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This study attempts to use a new source of data collection from open government data sets to identify potential academic social networks (ASNs) and defines their collaboration patterns. The purpose of this paper is to propose a direction that may advance our current understanding on how or why ASNs are formed or motivated and influence their research collaboration.

This study first reviews the open data sets in Taiwan, which is ranked as the first state in Global Open Data Index published by Open Knowledge Foundation to select the data sets that expose the government’s R&D activities. Then, based on the theory review of research collaboration, potential ASNs in those data sets are identified and are further generalized as various collaboration patterns. A research collaboration framework is used to present these patterns.

Project-based social networks, learning-based social networks and institution-based social networks are identified and linked to various collaboration patterns. Their collaboration mechanisms, e.g., team composition, motivation, relationship, measurement, and benefit-cost, are also discussed and compared.

In traditional, ASNs have usually been known as co-authorship networks or co-inventorship networks due to the limitation of data collection. This study first identifies some ASNs that may be formed before co-authorship networks or co-inventorship networks are formally built-up, and may influence the outcomes of research collaborations. These information allow researchers to deeply dive into the structure of ASNs and resolve collaboration mechanisms.

This paper aims to introduce a systematic computing and analytical procedure that is applied to the co-author network to identify the temporal evolution and growth of research collaborations in the area of e-governance. The empirical analysis of the temporal co-author network can trace the emerging authors and knowledge bursts over time.

The study applied social network theory to trace the author collaboration patterns in the domain of e-governance. Analysis of the co-author network using micro and macro parameters was done to trace the temporal evolution of the author collaborations.

E-governance is a multi-disciplinary research domain split over streams of management, politics, information technology and electronics. Hence, research collaborations play a significant role in its advancement. The knowledge sharing between individual authors, institutions and groups through research collaborations, resulting in extensive sharing of data, equipment and research methods, has boosted research activities and development in e-governance. In this paper, the authors systematically analyse the current scenario of research collaborations in the area of e-governance using co-author network to estimate its impact on the advancement of the field. The authors also analysed the temporal evolution of the co-author networks, which show remarkable growth of research collaborations in the domain of e-governance from the year 2000.

The co-author network analysis is only a proxy measure for the analysis of research collaborations. The names of the authors and the university affiliations used in the article are as retrieved from the research repository of Scopus. The degree, citations and other parameters related with authors have scope only within the environment of the co-author network used in the analysis. The criteria used in the study is limited to the degree of research collaborations and the number of co-authored publications in the giant component of the co-author network.

Institutions, authors and governments can trace and select suitable topics and choose research groups of co-authors over the world for future research collaborations in e-governance. The knowledge about the emerging and most discussed topics gives an overview of the global research trends of e-governance.

The study identified the evolution of creative collaborations in e-governance in the global perspective. The methodology introduced here is helpful to detect the proficient and productive author collaborations and the spectrum of related e-governance research topics associated with them. As the author collaborations can be mapped to the institutional and country-level collaborations, the information is helpful for researchers, institutions and governments to establish the best collaborations in e-governance research based on the author proficiency, collaboration patterns and research topics as per the requirements.

The paper introduces a novel research methodology using temporal analysis of co-author network to identify the evolution of research patterns and the associated research topics.

The coronavirus disease 2019 (COVID-19) pandemic has greatly impacted society and academic life and research practices. This study is an attempt to comprehend whether a global emergency of COVID-19 pandemic has an impact on researcher international collaboration. The authors analyze the research collaboration before and after the beginning of the COVID-19 pandemic to understand how scientists collaborated within their own nation's borders and beyond.

The authors analyze the research collaboration before and after the beginning of the COVID-19 pandemic to understand how scientists collaborated within their own nation's borders and beyond. The authors collected a dataset of research publications published in journals in the research area of business and economics and indexed in the WoS Core Collection database by researchers from 11 countries (Austria, Denmark, Greece, Indonesia, Iran, Ireland, Korea (South), Mexico, Pakistan, Romania and Vietnam). In total, 14,824 publication records were considered for the literature analysis. This study presented the scientometric analysis of these publications using bibliometric, statistical, factor analysis and network analysis methods. The results are evaluated and interpreted in the context of the Hofstede's model of cultural dimensions. The results of this study provide evidence to research management to properly allocate their efforts to improve the researcher cooperation during the ongoing COVID-19 pandemic and to overcome its negative outcomes in the years to come.

The results of our study show that uncertainty avoidance as the cultural factor defined by the Hofstede's model has significantly influenced the properties of research collaboration networks in the domain of business and economics. Uncertainty avoidance focuses on how cultures adapt to changes and cope with uncertainty, while the global COVID-19 pandemic introduced a lot of change and uncertainty all levels of society around the world.

