knowledge flow

Citation is an important element in scientific writing and has a prominent role in the production and dissemination of information. Citation analysis is one of the applications of citation that examines the relationship between citing and cited document and studies the rules governing this relation. Citation analysis of patents is nowadays frequently observed in studies and is an important tool for identifying and analyzing the technical knowledge within patents. This research tries to identify determinants of patent citations by using a survival analysis.

Research method was patent citation analysis. Research population consisted of 25,392 patents in the USPTO database in the Data Processing: Artificial Intelligence (AI) (Category: 706). There were 25392 AI patents in the USPTO database, among them, 13644 patents remained after deleting duplicates. Therefore, the new list, containing 13,644 patents, was saved in a plain text file by patents number, and these file was used to download the by Ravar Premep software. By using this software and using data mining technique, patents were saved in a separated location whit HTML format. Information needed for this analysis was: patent number, filed year, issue date, title, abstract, inventors, assignee, citations, and categories. This information was extract from patents in a comprehensive file. There were about 80 patent applications in the field at the USPTO, with the manually extracted information from the database added to this comprehensive file. To classify patent, first, patent that did not receive any citation in the field of AI were grouped into separate group and then the rest of the patents were divided into 3 groups using Bradford law based on number of citations. Group 1: Patents that have received at least 22 citations (412 patents).Group 2: Patent applications that have received at least 9 and at most 21 citations (1123 patents). Group 3: Patents that have received at least 1 and up to 8 citations (4975 patents). Group 4: Patent Letters That Did Not Receive Any Citation (7134 patents). In this study 8922 inventors were retrieved as the first inventors for 13,644 patents. Since the classification of the first inventors did not fit well with any of the conventional classification methods in scientometrics, the inventors were divided into three groups according to the number of inventions. Inventors with more than 20 patents in the first group, inventors with 11 to 20 inventions in the second group and inventors with 10 inventions and fewer in the third group. In the field of AI, 2898 assignees hold 13644 patents. Bradford law was used to classify assignees in terms of frequency of inventions because of their high fit to the data. According to this method, assignees were classified into three groups in terms of their ability to produce patents. First Class (Strong): assignees who have produced at least 87 patents (19 assignees). Second Class (Medium): assignees who have produced at least 7 patents (233 assignees). Third Class (Poor): Proprietors who have produced at least 1 patent (2646 assignees). Bradford law was also used to classify assignees in terms of citation. Since in this method the minimum number is equal to one, assignees whose patents did not receive any citations were placed in a separate group (Group 4) and patent holders whose patents received at least one patent. They were classified into 3 groups according to Bradford method. Cox and Kaplan-Meier regression were used to analyze the data.

The research findings showed that of the 6749 patents that received first citation, in the first two years, the probability of citing each patent was less than 50 percent, and the probability of being cited increased over time. So that probability has risen to over 90% after 84 months. Kaplan-Meier test results showed that it takes between 38 and 40 months on average to a patent obtain first citation in the field of AI. The Kaplan-Meier test results in survival analysis showed that one year after a patent first was cited, the probability of being cited for the ninth time was 2.2%, and that probability increased over time. The findings also showed that on average, a patent may be cited for the ninth time between 69 and 74 months after receiving its first citation. Kaplan-Meier test showed that in the first 4 months after receiving the ninth citation, the probability of receiving the 22th citation for patent applications was zero, and then the probability increased. Also the finding showed that of the 6749 patents reviewed  citation for the first time, in the first 2 years, the probability of citing each patent was less than 50%, and the probability of being cited increased over time. So the probability has risen to over 90% after 84 months.

The results of the Cox test showed that, at the significant level of 0.05, inventors and assignees were influenced the productivity and receiving citation of patents. The results showed that the frequency distribution of citations received by patents based on the first inventor and proprietor complies with Bradford’s scattering law. The results showed that the percentage of cited patents increased logarithmically over time. In other words, after a few years, the chances of citing a patent are reduced to a fixed amount. The results of the relationship between the power of first inventors both in terms of productivity and receiving citation showed that, the more the first inventors had a patent or citation, the shorter length of time need to be cited for the first time. The results of Cox test showed that at the significant level of 0.05 percent, inventors and assignees were influential in productivity and receiving citation. In other words, the chance of getting the first citation of assignees whose first inventor is in the first group (strong group) is 1.926 times higher than the patent of their first inventor in the third group. The results also showed that the probability of receiving the first citation for patents whose first inventors were in the first group was 1.925 times higher than that of the third group. Also those patent that the inventors where in second groups 1.44 times higher than of the third group. The results also showed that assignees were influenced by both the time they produced the invention and the citation received. The more assignees have had more or patents or citations, the less time it takes for them to be cited for the first time. The results also showed that the strongest assignees groups were more likely to receive their first citation at the same time interval than the weaker assignees. It may be argued that the role of countries in citing to patent applications is not very influential, but other factors are influential, one of which being the relevance of other patents that the inventor may cited or the evaluator of that role. And the type of citations in patent differs from those based on articles and other scientific documents.

The purpose of this research was to identify and prioritize the aspects of knowledge audit in academic libraries. 

