knowledge management

This study aims to identify, analyze knowledge-based governance strategies in science and technology parks using a meta-synthesis approach, emphasizing the multi-level and multi-dimensional nature of governance in knowledge-intensive innovation ecosystems. With the rapid advancement of digital technologies, the growing complexity of knowledge flows, and the increasing interdependence among universities, industries, and government agencies, traditional linear and hierarchical governance models have proven insufficient for addressing dynamic and heterogeneous challenges. Knowledge-based governance, therefore, is not merely a managerial or administrative mechanism but functions as an integrative platform for institutionalizing intelligent knowledge flows, fostering transparency, trust, accountability, and collaborative innovation, while also ensuring sustainable social, economic, and environmental outcomes across diverse stakeholders. This study provides a theoretically grounded and empirically informed framework for governance in science and technology parks, highlighting the alignment of institutional, organizational, digital, and international dimensions to enhance decision-making, knowledge sharing, learning, and ecosystemic resilience, ultimately contributing to innovation-driven regional development.

Grounded in an interpretive qualitative paradigm, this research employs the meta-synthesis method to systematically integrate and re-interpret findings from prior empirical and theoretical studies related to knowledge-based governance in science and technology parks. The study adopts Sandelowski and Barroso’s seven-step meta-synthesis framework, encompassing: (1) formulation of research questions; (2) comprehensive literature review; (3) systematic source identification and selection based on relevance and rigor; (4) detailed extraction of relevant data and concepts; (5) qualitative analysis and synthesis of primary, secondary, and final codes; (6) rigorous quality control to ensure the reliability, validity, and transparency of the synthesis process; and (7) presentation of synthesized findings in a structured framework. Through this methodology, the study develops a multi-dimensional, integrative set of governance strategies that reflects the interactions among institutional structures, organizational processes, digital platforms, policy frameworks, and international collaboration, providing a holistic understanding of governance mechanisms in science and technology parks. A total of 152 primary studies were examined, from which 78 secondary codes were generated and subsequently distilled into 9 overarching strategic dimensions, capturing the complexity and diversity of knowledge-based governance practices.

The meta-synthesis identifies nine interrelated strategic dimensions central to effective knowledge-based governance in science and technology parks:Transparency and accountability: This dimension encompasses institutional and legal transparency, open access to data, stakeholder responsiveness, and mechanisms for continuous reporting and feedback. The findings emphasize that transparency, coupled with stakeholder accountability, establishes the foundation for trust, collective learning, and decision-making legitimacy within multi-stakeholder environments. 2. Capacity building and empowerment: Effective governance requires both institutional capacity development and human capital empowerment. Key strategies include organizational strengthening, knowledge management systems, specialized training programs, intra- and inter-park knowledge sharing, and leadership development initiatives. These mechanisms enhance absorptive capacity, enable systematic learning, and facilitate the alignment of organizational objectives with broader governance goals. 3. Innovation and networking: The study underscores the role of open innovation, co-creation, and ecosystem-based networking as critical enablers of knowledge circulation and technology commercialization. By fostering interactions between startups, universities, research institutes, and industry partners, parks can support collaborative innovation, bridge gaps between knowledge producers and users, and accelerate the translation of knowledge into tangible economic and social value. 4. Digitalization and intelligent governance: Digital infrastructure, platform-based governance, and data-driven decision-making constitute the core of this dimension. The findings highlight how artificial intelligence, Internet of Things (IoT), and other digital technologies can optimize knowledge flows, enhance process efficiency, and support adaptive governance, while also enabling predictive analytics for strategic human capital planning and operational management within parks. 5. Smart policy-making: Adaptive and evidence-based policy frameworks, regulatory flexibility, and incentive structures are identified as essential for effective governance. Policies that integrate top-down guidance with participatory mechanisms allow for iterative learning, mitigate governance gaps, and align stakeholder interests while facilitating innovation and sustainable development. 6. Sustainable development and social responsibility: Governance strategies must incorporate environmental sustainability, ethical innovation, and social inclusion. Green technologies, low-carbon solutions, equitable access to resources, and socially responsible practices strengthen the legitimacy and long-term viability of parks, ensuring that knowledge-based growth is not solely economic but also socially and environmentally balanced. 7. Scientific diplomacy and international collaboration: Parks serve as nodes for global knowledge exchange, facilitating international technology transfer, cross-border learning, and collaborative innovation networks. Strategic partnerships at regional and international levels enhance the competitiveness of parks, allow for contextualized learning from diverse environments, and support the global positioning of national innovation systems. 8. Resilience and foresight: Governance frameworks must integrate adaptive capacities, risk management, strategic planning, and foresight mechanisms to address technological uncertainty, economic fluctuations, and evolving stakeholder expectations. Resilience is achieved not merely through robustness but by enabling rapid reconfiguration of resources, processes, and policies in response to emerging challenges. 9. Ecosystem convergence: Finally, the study highlights the convergence of university-industry-government networks and cross-sectoral collaborations as a central mechanism for integrated knowledge-based governance. Multi-level interactions among diverse actors facilitate trust, reduce conflicts of interest, accelerate knowledge transfer, and foster systemic innovation, ensuring that science and technology parks function as dynamic, learning-driven ecosystems rather than isolated entities.Collectively, these nine dimensions provide a multi-level framework that guides the design, implementation, and evaluation of knowledge-based governance strategies in science and technology parks. They emphasize the interplay between institutional structures, digital tools, human capital development, policy frameworks, and international cooperation, establishing a foundation for participatory, transparent, and sustainable governance capable of enhancing regional innovation capacity.

The findings of this meta-synthesis highlight that knowledge-based governance in science and technology parks is inherently multi-dimensional, dynamic, and deeply embedded in complex innovation ecosystems. The identification of nine interrelated strategic dimensions demonstrates that effective governance extends beyond traditional administrative or hierarchical approaches and requires an integrated framework combining institutional transparency, organizational capacity building, digital transformation, and collaborative innovation. These results are consistent with prior studies emphasizing the shift from linear governance models toward networked, participatory, and knowledge-driven systems.A key contribution of this study lies in revealing the synergistic interaction among governance dimensions. For instance, transparency and accountability not only enhance trust but also enable more effective knowledge sharing and stakeholder engagement, which in turn strengthens innovation networks and ecosystem convergence. Similarly, digitalization and intelligent governance act as enablers that amplify the effectiveness of other dimensions by facilitating data-driven decision-making and optimizing knowledge flows. This interconnectedness suggests that governance strategies cannot be implemented in isolation but must be designed as part of a coherent and adaptive system.Moreover, the findings underscore the critical role of contextual factors such as institutional structures, policy environments, and regional innovation capacities. The heterogeneity observed across science and technology parks indicates that while the proposed framework provides a comprehensive reference, its practical implementation should be tailored to local conditions. This aligns with the broader literature that emphasizes context-sensitive governance models in innovation ecosystems.Importantly, this study bridges a significant gap in the literature by integrating fragmented perspectives on knowledge management, innovation, and governance into a unified analytical framework. It advances the understanding of how knowledge-based governance can simultaneously promote innovation, resilience, and sustainable development. The emphasis on dimensions such as scientific diplomacy, sustainability, and foresight further expands the scope of governance beyond economic performance toward long-term societal and environmental impact.

This research contributes to the literature by presenting a novel, multi-dimensional, and integrative framework for knowledge-based governance in science and technology parks. Unlike prior studies that primarily focus on operational efficiency or sector-specific interventions, this study emphasizes governance as a participatory, dynamic, and sustainability-oriented system. By detailing strategic dimensions across institutional, organizational, digital, policy, and international domains, the findings provide actionable guidance for designing resilient, transparent, and socially responsible governance mechanisms. The study enhances understanding of how knowledge-based governance can simultaneously support innovation, learning, and sustainable development, offering a roadmap for the strategic transformation of science and technology parks into knowledge-intensive ecosystems that balance economic, social, and environmental objectives.