The study exclusively examines 14,824 research outputs which have been indexed in the WoS Core Collection database from 2019 till 15 November 2020 and only covered one research area (business economics). Thus, documents published in any other different channels and sources which are not covered in WoS are excluded from this study. The authors have analyzed the publications from just 11 countries, which represent a small part of the global research output. Also, the Hofstede’s cultural dimensions model is not a unique way to study cultural characteristics at the national level.

The results of this study will provide evidence to research management to properly allocate their efforts to improve the researcher cooperation during the still ongoing COVID-19 pandemic and to overcome its negative outcomes in the years to come.

Considering the global impact and social distress due to the outbreak of COVID-19 pandemic, this study is significant in the present scenario for identifying the changes in the characteristics of research collaboration networks of 11 diverse (in terms of geographical distribution and cultural differences in terms of the Hofstede’s cultural dimensions model) countries between 2019 (the year before COVID-19) and 2020 (the year of COVID-19), which has not been done before.

The purpose of this paper is to visualize the collaboration network among regions in library science (LS) in China. Using various methods and tools of social network analysis and geographical visualization, results were obtained, showing the structure and patterns of research collaborations in topological and geographical views, as well as the geographical distributions of contribution.

The sample includes all studies published in the top journal in library science in China from 2006 to 2015. First, co-occurrence data representing collaborations among regions was extracted from author affiliations. Second, the topological network of collaboration was generated by applying social network analysis tools and descriptive statistics, network indicators of the collaboration network and research communities were calculated. Third, the topological network was projected into a geographical map with corresponding coordinates and distances using geographical tools. Finally, the topological network maps and the geographical maps were produced for visualization.

The levels of contribution are very unbalanced between regions, and overall research collaboration is low. Beijing, Hubei and several other areas are central and significant regions in China; other regions are mostly connected with central ones through direct collaborations. Research collaborations in LS research in China are mostly distributed in the east and south of China, being centralized in the “Beijing–Hubei–Shanghai” triangle zone, as well as within the triangle’s extending zones. Finally, there are three distinct research communities that connect closely within themselves and loosely between them. The Beijing community is relatively centralized in geography, while other communities are scattered.

This study applied various methods and tools of social network analysis and geographical mapping analysis to reveal the collaboration structure and patterns among regions in LS research in China. Visualized maps in topological and geographical views help shed new light on research efforts.

The purpose of this paper is to reveal the structure and patterns of cross-national collaborations in Big Data research through application of various social network analysis and geographical visualization methods.

The sample includes articles containing Big Data research, covering all years, in the Web of Science Core Collection as of December 2015. First, co-occurrence data representing collaborations among nations were extracted from author affiliations. Second, the descriptive statistics, network indicators of collaborations, and research communities were calculated. Third, topological network maps, geographical maps integrated with topological network projections, and proportional maps were produced for visualization.

The results show that the scope of international collaborations in Big Data research is broad, but the distribution among nations is unbalanced and fragmented. The USA, China, and the UK were identified as the major contributors to this research area. Five research communities are identified, led by the USA, China, Italy, South Korea, and Brazil. Collaborations within each community vary, reflecting different levels of research development. The visualizations show that nations advance in Big Data research are centralized in North America, Europe, and Asia-Pacific.

This study applied various informetric methods and tools to reveal the collaboration structure and patterns among nations in Big Data research. Visualized maps help shed new light on global research efforts.

The purpose of this paper is to analyze collaboration networks and their patterns among higher education institutions (HEIs) in Chile and the Latin American region. This will provide evidence to educational managements in order to properly allocate their efforts to improve collaboration.

This quantitative study examines collaboration using a social network analysis (SNA) approach. The main source used to quantify collaboration is co-authorship of scholarly publications retrieved from the Web of Science scientific search engine.

The paper provides evidence that there is a low collaboration rate within-country as well cross-country among HEIs in Latin America. The collaboration network in Chile is highly dependent on two institutions; Pontificia Universidad Católica and Universidad de Chile. These institutions are considered leaders of opinion and knowledge facilitators. The density of the whole network is relatively low; only 5 percent of the potential connections exist in the current network.

The main limitation of this paper is that it does not take into account other possible collaborative efforts such as books, manuscripts, or other types of collaboration that do not result in tangible documents. However, co-authorship based on publications has been considered to be a good estimator of collaboration.

Collaboration is critical to promote research and increase its capacity. The approach presented in this study is helpful for educational managers in charge of allocating resources to effectively have an impact on collaboration. Decision makers will benefit from the evidence-based results generated by the SNA framework.

An understanding of the current status of research collaboration in Latin America allows researchers to detect the main areas of opportunity, which in turn serve to improve future decision making in this area.

