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While private entrepreneurial activity has been at the core of entrepreneurship, nonprofit ventures still need to be explored in the literature. Using norm-activation theory (NAT) and resource-based view (RBV) lenses, we explore the antecedents of undertaking nonprofit entrepreneurial activity. By examining 8544 entrepreneurs' decisions about the type of entrepreneurship to engage in, we find that not all human capital has a similar influence on people's decisions regarding the types of formation of their venture. The results suggest that entrepreneurs' job-related experiences and social orientation are significantly linked to nonprofit entrepreneurship. The results of our study contribute to the human capital theory by demonstrating that people's value influences how they use their knowledge resources. Plain English Summary: A combination of work experience and social orientation is at the heart of the decision to engage in nonprofit entrepreneurship, not just social orientation. Understanding the antecedent of engagement in nonprofit entrepreneurship is important since nonprofit organizations combine two competing organizational objectives – creating social values and economic wealth. The nonprofit sector presents an interesting alternative context since the financial incentive is crucial for engaging in entrepreneurial activity in the for-profit context. In this paper, we supplement the Resource-Based View (RBV) literature by incorporating human capital and the norm-activation theory (NAT) framework to investigate what influences an individual's decision to engage in nonprofit entrepreneurship. This framework enables us to investigate the influence of the combination of resources in the possession of entrepreneurs and the values that are important to them are used to engage in nonprofit entrepreneurship. [ABSTRACT FROM AUTHOR]

Collaboration is challenging in highway building projects since there are always a number of stakeholders involved, each with different responsibilities, backgrounds, objectives, and competing interests. The basis for addressing collaboration problems in building projects is knowledge. Knowledge management (KM) can benefit greatly from the distinctive characteristics of BIM (building information modeling). Therefore, the purpose of this study is to investigate knowledge collaboration in highway construction projects that is enabled by BIM. It first explores the motivations behind and difficulties with using BIM for knowledge-based collaboration. Next, it looks for possible ways to overcome those difficulties. It employs a large highway project as a study case in China. It uses in-depth interviews with a range of contractors working on this project to comprehend the difficulties they face in working together and investigate ways that BIM-supported KM can help stakeholders collaborate more effectively. Ultimately, it creates a conceptual model for knowledge-driven collaborative management within the BIM environment, offering both a theoretical framework and useful direction for knowledge-based collaboration amongst various stakeholders. The study explores the advantages of BIM characteristics in knowledge collaboration, which provides empirical evidence for the transformation from traditional IT-based knowledge collaboration to BIM-based knowledge collaboration in large and complex highway projects. [ABSTRACT FROM AUTHOR]

Purpose: This research is an empirical study that addresses whether knowledge resources impact on, or do not impact on, innovation development and if this impact is mediated by dynamic capabilities in the medical tourism sector in Mashhad city, Iran. Design/methodology/approach: A quantitative research methodology was applied and questionnaires were used for data collection in this study. A total of 108 questionnaires were collected of which 102 questionnaires were valid. Data were analyzed using structural equation modelling technique. Findings: Empirical evidence obtained from the study reveals that the dynamic capability of learning plays a significant role in transforming knowledge resources into innovation in the medical tourism sector. The mediating role of coordinating capability in the relationship between explicit and tacit knowledge and innovation is considerable and it influences human capital, as well. Sensing capability also exhibits some degree of a mediating role; however, integrating capability is not influential and its role in transforming explicit knowledge to innovation is rejected. Originality/value: Most studies on innovation in medical tourism focused on market and its typology, and neglected the role of knowledge resources and dynamic capabilities. The current study bridges this gap and thus contributes to the scientific literature. [ABSTRACT FROM AUTHOR]