The acceleration of digital and data-driven technologies in high-tech industries has reshaped competitive structures, value creation, and organizational practices, making many traditional mechanisms insufficient for complex environments. The growth in data volume, process automation, and interactions among intelligent platforms highlights the need for innovative digital governance frameworks. These frameworks, based on algorithms, automated protocols, and intelligent systems, enhance transparency and coordination beyond traditional systems. Achieving effective digital governance requires technological, knowledge, and organizational capacities that many organizations are still developing. Intellectual capital including human, structural, and relational components is a key driver of digital empowerment and innovation. Employees’ digital skills, data-driven infrastructures, organizational standards, and stakeholder trust networks are critical to supporting governance. The influence of intellectual capital on digital governance is often indirect, mediated by digital transformation, which reorganizes processes, infrastructures, and work patterns to enable digital capacities. Digital governance also plays a central role in knowledge management, as the creation, storage, sharing, and utilization of knowledge depend on data transparency, information quality, and integrated knowledge flows. Weak governance can disrupt these flows and limit the effective use of intellectual capital. Human and relational capital particularly drive knowledge flows and innovation capacity, while their interaction with knowledge management strengthens value creation and competitive advantage. At the macro level, regulatory frameworks moderate the relationships among intellectual capital, digital transformation, and governance, acting as enablers or constraints. Organizations must comply with regulations controlling data, privacy, and transparency, which shape digital governance and knowledge management, aligning technology, intellectual capital, and knowledge processes. Despite extensive studies, a fully integrated theoretical model connecting intellectual capital, digital transformation, governance, regulations, and knowledge management has not yet been established. This study aims to provide such a model, offering practical and theoretical insights for managers and policymakers in high-tech industries.

The present study is a quantitative, descriptive-analytical research aimed at examining the relationships among intellectual capital, digital transformation, digital governance, and knowledge management in companies located in the Urmia Science and Technology Park. The study population comprised senior IT managers, data managers, human resources managers, digital transformation specialists, and knowledge management experts working in these companies. Initially, a sampling frame was developed based on the official list of eligible employees, with inclusion criteria requiring continuous employment in one of the park''s units, at least two years of relevant experience in IT, data, human resources, or knowledge management, and a managerial or specialist role related to digital transformation. The minimum sample size of 210 participants was determined using Daniel Supr’s (2025) formula for Structural Equation Modeling (SEM/PLS-SEM), considering the number of constructs, indicators, path complexity, and desired statistical power. A simple random sampling method was employed, with unique numeric identifiers assigned to each member and selection performed using R software (version 4.3.2) with seed = 2025. To account for non-responses, 273 questionnaires were distributed, resulting in 210 valid responses after screening. Data were collected using a standardized questionnaire based on a five-point Likert scale. The validity of the instrument was assessed through content validity (via expert evaluation), convergent validity (using Average Variance Extracted, AVE), and discriminant validity (using the Fornell-Larcker criterion). Reliability was confirmed using Cronbach’s alpha and Composite Reliability (CR), both with acceptable thresholds of 0.7. Structural Equation Modeling (SEM) using Partial Least Squares (PLS-SEM) was employed to test the research model, allowing the examination of relationships among multiple variables, measurement errors, multicollinearity, latent constructs, and hypothesized paths. Statistical analyses were performed using SPSS and Smart-PLS. Model evaluation included R² (coefficient of determination), Q² (predictive relevance), T-values (for path significance), and the overall Goodness-of-Fit (GOF) index. Thresholds were applied to interpret model fit, explanatory power, and predictive accuracy. The results indicated that the model provided robust explanatory and predictive capabilities for the relationships among intellectual capital, digital transformation, digital governance, and knowledge management in the context of the park.

The findings of the study indicated that all factor loadings of the questionnaire items were above 0.4 and the T-statistics exceeded 1.96, demonstrating the acceptability of the indicators and the structural validity of the instrument. Cronbach’s alpha for all constructs was above 0.7, and the composite reliability of the research variables was also higher than 0.7, confirming the adequacy and stability of the instrument. Convergent validity of the constructs was assessed using the Average Variance Extracted (AVE), with all values exceeding 0.5, indicating a satisfactory convergence of the variables with their respective indicators. For discriminant validity, the Fornell-Larcker method was applied, showing that the square root of the AVE for each construct was greater than its shared variance with other constructs, confirming acceptable discriminant validity for all constructs. The coefficient of determination (R²) for the knowledge management variable was at a strong level, while it was moderate for digital governance and digital transformation, indicating a good model fit in explaining the variance of the dependent variables. The Q² index, which measures the predictive relevance of the model for endogenous constructs, was strong for knowledge management and moderate for digital governance and digital transformation, reflecting the model’s adequate predictive capability. The overall Goodness-of-Fit (GOF) index was calculated as 0.483, indicating a strong overall fit and proper alignment between observed and predicted values. Additionally, for hypothesis acceptance, the path coefficients needed to be positive and the T-values above 1.96; the results showed that all hypothesized relationships were statistically significant, and thus all research hypotheses were supported. In summary, the results of factor analysis, reliability and validity tests, R² and Q² indices, and the overall GOF confirm the validity, explanatory power, and predictive capability of the research model in examining the relationships among intellectual capital, digital transformation, digital governance, and knowledge management in companies located in the Urmia Science and Technology Park.

Digital governance plays a pivotal role in enhancing knowledge management and facilitates the impact of intellectual capital and digital transformation on knowledge management; in such a way that without a coherent digital governance framework, effective exploitation of organizational knowledge is not possible. Digital transformation has a significant impact on digital governance and accelerates the maturation of governance structures. Digital regulations also act as moderators, weakening the impact of human and structural capital on digital governance, which indicates the need for smart and flexible policymaking.

The study findings indicate that human, structural, and relational capital all positively influence digital governance. Human capital, including employees’ digital skills, specialized knowledge, and competencies, especially among IT managers and data specialists, is crucial for implementing effective digital standards and governance mechanisms. Structural capital, such as robust organizational frameworks, integrated information flows, and comprehensive documentation, enhances governance by enabling secure and transparent management of digital information. Relational capital, consisting of trust-based relationships and strategic collaborations, strengthens the organization’s ability to operate effectively within interconnected digital environments. Digital governance, in turn, has a significant positive effect on knowledge management. It improves the accuracy, reliability, and accessibility of organizational data, facilitating knowledge sharing, integration, and optimal use of expertise. Digital transformation positively affects governance by modernizing processes, adopting advanced technologies, and developing data-driven infrastructures. Moreover, digital governance mediates the relationship between intellectual capital and knowledge management, as well as between digital transformation and knowledge management, highlighting that the benefits of intellectual capital and transformation are realized primarily when strong governance is in place. However, digital regulations can negatively moderate these relationships, as overly restrictive frameworks limit organizational flexibility and the effective use of human, structural, and relational resources. Overall, these results emphasize digital governance as a key link connecting intellectual capital, digital transformation, and knowledge management. To enhance knowledge flows and governance while maximizing intellectual assets, organizations must invest simultaneously in human, structural, and relational capacities and implement adaptive regulatory approaches that support innovation and digital effectiveness.

In the knowledge era, higher education is recognized as one of the most important domains for knowledge creation, sharing, and management. However, knowledge management processes in these environments often face challenges such as knowledge fragmentation, resource heterogeneity, hierarchical structures, and weak interactions among actors. Conventional approaches to knowledge management mostly focus on human and structured dimensions, paying less attention to non-human elements—such as technology, physical spaces, or even policies—within knowledge networks. This research aims to investigate the implications of Bruno Latour’s Actor-Network Theory (ANT) elements in knowledge management within higher education, seeking to provide a comprehensive and interactive perspective that enables more efficient utilization of all actors—both human and non-human—in university settings.

Considering the purpose of this study — analyzing the implications of Bruno Latour’s Actor-Network Theory in knowledge management within higher education — the most suitable method is "speculation" or "Speculative essay". This qualitative and non-traditional approach enables in-depth analysis, the integration of theories, a critique of existing frameworks, and the presentation of innovative perspectives. Data were collected through a comprehensive review of scholarly texts, research articles, and relevant theoretical sources, and then analyzed through reflective and critical thinking. As a preliminary step toward theory building, this method enables the researcher to introduce innovative ideas scientifically and systematically.

