Research Trends and Collaboration Patterns on Polymyxin Resistance: A Bibliometric Analysis (2010–2019)

Background: Antimicrobial resistance is a serious public health problem that has become a global threat. Special attention should be given to polymyxins (polymyxin B and colistin) which, since their reintroduction into clinical practice, are considered “last resort” drugs. The objective of this study is to perform a bibliometric analysis of scientific research on polymyxin resistance.Methods: Scopus was used to retrieve documents relevant to polymyxin resistance from 2010 to 2019. Data was exported to Microsoft Excel for table presentation. SciVal was used for volume and citation analysis as well as collaboration patterns. Also, we extracted data regarding the top documents, authors, countries, institutions, and the metrics of journals. VantagePoint and VOSviewer were used for geographical distribution of worldwide research and keyword co-occurrence analysis, respectively.Results: A total of 1,409 documents were retrieved. The retrieved documents received 25.0 citations per document. Articles (73.88%) and letters (18.09%) were the most frequent types of documents. During 2010–2019, there was a significant growth in publications (p-value < 0.001). The received citations were 35,209 with a peak in 2016 (11,250 citations). China and the United States led the scientific production with 299 (21.2%) and 238 (16.9%) publications, respectively. Little or no contribution came from central Asia, Sub-Saharan Africa, and Latin America. Chinese institutions have caused the greatest impact, with University of Zhejiang (China) being the most prolific institution on the subject (88 documents). In terms of the most productive journals, Antimicrobial Agents and Chemotherapy ranked first with 196 (13.9%) documents. Most of the documents were published in quartile one journals and only had national collaboration (43.2%). Analysis of keyword co-occurrence revealed that research on polymyxin resistance during the last decade has focused on its relationship with public health, pharmacology, and genetics.Conclusion: The number of documents on polymyxin resistance has increased significantly in the recent years, with a steep growth from 2016 onwards. China and the United States led the scientific production. Most of the documents were published in high-quality journals. Greater joint efforts and more contribution from central Asia, Sub-Saharan Africa, and Latin America are still needed to tackle this global problem.

Gender and Collaboration

We connect gender disparities in research output and collaboration patterns in economics. We first document large gender gaps in research output. These gaps persist across 50 years despite a significant increase in the fraction of women in economics during that time. We further show that output differences are closely related to differences in the co-authorship networks of men and women: women have fewer collaborators, collaborate more often with the same co-authors, and a higher fraction of their co-authors collaborate with each other. Taking into account co-authorship networks reduces the gender output gap by 18%.

Global scientific collaboration: A social network analysis and data mining of the co-authorship networks

Co-authorship networks consist of nodes and numerous links indicating scientific collaboration of researchers. These networks could be studied through social networks analysis and data mining techniques. The focus of the article is twofold: the first objective is the analysis of the co-authorship networks of the top 60 countries that had the highest number of scientific publications in the world, and the second one is the discovery of collaboration patterns of highly cited papers of these countries. To do so, all scientific publications of the top 60 countries in all fields as well as their highly cited papers were included in the study period between 2011 and 2015. The research samples in the first part included 10,460,999 documents and in the second part encompassed 711,025 highly cited papers. Required data were extracted from web of science database. To analyse co-authorship networks, centrality indices and clustering coefficient were used. UCINET, Pajek, VOSviewer and BibExcel software were used to map co-authorship networks of the countries and to calculate indices. Finally, the discovery of collaboration patterns in highly cited papers is studied through association rules. The research data indicated that over 95% of documents has been produced by the top 60 countries. In addition, the USA, Germany, England, France and Spain launched the most co-authorship. Quantitatively, there have been the most powerful collaboration links between China and the USA, the USA and England, the USA and Germany, and the USA and Canada. The clustering data indicated that collaborations of the top countries of the world were in three main clusters. The Friedman test showed that there was a significant difference in the priorities of the countries for collaboration; and the USA, China, England, Germany, France, Japan and Italy are in the top priority for collaboration, respectively. The results of collaboration pattern in highly cited papers indicated that the USA participates in more than half of collaboration patterns for producing highly cited papers.

