoring, play a decisive role in the emergence of social action. The proposed strategies for promoting social action include strengthening social capital, empowering employees, and institutionalizing justice and organizational transparency. The ultimate outcomes of these actions are increased job satisfaction, organizational commitment, creativity, and the organization’s cultural capital. The results of this study can serve as a practical and theoretical guide for organizations and managers in improving social interactions and responsible employee behavior.

Abstract Over the past two decades, Non-Governmental Organizations (NGOs) have become pivotal pillars of welfare systems in many countries; however, there remains a lack of a clear theoretical and empirical formulation of the direct and indirect functions of these institutions. The present study was conducted with the aim of providing a comprehensive model of NGO roles within Iran’s social welfare and social security system. Adopting a qualitative approach within an interpretivist paradigm, data were collected through semi-structured interviews with 12 experts, including NGO managers, legal advisors, and faculty members. Data analysis was carried out using the thematic analysis method based on the Attride-Stirling (2001) model, which ultimately led to the extraction of 29 open codes and 5 basic themes. The findings indicate that NGO roles can be categorized into two levels: first, direct service-providing and empowering roles, including health and welfare service delivery, bridging service gaps, and empowering vulnerable groups; and second, indirect advocacy and supervisory roles, such as monitoring health rights, fostering transparency, needs assessment, policy innovation, and inter-organizational networking. The study concludes that NGOs in Iran have been largely reduced to direct, executive roles and, due to significant structural barriers—such as the lack of supportive legislation, financial dependence on the government, and the absence of a unified database—have failed to perform indirect monitoring and policy-making functions. Ultimately, achieving an efficient hybrid welfare system requires a fundamental redefinition of the relationship between the government and NGOs, alongside the establishment of supportive institutional, legal, and financial frameworks.

Abstract The aim of the present study is to explain the paradigmatic model of "development of mutual trust between humans and systems" in executive agencies. This research is applied in terms of purpose and qualitative in terms of methodology with a data-based theory approach. The statistical population included experts, senior managers of information technology, and public administration specialists, who were conducted using a purposive sampling method (snowball), 17 semi-structured interviews until theoretical saturation was achieved. The data analysis process was carried out using three-stage coding (open, axial, and selective) with maxquda software. The findings show that the pivotal phenomenon of "development of mutual trust" is the result of the interaction of causal conditions (governance and legal requirements, complexity of administrative tasks, need for computational transparency), contextual conditions (digital literacy and user expertise, fear of substitution, ambiguity in the legal accountability of the system), and intervening factors (complexity of algorithm logic and fear of substitution). In the strategy phase, continuous training and empowerment, participatory design of systems plays a key role in reducing organizational uncertainties. The results of this model indicate that the deployment of intelligent systems in the public sector, beyond technical aspects, requires a mental re-creation of the role of machines in decision-making processes. By providing a comprehensive framework, this research offers operational solutions for enhancing social capital and national productivity through the transition to data-driven governance.

Abstract This research aims to identify and elucidate the thematic network of an organization’s public policy-making model, grounded in the social construction framework of political groups, through a qualitative approach. Methodologically, the study is qualitative in nature and employs thematic analysis. The statistical population includes 10 professors and experts in the field of public policy. The sample size was determined using the snowball sampling technique, with interviews continuing until theoretical saturation was achieved. Semi-structured interviews were utilized for data collection, and data analysis was performed via thematic analysis using MAXQDA software.The research findings yielded a total of 717 primary codes, categorized into 59 basic themes, seven organizing themes, and one global theme. The results revealed that the thematic network comprises seven dimensions: 1) the socio-cultural context of policy formation, 2) the intellectual foundations of policymakers, 3) symbolic and meaning-making concepts, 4) the power and hegemony of political groups, 5) the construction of policy reality, 6) the ideological transformation of policymakers and political groups, and 7) the social construction of policy. This model advances Schneider and Ingram’s theory of the social construction of target populations from the level of describing outcomes to the level of explaining the components that shape social construction, providing a practical framework for mitigating the subjective biases of policymakers.