The findings of this theoretical research indicate that in the field of higher education, both human and non-human actors (such as individuals, organizations, technologies, and objects) play a crucial role in knowledge management through dynamic networks. These heterogeneous networks influence all four dimensions of knowledge management—creation, application, transfer, and retention—and are the driving force behind these processes. In other words, knowledge creation is the result of the interaction and synergy between various actors. Additionally, the application and transfer of knowledge cannot occur without the involvement of non-human elements (such as digital systems, documents, and organizational procedures) alongside human actors. Knowledge retention (preservation and storage) also depends on the collaboration between human actors (such as knowledge managers or librarians) and material-technological infrastructures (such as databases and archives). Therefore, knowledge processes in universities are not merely human actions but are the outcome of networking and reciprocal interactions between human and non-human elements.According to Actor-Network Theory, the process of "translation" plays a central role in explaining these patterns. This concept suggests that actors continuously redefine their interests and roles within the network, transforming and re-producing reality and knowledge through their interactions. In other words, some actors act as active mediators (having a role in mediation), reshaping the content of knowledge or relationships. In contrast, others merely serve as intermediaries, transferring knowledge or instructions without altering their nature. Furthermore, it was observed that the stable networks formed in this context gradually turn into "black boxes"—complex structures and processes that, due to their stability and acceptance, are assumed to be self-evident, and their internal details become invisible to the actors. Consequently, many established practices, technologies, or institutions function as black boxes, and their stable performance makes it difficult to question their inner workings. Collectively, these concepts demonstrate that knowledge management in higher education is the result of networked actions among various factors (human and non-human) through continuous translations and mediations, and its sustainability depends on networks that eventually solidify into black boxes.

This paper examines the implications of Actor-Network Theory for knowledge management in higher education, providing insights into the complex interactions between human and non-human actors in educational processes. It highlights the significance of dynamic networks and novel concepts such as translation, mediation, and black-boxing in the facilitation and preservation of knowledge. The findings provide valuable insights for universities to improve their knowledge management practices through these theoretical frameworks.

Knowledge is not a static, human-centered asset, but a dynamic product of heterogeneous networks of human and non-human actors. This view poses a serious challenge to humanistic traditions that view technology and objects as passive instruments; whereas actor-network theory suggests that digital systems, documents, procedures, and even academic spaces are active co-constructors of knowledge realities. This study extends the application of this theory to the organizational-educational domain and shows that blurring the line between human and non-human agents provides a deeper understanding of the complexity of the contemporary university. From a practical perspective, if knowledge management is a product of dynamic networking, it is not enough to rely solely on “strengthening human capacity” or “upgrading technology”; rather, flexible networks must be designed that allow for the opening of black boxes and prevent the process from becoming fixed. Ultimately, universities must create spaces that enable not only knowledge production, but also the ongoing review of knowledge production mechanisms.

Today, productivity as a continuous process provides the power and ability necessary to solve many problems and studies the existing inadequacies in the country such as low profitability, increased waste, inability to compete, lack of maximum utilization of production capacity and generally lack of proper understanding of a system. Governments and companies try to get as close as possible to these indicators by using appropriate techniques and methods. Factors such as employee training and employment, multi-skill training programs, employee motivation, job satisfaction, bonuses paid to employees and organizational culture are effective in increasing employee productivity. On the other hand, according to some researchers, knowledge management is known as a strategic lever for improving organizational productivity. Knowledge management is a set of processes for identifying, storing, sharing, and utilizing the organization's valuable knowledge. Empirical studies show that employees who enjoy a higher level of well-being are more likely to participate in knowledge sharing and creation processes, which can improve organizational performance. In the oil industry, the nature of its activities is often based on specialized knowledge and technical skills, the importance of knowledge management for optimizing human resources and large volumes of data and work experience is particularly evident. On the other hand, ignoring employee well-being can lead to reduced motivation, inefficient knowledge management processes, and consequently a decline in organizational productivity. Organizations that make meaningful investments in the area of human resource well-being usually enjoy a higher level of motivation, productivity, and competitive advantage. In high-risk and complex industries such as the oil industry, the importance of employee well-being is doubly important. This industry is inherently tied to difficult working conditions, environmental pressures, technical complexities, and high productivity requirements. In such environments, improving well-being can increase job satisfaction and work output in addition to reducing job stress and physical and psychological pressures. The technical knowledge of experienced and sometimes retired employees in the oil industry is a valuable resource that must be preserved and utilized. If employees feel a sense of well-being and value, they are more likely to share their knowledge and experiences with others. Indeed, by improving the overall welfare of employees within the organization, and through identifying and preserving knowledge, acquiring, transferring, sharing, and applying it, organizational productivity will subsequently be enhanced. The present study was conducted under the title "The Effect of Employee welfare on Organizational Productivity Components Considering the Mediating Role of Knowledge Management in the Oil Industry". This study sought to answer the general question: Does employee welfare have an effect on organizational productivity components (including motivation, feedback, organizational support, and social status) in the oil industry? Does knowledge management play a mediating role in the relationship between employee welfare and organizational productivity components?

The present study is an applied research in terms of its purpose and uses a descriptive-survey method in terms of data collection. In this study, structural equation modeling analysis using the PLS method in SmartPLS4 software was used to test the hypotheses in the inferential statistics section. The data collection tool was standard questionnaires, which were used to examine the validity of the questionnaire questions using convergent validity and divergent validity indices, and to examine the reliability using Cronbach's alpha and composite reliability indices. The statistical population of this research consisted of 265 experts and human resource managers of the Ministry of Petroleum in Tehran. The sample size was calculated as 157 using Cochran's formula.

The findings of the research based on the fitted structural equation model in the case of significant values at the 95% confidence level showed that employee well-being with significant numbers of 36.93, 5.27, 2.74, 2.23 has a direct and positive effect on organizational productivity components (including motivation, feedback, organizational support and social status) in the oil industry. The results also showed that knowledge management with significant numbers of 4.85, 4.82, 2.11, 5.39 plays a mediating role in the relationship between employee well-being and organizational productivity components, meaning that improving employee well-being can lead to increased productivity if knowledge management is improved.

The findings reveal that employee welfare has a significant direct positive impact on all key components of organizational productivity (motivation, feedback, organizational support, and social status) in Iran’s oil industry, with the strongest effect observed on employee motivation. More importantly, knowledge management plays a strong and significant mediating role in this relationship. When employees experience higher levels of well-being, they are more willing to share and apply their knowledge, which in turn enhances organizational productivity.In the high-risk, knowledge-intensive oil sector, employee welfare and knowledge management function as two sides of the same coin. Simultaneous investment in both creates a virtuous cycle that not only boosts productivity but also fosters a healthier, more engaged, and sustainable workforce. This study is among the first to empirically examine the mediating role of knowledge management between employee welfare and organizational productivity in Iran’s oil industry, highlighting that balanced attention to “people” and “knowledge” is essential for achieving sustainable performance in this strategic sector.

Oil industry managers should adopt policies that promote both employee well-being and knowledge management simultaneously, and subsequently increase employee satisfaction and engagement, and organizational productivity. This study is the first to focus on the importance of the relationship between employee well-being and organizational productivity, considering the mediating role of knowledge management in the oil industry in a country.

In the banking system, customers are the main focus and in fact all the work is to seek their satisfaction, attention and attraction. Customer goals must be realized in customer relationship management strategy. Customer relationship management and knowledge management are key and strategic tools for all companies, especially in the current competitive environment. Due to the importance of the topic in this research, the role of knowledge management system on customer-oriented management was examined. The statistical population of the research is the employees of Sepah Bank in Shahrekord, 160 of whom were used as a statistical sample according to the Karjesi-Morgan table. The research collection tool was the standard questionnaire of knowledge establishment and customer-centered management. The validity of the instrument was based on form and content validity, and Cronbach's alpha was used for reliability. The results showed that knowledge management and customer-oriented management have a significant relationship. Also, the components of establishing knowledge management system showed a significant positive relationship with customer-oriented management. This means that customer-oriented management will increase with the increase in the establishment of knowledge management system.

