Knowledge Retrieval and Semantic Systems

Abstract The purpose of this research was to determine the effect of organizational culture on knowledge concealment with the role of politeness in the workplace and rejection in the workplace. The present study was applied in terms of its purpose and descriptive in terms of correlational data collection. The statistical population of this research was all the employees of Chaharmahal and Bakhtiari universities, whose number is 2255 people, according to the size of each region, a sample size of 660 people was selected using Cochran's formula, and the sample people were selected using the stratified sampling method. They were chosen according to the volume of each floor. The research tools are the standard questionnaire of incivility in the workplace by Cortina et al. (2001), the standard questionnaire of organizational culture by Jaghargh et al. (2012) and the standard questionnaire of knowledge concealment by Conley et al. (2012) and the standard questionnaire of rejection in the workplace by Faris. et al. (2008) that the validity of the questionnaires was examined based on the content, form and structure validity and after the necessary terms the validity was confirmed and on the other hand the reliability of the questionnaires was 0.88 and 0.89 respectively by Cronbach's alpha method. 0.0, 0.87 and 0.90 The results of the research showed that organizational culture has a significant relationship with knowledge concealment, and in addition, rejection in the workplace and incivility in the workplace create positive channels between organizational culture and knowledge concealment as mediators.

Abstract Introduction In today's competitive landscape, knowledge is recognized as a critical organizational asset and a key driver of success. Consequently, many organizations invest significantly in Knowledge Management (KM) initiatives. However, the success of these initiatives is not guaranteed by technology alone; it is profoundly dependent on establishing a supportive organizational culture. While KM rests on three main pillars technology, processes, and people the human and cultural factors are paramount. A primary obstacle to KM implementation is the tendency for knowledge hoarding, driven by the belief that "knowledge is power." Therefore, fostering a "Knowledge Culture" an environment where creating, sharing, and utilizing knowledge are valued and encouraged as natural behaviors is essential. Experts like Liebowitz and Chen assert that up to 80% of KM success is attributable to people and culture. The challenge for organizations is not merely implementing KM systems but cultivating this underlying culture. Changing organizational culture to embrace knowledge is often cited as one of the most difficult aspects of KM. Without a deep understanding of the factors that shape a knowledge culture, efforts to implement KM risk failure, leading to wasted resources and employee resistance. This study addresses this critical gap by aiming to systematically identify and prioritize the key factors that influence the development and sustenance of a knowledge culture within organizations. By doing so, it seeks to provide a robust framework to help organizations assess their cultural readiness and strategically enhance their knowledge environment. Literature Review Knowledge Management infrastructure is commonly conceptualized through models like Becerra-Fernandez's, which identifies three core components: technology, processes, and people. The "people" layer, encompassing culture, is consistently highlighted as the most critical. Knowledge culture is understood as a specific subset of organizational culture. It is defined as a way of organizational life that enables and motivates people to create, share, and utilize knowledge for the benefit and sustained success of the organization. It reflects the organization's values, beliefs, and behaviors concerning knowledge. Scholars such as Davenport and Prusak, and De Long and Fahey, have emphasized the inseparable link between culture and KM, noting that culture dictates what knowledge is valued, defines the relationship between individual and organizational knowledge, and shapes the social interactions through which knowledge is shared. Given its importance, numerous studies have explored the factors influencing knowledge culture, though often in a fragmented, case-specific manner. Research by authors like Pahlavani et al. pointed to factors such as information systems, people, processes, and reward systems. Khairandish and Abtahi identified participation, learning, trust, and knowledge leadership. Studies by Niknam and Jafari, utilizing the Sarros et al. organizational culture profile, found significant correlations with KM and factors like performance orientation, competitiveness, and supportiveness. International research, such as that by Oliver and Kandadi, used case studies to identify ten major factors, including leadership, communication, and reward systems. Al-Alawi et al. highlighted trust, communication, and information systems as critical for knowledge sharing. While these studies provide valuable insights, a comprehensive synthesis that consolidates these findings and provides a generalizable, prioritized list of factors remains absent from the literature. This research addresses this gap by employing a systematic meta-synthesis approach to integrate the findings of previous qualitative and quantitative studies. Methodology This applied research was conducted using a qualitative approach and employed the meta-synthesis method. Meta-synthesis is a systematic approach for integrating findings from multiple qualitative studies to develop a more comprehensive and holistic understanding of a phenomenon. This study specifically followed the seven-step model proposed by Sandelowski and Barroso. The research process began with formulating the primary research question regarding the factors affecting knowledge culture in organizations. Subsequently, a systematic literature review was conducted. Key Persian and English scientific databases were searched using keywords such as "knowledge culture," "knowledge-based culture," "organizational culture in knowledge management," and their Persian equivalents. In the initial screening, 95 studies were selected based on title relevance. After reviewing the abstracts, this number was refined. A final, in-depth content analysis of the full texts resulted in the selection of 24 highly relevant primary studies for the meta-synthesis. From these selected studies, data on the factors influencing knowledge culture, along with study characteristics, were extracted and coded. The extracted codes were then analyzed, compared, and synthesized into broader thematic categories representing the key factors. Finally, to prioritize these factors, they were scored based on three indicators: frequency of occurrence across the studies, recency of the studies, and the factor's direct relevance to knowledge culture, organizational culture, and knowledge management. Results The meta-synthesis of the 24 selected studies led to the identification of 47 distinct factors that influence knowledge culture in organizations. These factors encompass a wide range of organizational dimensions, from leadership and strategy to individual behaviors and technological infrastructure. Examples include leadership, trust, reward systems, communication, organizational structure, learning, and information technology. To determine the most critical factors, each of the 47 factors was scored based on frequency, recency, and relevance. This prioritization process revealed that 11 factors stood out as having the most significant impact. Topping the list with the highest score was Reward Systems, followed closely by Education, Learning, and Empowerment. Supportiveness and Trust secured the next positions, underscoring the importance of a safe and encouraging environment. Creativity and Innovation, along with Communication, formed the next tier of highly influential factors. Performance Orientation, Stability, and Competitiveness followed, all achieving identical scores that reflect their consistent, albeit slightly less frequent, mention in the literature. Leadership, while often considered paramount, ranked tenth in this specific prioritization, suggesting its influence may be channeled through other factors. Finally, Information and Communication Technology, though essential as an enabler, ranked eleventh, confirming the consensus that technology is a necessary but insufficient condition for KM success. Discussion The findings of this meta-synthesis provide a consolidated and prioritized framework for understanding the drivers of knowledge culture. By integrating results from 24 previous studies, it moves beyond single-case insights to offer a more generalizable model. The top-ranked factor, Reward Systems, underscores the fundamental principle that behavior is driven by incentives. Organizations seeking to promote knowledge sharing must align their reward structures to recognize and reinforce such behaviors, moving away from traditional systems that may inadvertently reward knowledge hoarding. The high priority of Education, Learning, and Empowerment highlights that a knowledge culture is not a static state but a dynamic process requiring continuous development. Employees need not only the skills to manage knowledge but also the autonomy and motivation to do so. This is closely linked to Supportiveness, which implies a managerial and organizational environment that encourages experimentation and views mistakes as learning opportunities. Trust, another top-tier factor, is the social glue that enables open communication and sharing, as without it, employees are unlikely to share their valuable knowledge. Interestingly, while Leadership is often cited as paramount, its ranking suggests that its influence might be channeled through more direct mechanisms like creating supportive structures, building trust, and establishing effective reward systems. The position of ICT confirms that the cultural and human elements are the true differentiators in fostering a successful knowledge culture. Conclusion This study successfully identified and prioritized 11 critical factors that significantly influence the development of a knowledge culture in organizations. The findings offer a robust, evidence-based framework for both researchers and practitioners. For managers, this prioritized list provides a clear diagnostic tool. Organizations can assess their current standing on these 11 dimensions to identify strengths and weaknesses, enabling a more focused and strategic approach to fostering a knowledge-conducive environment. By addressing these core factors starting with reward systems, learning opportunities, and building trust organizations can significantly enhance their readiness for successful KM implementation, thereby improving innovation, performance, and competitive advantage. This research contributes to the field by synthesizing fragmented knowledge into a cohesive and prioritized model, offering a foundation for future research to empirically test and refine these relationships in various organizational contexts. Acknowledgment The author would like to thank all the researchers whose valuable work formed the basis of this meta-synthesis, and all those who provided support and guidance throughout this study.  