Copyright of Iskolakultúra is the property of University of Szeged, Faculty of Arts & Social Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: In recent decades, web search engines have become one of the most prominent and essential tools for accessing information in today's interconnected world. With the increasing volume of information available on the web, the demand for locating and accessing relevant and meaningful information has also risen. Traditional search engines typically retrieve results based on keyword matching and the number of similar entries in the texts. This method often leads to undesirable and irrelevant results. These problems are even more pronounced in Persian and Arabic due to the complex grammar of these languages, which is not machine-readable. The aim of this research is to review and present solutions for semantic search and retrieval of Persian and Arabic texts. Method: This research is a content analysis study, and the library method was used to collect data. To collect information and access the required resources, various sources were used, including scientific articles, books, theses, and reports. For collecting Persian articles, sources, and for collecting English articles, sources with publication dates from 2020 onwards were used. The content analysis method was utilized to analyze the collected data. By employing data analysis and interpretation methods, the results of previous studies were reviewed and evaluated alongside the new findings of the research. This evaluation involved identifying the issues and constraints of current semantic search engines and offering suggestions for enhancement. Findings: In Persian and Arabic text semantic search and information retrieval research, methods based on text semantic analysis and processing using pre-trained language models, clustering algorithms like K-Means, and knowledge resources such as knowledge graphs are employed. Additionally, the dataset, the utilization of models and algorithms, and the method of semantic search and retrieval between words all influence the system's performance and accuracy. According to the findings of numerous studies, there is a wide range of methods and algorithms available for text semantic search and retrieval, each of which can produce different results. These findings demonstrate that each of the methods used has the ability to retrieve the semantic meaning of texts and varies in terms of search accuracy capabilities. An examination of the research findings reveals that some methods outperform others. These methods demonstrate strong semantic search capabilities by employing various techniques and algorithms such as topic analysis, neural networks, vector representations, and more. On the other hand, the appropriate method should be chosen based on the nature of the problem and the characteristics of the data. Each problem and dataset may have its own unique requirements. Selecting the best method and adjusting its parameters is critical for optimal performance. Conclusion: Each of the presented methods offers unique solutions for the issues and linguistic characteristics of the two languages, Persian and Arabic. Additionally, various methods utilizepre-trained language models like BERT, clustering algorithms such as K-Means, and knowledge resource-based retrieval systems like knowledge graphs. The presented solutions also utilize specific datasets and resources for training and evaluation. The differences in the dataset and how these models and algorithms are used and configured are critical. Some methods perform information retrieval based on meaning and semantic relationships between words, while others use keyword and root-based methods. This variation in the search and retrieval method can impact the system's performance and accuracy. Each method has a different performance and accuracy in retrieving information, which is attributed to the varied ways in which models, algorithms, and data sources are utilized.

The processes of globalisation, the ongoing threat of the COVID-19 epidemic, the continuing war in Ukraine, and constantly emerging new technological solutions require organisations to adapt to changes constantly. Meanwhile, implemented business process management (BPM) often fails to integrate processes and knowledge resources. The awareness of the IT systems’ role in management processes is still lacking. These premises influenced the implementation of the main research goal to identify the approach of Polish private and public enterprises and various industries to the BPM integration with knowledge management (MK) in the context of using new information technologies. The presented research results justify the usefulness of building relationships between the process and knowledge resources under dynamically changing conditions using IT systems. The diagnostic survey results confirmed the key importance of developing such BPM and MK elements as evidence-based decisions, strategic goals, measurement systems, databases, digital innovations, and IT use for data processing. The presented material can support managers of various organisation types in decision-making processes by fully understanding the IT systems’ role and potential in process and knowledge management. Also, the article’s implications are a source of guidelines, helping organisations to implement management systems based on modern technologies. The value of the publication is a wide range of respondents: 107 large, medium, small, and micro-enterprises operating in Poland. The article’s research results also concern economic activities such as production, logistics, transport, banking, insurance, IT, telecommunications/ media, public administration, healthcare/pharmaceuticals, consulting, energy, and construction.

Under the guidance of the new vocational education method of artificial intelligence, this paper divides the skill-based society into skill-based organizations, and constructs a knowledge dynamic equilibrium model based on superimposed knowledge fields. The knowledge-explicit module of skill-based talent flow and the external dynamic equilibrium module are integrated to achieve the evolutionary modeling of knowledge resources in skill-based organizations. Based on the discussion of the new vocational education law, the characteristic models of intellectual resource development, knowledge dynamic growth, group evolution and talent motivation in skill-based organizations are proposed respectively. The simulation analysis of the knowledge dynamic equilibrium network is combined with the analysis of influencing factors to inspire the education of higher vocational colleges and universities under the new vocational education method. As measured by the data, the average path length mean values of the intra-organizational knowledge network when N=160, 260, 330 are 2.2761, 2.4437 and 2.5394, respectively, which indicates that skilled talents have a strong willingness to interact with each other and share knowledge. The construction of skill-based organizations should fully create a strong environment for talent exchange and focus on cultivating students’ willingness and ability to communicate in vocational education.