Sustainability has become one of the primary concerns of organizations and a symbol of their excellence. With the growing population and increasing demand for healthcare services, sustainable management of medical waste has gained critical importance. This study aims to assess the commitment of healthcare center managers to sustainability through the selection of waste disposal methods, utilizing knowledge management approaches and multi-criteria decision-making.

This applied research employs a hybrid multi-criteria decision-making approach. Initially, sustainability criteria in economic, environmental, and social dimensions were identified through expert opinions and a review of specialized literature. Then, in a case study, various medical waste disposal methods were evaluated and ranked with input from waste management and sustainability experts. Data collection tools included specialized questionnaires and semi-structured interviews.

The results indicated that methods such as recycling, source reduction, and innovative technologies showed the highest alignment with sustainability principles. In contrast, traditional methods like landfilling and incineration ranked lower.

Knowledge management serves as an effective tool for institutionalizing sustainability in healthcare centers, and multi-criteria decision-making enhances this process.By focusing on the linkage between knowledge management and sustainability commitment in medical waste management, this study offers a novel perspective in the literature on sustainability and organizational decision-making.

The present study aimed to design a succession planning model with a knowledge management approach in public universities, using a qualitative method based on grounded theory and semi-structured interviews with 16 experts from public universities in Iran. The data were analyzed in three stages of open, axial, and selective coding. The research findings represented 26 general categories that were designed in the form of a paradigmatic data-based model. Causal factors included talent pool (identifying talents, identifying needs, forming a talent pool), training and preparing employees, human resource management, motivation, and the mission of universities; axial category, succession planning with a knowledge management approach (sharing, recording and maintaining, creating and maintaining knowledge); contextual characteristics included psychological factors, employee knowledge and skills, organizational support, organizational structure, leadership style, resistance to change, specialization, and cultural factors (organizational culture and cultural influence); The intervening categories included political, legal, and environmental factors, which indicate that national and international consequences (internationalization of academic services and elite development of society), behavioral consequences, and performance consequences are achieved from strategies for optimizing performance evaluation indicators and standardizing managerial jobs based on knowledge management indicators, systems thinking, participatory management, use of emerging technologies (knowledge management information systems, artificial intelligence, creativity, and innovation), and futurism. The emphasis on a holistic approach to succession planning and the resulting elite development is a distinctive feature of this research.

The purpose of this study is to design a model for enhancing knowledge management based on intellectual and professional capital in the banking industry based on thematic analysis. The research method is applicable–developmental in terms of purpose, and qualitative in terms of implementation. The statistical population includes 18 university professors, managers, and experts from Gharz‑al‑Hasna Mehr Iran Bank. The sample size was determined through purposive sampling, and interviews continued until theoretical saturation was reached. Semi‑structured interviews were used for data collection. Thematic analysis was applied for data analysis using Maxqda software. The findings of the study revealed that knowledge management in organizations consists of six main dimensions: intelligent knowledge infrastructures (flexible knowledge infrastructures, smart accessibility, simplicity of knowledge systems, and automated organizational knowledge storage), knowledge empowerment (individual knowledge sharing, voluntary participation, and collective knowledge sharing), internal value creation (practical use of employee knowledge, decision‑making, and analysis of employee knowledge), external value creation (acquisition of knowledge and learning from customer experiences), comprehensive knowledge support (managerial support, strategic guidance, and psychological safety and trust), and knowledge culture (learning on the job, valuing knowledge acquisition, sustainability of knowledge management, and internalization of knowledge‑based behavior).

The primary objective of This study examines knowledge management in relation to the sustainability and long-term development of businesses, with a particular focus on women-owned enterprises, and designs a comprehensive knowledge management framework using the Delphi technique. Knowledge management is a critical driver of organizational success, enabling businesses to leverage internal and external knowledge to achieve competitive advantage, innovation, and operational efficiency. In a dynamic business environment, organizations that effectively implement knowledge management practices are better equipped to respond to market changes, technological advancements, and evolving customer demands. Businesses are increasingly significant contributors to the national economy but face unique challenges, including limited access to financial resources, insufficient market networks, and barriers to professional training and mentorship. This study aims to identify modern tools, methods, and techniques of knowledge management that enhance organizational performance, foster innovation, and strengthen sustainability. Beyond assessing the impact of knowledge management practices, this study explores how these practices influence long-term business growth and resilience. Specifically, this study evaluates how knowledge management supports sustainable development by facilitating knowledge creation, dissemination, utilization, and retention. It investigates how businesses can capture valuable knowledge from employees, particularly key personnel, and transform it into actionable strategies that improve productivity, innovation, and market competitiveness of the company. The central goal is to propose a practical and actionable framework grounded in real-world organizational conditions that supports continuous improvement and sustainable growth. This study also addresses the gaps in the literature. While many studies focus on large organizations, fewer examine SMEs, particularly women-owned enterprises, which represent a growing and important economic segment. By focusing on this group, this study provides context-specific insights to guide policymakers, business leaders, and knowledge management practitioners in implementing effective strategies. The developed framework serves as a roadmap for organizations seeking to leverage knowledge assets to achieve strategic objectives, improve business processes, and ensure long-term sustainability.Design/methodology/approach: This applied qualitative study employs a descriptive-analytical approach to understand complex organizational processes. The Delphi survey technique was used to gather expert insights and develop the knowledge management framework, as it allows for iterative rounds of feedback and consensus-building among experts. In the first stage, key components, indicators, and constructs were identified through an extensive review of the academic literature, industry reports, and case studies. These were structured into a questionnaire based on a five-point Likert scale, capturing both quantitative and qualitative expert perspectives. The statistical population included 30 experts and professors in knowledge management, business management, and entrepreneurship, selected through purposive sampling to ensure their sufficient expertise. The questionnaire covered 11 major components and 128 items, including the objectives of knowledge utilization, information technologies, human resources, knowledge sharing, knowledge development, and evaluation. External factors—individual, organizational, governmental, economic, and socio-environmental—were also incorporated to capture the multidimensional nature of knowledge management in supporting sustainability. Validity and reliability were confirmed through expert review and Cronbach’s alpha. Data analysis was conducted using SPSS version 25, employing descriptive and inferential statistics to identify the trends and critical components. Multiple iterative rounds of the Delphi method ensured that the final framework reflected the most impactful knowledge management practices for female-owned businesses.

The findings identified key components crucial to knowledge management and sustainability of women-owned businesses. These include the objectives of knowledge utilization, application of information technology, human resource management, systematic knowledge sharing, knowledge development, and continuous evaluation. External factors, such as individual capabilities, organizational culture, governmental policies, economic conditions, and socio-environmental influences, significantly shape the effectiveness of knowledge management initiatives. Knowledge management is a central mechanism for promoting sustainability and growth, enabling the systematic capture, organization, and application of knowledge. This enhances operational efficiency, supports informed decision-making, and creates a long-term value. Among the specific objectives, improving organizational productivity (average rating 4.30), fostering innovation and creativity, transferring employee experiences, and enhancing market competitiveness (average rating 4) were prioritized. These results demonstrate that organizations view knowledge management not only as an efficiency tool but also as a strategic asset for growth and competitiveness. This study also highlights the importance of building long-term relationships with customers, preserving and developing human capital, adapting to market changes, and fostering strong leadership. The integration of knowledge management with advanced technologies, systematic documentation, and retention of key employees were identified as essential strategies for enhancing business processes and cultivating a learning culture. Knowledge sharing, facilitated through regular meetings, workshops, and collaborative platforms, supports employee engagement and skills development. Knowledge development programs, including training, mentorship, and experiential learning, equip employees to drive innovation and contribute to business growth. External enablers, such as governmental support, financial incentives, insurance programs, and social security benefits, were also identified as crucial for the effective implementation of knowledge management practices. Sales and marketing skills, combined with effective customer relationship management, are emphasized as key drivers of business sustainability. Organizations that integrate robust knowledge management with strong marketing and customer engagement strategies are better positioned to respond to market dynamics, attract and retain customers, and achieve their long-term objectives.

