Network structure, self-organization, and the growth of international collaboration in science

Abstract

Using data from co-authorships at the international level in all fields of science in 1990 and 2000, and within six case studies at the sub-field level in 2000, different explanations for the growth of international collaboration in science and technology are explored. We find that few of the explanations within the literature can be supported by a detailed review of the data. To enable further exploration of the role of recognition and rewards as ordering mechanisms within the system, we apply new tools emerging from network science. These enquiries shows that the growth of international co-authorships can be attributed to self-organizing phenomenon based on preferential attachment (searching for recognition and reward) within networks of co-authors. The co-authorship links can be considered as a complex network with sub-dynamics involving features of both competition and cooperation. The analysis suggests that the growth of international collaboration is more likely to emerge from dynamics at the sub-field level operating in all fields of science, albeit under institutional constraints. Implications for the management of global scientific collaborations are explored.Version 24 June 04 to domestic collaborations. Narin et al. (1991) has shown that internationally coauthored articles are more highly cited than other articles. Despite this body of evidence, the question of why this class of research is growing so quickly or why it has a relatively high impact needs more discussion. A theoretically satisfying explanation of the phenomenon has yet to be offered. (Katz & Hicks 1987;Wagner-Döbler 2001) This article continues these inquiries along two lines. Drawing upon data (published elsewhere) for 1990 and 2000, different explanations offered within the literature for the increase in international collaboration are discussed. We find that existing explanations are incapable of fully explaining the emerging structure of ICS. In seeking other explanations, we turn to recent literature from the network sciences. Physicists needing large datasets for the study of network dynamics have used scientific co-authorships as a subject. In the process, they have revealed fascinating dynamics about collaborative networks, including the mechanism of preferential attachment as a structuring factor.Using the tools developed by Barabási & Albert (1999) and Newman (2001) we investigate whether these mechanisms also apply at the international level. Our findings reveal the emerging structure of linkages within the international system at the sub-field level, and perhaps move science studies closer towards a theoretically satisfying explanation for the rise of international collaboration. A brief review of the literature examining the rise of international collaborationOver the past 25 years, a number of reasons have been suggested to explain the growth of ICS. One group considers the environment within which science operates: the environmental factors can be divided into internal and external factors. A second group considers the con...

Programa Seis Sigma Auto-organizado: modelo da situação atual e necessidades de mudanças

“…A self-organizing network is characterized by the absence of an explicit coordinating leadership (Wagner & Leydesdorff, 2005), the ability to develop without significant direct external interference (Rycroft & Kash, 2004), the intense inter-relationship and communication between network participants (Anderson, 1999), the coevolution of the participants and the network (Kash & Rycoft, 2000), the learning capacity and use of this learning (Vany, 1996), the knowledge of the capabilities of all participants and access to these capabilities (Kash & Rycroft, 2002), the existence of mutual trust and aid (Kash & Rycroft, 2002), the ability to meet quickly a team to solve a problem and then dissolve it right after (Quinn et al, 1996) and the use of information systems to systematize the knowledge developed and accumulated by the network (Crowston et al, 2007).…”

“…Among the various works already carried out, we can find examples related to academic and scientific research networks (Bennett & Kidwell, 2001;Wagner & Leydesdorff, 2005), development networks of free software (Crowston et al, 2007), research and development networks in the automotive industry (Rycroft & Kash, 2004), networks of companies to improve sustainability (Espinosa & Porter, 2011), local public administration networks for economic policy development (Lee et al, 2012), networks of farmers (Dutta et al, 2005), networks of fashion industries (Schuh et al, 2008;Scherrer-Rathje et al, 2009), team management (Parker et al, 2015), among others. In all the literature reviewed, self-organizing networks were not addressed in the scope of Six Sigma programs, although there are common characteristics.…”

“…Coevolution of the participants of the network and the network itself (Kash & Rycoft) Participants do not develop jointly, only through external training Promotion of the learning through interaction and consultation to IS and direct meetings Extensive knowledge of the skills of participants and access to these capabilities (Kash & Rycroft, 2002) Only the MBB know the capabilities of those involved Make available the capabilities of those involved through IS and make them accessible Existence of mutual trust and aid (Kash & Rycroft, 2002) There is confidence, but only the MBB helps Make available the capabilities of those involved through IS and make them accessible Ability to be developed without significant direct external interference (Rycroft & Kash, 2004) Projects are developed primarily from indications of the owners of processes Method for generation and selection of ideas within the Six Sigma structure Non-existence of an explicit centralized leadership (Wagner & Leydesdorff, 2005) Leadership that is explicit and centralized in the MBB, who select the projects and have the knowledge Modification of the performance of MBBs so that they can be supporters of the Six Sigma program.…”

“…Among the various types of collaborative networks, self-organizing networks stand out for their no centralized management, the intense participation of those involved, their ability to keep their development without significant external interference and the ability to promote the learning of all those involved in the network through the systematization and availability of the knowledge generated (Kash & Rycoft, 2000;Rycroft & Kash, 2004;Dutta et al, 2005;Wagner & Leydesdorff, 2005;Schuh et al, 2008). Gutiérrez et al (2012) claim that the Six Sigma program of an organization can be considered as a learning network, providing an organizational structure composed of a network of professionals who work together oriented towards projects.…”

Collaborative Networks in the Internet of Services

“…43 Moreover, the identification of groups with similar scientific interests and research lines allows increasing effectiveness in research, as it prevents duplication of experiments. 41,44,45,46,47 The existence of a group consisting of a small number of researchers with little or no integration with other groups of the same scientific field can be explained by that group possibly being at the beginning of its research activity period. 48,49 However, the researchers with the largest number of publications are not always at the research front, especially in the case of an extended time window, in this case 20 years (1990-2009), because many of the prolific authors are likely to become heads of departments or lab directors.…”