Structure Of Collaboration Networks Research Articles

Social structure of social media research in tourism and hospitality

ABSTRACTIn recent years, the number of publications on social media has increased exponentially. Although several attempts have been made to review social media studies in tourism and hospitality, the social structure of collaborative networks has yet to be analysed. By performing authorship and co-authorship analyses of 385 articles, this study explored the progress of social media research and analysed key authors’ productivity, educational background and centrality in research communities. Regional differences in socially constructed social media knowledge were investigated. Networks between universities were also analysed and compared based on region. Findings suggest future research directions for various regions and provide important implications to the academia and industry.

Patent collaboration networks in Sweden and Spain during the Second Industrial Revolution

ABSTRACTThis article aims to analyse and compare the patent collaboration networks of Spain and Sweden during the Second Industrial Revolution, a key period for technological and industrial development in several economies and the distinct development paths taken by these two countries. The data used are from two new historical patent datasets for Spain and Sweden for the period 1878–1914. To study the structure of collaboration networks in both countries, we applied social network analysis methods and focused on two specific key network properties: connectivity and openness to external nodes. The results demonstrate that collaboration networks were better connected and more open to foreign influence in Sweden than in Spain. This research opens new paths for further multidisciplinary studies both on the evolution of industrial economies and on innovation networks dynamics.

A social network analysis on immigrants and refugees access to services in the malaria elimination context

BackgroundThere has been significant progress in eliminating malaria in Iran. The aim of this study is to investigate the structure of inter-organizational collaboration networks in the field of unauthorized immigrants and refugees access to services in order to eliminate malaria.MethodsThis study employed social network analysis, in which nodes represented stakeholders associated with providing access of immigrants and refugees to services in the field of malaria elimination, and ties indicated the level of collaboration. This study adopted socio-centric analysis and the whole network was studied. In this regard, 12 districts of the malaria-endemic area in Iran were selected. Participants included 360 individuals (30 representatives of the organization/group in each district). The data were gathered by interview, using the levels of collaboration scale. UCINET 6 was used for data analysis. The indices of density, centralization, reciprocity, and clustering were investigated for each twelve network and at each level of collaboration.ResultsThe average density of the networks was 0.22 (SD: 0.04). In districts with a high incidence of imported malaria, the values of network density and centralization were high and the networks comprised of a larger connected component (less isolated clusters). There were significant correlations between density of network (r = 0.66, P = 0.02), degree centralization (r = 0.65, P = 0.02), betweenness centralization (r = 0.76, P = 0.004), and imported malaria cases. In general, the degree centrality and betweenness centrality of the organizations of health, district governor, and foreign immigrants’ affairs were higher. In all networks, 60% of the relationships were bilateral. At a higher level of collaboration, the centralization declined and reciprocity increased. The average of betweenness centralization index was 22.76 (SD = 3.88).ConclusionsHigher values of network indices in border districts and districts with more cases of imported malaria, in terms of density and centralization measures, can propose the hypothesis that higher preparedness against the issue and centralization of power can enable a better top-down outbreak management, which needs further investigations. Higher centrality of governmental organizations indicates the need for involving private, non-governmental organizations and representatives of immigrant and refugee groups. Recognition of the existing network structure can help the authorities increase access to malaria prevention, diagnosis, and treatment services among immigrants and refugees.

Massive Collaborative Wireless Sensor Network Structure Based on Cloud Computing

To explore the wireless sensor network (WSN) structure, the cooperative WSN architecture of mass data processing based on cloud computing is studied. The technology of WSN and cloud computing is deeply discussed. The system and node structure of WSN are studied by theoretical analysis method, and the performance of the WSN is studied by using the numerical simulation method. The mass data processing technology based on Map Reduce and its application in WSN are discussed. The numerical simulation method is used to experiment on the architecture of SVC4WSN and MD4LWSN. The relationship between the optimal network number and the node communication radius at different node density is verified. Moreover, the energy and time delay Reduce path is compared with three protocols of LEACH, PEGASIS and PEDAP. The results show that the two Reduce paths have better performance in both network survival time and the total time slot of data acquisition.