The method of this research is descriptive-survey. The statistical population of the research includes the final managers and managers of central library departments of universities affiliated to the Ministry of Science, Research and Technology. The sampling method of the libraries, considering their dispersion in the whole country, is first by random cluster sampling method and then by targeted method of the central library of the largest university in the center of the province. Finally, the number of 279 final managers and department managers of central libraries of universities affiliated to the Ministry of Science, Research and Technology were selected as the statistical sample of the research. The knowledge audit questionnaire has been compiled with 99 items and includes 14 dimensions of vision and organizational goals (7 items), analysis of knowledge data and information (6 items), measurement of explicit and tacit knowledge (6 items), drawing a knowledge map. (6 items), identifying strategic elements of the organization (8 items), analyzing the gap between existing and desired knowledge (5 items), preparing the organization (6 items), identifying the knowledge audit process (7 items), forming a knowledge audit working group (8 items) ), analysis of knowledge flow (12 items), identification of valuable assets of the organization (6 items), evaluation of information and knowledge (6 items), measurement of current knowledge health (9 items) and knowledge application analysis (7 items). 

Based on the results of the research, the components of knowledge flow analysis (4.57), measuring the health of current knowledge (4.12), forming a knowledge audit working group (3.68) and identifying the strategic elements of the organization (3.12) have a higher average rating than others. The indicators are in terms of the possibility of occurrence and influence in the knowledge audit of academic libraries and have a more favorable situation in academic libraries, and in the same way, other indicators are placed in the next ranks. 

Based on the results of the research, it was found that managers can benefit from knowledge audit in improving the quality of university library services. By applying knowledge audit, managers review, examine, measure and evaluate the intellectual assets of the organization and evaluate the knowledge reserves and flow of the entire organization.

Content analysis of journals by identifying the characteristics of the information recorded in the articles helps the editors of the journals to identify the strengths and weaknesses of the journal. The objective of this research is to study the knowledge and content flow of articles in the journal of accounting knowledge as one of the most prestigious scientific publications in the field of accounting knowledge in Iran from the beginning of 2005 to the end of 2019.

This research is a scientometrics study and using the content analysis method (quantitative approach). The population of the study consisted of all the articles published in the journal that were all selected as a statistical sample. The research data were also collected using a checklist tool and statistical analysis using Excel software.

Findings of the research show that in 285 articles published during these years, 696 authors have contributed, of which MA degree with 34% and assistant professors with 30% are at the top of the table are the authors of this journal. Among the universities and educational institutions, Shiraz University is ranked first with 25 articles, and the University of Tehran is ranked second with 34 articles. In terms of topic orientation, 83% of the publications are in the field of financial accounting and auditing with 10% in the next rank. From the total 8179 references cited in the articles, 73% were in English and 27% in Persian.

Nowadays, one of the key issues in enterprise 2.0 is how to use the innovative knowledge of users and customers systematically and purposely, and also and benefit from the knowledge sharing into organizational processes. One effective approach is to make use of an open innovation approach, leading to improvement of knowledge flows into the organization. However, to date, specific knowledge management architecture for managing such knowledge flows based on the open innovation approach has not been studied yet at enterprise 2.0. In this research a new campestral architecture is introduced for knowledge management in enterprise 2.0 that is based on open innovation approach. For this purpose, grounded theory, a qualitative inductive research has been used with emphasis on content analysis of documents and related research studies. The results of content analysis show that the key intersection between knowledge management sharing, enterprise 2.0 and open innovation is knowledge flow management. Therefore, using the characteristics of in-flow and out-flow of knowledge, a conceptual architecture composed of five different layers with seventeen components is proposed. These layers are the logic of business, interface, process and flow of knowledge, infrastructure, and context. In the proposed architecture, each layer has some components that are connected to each other and some of them are connected to the components of other layers as well. The proposed architecture is also compared with two similar architectures in this context as well.

Knowledge management is used in the organization for guidance on the process of creating, disseminating and applying knowledge for organizational purposes. Understanding the weaknesses of/and barriers to the success factors in the flow of knowledge in the organization can affect the knowledge management process. Therefore, the present study deals with the identifying and prioritizing the barriers to knowledge flow in university libraries based on the maturity of knowledge management model taken from the American Productivity and Quality Center.

The present study is a survey-analytical study. The statistical population included 184 managers of central libraries of some universities, all included as the research census. Data were collected through a researcher-made questionnaire.

The barriers to knowledge flow are ranked in priority order: Management factors with a mean rate of 5.72 in the first rank, the source of knowledge with a mean rate of 5.7 in the second rank, organizational factors with a mean rate of 4.67 in the third rank, time factor with a mean rate of 4.37 in the fourth rank, communication channel with a mean rate of .22 in the fifth rank, individual factors with a mean rate of 4.21 in the sixth rank, technical factors with a mean rate of 3.92 in the seventh rank, and knowledge characteristics with a mean rate of 3.72 in the eighth rank. In terms of ranking the barriers of the dimensions of the flow of knowledge with the level of maturity of knowledge management the barriers are the level of innovation, the level of optimization, the level of standardization, the level of development and the level of beginning, respectively.

Academic libraries face the barriers and bottlenecks in the main steps of the knowledge management cycle. Although these obstacles exist in the entire dimensions of the flow of knowledge, the barriers are more tangible in the management dimension. Therefore, attention to effective leadership indicators, the right styles of management, organizational support, and attention to knowledge workers are necessary to eliminate these barriers.