Purpose: In recent decades, web search engines have become one of the most prominent and essential tools for accessing information in today's interconnected world. With the increasing volume of information available on the web, the demand for locating and accessing relevant and meaningful information has also risen. Traditional search engines typically retrieve results based on keyword matching and the number of similar entries in the texts. This method often leads to undesirable and irrelevant results. These problems are even more pronounced in Persian and Arabic due to the complex grammar of these languages, which is not machine-readable. The aim of this research is to review and present solutions for semantic search and retrieval of Persian and Arabic texts. Method: This research is a content analysis study, and the library method was used to collect data. To collect information and access the required resources, various sources were used, including scientific articles, books, theses, and reports. For collecting Persian articles, sources, and for collecting English articles, sources with publication dates from 2020 onwards were used. The content analysis method was utilized to analyze the collected data. By employing data analysis and interpretation methods, the results of previous studies were reviewed and evaluated alongside the new findings of the research. This evaluation involved identifying the issues and constraints of current semantic search engines and offering suggestions for enhancement. Findings: In Persian and Arabic text semantic search and information retrieval research, methods based on text semantic analysis and processing using pre-trained language models, clustering algorithms like K-Means, and knowledge resources such as knowledge graphs are employed. Additionally, the dataset, the utilization of models and algorithms, and the method of semantic search and retrieval between words all influence the system's performance and accuracy. According to the findings of numerous studies, there is a wide range of methods and algorithms available for text semantic search and retrieval, each of which can produce different results. These findings demonstrate that each of the methods used has the ability to retrieve the semantic meaning of texts and varies in terms of search accuracy capabilities. An examination of the research findings reveals that some methods outperform others. These methods demonstrate strong semantic search capabilities by employing various techniques and algorithms such as topic analysis, neural networks, vector representations, and more. On the other hand, the appropriate method should be chosen based on the nature of the problem and the characteristics of the data. Each problem and dataset may have its own unique requirements. Selecting the best method and adjusting its parameters is critical for optimal performance. Conclusion: Each of the presented methods offers unique solutions for the issues and linguistic characteristics of the two languages, Persian and Arabic. Additionally, various methods utilize pre-trained language models like BERT, clustering algorithms such as K-Means, and knowledge resource-based retrieval systems like knowledge graphs. The presented solutions also utilize specific datasets and resources for training and evaluation. The differences in the dataset and how these models and algorithms are used and configured are critical. Some methods perform information retrieval based on meaning and semantic relationships between words, while others use keyword and root-based methods. This variation in the search and retrieval method can impact the system's performance and accuracy. Each method has a different performance and accuracy in retrieving information, which is attributed to the varied ways in which models, algorithms, and data sources are utilized. [ABSTRACT FROM AUTHOR]

Copyright of Education of Economists & Managers / Edukacja Ekonomistow i Menedzerow is the property of Warsaw School of Economics, Department of Human Capital Development and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

One of the basic tasks of a business strategy is to ensure, among other things, the maximum use of all of an enterprise's resources. In the 21st century, one of the most important resources with a continuously increasing influence on an enterprise's results is the enterprise's knowledge. In order to make its acquisition and use as cost-effective as possible, the knowledge strategy of an enterprise must be defined. The core of this paper is the description of a new methodology for creating such a strategy. This methodology has been designed to enable both the easiest possible implementation in practical conditions and the most effective use of the knowledge strategy in supporting the creation and implementation of business strategy. [ABSTRACT FROM AUTHOR]

This paper investigates the Arabic verbal humorous comments pertaining to COVID-19 on social media. The main objectives of the paper are to identify the distinct categories that are highlighted in those comments disseminated between March and September 2020, on the AlMamlaka and Roya Jordanian Facebook accounts. Additionally, the study examines the claim of Attardo and Raskins's (1991) that the "target" is an optional Knowledge Resource in the General Theory of Verbal Humor. The research design employed in this study is descriptive qualitative. The researchers conducted a thematic analysis to analyze 15 comments, applying the General Theory of Verbal Humor of Attardo and Raskin (1991). The analysis revealed eight emerging categories: governmental, gender, COVID-19, lockdown, behavior, conspiracy, geographical, and facemask jokes. The study found that humorous comments conform to the six Knowledge Resources of the General Theory of Verbal Humor. The most prominent logical mechanism used in the comments was irony and sarcasm, enabling Jordanians to shed light on hidden issues to express their reactions and feelings. The study also found that identifying the target in a humorous comment is crucial in determining the various categories of humorous comments. The research opens avenues for further exploration into the utilization and interpretation of humor in diverse cultural settings, during other natural disasters, and its impact on understanding humorous content. [ABSTRACT FROM AUTHOR]