This study demonstrates that knowledge management plays a pivotal role in the sustainability and long-term development of female-owned businesses. It contributes to enhanced productivity, increased innovation, strengthened competitiveness, and overall improved organizational performance. Effective knowledge management requires a holistic approach that integrates human resources, technological tools, knowledge sharing, documentation, and leadership practices. Retaining key employees, developing technical and managerial skills, and fostering continuous learning are essential for effective knowledge utilization, enabling businesses to adapt, innovate and sustain growth over time. Advanced technologies such as knowledge management software, data analytics, and collaborative platforms facilitate knowledge capture, storage, dissemination, and application. External factors, including governmental policies, economic conditions, and socio-environmental considerations, play a significant role in supporting knowledge management initiatives. Providing financial support, insurance programs, and social security benefits strengthens the organizational capacity to implement knowledge management effectively. Ethical standards and corporate social responsibility initiatives reinforce trust, credibility, and long-term sustainability. Knowledge management is not an isolated activity but an integrated organizational strategy that interacts with multiple dimensions of business operation. Aligning knowledge management practices with strategic objectives enhances productivity, encourages innovation, maintains competitive advantage, and supports sustainable growth. The proposed framework offers a practical roadmap for women entrepreneurs and business leaders to implement effective knowledge management practices, ensuring resilience, long-term success, and contributions to the national economy. Thus, knowledge management serves as a strategic asset that enables sustainable organizational development and long-term business growth in contemporary economic contexts.Research limitations/implications: This study is subject to several limitations: Sample Size and Scope: The findings are based on a relatively small purposive sample of 25 experts, which may affect the generalizability of the results. Methodological

Constraints: 

While the Delphi technique is robust, its reliance on consensus may marginalize dissenting or highly innovative viewpoints. Contextual Specificity: The research was conducted within a specific geographic and economic context (Iran), potentially limiting the direct applicability of the proposed framework to other environments. Subjective Assessment: Data collection based on expert judgment using Likert scales carries an inherent risk of subjective bias in evaluating the components. Temporal Limitation: The rapid evolution of knowledge management technologies and market conditions means that the findings reflect a specific point in time.Practical implications: This study provides a validated framework for implementing knowledge management (KM) to achieve sustainable business practices. Managers should prioritize documenting key employees' knowledge and fostering regular knowledge-sharing sessions. Invest in information technology, particularly decision support systems, to facilitate knowledge storage and access. Focus on developing employees' technical and managerial skills based on the assessed training needs. These actions directly enhance productivity, innovation, and long-term competitive advantages.

Originality/value: 

This study confirms the pivotal role of knowledge management in ensuring the sustainability and long-term development of businesses. The purposeful application of knowledge management leads to increased productivity, process improvement, enhanced innovation, and the creation of competitive advantage. Advanced technologies, knowledge documentation, and retention of key employees were identified as critical factors for improving organizational performance. Additionally, sales and marketing skills, along with establishing sustainable customer relationships, play a significant role in long-term business growth and success. Based on these findings, managers and policymakers should strengthen the culture of knowledge management and develop the necessary infrastructure to provide a conducive environment for sustainable growth and the empowerment of entrepreneurs.

Despite the rapid growth in the production and utilization of big data and its vast potential for enhancing innovation and improving performance, many Iranian knowledge-based enterprises (KBEs) still face serious challenges in effectively leveraging this strategic resource. If such limitations persist, they are likely to weaken these firms’ competitive positions in today’s turbulent business environment by reducing product commercialization. A review of the existing literature indicates that most prior studies have been conducted in developed countries, and their findings are not necessarily applicable to Iran’s local context. Moreover, much of the research has focused only on partial relationships among the variables, with limited attention given to developing and testing a comprehensive conceptual model that explains the entire value-creation pathway from big data knowledge management capabilities (BDKMC) to business performance (BP). Accordingly, this study seeks to address this research gap and provide empirical evidence within the context of Iranian KBEs. Therefore, this study examines the impact of BDKMC on BP by clarifying the mediating roles of innovation capability (IC), business process innovation (PI), and competitive advantage (CA). This study aims to deliver an integrated and precise picture of how big data can be intelligently harnessed to foster innovation, build CA, and enhance BP.

This study was designed and conducted within a positivist paradigm, following a deductive reasoning approach. In terms of purpose, it is categorized as applied research, while methodologically, it is descriptive in nature and implemented as a cross-sectional survey. The population of interest comprised 5,048 knowledge-based companies in Tehran Province. To ensure adequate statistical precision and reduce the likelihood of Type I and Type II errors, the minimum sample size was estimated using G*Power 3. Based on four predictor variables, a significance level of 0.05, an effect size of 0.05, and a statistical power of 0.90, the required sample size was determined to be 313. The unit of analysis was company managers, with one questionnaire administered to each firm in the sample. Sampling was conducted using a simple random sampling procedure using the random sampling function in SPSS. Data were collected using a standardized instrument consisting of 47 items. The research model was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) in SmartPLS 3. In the preliminary stage, factor loadings were inspected to ensure that all exceeded the minimum threshold of 0.40. The model evaluation was conducted in three steps: measurement, structural, and overall models. Within the measurement model, internal consistency reliability was assessed using Cronbach’s alpha, rho_A, and composite reliability (CR) values. Convergent validity was examined using the average variance extracted (AVE), while discriminant validity was assessed using both the Fornell–Larcker criterion and the Heterotrait–Monotrait ratio (HTMT). In the structural model, the predictive capability was first evaluated through the explained variance (R²) and Stone–Geisser’s Q² (predictive relevance). The study hypotheses were then tested. Finally, the overall model fit was assessed using three key indices: the root mean square residual covariance (RMStheta), standardized root mean square residual (SRMR), and goodness-of-fit (GOF) index. Together, these indices ensured the robustness and reliability of our proposed conceptual model.

The results revealed that BDKMC significantly affected IC (β = 0.329, t = 4.669), BPI (path coefficient = 0.239, t = 3.010), and CA (β = 0.425, t = 6.749). However, the direct effect of BDKMC on BP was not supported (β = 0.052, t = 0.985). Furthermore, IC has significant positive effects on BPI (β = 0.536, t = 9.632), CA (β = 0.443, t = 7.562), and BP (β = 0.299, t = 3.514). In addition, BPI significantly influenced both CA (β = 0.165, t = 2.360) and P (β = 0.146, t = 2.071) in this study. Finally, CA had a strong and significant impact on BP (path coefficient = 0.342, t = 5.517). Regarding the mediation effects, the mediating roles of IC and BPI were not supported (β = 0.098 and 0.035; t = 1.812 and 0.794, respectively). However, the mediating role of CA was confirmed (β = 0.145, t = 2.013).Research limitations: Despite its theoretical and practical contributions, this study is subject to several limitations, which provide avenues for future research. First, reliance on self-reported data from managers of knowledge-based firms may introduce response bias. Future work could enhance validity by employing multi-method approaches, such as in-depth case studies and semi-structured interviews, to reveal the more nuanced mechanisms of value creation through big data knowledge management. Second, the geographical and industrial scope—focusing on firms in Tehran Province and analyzing heterogeneous industries without differentiation—may limit the generalizability of the findings. Expanding geographical coverage, conducting cross-national comparisons, and pursuing industry-specific studies could address this issue while exploring variations across technological domains and organizational life-cycle stages. Third, the cross-sectional design restricts causal inference and leaves room for reverse or bidirectional effects to be observed. Longitudinal designs can offer stronger causal insights. Fourth, the dynamic nature of environments and the rapid evolution of big data technologies may constrain the measurement validity. Data mining, document and social media content analysis, updated measurement instruments, and novel theoretical perspectives may help mitigate this concern. Fifth, the lack of distinction among firms in terms of size, age, technological focus, and business models may obscure relevant differences. Future research could employ cluster analysis, multigroup analysis, or multilevel modeling to uncover subgroup-specific patterns and test the conceptual framework accordingly. Finally, the insignificant mediating effects highlight the need for further investigation to capture the complexity of relationships and provide a more holistic understanding of the value creation process.