Using social network analysis to characterize the collaboration network of backyard poultry trainers in ackCalifornia

In order to better understand collaboration among trainers in the backyard poultry community (i.e. feed store managers, youth development programs (i.e. 4-H), veterinarians, government agencies, extension resources and backyard poultry club leaders), Social Network Analysis (SNA) was used as a tool to better characterize and quantify the current collaboration network structure of backyard poultry trainers in California. Invited trainer attendees of two “Train-the-Trainers” poultry workshops (n = 67) held in Northern and Southern California were given a survey that asked them to list contacts that they collaborated with on backyard poultry (BYP) related work. The collaboration network in this study included a total of 109 trainers, 18 practitioners, and 32 individuals who are both trainers and practitioners for a total of 170 nodes (11 individuals did not have affiliation information available). In order to help identify central actors or collaboration leaders, the surveys were analyzed using Social Network Analysis (SNA), which allows for a quantitative analysis of relationships among various stakeholders. While the SNA showed that the existing collaboration network is disconnected with a clustering coefficient of 0.043 and median total degree centrality of 1 (range 9) and therefore not conducive for collaboration, key insights that could help restructure and improve the network were identified. As an example, among different poultry groups, 4-H was identified as the organization with the second highest median coverage score and fifth highest median centrality score. In addition, 4-H group leaders act as both trainers and practitioners. Consequently, outreach to 4-H group leaders throughout the state would potentially have the greatest impact with respect to overall coverage both inside and outside the 4-H network due to their high centrality and boundary spanning roles. Using SNA to strengthen the collaboration network infrastructure of backyard poultry trainers ultimately offers a more targeted approach toward extension for backyard poultry owners, which could ultimately facilitate communication and knowledge-sharing with BYP owners during a disease outbreak.

Evaluation across and within collaborative manufacturing networks: a comparison of manufacturers’ interactions and attributes

Evaluation on collaborative manufacturing network (CMN) structure characteristics has important implications for network operations such as production decision-making, product recovery, creating consensus. Several recent studies suggest that augmenting network structure with nodes’ attributes can provide a more fine-grained understanding of the network. However, there have been few studies to provide a systematic understanding of these effects in a CMN at scale. This gap is bridged using an industrial printing machinery CMN data-set collected on a web-based producing and outsourcing service platform. Novel phenomena with respect to both interaction and attribute metrics across and within the CMNs are observed. Moreover, although many studies employ either interaction or attribute data to study the relative roles of manufacturers in a CMN, relatively little is known about the relationship between these two types of data. This study explores this relationship by comparing two defined metrics (i.e. relational capability and node capability), which evaluate the manufacturers’ interactions and attributes, respectively. We examine to what extent the two metrics of manufacturers correlate with each other, and how possible dissimilarities and similarities can be explained based on the collected industrial CMN data-set. The insights thereby provide a better basis for efficient operations decision-making in CMN.

Examining capacity for “cross-pollination” in a rural school district: A social network analysis case study

Teacher collaboration is a vital factor in successful school reform, and the networks in which educators are embedded support (or constrain) access to essential social capital resources. In this study, authors used social network analysis to examine the changing structure of teacher collaboration networks over the course of a rural District’s 3-year Professional Learning Community (PLC) initiative. Visual depictions (sociograms) of district- and school-level teacher collaboration networks were generated, and measures of network cohesion – including size, density, connectedness, components, and degree – were calculated at three points in time. Authors worked in partnership with district administrators to explore how location of teachers and principals, and network capacity for diffusion of innovation, changed over time. School leaders may not know how to purposefully influence communication ties between teachers, relying instead on the invisible web of personal affiliations through which professional opinions travel. This study contributes to the field’s understanding of how administrator choices about organizational structure affect “cross-pollination” and the networks through which teachers are able to access and contribute the knowledge and ideas they need in order to deliver high-quality curriculum and instruction to all students.