Social network analysis and data visualization of MIS international collaboration in Taiwan

PurposeThe purpose of this paper is to apply social network analysis (SNA) to study faculty research productivity, to identify key leaders, to study publication keywords and research areas and to visualize international collaboration patterns and analyze collaboration research fields from all Management Information System (MIS) departments in Taiwan from 1982 to 2015.Design/methodology/approachThe authors first retrieved results encompassing about 1,766 MIS professors and their publication records between 1982 and 2015 from the Ministry of Science and Technology of Taiwan (MOST) website. Next, the authors merged these publication records with the records obtained from the Web of Science, Google Scholar, IEEE Xplore, ScienceDirect, Airiti Library and Springer Link databases. The authors further applied six network centrality equations, leadership index, exponential weighted moving average (EWMA), contribution value and k-means clustering algorithms to analyze the collaboration patterns, research productivity and publication patterns. Finally, the authors applied D3.js to visualize the faculty members' international collaborations from all MIS departments in Taiwan.FindingsThe authors have first identified important scholars or leaders in the network. The authors also see that most MIS scholars in Taiwan tend to publish their papers in the journals such as Decision Support Systems and Information and Management. The authors have further figured out the significant scholars who have actively collaborated with academics in other countries. Furthermore, the authors have recognized the universities that have frequent collaboration with other international universities. The United States, China, Canada and the United Kingdom are the countries that have the highest numbers of collaborations with Taiwanese academics. Lastly, the keywords model, system and algorithm were the most common terms used in recent years.Originality/valueThis study applied SNA to visualize international research collaboration patterns and has revealed some salient characteristics of international cooperation trends and patterns, leadership networks and influences and research productivity for faculty in Information Management departments in Taiwan from 1982 to 2015. In addition, the authors have discovered the most common keywords used in recent years.

Pola Kolaborasi Bisnis CV. Promindo Utama

Collaboration is a process of thinking in which the parties involved look at the different aspects of a problem and find solutions to these differences and their limited views on what can be done. Collaboration is defined as togetherness, cooperation, sharing of tasks, equality, and responsibility where the collaborating parties have the same goal, common perception, willingness to process, and provide mutual benefits. This research is motivated by the fact that the process, mechanism and benefits of collaboration between CV. Promindo Utama and its partners do not always go as desired. This condition can certainly hinder the development of the company and or correct the company to make improvements in collaboration patterns in partnerships. In general, this study aims to determine how the business collaboration patterns built by CV. Promindo Utama with its partners and know the factors that support and tend to hinder the collaboration. This research uses descriptive qualitative research. The data collection used was observation and interviews which were conducted for about 1 month. The results showed that in general the collaboration between CV. Promindo Utama and its partners have been running optimally even though there are still some obstacles. Besides the obstacles that exist, the collaboration pattern that occurs is able to run smoothly.

Cross-Organization Emergency Response Process Mining: An Approach Based on Petri Nets

To support effective emergency disposal, organizations need to collaborate with each other to complete the emergency mission that cannot be handled by a single organization. In general, emergency disposal that involves multiple organizations is typically organized as a group of interactive processes, known as cross-organization emergency response processes (CERPs). The construction of CERPs is a time-consuming and error-prone task that requires practitioners to have extensive experience and business background. Process mining aims to construct process models by analyzing event logs. However, existing process mining techniques cannot be applied directly to discover CERPs since we have to consider the complexity of various collaborations among different organizations, e.g., message exchange and resource sharing patterns. To tackle this challenge, a CERP model mining method is proposed in this paper. More specifically, we first extend classical Petri nets with resource and message attributes, known as resource and message aware Petri nets (RMPNs). Then, intra-organization emergency response process (IERP) models that are represented as RMPNs are discovered from emergency drilling event logs. Next, collaboration patterns among emergency organizations are formally defined and discovered. Finally, CERP models are obtained by merging IERP models and collaboration patterns. Through comparative experimental evaluation using the fire emergency drilling event log, we illustrate that the proposed approach facilitates the discovery of high-quality CERP models than existing state-of-the-art approaches.