Collaborative management of knowledge resources is a particularly important issue in the context of collaborative development of vocational education since it can increase utilization of knowledge resources, narrow knowledge gap, promote educational equity, and support the innovation and collaboration of vocational education. However, currently available studies and methods are quite deficient in the aspect of knowledge attribute regulation, such as the difficulty in meeting requirements for different-type knowledge resources, the ignorance of the dynamic feature of knowledge resources, and the insufficient consideration of knowledge attributes. To solve these matters, this study aims to discuss the importance of collaborative management of knowledge resources in a backdrop of the collaborative development of vocational education, with special attention on the key role of knowledge attribute regulation in collaborative management of knowledge resources. In the paper, a collaborative knowledge resource management evolution model was built to reveal the dynamic evolution process of the collaborative management of knowledge resources, so as to provide theoretical evidences for the decision-making of knowledge attribute regulation. On this basis, the paper further proposed a decision-making method of knowledge attribute regulation for the collaborative management of knowledge resources, in the hopes of realizing efficient collaborative management of knowledge resources and promoting the collaborative development of vocational education. [ABSTRACT FROM AUTHOR]

Determining preservice teachers' competence in proportional reasoning is a very complex task, and existing research methods do not provide effective tools in doing that. This study describes an interview structure and application of it in determining preservice teachers' competence in proportional reasoning. The interview structure consists of in-depth questioning and cognitive conflicts and is situated in the knowledge-in-pieces epistemological perspective. The preservice teachers' competence in proportional reasoning was determined by examining the knowledge resources that they drew upon when reasoning about proportional and nonproportional situations. Semi-structured interviews were conducted with six preservice teachers to demonstrate the effectiveness of the interview structure. The case analysis indicated the preservice teachers' attention to the various fine-grained knowledge resources. However, they mostly drew upon the qualitative relationships, cross-multiplication, and across-multiplication. The preservice teachers' over-attention to these three knowledge resources hindered their ability to distinguish proportional relationships from nonproportional relationships. Furthermore, the productivity of knowledge resources was easily influenced by the relationships presented in problems and participants' past learning experiences. Implications of the application of the interview structure in teacher education programs and further research suggestions are discussed. [ABSTRACT FROM AUTHOR]

The study is dedicated to the analytical aspects of the prospects of integrating knowledge resources and infor-mation technologies into the system of professional training for cadets at military higher education institutions. An analysis of current trends in the development of the military education sector requiring optimization through the integration of knowledge and information technologies is conducted. The concept of "knowledge resource" is elucidated, and the value of knowledge resources in the training of military personnel is characterized. The main components of knowledge resources in the system of professional training for future military personnel are identified, including educational programs, educational materials (sylla- bi, textbooks, manuals, lecture materials, presentations, recommendations for independent work and seminar classes), human resources (scientific and pedagogical staff conducting formal training for military personnel, possessing sufficient knowledge and experience in the military field), informal and non-formal forms of learning (webinars, seminars, conferences), knowledge assessment system (tests, quizzes, practical assignments, etc.), video and audio materials. The feasibility of implementing in- formation technologies in the military professional education system is substantiated. The research reveals the impact of an integrated approach on the activity, motivation, and adaptability of cadets to modern challenges and threats. The distinction between information technologies and knowledge resources is justified, highlighting that information technologies are tools for processing and transmitting information, while knowledge resources are the information used for acquiring knowledge and solving tasks. Information technologies can assist in accessing knowledge resources, facilitating their processing, and rapid dissemination. The obtained results can serve as a basis for further development of educational programs and strategies for the development of military education aimed at preparing future military leaders. [ABSTRACT FROM AUTHOR]