The Scientific Collaboration Networks in University Management in Brazil

The scientific collaboration, externalized through the formation of networks or research groups, has been used by researchers in the processes of production and publication of researches in the various areas of knowledge. On the basis of this, the aim of this article is to identify the structure of scientific collaboration networks in University Management among higher education institutions, based on the institutional links of researchers in this area. In terms of methodological steps, two data collections were done: one in the publications database of the Journal of University Management in Latin America (GUAL) to select the articles of interest in the research, and another in the current database of the Directory of Research Groups (DRG) of the National Council for Scientific and Technological Development (CNPq) to identify the research groups in University Management registered in the Directory. The main results evidenced the predominance of scientific collaboration in the production of research in the area and that the formation of networks is influenced by several factors, such as social aspects and professional aspirations of researchers, interests in sharing resources, as well as the geographical proximity of institutions.

Structural dynamics of innovation networks in German Leading-Edge Clusters

We study the effects of a German national cluster policy on the structure of collaboration networks. The empirical analysis is based on original data that was collected in fall 2011 and late summer 2013 with cluster actors (firms and public research organizations) who received government funding. Our results show that over time the program was effective in initiating new cooperation between cluster actors and in intensifying existing linkages. A substantial share of the newly formed linkages is among actors who did not receive direct funding for a joint R&D project, which indicates a mobilization effect. Furthermore, we observe differential developments regarding clusters’ spatial embeddedness. Some clusters tend to increase their localization, whereas others increase their connectivity to international partners. Changes in centrality are mainly determined by initial positions in the network, but the determinants of these changes differ substantially between clusters.

Bionetworking and Strategic Linking between India and Japan: How Clinical Stem Cell Intervention Continues despite New Regulatory Guidelines

Based on a case study of a clinical stem cell intervention (CSCI) center in Chennai, India, this article explores distinct entrepreneurial strategies for the promotion of unrecognized clinical stem cell applications in India. It shows that the center—an Indo-Japanese joint-venture—is able to promote the CSCI due to its central position in a network relationship, its possession of specialized skills and knowledge, and its ability to maneuver other actors in the network and to identify and utilize their latent value. We examine the developmental history of the making and remaking of regulation and the shift in the way clinical stem cell application providers function—from institutional embedment to strategic linking through collaborative networks. We ask why and how unauthorized clinical applications are sustained and promoted in India. We conclude that this is possible as a result of a number of factors: jurisdictional ambiguity, institutional inability, issues concerning the legal enforceability of the relevant guidelines, the complexity of the collaborative network structure that facilitates the circumvention of the regulation, and the nonfunctioning of apex-level committees.

Quintuple helix structure of Sino-Korean research collaboration in science

The Triple Helix Model has been used for science-mapping in research collaboration since the 1980s. As knowledge-producing activities have rapidly expanded and become interrelated, the triple helix framework is limited in uncovering a broader range of stakeholders and multilateral collaborative activities. In this vein, the present study employs the N-tuple Helix Model as a suitable alternative to analyze the structure of scientific collaboration networks beyond university---industry---government (UIG) relations. The networks of N-tuple Helix relations embedded in Sino-Korean research collaboration are examined in terms of five actors, such as universities, industries, governments, hospitals, and Non-Governmental Organizations (NGOs). The results found that the quintuple helical network exists in Sino-Korean research collaboration. While traditional UIG actors play a pivotal role, hospital and NGO sectors emerge as new drivers for knowledge production and innovation. Each sector is significantly associated with the others and plays distinctive roles and functions. The overall findings provide new insight into a possible change in the traditional Triple Helix framework by demonstrating an alternative "five-helix model" of innovation as a new evolving structure and new dynamic of international collaboration in science.

Clique to Win? Impact of Simmelian Ties on Collaborative Project Performance

Large infrastructure and public works projects require resources not often found in individual firms. Competitive bidding motivates contractors to form partnerships with subcontractors to win and implement such projects. Projects with no prior interactions between partners tend to develop structural holes, providing the coordinating contractors with brokering privileges. But through repeated project interactions communication and trust develops giving rise to cohesive clique networks and Simmelian ties. Instead of asymmetric power structures, cliques develop group norms and constrain opportunistic behavior by members. How do these two different collaborative arrangements engaging distinct network microstructures impact project outcomes? This study examines the role of network structures on collaborative project outcomes in a novel setting where multiple firms collaborate and compete to win and execute projects. Multi-year longitudinal network analysis of public infrastructure projects implemented in the State of California, reveal that compared to dyadic ties, Simmelian ties and network closure between team members help thwart external competition and internal opportunistic behavior leading to favorable project outcomes. Our empirical results contribute to network theory and multipartner alliance formation by examining the dynamics of inter-firm collaborative network structures and subsequent effect on collaborative work.