Practical implications:

 This study’s findings offer several practical insights for managers and policymakers in KBEs. First, they highlight the critical role of BDKMC in enhancing innovation and creating CA, suggesting that firms should strategically invest in knowledge management systems and processes to fully leverage their data resources. Second, the results indicate that IC and the BPI serve as key mechanisms through which the BDKMC impacts BP. Therefore, managers should focus not only on technological adoption but also on fostering a culture of continuous innovation and process improvement to translate data-driven insights into tangible performance results. Third, the confirmed mediating role of CA underscores the importance of aligning innovation and process initiatives with strategic objectives to sustain superior performance in dynamic business environments. Collectively, these insights provide actionable guidance for KBEs aiming to optimize their big data strategies, strengthen their innovation pipelines, and enhance their overall organizational competitiveness and performance.

Originality/value: 

This study, for the first time, investigates the impact of BDKMC on the performance of Iranian KBEs and provides unique empirical evidence from these companies. The findings address existing gaps in both theoretical and practical literature and offer novel insights into the dynamics of innovation and competitive advantage within this context.

In the contemporary knowledge-based economy, private companies in developing nations, particularly Iran, face profound challenges in leveraging intellectual resources to secure sustainable competitive advantages. Traditional factors of production, such as labor, land, and physical capital, have yielded intangible assets such as organizational knowledge, innovation capabilities, and adaptive learning. This shift demands that firms reconfigure their strategies to prioritize knowledge synergy; however, many private enterprises grapple with resource limitations, inadequate infrastructure, and misalignment between knowledge initiatives and business goals. These barriers not only stifle innovation but also erode resilience in the face of environmental volatility and technological disruptions.This study investigates how knowledge management mechanisms enable private companies to cultivate and maintain competitive advantages during the transition to a knowledge-based economy. Researchers have focused on the structural, cultural, and strategic enablers that foster knowledge integration within resource-constrained settings. By addressing the core problem of underdeveloped knowledge infrastructures, this study illuminates pathways for overcoming systemic constraints, such as limited access to advanced technologies and skilled talent. It posits that effective knowledge management serves as a pivotal strategic lever, transforming intellectual assets into drivers of long-term value creation and organizational agility.This study addresses critical gaps in the literature, where prior studies often overlook the unique challenges faced by private firms in sanctioned environments such as Iran. Through targeted exploration, this study answers the following key question: Which knowledge management processes significantly enhance competitive advantages How do synergy mechanisms operate under resource scarcity conditions What structural and cultural factors underpin successful knowledge management How do policy frameworks bolster innovation capacities Ultimately, this study empowers private enterprises to harness knowledge as a cornerstone of strategic differentiation, fostering economic transformation at both the firm and national levels.

Design/methodology/approach: 

This study adopted a qualitative, exploratory approach to uncover latent patterns and relationships in the existing literature, employing the meta-synthesis method as the core framework. This methodology draws on Sandelowski and Barroso's (2007) seven-step model, which facilitates the structured integration of diverse qualitative findings into cohesive themes. The process begins with formulating research questions, followed by systematic literature reviews, source selection, data extraction, synthesis, quality control and presentation of results.Data collection targeted secondary library sources, including Persian and English scientific articles, policy reports, and industry analyses. For Persian sources, the temporal scope spanned 1390–1404 (solar calendar, approximately 2011–2025 Gregorian), capturing long-term domestic trends in knowledge-based development in Iran. English sources covered 2021–2025, emphasizing recent global advancements in knowledge management and digital transformation. The inclusion criteria prioritized topical relevance (knowledge management and competitive advantage in private firms), scientific rigor (peer-reviewed publications in reputable journals), and temporal alignment. The exclusion criteria eliminated irrelevant, low-quality, or out-of-scope materials.The research population comprised 243 primary sources, from which purposive and systematic sampling yielded 65 high-quality samples for analysis. Analysts conducted a thematic analysis through three-stage coding: open coding extracted 410 conceptual codes from the texts, axial coding grouped these into 23 subthemes, and selective coding synthesized them into four main themes. Validation measures included expert panel reviews for content validity, source triangulation for comprehensiveness, and inter-coder agreement (85% reliability coefficient). All coding and analysis were performed manually, without software, to preserve interpretive depth and ensure methodological transparency.This design aligns with the exploratory goal of generating a localized framework tailored to Iranian private firms, integrating interdisciplinary insights from economics, strategy and technology. By synthesizing fragmented literature, the approach not only identifies emergent patterns but also constructs a robust analytical model for knowledge-driven competitiveness

The meta-synthesis revealed that knowledge sharing emerged as the most salient subtheme, accounting for 15% of the conceptual codes and playing a central role in bolstering organizational resilience. Analysts identified four overarching themes: processes of organizational knowledge management, mechanisms for competitive advantage, structural and cultural enablers in the knowledge-based economy, and strategic and policy frameworks.Under knowledge management processes, subthemes such as knowledge creation, sharing, application, and preservation dominated, with the SECI model (Nonaka & Takeuchi, 1995) being highlighted as a key mechanism for converting tacit to explicit knowledge. These processes enhance innovation and adaptability, particularly in volatile market conditions. Dynamic capabilities, green innovation, and strategic flexibility stood out as competitive advantage mechanisms, enabling firms to respond to environmental changes and differentiate their products. Structural and cultural enablers encompass human capital development, organizational redesign for knowledge flow, and cultural values promoting trust and collaboration, which collectively mitigate resource constraints.Strategic and policy frameworks emphasize performance evaluation indices, supportive policies for knowledge-based firms, and alignment between national goals and firm strategies. These findings align with global benchmarks, such as the OECD countries' 2.7% GDP allocation to R&D in 2023 and Iran's growth in knowledge-based firms from 5,000 to over 10,115 units between 2019 and 2024. The radar chart visualization of themes underscores the prominence of knowledge sharing, with evaluation performance (frequency 33) as a cross-cutting driver.Overall, this study demonstrates that integrating knowledge management processes fosters sustainable competitive advantages, even under sanctions, by amplifying innovation and resilience. These insights validate the strategic imperative of investing in knowledge infrastructure for private firms navigating economic transitions.

Research limitations/implications: 

The primary limitation of this study stems from restricted access to proprietary data from private companies, driven by confidentiality, competitive, and security concerns. This barrier hinders in-depth operational analyses, rendering some knowledge management dimensions less observable in real-world contexts. Additionally, the absence of standardized performance indicators for knowledge initiatives in private enterprises compromises comparative validity and generalizability. Economic sanctions and technological restrictions have further exacerbized these challenges, limiting firms' adoption of advanced tools and impeding digital transformation pathways. The rapid evolution of technology and policy landscapes has also introduced volatility, necessitating ongoing revisions to maintain relevance.Despite these constraints, the findings have significant implications for theory and practice. Theoretically, this study advances the knowledge management literature by proposing a context-specific model for resource-constrained environments, bridging gaps in interdisciplinary integration. Practically, it guides private firms to prioritize knowledge sharing and SECI processes for resilience building, while policymakers can leverage insights to craft supportive frameworks, such as incentives for R&D and human capital development.Future research should pursue comparative studies between the public and private sectors to uncover scalable models, longitudinal evaluations of the impact of knowledge management on sustained advantages, and cross-cultural analyses to contextualize theories. The integration of emerging technologies, such as AI, blockchain, and big data, into knowledge systems warrants exploration, as it has the potential to accelerate digital capabilities and innovation. These directions promise empirically grounded strategies that are resilient to market fluctuations.

