درخت حوزه‌های تخصصی

The present study was aimed at providing a smart model of professional development of second high school principals in Tehran province. This study was based on  a combined strategy of successive explorations. The research method was qualitative case study and in the form of content analysis. The selection of the sample in the qualitative section was made by a targeted sampling method with a criterion-based technique. The sample size was up to 20 people emerging in order. The data collection tool consisted of two sections, semi-structural interviews in the field and a review of upstream documents and training documents in the library section, and data analysis in the qualitative section based on the content analysis using  ATLASTI software. The quality of this study was observed, from the point of view of experts , and  6 dimensions and 29 components were considered in the professional development of second high school principals. The identified dimensions are educational, research, service, ethical, cultural, and executive. This is not  only an evaluation of the candidates for the second-high school administrative candidates in the field, but also the role of a way to promote the material and the competence of these scholars. Due to the limited resources of some organizations, it is not possible to set up an office or deputy for the subject of digital transformation.

By presenting the possibility of automatic reasoning by machines, semantic technology provides a new method for managing data and utilizing artificial intelligence based on formal and explicit patterns; emergence of these technologies in e-learning has enabled the development of next-generation learning and has created semantic-rich learning environments; So that, some researchers refer to this phenomenon as the next big wave in educational technologies. Despite the undeniable importance of this phenomenon and the many studies that have been done on semantic-rich learning environments, there is no combined knowledge that can demonstrate the evolved nature of these environments and related theories. the research, with the aim of extracting repetitive themes in the field of semantic-rich learning and expressing the basic opportunities and challenges in this field, systematically reviews the articles published in the WOS database, during the years 2000 to 2020 using the paradigm funnel technique; and has used Nvivo software in document analysis and theme extraction.

Purpose: This study analyzes the activities of top Times researchers in the field of political science with an emphasis on examining the ResearchGate network.  Method: This study opted for altmetric approach. Two research communities have been surveyed. The number of 145 faculty members affiliated to the top 10 universities of the Times 2021 in the field of political science was stratified sampling randomly, selected. Participation in the ResearchGate network was examined, for them. For the attendees, the indicators of citations, RG-score, and reads were extracted and compared. For the top 15 best Times scientific institutes, the RG scores per member and publication per member were calculated and compared. Correlation between Times Ranking and ResearchGate's indicators, done too. For data analysis, LibreOfficeCalc, and SPSS22 were exploited.  Findings: Only, 39% of all faculty members belong to the best Times centers in the field of political science, have seen by registration in the ResearchGate network. For 57 registered individuals, there was a significant correlation between ResearchGate's indicators with each other. But there was no significant relationship between the Times rankings and the mentioned indicators, except for the reads (P-value = 0.018) with a weak reverse correlation (Spearman coefficient= - 0.314). Furthermore, comparative analysis for the top 15 Times institutes had done from standpoint of RG-Score, too.  Originality: The Correlation relationship between Times rank and ResearchGate’s indicators in the field of political science, in addition, the participation of faculty members of the best scientific centers in this mentioned field had not been done yet.

Although there have been many publications on the subject of CKM, particularly in recent years, not much research has been conducted on the performance analysis and science maps of these studies. To overcome this constraint, a bibliometric study of the current body of academic literature on CKM is conducted the study's methodology involved conducting a bibliometric examination of publications indexed in the Web of Science (WoS) and Scopus from 1992 to 2022. The search strategy employed for this review was guided by the PRISMA standards, resulting in 255 papers being located during the search procedure. To visualize and quantitatively analyze bibliometric networks the VOS viewer tool and the bibliometric R-package were utilized. The descriptive statistics reveal a significant increase in CKM studies since 2011, with the majority of publications occurring in 2021, 2019, and 2013, respectively. China, Iran, and the United States are the countries with the highest number of publications, respectively. The “JOURNAL OF KNOWLEDGE MANAGEMENT” is a core journal in this field, and “Hussin A” is the most prolific author in this scientific domain. The results of the thematic analysis indicate that “co-creation” has gained popularity in recent years, and over the past seven years, “knowledge sharing” and “customer knowledge development” have replaced “market orientation” and “customer relations”, respectively.  Additionally, the co-word analysis of the author's keywords identified six clusters, including “Knowledge Management and Market Orientation,” “Knowledge Sharing and Co-Creation,” “CKM and Customer Engagement,” “CKM, Tools and Technique,” “Knowledge Management and CRM,” and “CRM.”By identifying and deriving key CKM themes, this study makes a significant contribution to the CKM literature. Researchers can utilize the scientific analysis of a variety of sectors, such as customer knowledge management, to understand the scientific boundaries and gain a general understanding of the scientific method. Another goal is to identify research goals for policymakers in many scientific disciplines and modify them to meet future societal requirements.

Mobile games are getting a lot of attention as a content-based sector of the digital economy. Especially considering "Free with In-App Purchase" as the mainstream business model of these games, designing the right economic structure to monetize the content of mobile games is crucial. However, there is limited knowledge about the mechanisms of persuading users to pay for in-game content and most of the studies are merely focused on the revenue models. Due to this knowledge gap, this study attempts to aggregate the game monetization methods into a multi-level classification and focus on identifying the main content monetization mechanics of five genres: Arcade, Sport, Puzzle, Racing, and Platformer/ Runner. For this purpose, interviews were conducted by game design and economics experts about successful mobile games. As a result, a new multi-level classification for mobile games revenue models is proposed which includes monetization via selling core items, selling performance items, and providing supplementary services in addition to retailing and in-game advertising. It also became clear that monetization mechanics for each of these methods vary in different genres and change depending on the type of game. The results of this study can be useful for digital game researchers, designers, and marketeers to structure a better revenue stream.