Drawing on the resource-based view of the firm, and counter to the mainstream literature, we propose and empirically show that two knowledge resources can be substitutive (rather than complementary) for each other. Our test focuses on the interplay between managers' and workers' knowledge stock, considered as knowledge resources that firms can apply to improve innovation. We hypothesise a mutually exclusive effect of managerial experience (managers' knowledge stock) and labour skills (workers' knowledge stock) on product innovation. Drawing on the most recent waves of the World Bank Enterprise Survey (WBES), we construct a cross-sectional sample of 2,725 manufacturing firms. We used binary choice model to test the proposed effects. The results show negative interaction between labour skills and managers' experience in determining the probability to achieve product innovation, putting the knowledge resource complementarity hypothesis into question, and opening an academic debate that will have implications for knowledge management practice. [ABSTRACT FROM AUTHOR]

Numerous studies emphasise the contribution of inquiry-based learning approaches to positive learning outcomes for students; however, in this study, we explore how a scientific methods assignment may qualify as a profession-oriented, inquiry-based learning approach in teacher education. The paper presents analysis of student teachers' reports on a scientific methods assignment completed during their fifth school placement. The student teachers were each required to conduct a focus group interview with a group of pupils. The overall aim of the assignment was to integrate aspects of inquiry-based learning and a profession-oriented approach. Our analysis demonstrates that the scientific methods assignment qualifies in some ways as a profession-oriented, inquiry-based learning assignment. However, several aspects of the assignment need to be improved and further developed to optimise its potential. The paper is concluded with some suggestions for further developments. [ABSTRACT FROM AUTHOR]

The computation of natural language enables a suitable transmission through the universe by retrieving the correct sense of each word. A word may be monosemous or polysemous. The use of polysemous words in an appropriate context plays a critical role in communication. Over the last 2 decades, a significant amount of research has been done for automatically solving the correct sense of a polysemous word in the context of word sense disambiguation. A word sense disambiguation algorithm identifies the proper sense of a polysemous word by analysing the contextual data. Nevertheless, there is a gap in the contemporary literature regarding the availability of datasets in Asian languages, especially Bengali. Therefore, in this work, we have presented a dataset comprising hundred Bengali polysemous words. Each word in this dataset consists of three or four disjoint senses, and each sense comprises ten paragraphs. Each paragraph describes the sense of a particular polysemous word. We have performed statistical analysis on the basis of seven relevant and important characteristics. A general framework has also been presented for training and testing with possible guidelines for performance analysis. A baseline strategy has been introduced based on four feature sets. Finally, a set of experiments have been performed to analyse the system performance. [ABSTRACT FROM AUTHOR]

The explosive growth and widespread accessibility of medical information on the Internet have led to a surge of research activity in a wide range of scientific communities including health informatics and information retrieval (IR). One of the common concerns of this research, across these disciplines, is how to design either clinical decision support systems or medical search engines capable of providing adequate support for both novices (e.g., patients and their next-of-kin) and experts (e.g., physicians, clinicians) tackling complex tasks (e.g., search for diagnosis, search for a treatment). However, despite the significant multi-disciplinary research advances, current medical search systems exhibit lowlevels of performance. This survey provides an overview of the state of the art in the disciplines of IR and health informatics, and bridging these disciplines shows how semantic search techniques can facilitate medical IR. First, we will give a broad picture of semantic search and medical IR and then highlight the major scientific challenges. Second, focusing on the semantic gap challenge, we will discuss representative state-of-the-art work related to feature-based as well as semanticbased representation and matching models that supportmedical search systems. In addition to seminal works, we will present recent works that rely on research advancements in deep learning. Third, we make a thorough cross-model analysis and provide some findings and lessons learned. Finally, we discuss some open issues and possible promising directions for future research trends. [ABSTRACT FROM AUTHOR]

Teachers' knowledge of proportional reasoning is important, particularly in the middle grades in the USA. This exploratory study investigated 32 teachers' use of knowledge resources in two mathematically similar tasks (one a paper and pencil task, the other a dynamic task) around proportional reasoning. The two tasks invoked different knowledge resources by the same teachers. Results suggest questions to the field around how we access or invoke teacher knowledge and the need to more purposefully explore the potential benefits of using a dynamic task to invoke knowledge resources. [ABSTRACT FROM AUTHOR]