Originality/value:

 This research pioneers a localized meta-synthesis framework customized for Iranian private firms, diverging from conventional quantitative paradigms to offer a nuanced and interdisciplinary analytical model. By synthesizing economic, strategic, and technological perspectives, it challenges fragmented methodologies and introduces novel explorations of advanced technologies—such as AI and quantum computing—in knowledge practices under sanction-impacted conditions. This approach, which is largely underexplored in the domestic literature, opens new avenues for holistic, context-sensitive organizational research and knowledge-based policy discourse.This study’s value lies in its actionable insights for enhancing competitiveness amid resource scarcity, providing a blueprint for firms to align knowledge initiatives with strategic objectives. By addressing overlooked dimensions such as cultural enablers and policy synergies, this study contributes to global knowledge managemenat theory while fostering Iran's transition to a resilient, innovation-driven economy.

Knowledge management in public policymaking process, synthesised the insights from interdisciplinary works to promote training and skills in the field policy, and is very necessary for the success of the policy considering the growing complexity of policy issues.

The main goal of this research is to collect; summary; assessment; and the connection and coherence of the theoretical literature in the field of knowledge management in public policymaking process.

This research has been done using the qualitative method of metasynthesis. The research sampling method is purposeful sampling, articles and studies have been selected that can answer the research question.

The knowledge management cycle; creation; retention; sharing and knowledge application; knowledge infrastructure; policy cycle; policy area; and outcomes, has been extracted as different dimensions and factors affecting on knowledge management in the process of public policymaking.

Finally, the proper distribution of knowledge and policy learning in the field of policy making; policy diffusion, innovation and competitiveness; increasing the intellectual, social and psychological capital of the policy arena; improve problem-solving capacity, performance and productivity; And finally, the formulation, implementation and evaluation of the policy will be among the results of the implementation of knowledge management in the public policy making process.

This research was conducted with the aim of investigating the impact of information technology and administrative management on the success of e-government with the mediating role of knowledge management (case study of Dezful municipality).

The current research is applied in terms of purpose and descriptive-survey in nature, also simple random sampling method was chosen. The statistical population of the research was 1860 employees of Dezful municipality, of which 319 were selected as a sample. In order to analyze the data obtained from the questionnaire, SPSS and PLS software were used in the form of descriptive and inferential statistics. In this study, partial least squares structural equation modeling is used to test and validate the research model and proposed hypotheses, and the t-value is the main criterion for rejecting or accepting hypotheses.

Information technology and administrative management significantly increase the success of e-government. Also, knowledge management plays a vital intermediary role between information technology and administrative management for the greater success of e-government.

At the end of this research, it is recommended that the managers of Dezful municipality pay special attention to the basic variables of information technology, administrative management and knowledge management in order to realize electronic government in urban management.

In the current era of digital transformation and data dominance, knowledge has emerged as one of the most valuable and strategic resources alongside traditional organizational assets such as capital, labor, and technology. Businesses across various sectors increasingly recognize that sustainable competitive advantage no longer depends solely on tangible assets, but on the effective creation, sharing, and application of knowledge. Within this broader context, the cooperative sector—explicitly recognized as one of the three fundamental components of the national economy according to the IR Constitution—holds a distinctive position. Cooperatives play a vital role in promoting social equity, community participation, and inclusive economic growth.At the same time, the insurance industry has become a key mechanism for managing and mitigating diverse types of risks faced by individuals, organizations, and economic sectors. Insurance provides not only financial protection but also a framework for stabilizing enterprises and promoting sustainable development through risk pooling and redistribution. Given these overlapping concerns, this paper seeks to introduce a market-based knowledge management model as a fundamental component for the development of the cooperative sector, while simultaneously integrating the risk coverage functions of the insurance industry into the conceptual framework. The overarching objective is to explore how knowledge-based management practices—when aligned with market dynamics and supported by insurance mechanisms—can contribute to the sustainable growth and resilience of cooperative enterprises.

This research adopts an applied and exploratory approach, reflecting its dual focus on both theoretical model-building and practical implications for organizations. To gather in-depth qualitative data, semi-structured interviews were conducted with key professionals and industry experts. These interviews provided rich insights into the intersection between knowledge management, cooperative development, and insurance-based risk management.The collected data were analyzed using the ATLAS.ti software and processed according to the Strauss and Corbin grounded theory methodology, which includes open, axial, and selective coding phases. This approach allowed the researchers to extract, categorize, and connect the core dimensions and subcomponents of the model in a systematic manner. Sampling was conducted purposefully, targeting individuals with substantial expertise in the business and cooperative domains, particularly those possessing experience in the insurance industry. A total of twelve (12) semi-structured interviews were performed with senior experts, managers, and practitioners who have worked in both cooperative organizations and insurance institutions. The diversity of their backgrounds ensured that the resulting model captured multiple perspectives across managerial, operational, and policy-making levels.

The findings of this study reveal that risk management and the utilization of insurance capacities occupy a central place among the structural factors influencing the implementation of market-based knowledge management within cooperatives. The data analysis identified a complex network of causal, contextual, and intervening variables shaping the success of such initiatives. From a causal perspective, the study highlighted managerial support for knowledge implementation, the overall knowledge level and competency of managers, human resource management strategies, and the existence of strategic managerial planning for the execution of knowledge management systems as critical drivers. Moreover, several intervening factors were identified, including organizational restructuring and adaptation, the development of formal and informal social networks, the promotion of structural professionalism, the cultivation of a participatory culture, the strengthening of value-based governance, and the creation of organizational trust. Finally, contextual factors influencing the effective implementation of the model comprised the provision of adequate facilities and infrastructure, financial support for the continual updating of organizational knowledge, and the fair and transparent distribution of resources within the cooperative framework. Overall, the results underscore that an integrated approach—one that connects knowledge management processes, market mechanisms, and insurance-based risk management—can significantly enhance organizational learning, reduce vulnerabilities, and promote innovation within the cooperative sector.

The proposed model offers a comprehensive framework that can strengthen the role and share of cooperatives in the national economy. By embedding insurance-related risk management practices into a knowledge-driven system, cooperatives can better ensure the stability and sustainability of their enterprises. The synergy between knowledge management and insurance allows cooperatives to anticipate potential risks, design preventive strategies, and allocate resources more efficiently. In conclusion, this research demonstrates that it is possible to design and implement a knowledge management model tailored specifically for the cooperative sector, where the insurance industry’s contribution is explicitly integrated. Such a model not only enhances organizational performance but also reinforces resilience against market uncertainties and operational risks. Consequently, the framework can serve as a guiding tool for policymakers, managers, and practitioners seeking to leverage the dual power of knowledge and insurance to foster sustainable economic development within the cooperative ecosystem. By emphasizing both theoretical and practical dimensions, the study provides a foundation for future empirical research on the interaction between knowledge management and risk governance. It also encourages decision-makers to view knowledge as a strategic economic asset and to utilize insurance mechanisms as a means of safeguarding and expanding that asset. Ultimately, this integrative approach can contribute to the broader goal of achieving inclusive, knowledge-based, and risk-resilient growth across all segments of the cooperative economy.

The present study was conducted with the aim of validating the incentive marketing model for attracting investors in the banking system with a customer knowledge management approach. In this study, using a quantitative method and questionnaire tools, data related to customers of Mellat Bank in Tehran were collected and analyzed through confirmatory factor analysis, linear regression, and structural equation modeling. The results showed that various dimensions of incentive marketing, including technology integration, analysis of received information, customer-centric approach, supply chain optimization, and sustainability of production and operations strategies, all have a positive and significant effect on attracting investors. Among these dimensions, technology integration and analysis of received information played the most role, which indicates the importance of utilizing new technologies, digitizing services, and analyzing customer data in the banking system. The results also indicated that a customer-centric approach and paying attention to investors' needs and preferences can strengthen their trust and loyalty. In addition to confirming the innovation of the presented model, the findings emphasize the necessity of banks investing in developing technological and data-driven infrastructures, institutionalizing a customer-centric culture, and creating coordination in the banking service chain. Finally, the proposed model can be a practical guide for bank managers and economic policymakers to improve the position of the country's banking system in attracting and retaining capital.