Abstract Components affecting organizations should always be evaluated and measured so that organizations can advance their development model. The purpose of this study was to investigate the relationship between organizational culture and knowledge management with efficient performance management of the General Administration of Sports and Youth of Alborz Province. The method of this applied research was descriptive-correlation. According to Morgan's sample size table, 127 employees of the General Administration of sports and youth of Alborz province completed standard questionnaires of Denison Organizational Culture (2000), Lawson Knowledge Management (2004), Moghimi and Ramazan Applied Management (2011) randomly. Data analysis was performed by Pearson correlation coefficient method and regression analysis. By calculating the Pearson correlation coefficient, a positive and meaningful relationship between organizational culture and knowledge management with efficient performance management was shown. Also, regression analysis showed that organizational culture and knowledge management predict 0.28% and 0.47% of effective performance management of staff, respectively. Based on the findings of the research, it can be said that the correct application of the components of knowledge management and organizational culture in efficient performance management is very smart and it paves the way for advancing goals and provides management with the tools for growth, success and promotion of the organization.

Abstract The main advantage of organizations today is knowledge. Knowledge is a powerful tool that is developing and changing day by day. A lot of research to identify key success factors and implementation of knowledge management has led to the introduction of the key factors for the success of knowledge management. Contextual factors play a key role in the successful deployment of knowledge management in Organization and determination and assessment of each of these factors for the establishment of knowledge management. This study examined the factors underlying Knowledge Management in Disaster Management Organization of Tehran Municipality. For this purpose, a questionnaire on the status of each of these factors and the importance of knowledge management is developed and graded. Then, using SPSS software and Friedman test these ratings have been achieved.