Purpose: Provide insights on how social entrepreneurship (SE) knowledge can be more effectively generated by universities through the entrepreneurial creation and effective management of a knowledge network centered on international collaborative research; illuminate how one such network has enabled Latin American researchers to advance the knowledge and practice frontiers in the hemisphere and globally. Methodology/Approach: Retrospective analysis of the two-decade evolution of the Social Enterprise Knowledge Network, a pioneering international research collaboration (IRC) of Ibero-American management schools. Findings: Documents factors and dynamics enabling the successful creation and operation of international knowledge networks. Analyzes the key mechanisms for capturing synergies in collaborative research. Identifies specific effectiveness determinants for successfully operating an international social enterprise knowledge generation network. Identifies multiple impacts of a knowledge generation network. Research Implications: Advances understanding of IRCs. Provides a model for assessing knowledge network multiple impacts. Identifies a series of future research opportunities and needs. Practical Implications: Provides operational guidance for researchers developing or operating collaborative international knowledge networks. Social Implications: Reveals the value of collaboration in international research and factors that contribute to effective collaboration. Originality/Value: Provides unique retrospective study of an IRC network operated by developing country schools of management. Expands the scope of recent comparative research on SE education to include a set of countries in Ibero-America. Documents an approach to assessing the impacts of a knowledge network. Identifies important areas for advancing future social enterprise research and teaching.

This study aims to understand the extent to which scholarly networks are connected both in person and through information and communication technologies, and in particular, how distance, disciplines, and motivations for participating in these networks interplay with the clusters they form. The focal point for our analysis is the Graphics, Animation and New Media Network of Centres of Excellence (GRAND NCE), a Canadian scholarly network in which scholars collaborate across disciplinary, institutional, and geographical boundaries in one or multiple projects with the aid of information and communication technologies. To understand the complexity in such networks, we first identified scholars’ clusters within the work, want-to-meet, and help networks of GRAND and examined the correlation between these clusters as well as with disciplines and geographic locations. We then identified three types of motivation that drove scholars to join GRAND: practical issues, novelty-exploration, and networking. Our findings indicate that (1) scholars’ interests in the networking opportunities provided by GRAND may not easily translate into actual interactions. Although scholars express interests in boundary-spanning collaborations, these mostly occur within the same discipline and geographic area. (2) Some motivations are reflected in the structural characteristics of the clusters we identify, while others are irrelevant to the establishment of collaborative ties. We argue that institutional intervention may be used to enhance geographically dispersed, multidisciplinary collaboration.

This chapter presents the strategy employed to develop a methodology to evaluate research collaboration networks in a higher education context. The research design comprised four successive tracks. We understand these methodological tracks as the tactics employed to organise available means to accomplish an objective. In the first track, we selected the key subjects, the ego networks and the network leaders to be analysed. In the second track, we visualised networks through graphs. In the third track, the statements of the subjects about formed networks were pursued, based on interviews. In the fourth track, case studies were researched and described. The study included qualitative and quantitative data to uncover the interactive processes of doing collaborative research inside a network. The methodology was useful to obtain visual understanding of the networks of co-authorial relations, quantitative and qualitative markers to be used in participatory evaluation of collaborative research networks, as well as an extended view of the life cycles of collaborative research networks. The main contribution of the chapter is to show a sequence of cross-disciplinary methodological steps allowing to understand different types of relations inside research network.

The purpose of this paper is as follows: studying a case for technological innovation in Iran; studying the process of network creation; studying different challenges in finding, forming and performing of a collaboration network; studying comprehensive identification and analysis of the challenges in the network creation process; studying an active collaboration network in the field of medical equipment; and studying a network with different partners (consisting of a large company, a small- and medium-sized company, two subcontractors, three universities, a start-up, an accelerator and a venture capital fund).

The qualitative research method has been used because of a deep and rich analysis of the studied network. The study also provides an overview of finding and forming of partners and details of collaborations in the network, including partner’s goals from network entry, initial negotiations between members, business plan, shared resources and final results are expressed. The data used in this study has been collected by a totally seven semi-structured interviews. To analyze the collected data by open coding, the MAXQDA12 software was used and the basic concepts were identified and were categorized based on their similarities.

The studied network was identified as a strategic alliance. Details of finding, forming and performing of the studied network were explained. In total, 4 collaboration models and 28 different challenges in the network creation process were identified. In total, 28 different challenges were divided into 7 categories (based on their existence or absence in each of the 4 identified collaboration models). In total, seven categories of challenges were analyzed completely and the relations between challenges and partners of collaboration models were studied.

The collaboration network studied in this research involves several technological collaborations among different actors. Saadat, as the hub of this network, has been involved in all these collaborations, and other members have joined the network in accordance with network requirements and their capabilities. This network has been formed and developed with the aim of developing and producing various modules of vital signs monitoring since 2009. Some of the collaborations in this network, which are for production of a specific module and require long-term collaboration between the partners (such as the production of electrocardiograph or heart attack rapid diagnostic module), continue to be ongoing and some of them that focus on research and development or acquisition of technical knowledge (such as academic collaboration) after the specified result has been ended.