Documenting experiences is of great importance as one of the key strategies in preserving and transferring organizational knowledge, especially in defense organizations that face complex, sensitive, and dynamic environments. However, the process of documenting experiences in these organizations is accompanied by numerous challenges and obstacles that can lead to the loss of vital knowledge, rework, or a reduction in the effectiveness of future decision-making. The aim of this study is to design a model for diagnosing the pathology of the process of documenting experiences in one of the country's defense organizations.

The present study is qualitative and conducted with a thematic analysis approach. The statistical population includes experts and individuals with experience in the field of documenting experiences in one of the country's defense organizations. Sampling was carried out purposively and with a theoretical adequacy criterion with a number of 15 people. Sampling was purposeful and based on the criterion of theoretical adequacy. Data were collected through semi-structured interviews and analyzed using the Atride and Stirling three-stage coding method including basic themes, organizing themes, and overarching themes. In order to validate the findings, participant review, expert review, and data consistency were used.

Based on the analysis of interview data, 93 basic themes were categorized into 31 organizing themes and 8 overarching themes, including weak institutional and organizational structures in documenting experiences, inefficient documentation processes and procedures, cultural and motivational deficiencies in recording and transferring experiences, human resource challenges including competence, training, and transfer of tacit knowledge, weak technological infrastructure and knowledge management systems, lack of an evaluation and feedback system in documenting and using experiences, security restrictions and information classification in the documentation process, and communication barriers and interdepartmental interactions in exchanging experiences.

The research findings led to the identification of a set of themes that represent the barriers, challenges, and requirements for documenting experiences in defense organizations. Based on these themes, a conceptual model was designed that encompasses key dimensions of the pathology of this process. This model can provide a basis for policy reform, process redesign, and upgrading the knowledge management system in defense organizations.

This research aims to investigate the influence of the Big Five personality traits, including extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience, on financial knowledge sharing (explicit and tacit) within the General Staff of the Islamic Republic of Iran Army. This research is applied, employing a survey-based, correlational, and cross-sectional design, utilizing a questionnaire as the primary data collection instrument. The statistical population of the study comprises financial personnel from three divisions: the Army Plan and Budget Department, the Army Treasury Department, and the Army Audit Organization, in the year 2023. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to test the research hypotheses. Additional statistical tests were also conducted. The research findings indicate that agreeableness has a positive effect on financial knowledge sharing (both explicit and tacit). However, no significant relationship was observed between extraversion, conscientiousness, neuroticism, and openness to experience and financial knowledge sharing (explicit and tacit). Furthermore, the financial personnel of the Army's General Staff are characterized by high levels of agreeableness, conscientiousness, emotional stability, and openness to experience, along with a moderate degree of extraversion, exhibiting a favorable inclination towards sharing their financial knowledge. Based on these findings, the personality trait of agreeableness positively influences the financial personnel's willingness to share their knowledge. Therefore, it is crucial for relevant commanders and managers within the Army to consider this trait in their recruitment and appointment procedures.

Purpoae: 

The Purpoae is to identify the dimensions and components of the conceptual model of social innovation based on knowledge management in the education system

This research employed an exploratory mixed-methods approach, combining qualitative and quantitative phases. In the qualitative phase, 15 experts were purposefully selected and interviewed. Thematic analysis using ATLAS.ti software was conducted to extract foundational, organizing, and overarching themes, ensuring the content validity and reliability of the preliminary measurement instrument. In the quantitative phase, the study population included principals and teachers from primary schools in Fars Province. Using Cochran’s formula, a sample of 261 participants was selected through simple random sampling. All extracted themes were tested via Confirmatory Factor Analysis using LISREL software.

The qualitative analysis yielded a model comprising one core construct, six dimensions Knowledge Management, Innovative Social Education, Information Technology, Educational Excellence, Support and Resources, and Student Challenges and 15 components: Knowledge Creation, Knowledge Storage, Knowledge Sharing, Knowledge Utilization, Organizational Culture, Creativity in the Educational Process, Executive Management, Educational Technology, Educational Strategy and Goal Setting, Educational Content, Organizational Communication, Human Resource Management, Financial and Material Resource Management, Student Challenges, and Social Challenges.

Successful social innovation requires systemic empowerment to transform tacit and explicit knowledge into practical solutions that address inequalities and ensure sustainable community development.

The aim of the present study is to identify the dimensions of the knowledge management model based on the Asian Productivity Organization Model in Fars Province Water and Wastewater Company with a thematic analysis approach. This study has a mixed approach that is developmental-applied in terms of purpose and survey in terms of nature and method. The data collection method in this study was a combination of library and field studies, and the data collection tools were referring to documents, interviews with experts, and a questionnaire, the validity and reliability of which were confirmed with a high percentage. The statistical population of this study included 17 university professors, experts in the field of knowledge management, and senior managers of the Water and Wastewater Company, who were selected through purposive sampling; in this qualitative study, NVIVO version 11 software was used to extract and analyze the codes related to the interviews with experts, and SPSS version 26 software was used in the quantitative part. The results of open coding of the collected qualitative data led to the extraction of 92 initial codes, 30 basic themes, and 10 organizing themes: knowledge-based leadership of the organization, knowledge-based human resources of the organization, expansion and promotion of knowledge culture, leadership of the organization's knowledge infrastructure, developmental orientation to knowledge processes, organization of new knowledge, belief in innovation in the organization, capacity building in the organization, improvement of efficiency and productivity in the organization, and improvement of the organization's quality; of which 79 codes related to the knowledge management model based on the Asian Productivity Organization Model in the Fars Province Water and Wastewater Company were approved by experts in the fuzzy Delphi process.

TThe petrochemical industry plays a significant role in economic development and reducing dependence on oil. However, the development of this industry is associated with various risks. This study is survey in terms of data collection and applied in its orientation. The target population consisted of managers and consultants of petrochemical development projects, and judgmental sampling was employed. The sample size was 10 experts, and the data collection tools included expert questionnaires, priority assessment, and structured interviews. In the first step, 25 risks were identified through a literature review and expert opinions. These risks were classified into five categories: economic, technical, legal and regulatory, environmental, and supply chain, and were evaluated using the fuzzy Delphi method. Eight risks with desirable defuzzified values were selected for final prioritization. The final risks were ranked using the Cupras method, and the priority risks included reduced global demand for petrochemical products, financing costs, increased logistics and transportation expenses, equipment and technology failures, and exchange rate fluctuations. Practical recommendations were developed based on the prioritized risks and insights from focus group interviews, taking into account a knowledge management approach.Knowledge management in the petrochemical industry, through the use of big data analysis and business intelligence, facilitates demand forecasting, supply chain optimization, financial resource management, and risk control. By simulating market trends, recording experiences, and leveraging technologies such as the Internet of Things, it reduces costs, increases efficiency, and enhances information sharing across organizational units, thereby enabling smarter decision-making and more effective responses to emerging challenges.

This article seeks to identify and measure the indicators of the creative ideas valuation model so that the proposed ideas can be properly evaluated and valued and to inform the owners of ideas and knowledge-based centers about the intellectual value of their produced ideas. . Therefore, according to this assumption, the research method is based on the Delphi model and through the preparation of a questionnaire for the elites to identify the components and indicators of valuing ideas. The main goal has been to answer the question, is it possible to design a valuation model for innovative ideas based on this model, and what are the components, dimensions and indicators of this model This research was conducted with a descriptive-analytical method and its statistical population included academicians and elites, managers and planners of knowledge-based centers and owners and experts of these centers, from among these groups 333 people were studied as a sample using a proportional systematic random sampling method. have been interviewed in this research. The results of the study have shown that the valuation of innovative ideas has 5 main components (characteristics of the idea, characteristics of idea-generating and innovative people, internal and external organizational factors, organizational structure and the transnational and global environment of knowledge-based centers) that each of these components While communicating with each other, they have a specific importance and weight, or in other words, their own rank in the explanatory model.