Name usage pattern in the synonym ambiguity problem in bibliographic data

Individuals often appear with multiple names when considering large bibliographic datasets, giving rise to the synonym ambiguity problem. Although most related works focus on resolving name ambiguities, this work focus on classifying and characterizing multiple name usage patterns--the root cause for such ambiguity. By considering real examples bibliographic datasets, we identify and classify patterns of multiple name usage by individuals, which can be interpreted as name change, rare name usage, and name co-appearance. In particular, we propose a methodology to classify name usage patterns through a supervised classification task and show that different classes are robust (across datasets) and exhibit significantly different properties. We show that the collaboration network structure emerging around nodes corresponding to ambiguous names from different name usage patterns have strikingly different characteristics, such as their common neighborhood and degree evolution. We believe such differences in network structure and in name usage patterns can be leveraged to design more efficient name disambiguation algorithms that target the synonym problem.

Collaborative planning for city development. A perspective from a city planner

A number of definitions related to collaborative governance have been developed since early 2000. The common characteristics of collaborative governance are, among others, policy consensus, community visioning, consensus rule-making, and collaborative network structures. Collaborative planning is a new paradigm of planning for a complex contemporary society through which it encourages people to be engaged in a dialogue in a situation of equal empowerment and shared information to learn new ideas through mutual understanding, to create innovative outcomes and to build institutional capacity. This indicates that collaborative planning can provide policy makers with more effective community participation. Collaborative process is the key of collaborative planning which also emphasizes the significant role of collaborative leadership. The process includes a participatory activity of dialogue oriented to the joint decision and summarized in a collaborative process. The collaborative leadership is crucial for setting and maintaining clear ground rules, building trust, facilitating dialogue, and exploring mutual gains. Along with the shift of planning paradigm, the role of city planner will also change since the city planning deals with the political process. In the political process, city planners must be able to perform as technocrats, bureaucrats, lawyers and politicians who always uphold their ethics because they are responsible to the society, the assignor for their integrity and professionalism.

A typology of collaborative research networks

PurposeMany studies have investigated how the structure of the collaborative networks of researchers influences the nature of their work, and its outcome. Co-authorship networks (CANs) have been widely looked at as proxies that can help bring understanding to the structure of research collaborative ties. The purpose of this paper is to provide a framework for describing what influences the formation of different research collaboration patterns.Design/methodology/approachThe authors use social network analysis (SNA) to analyze the co-authorship ego networks of the ten most central authors in 24 years of papers (703 papers and 1,118 authors) published in the Proceedings of CASCON, a computer science conference. In order to understand what lead to the formation of the different CANs the authors examined, the authors conducted semi-structured interviews with these authors.FindingsBased on this examination, the authors propose a typology that differentiates three styles of co-authorship: matchmaking, brokerage, and teamwork. The authors also provide quantitative SNA-based measures that can help place researchers’ CAN into one of these proposed categories. Given that many different network measures can describe the collaborative network structure of researchers, the authors believe it is important to identify specific network structures that would be meaningful when studying research collaboration. The proposed typology can offer guidance in choosing the appropriate measures for studying research collaboration.Originality/valueThe results presented in this paper highlight the value of combining SNA analysis with interviews when studying CAN. Moreover, the results show how co-authorship styles can be used to understand the mechanisms leading to the formation of collaborative ties among researchers. The authors discuss several potential implications of these findings for the study of research collaborations.

Standing on the shoulders of giants: the effect of outstanding scientists on young collaborators’ careers

Collaboration is one of the key features in scientific research. With more and more knowledge accumulated in each discipline, individual researcher can only be an expert in some specific areas. As such, there are more and more multi-author papers nowadays. Many works in scientometrics have been devoted to analyze the structure of collaboration networks. However, how the collaboration impacts an author's future career is much less studied in the literature. In this paper, we provide empirical evidence with American Physical Society data showing that collaboration with outstanding scientists (measured by their total citation) will significantly improve young researchers' career. Interestingly, this effect is strongly nonlinear and subject to a power function with an exponent <1. Our work is also meaningful from practical point of view as it could be applied to identifying the potential young researchers.

