Middle East Countries’ Contribution to Global Engineering Research: A Bibliometric Analysis

This study aims to examine the research output in engineering by the Middle East countries.  The data on engineering research by Middle East countries were collected from Web of Science. Collected data were analyzed with various tools such as Average Annual Growth Rate (AAGR), Compound Annual Growth Rate (CAGR), Activity Index (AI), and Relative Specialization Index (RSI). The level of regional and international cooperation in the Middle East countries was also identified. Findings showed Iran has the highest overall performance in total documents, total citations, h-index, and highly cited papers, but most of the publications by Yemen were international cooperation. Iran, Kuwait, Oman, Saudi Arabia, UAE, and Yemen in the field of petroleum engineering; Bahrain and Qatar in industrial engineering; Turkey in geological engineering; Syria in agricultural engineering; Lebanon in medical engineering; Israel in cell & tissue engineering; Iraq in civil engineering; Egypt in Chemical Engineering; and Jordan in Software Engineering have the highest RSI in their countries. Results show that Iran had the best performance in most of the indicators (quantitative indices) and Saudi Arabia has good performance in qualitative indices among Middle East countrie

Quality issues in co-authorship data of a national scientific community

A stream of research on co-authorship, used as a proxy of scholars’ collaborative behavior, focuses on members of a given scientific community defined at discipline and/or national basis for which co-authorship data have to be retrieved. Recent literature pointed out that international digital libraries provide partial coverage of the entire scholar scientific production as well as under-coverage of the scholars in the community. Bias in retrieving co-authorship data of the community of interest can affect network construction and network measures in several ways, providing a partial picture of the real collaboration in writing papers among scholars. In this contribution, we collected bibliographic records of Italian academic statisticians from an online platform (IRIS) available at most universities. Even if it guarantees a high coverage rate of our population and its scientific production, it is necessary to deal with some data quality issues. Thus, a web scraping procedure based on a semi-automatic tool to retrieve publication metadata, as well as data management tools to detect duplicate records and to reconcile authors, is proposed. As a result of our procedure, it emerged that collaboration is an active and increasing practice for Italian academic statisticians with some differences according to the gender, the academic ranking, and the university location of scholars. The heuristic procedure to accomplish data quality issues in the IRIS platform can represent a working case report to adapt to other bibliographic archives with similar characteristics

Human resource management–research performance linkage in higher education institutions

Research performance enhancement has become a greater issue in recent decades. However, studies analyzing the determinants of research performance and identifying human resource management (HRM) practices that improve research performance have been few and inconsistent. This paper overviews the factors affecting research performance and responds to calls for HRM practices that are customized for research and higher education institutions (HEIs). The paper is based on a theoretical HRM-performance linkage and aims to identify research performance measures, define scholars’ skills, abilities, research-oriented attitudes, and behaviors related to research performance, and generate bundles of abilities, motivation, and opportunities enhancing HRM practices associated with research performance. Finally, a theoretical framework for the HRM–research performance chain is developed

Italian sociologists: A community of disconnected groups

Examining coauthorship networks is key to study scientific collaboration patterns and structural characteristics of scientific communities. Here, we studied coauthorship networks of sociologists in Italy, using temporal and multi-level quantitative analysis. By looking at publications indexed in Scopus, we detected research communities among Italian sociologists. We found that Italian sociologists are fractured in many disconnected groups. The giant connected component of the Italian sociology could be split into five main groups with a mixture of three main disciplinary topics: sociology of culture and communication (present in two groups), economic sociology (present in three groups) and general sociology (present in three groups). By applying an exponential random graph model, we found that collaboration ties are mainly driven by the research interests of these groups. Other factors, such as preferential attachment, gender and affiliation homophily are also important, but the effect of gender fades away once other factors are controlled for. Our research shows the advantages of multi-level and temporal network analysis in revealing the complexity of scientific collaboration patterns

Homophily in higher education research: A perspective based on co-authorships

Research collaborations are the norm in science today, and are usually evaluated using co-authorships as the unit of analysis. Research collaborations have been typically analyzed using a mapping perspective that focuses on countries, institutions, or individuals, or by assessments of the determinants of research collaboration, i.e., who engages in collaborations and who collaborates the most. One analytical perspective that has been used less frequently is the homophily perspective, which attempts to understand the likelihood of research collaborations based on the similarity of collaborators’ preferences and attributes. In addition, compared to studies focused on the fields of the natural and exact sciences, engineering, and the health sciences, research collaborations in the social sciences have been underexamined in the literature, despite the growing numbers of social scientists who engage in such collaborations. This study assessed homophily with respect to geographical, ascribed, acquired and career-related attributes in co-authorships in the social sciences, based on a co-authorship matrix of 913 higher education researchers. The findings showed that geographic and institutional attributes were by far the most powerful homophilic drivers of collaborations, suggesting the importance of physical proximity, national incentives, and shared culture, language, and identity. Another driver was the similarity of acquired attributes, particularly certain preferences regarding research agendas; these absorbed the residual explanatory power that ascribed attributes such as gender or age had in co-authorship preferences. The study is novel in its analysis of the extent to which similarities in the research agendas of researchers predicted co-authorship. The findings indicate the need for further co-authorship homophily analyses around a broader set of acquired attributes and the trajectories that lead to them.info:eu-repo/semantics/acceptedVersio

Research Collaboration Influence Analysis Using Dynamic Co-authorship and Citation Networks

Collaborative research is increasing in terms of publications, skills, and formal interactions, which certainly makes it the hotspot in both academia and the industrial sector. Knowing the factors and behavior of dynamic collaboration network provides insights that helps in improving the researcher’s profile and coordinator’s productivity of research. Despite rapid developments in the research collaboration process with various outcomes, its validity is still difficult to address. Existing approaches have used bibliometric network analysis with different aspects to understand collaboration patterns that measure the quality of their corresponding relationships. At this point in time, we would like to investigate an efficient method to outline the credibility of findings in publication—author relations. In this research, we propose a new collaboration method to analyze the structure of research articles using four types of graphs for discerning authors’ influence. We apply different combinations of network relationships and bibliometric analysis on the G-index parameter to disclose their interrelated differences. Our model is designed to find the dynamic indicators of co-authored collaboration with an influence on the author’s behavior in terms of change in research area/interest. In the research we investigate the dynamic relations in an academic field using metadata of openly available articles and collaborating international authors in interrelated areas/domains. Based on filtered evidence of relationship networks and their statistical results, the research shows an increment in productivity and better influence over time