In high-technology industries, employee spinouts have increasingly been identified as attractive targets for acquisitions. Yet employee spinouts may originate from different knowledge contexts. This study adopts a resource base perspective to examine the impact of both the knowledge heritage and the product strategy of spinouts originating from different contexts (i.e. from the same industry or from a related downstream industry) on the potential to be acquired by firms in the same industry or in related industries. Our findings, based on data from the semiconductor industry and its related downstream industries, show that spinouts from firms in a focal industry represent appealing targets for a broad range of buyer firms from within the focal industry or from related, downstream industries, independent of their product strategy at entry. By contrast, spinouts from downstream, user industries that enter into an upstream industry, tend to appeal to a more limited set of buyers. Our study suggests that managers and academics should consider the acquisition of spinouts whose founders have origins in related industries as a channel to access critical knowledge from upstream or downstream contexts. Yet because many of the critical knowledge resources that spinouts possess are embodied in their founders, such acquisitions also require careful management of personnel decisions post-acquisition. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to develop a complementarity view of the heterogeneous knowledge archetypes. The study first employed a psycho-cognitive perspective to provide theoretical backing for the emergence of knowledge types. Then, a complementarity methodology was employed to synthesize the co-created, heterogeneous knowledge resources into an operation-friendly model. The study shows that, by using the psycho-cognitive lens, the explicit, implicit, and tacit knowledge types are co-created. And that knowledge is actually created as a bundle of heterogeneous but complimentary resources. The complementary view is built off the assumption that a bundle of resources grants a higher value and that a separate use of resource may produce zero value. This paper highlights the capability of the knowledge-as-a-bundle to offer higher values to organizations when deployed jointly rather than the separate use propagated with the dichotomous view of the knowledge resources (types). This paper, therefore, adds, to the existing literature in the knowledge management field, a complementarity lens of knowledge typologies. [ABSTRACT FROM AUTHOR]

According to the Bible, a disrespectful use of God's name may be perceived as blasphemous or at least profane. In order to avoid the risk of violating that religious and linguistic taboo, sensitive language users representing the Judeo-Christian world have developed various euphemistic ways of referring to God. On the other hand, however, jokes that include God's name and laugh at him are not uncommon in Western culture. Assuming a linguistic-semantic perspective, the present paper examines a group of "God jokes", which are jokes that contain God's name and were tagged with the word god in the collection entitled "The best god jokes", published on the website unijokes.com. The aim of the study is to identify the place and role of God's name in the semantic script of "God jokes", or in other words, to check "how much" God there really is in the text of jokes that are supposed to laugh at God, potentially violating the religious taboo. Following the General Theory of Verbal Humor (Raskin and Attardo 1991; Attardo 2001), the use of God's name is analyzed in the knowledge resources of the semantic script of a joke: the target, the script opposition, the situation, the narration, and the language. [ABSTRACT FROM AUTHOR]

Objectives: One of the major duties of nurses is proper medication administration while maintaining patient safety, which requires sufficient knowledge and practice. Any gaps in knowledge used by nurses can lead to irreversible injury or death of the patient. This study is aimed to determine and compare the pharmacology knowledge and performance of nurses and nursing students in using the information resources in pediatrics wards., Method: This descriptive observational study was performed on 300 nurses and nursing students. Sources of knowledge and performance of nurses and nursing students were analyzed with researcher-made tools to determine their pharmaceutical knowledge, sources of knowledge, and attitudes by independent t-test, chi-square, one-way analysis of variance, Pearson, and Spearman tests., Result: Three hundred questionnaires were examined. The clinical experience of nurses and students was their most important source of information in drug challenges for 33.7% of the participants. About 24.6% of nurses obtained the required information from specialized books on pediatric medicine. About 17.1% of the participants attained their knowledge from multiple sources (e.g. various available sources such as the Internet, pharmacy books, software, and their experiences and colleagues), while electronic sources and the Internet were the sources of knowledge for 15.5% and 7.7% of the nurses, respectively. Concerning nursing students, 6.3% used books, 41.7% considered colleagues (clinical experiences), 20.8% employed electronic resources, 22.8% used the Internet, and 9.1% relied on multiple sources. There were significant differences in the knowledge and performance of the nurses based on their source of pharmacological knowledge (P < 0.05)., Conclusion: Most of the resources used in the hospital are not up-to-date and evidence-base, and the majority of nurses tend to rely on their clinical experience or their collegues information for medication administration rather than reading books or searching for up-to-date approaches and information. Nursing students also trust nurses' clinical experiences more than other sources provided for them including books and Internet. Some action should be taken by the managers for boosting the nurses' tendency for using up-to-date information resources., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2022.)