The structure and change of the research collaboration network in Korea (2000–2011): network analysis of joint patents

This study is to examine the structure, characteristics, and change of a research collaboration network using co-assignee information of joint patents in Korea. The study was conducted in three stages: data collection, network construction, and network analysis. For network analysis, network topological analysis, node centrality analysis, and block modeling were performed in sequence. The analysis results revealed that the network has small-world properties. The results also showed that while government-sponsored research institutes (GRIs) played a role as a hub and bridge in the network in the early 2000s, universities gradually took their place to play a key role as a hub and bridge in the network. In addition, the block modeling analysis indicated that while, in the early 2000s, GRI-centered network density was shown to be high, the network density became concentrated around universities after 2004, and this tendency intensified after 2008. Bearing in mind a lack of empirical studies on inter-organizational research collaboration networks using patent data, this study made an academic contribution by specifically analyzing the structure and change of research collaboration networks by targeting Korea's major innovative actors. From the policy perspective, it provides important implications for figuring out the effects of university---industry---GRI (UIG) collaboration policies implemented so far, and can be of assistance for making evidence-based policies to build up a more effective UIG collaboration network or establish a new national science and technology innovation system.

The Structure of Collaboration Networks: An Illustration of Indian Economics

Abstract The main aim of this study is twofold: first, to examine the underlying structure of coauthorship in Indian economics; and second, to explore the link between the participation in scientific collaborations and academic visibility. We decipher the structure of co-authorship by presenting collaboration networks of scholars who published articles in six Indian economics journals during 1966-2005, which is split into four windows: 1966-75, 1976-85, 1986-95, and 1996-2005. In this study, the following social network measures are applied: the size of the network, the size of the main component, average degree, path length, and clustering coefficient. The study presents the following three features of Indian economics: first, a substantial proportion of Indian authors are isolated, albeit declining very slowly over a period of time; second, it appears that the structure of scholarly collaboration in Indian economics is highly fragmented, and the observed size of main components accounts for a small proportion of the total authors; third, and more importantly, the size and composition of co-authorship networks presented in the paper seldom impact the scientific visibility of authors.

Doing Things Together: Objectives and Effects of Harald Szeemann’s Happening &amp; Fluxus, 1970

Abstract Harald Szeemann’s exhibition Happening &amp; Fluxus (Kölnischer Kunstverein 1970) was the first to bring Fluxus into an institutional art world context. Previously avoiding such situations, Fluxus had primarily grown through artist-based networking, collaboration and self-curation during the 1960s. The exhibition evoked conflict both before and after the opening but had surprisingly little impact on Fluxus’s aftermath. This article explores Szeemann’s art historical take on the works in Happening &amp; Fluxus. It concludes that by reducing attention to Fluxus’s collaborative strategies and network structure, Szeemann overlooked the characteristics that are today acknowledged as the group’s most significant.

Formation and performance of collaborative disaster management networks: Evidence from a Swedish wildfire response

Abstract Natural disasters present a multitude of entangled societal challenges beyond the realms and capacities of single actors. Prior research confirms that effective collaboration is of critical significance to address such complex collective action problems. Yet, studies rarely investigate if patterns of collaboration are appropriately aligned (‘fit’) with how different challenges (tasks) are interdependent, or how levels of fit influence collective action performance. We develop a set of hypotheses specifying what constitutes a good fit between collaborative networks and task interdependency. Using unique empirical data from the response to a major wildfire in Sweden, we examine how individual actors select collaboration partners and tasks during the formation the collaborative crisis response network. Then we test if levels of fit in the established network influence performance. We show that patterns of actor and task interdependency influence the formation of collaborative networks and that a good fit seems to be associated with more effective collaboration. Our data even suggest that a good fit is more important for performance than actors’ prior crisis management experience and level of professionalization. Further, we show that actors only partially engage in actor-task configurations conducive to high performance. Our study probes the limitations of simplified accounts of collaborative disaster management by enabling more precise and theoretically informed empirical inquiries regarding the mechanisms that shape the structure and performance of collaborative networks.