فهرست مطالب مهران بادین دهش

The goal of the current research is to study the research process around the concept of leadership and leadership style, using the method of analysis and Scientometrics mapping. This research is descriptive-analytical and has been carried out with a Scientometrics approach. The tool of data collection was the databases resulting from searching and cataloging, and the method of analysis was scientific tools and maps using R software. The number of reviewed articles is 2178 published in the Web of Science database between 1992 and 2022. The extracted articles were classified into six clusters based on the clustering method of bibliographic pairs. The naming of the clusters was done based on the important parameters of the frequent keywords of each, and based on this, clusters one to six, which were sorted based on the average age of the articles, were named "leadership styles based on growth and learning", "leadership styles based on The general roles of the leader", "leadership styles based on power distribution", "leadership styles based on the welfare of followers", "leadership styles based on ethics" and "leadership styles based on unethical pro-organizational behaviors" were named.

Conducting research with a theoretical contribution, reviewing the theoretical background without bias, and identifying emerging research areas are one of the most important concerns of every researcher in conducting academic research. The abundance of useless and scientifically worthless research in the country doubles the need to pay attention to these issues. One of the existing strategies to solve these problems is the approach of academic social networks analysis. Considering research areas as social structures, these networks are drawn based on bibliometric criteria such as co-citation, citation, bibliographic pairing, co-occurrence of vocabulary, and co-authorship, each of which has its uses and are used to answer special questions. In this article, the approach to social networks analysis will be introduced first, and then the bibliometric criteria used in drawing these networks will be examined. It is also stated that each of the drawn networks is suitable for answering what questions. Then, the step-by-step stages of implementing a social network analysis are introduced. Also, the most important databases used to collect the necessary meta-data are introduced and some existing tools to analyze and illustrate academic social networks are briefly reviewed. Examples of applications of this approach are also shown.     In order to conduct academic social network analysis, a 5-step process must be performed. In the first step, the research design should be determined. The analysis is done to answer what questions and what method is suitable to answer those questions. In the second step, it is necessary to collect bibliographic data. First, you have to choose the right database and then, by choosing the right search keywords in a specific time frame, search and collect the necessary metadata for network drawing and analysis. In the third step, the collected data should be analyzed. In this step, the appropriate bibliographic software should be selected and the data should be prepared for analysis. Illustration of the networks is done in the fourth step, in which the appropriate method and tool of the illustration should be determined by the researcher. In the final step, the drawn networks should be described and interpreted.     Each of the networks drawn by metadata collected from scientific databases has a specific application. Citation networks are used to identify the most important and influential works, authors, and publications. Also, based on the citation networks drawn based on the timeline, it is possible to identify the development process of a research field, its theoretical foundation, and theoretical fields affecting the research field. Co-citation networks that are drawn based on the cited references of the selected documents provide the most relevant sources for research. Also, the clusters obtained from this analysis show the historical streams of the research field. The bibliographic coupling networks which are the reverse of co-citation examine the cited documents and the clusters obtained from them showing the contemporary streams of the research field under investigation. Co-authorship networks are a measure of cooperation between authors, institutions, publications, and countries. Word co-occurrence networks identify important themes in a domain, and as a content analysis technique, they are the only network that uses the actual content of documents. The output of the word co-occurrence network is a network of themes and shows the conceptual space of a field.      Conducting targeted and useful research is one of the important issues faced by researchers and students, especially graduate students who have to conduct research in the form of a thesis or dissertation. From choosing new topics to reviewing literature and theoretical background in an appropriate way, all of them are problems that researchers have to overcome, and in this way, they need a clear strategy and roadmap. The social network analysis approach based on bibliographic criteria is one of the strategies proposed to help solve these problems. The analysis of academic social networks that are formed based on bibliographic criteria such as citation, co-citation, co-authorship, word co-occurrence, and bibliographic coupling, by adding an objective and quantitative accuracy, reduces the consequences of personal reviews and subjective biases of researchers and It helps to get a more comprehensive understanding of research areas. Each of these networks is suitable for answering specific questions. Using the approach of social network analysis can have a significant help in guiding researchers in conducting targeted research. The use of this method helps researchers, especially newcomers to a field, to get a better understanding of that field, get acquainted with important sources for study, and helps them determine their research position and advance research flows in a specific field. For this reason, getting familiar with this approach and using it is one of the topics that researchers and higher education institutions should pay attention to in order to reduce the amount of aimless and useless research.

Analyzing social networks of open innovation field for drawing the intellectual and conceptual structure of this field.

This research is applied research that has been done by academic social network analysis. In this research, 2099 documents of open innovation field that published between 2003-2018 in Web of Science were analyzed. We use CitNetExplorer and VOSviewer for analyzing data.

The number of studies in open innovation represents a sharp increase since 2014. Subjects and concepts that relate to open innovation have not been changed dramatically. Ten important journals received 20% of citations, and 14% of all citations pertain only to 10 articles. Common theoretical background categorized in 4 clusters and contemporary research streams categorized in 5 major clusters. The US has published the most documents in this field, and Iran is the 46th country with only five documents.

Conclustion: 

Open innovation paradigm has been applied in many areas and according to its role in wellbeing, economic growth, environmental improvement, and etc. more attention to this field is needed. Purposeful research and collaboration with other countries are necessary.

The theory of good governance started in 1989 by World Bank. Good governance is defined as the process and structures that guide political and socio-economic relationships. The social capital at a society includes institutions, relationships, attitudes and values that govern interactions among people contributing to economic and social development. In this research, the impact of good governance on social capital has been examined. Therefore, five different dimensions were considered for evaluating good governance including: rule of law, voice, accountability, transparency and trust. Questionnaire was the main instrument for collecting data in this study. The questionnaire has been validated by experts in this field and its reliability was calculated with cronbach alpha. We have distributed 384 questionnaires among students of social science at Shahid Beheshti University. In order to analyze the gathered data, SPSS software was used. To test the hypothesis, we used one-sample T- test. The results show that good governance has a positive effect on social capital. Among different dimensions of good governance, rule of law has the highest influence on social capital.