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Relations in university settings are becoming more heterogeneous in terms of race, ethnicity, religion, nationality, class, and gender. In South Africa, transformation imperatives have radically changed the complexion of the country’s university campuses but have also entrenched political imperatives in its universities. As a consequence, the university is a highly politicised space. This is not new. What is new is a communication environment characterised by real-time, global networked digital communication and the uptake of digital media platforms (including social media platforms). We explore the effects of politicisation and new modes of communication using the case of a controversial article published in a South Africa journal and the ensuing polemic. Drawing on both institutional theory and Castells’ description of the network society, we conceptualise collegiality along two dimensions: horizontal collegial relations which exist for the purpose of knowledge creation and transfer which, in turn, depends on self-governance according to a taken-for-granted code of conduct; and vertical collegiality which describes collegial relations between academic staff and university management, and which is necessary for the governance of the university as a complex organisation. We conclude that the highly personal nature of communication that is propelled by digital communication has a direct impact on collegial relations within the university. The motivations of both university academic staff and management, as well as the public, extend beyond stimulating collective debate in the service of knowledge production to serving individual and/or ideological agendas as the communication of science becomes politicised. While issues pertaining to collegiality in South Africa may at first glance appear to be unique to the country, we believe that in a globally transforming academy, the South African case may offer novel insights and useful lessons for other highly politicised university systems.

This chapter focuses on scientific and research networks. All six facets of knowledge networks are described. The importance of three facets is called out, including domain, knowledge, and nodes. The authors provide profiles of five networks, including an invisible college in chemistry, a professional association network in engineering, an editorial network, a national biological observation collaboration, and a national science museum.

The purpose of this paper is to advocate that case study research needs to renew itself and employ its full potential as an innovative theory‐generating methodology in management disciplines; and to propose that a viable strategy for such renewal is to exploit the power of case study research and network theory as supplementary methodologies.

The paper is a reflective and synthesising comparative study.

If one steps down from the tip of the iceberg and inspects the underwater properties of case study research and network theory a common core is found: the recognition of complexity. The methodologies supplement each other, case study research primarily using verbal language and qualitative data, while network theory uses a nodes‐and‐links language that opens up for verbal, graphic and mathematical treatment. Case study research is primarily associated with qualitative research in social sciences and network theory with quantitative research in both social and natural sciences. By abolishing the unfortunate categories of qualitative/quantitative and natural sciences/social sciences that have been set against each other, and letting them join forces for a common goal – to learn about life – people open up for methodological creativity.

By comparing case study research with network theory on a fundamental level, the paper offers a novel perspective on research. It is a contribution to an overriding desire to improve the understanding of management and society.

Approaches to solving sustainability problems require a specific problem-solving mode, encompassing the complexity, fuzziness and interdisciplinary nature of the problem. This paper aims to promote a complex systems’ view of addressing sustainability problems, in particular through the tool of network science, and provides an outline of an interdisciplinary training workshop.

The topic of the workshop is the analysis of the Sustainable Development Goals (SDGs) as a political action plan. The authors are interested in the synergies and trade-offs between the goals, which are investigated through the structure of the underlying network. The authors use a teaching approach aligned with sustainable education and transformative learning.

Methodologies from network science are experienced as valuable tools to familiarise students with complexity and to handle the proposed case study.

To the best of the authors’ knowledge, this is the first work which uses network terminology and approaches to teach sustainability problems. This work highlights the potential of network science in sustainability education and contributes to accessible material.

The purpose of this paper is to propose an approach for conceptualizing science based on collaboration and competences of researchers.

The research is conducted by exploratory analysis of collaboration and competences using case studies from humanistic, engineering, natural sciences and a general topic.

The findings show that by applying the proposed approach on bibliographic data that readily exist for many national sciences as well as for international scientific communities, one can obtain useful new insights into the research. The approach is demonstrated with the following exploratory findings: identification of important connections and individual researchers that connect the community of anthropologists; collaboration of technical scientists in the community of anthropologists caused by an interdisciplinary research project; connectivity, interdisciplinary and structure of artificial intelligence, nanotechnology and a community based on a general topic; and identifying research interest shift described with concretization and topic-shift.

As demonstrated with the practical implementation (http://scienceatlas.ijs.si/), users can obtain information of the most relevant competences of a researcher and his most important collaborators. It is possible to obtaining researchers, community structure and competences of an arbitrary research topic.

The map for collaboration and competences of a complete science can be a crucial tool for policy-making. Social scientists can use the results of the proposed approach to better understand and direct the development of science.

Originality and value of the paper is in combining text (competences) and network (research collaboration and co-authoring) approaches for exploring science. Additional values give the results of analysis that demonstrate the approach.

In recent years, network science has become a dynamic and promising discipline. This study aims to provide a brief summary of the subject and the application to the tourism domain.

This paper is based on a non-exhaustive survey of the literature.

The state-of-the-art of network science in tourism is explored and discussed, together with possible future developments.

This paper uses a limited set of works, those deemed the most significant to sketch the situation. The choice might be subjective, but the overall picture is clear. Given what accomplished so far, the methods of network science seem interesting both for their theoretical and practical outcomes. In essence, they provide a better and more objective view on the structural and dynamic characteristics of the tourism phenomenon and of the different tourism systems and components.

This paper critically reflects on the state of network science and its application to the tourism domain. Even without claiming to be complete, this paper takes a general perspective approach rather than examining single topics or issues.

This chapter discusses the emerging network science approach to the study of complex adaptive systems and applies tools derived from statistical physics to the analysis of tourism destinations. The authors provide a brief history of network science and the characteristics of a network as well as different models such as small world and scale free networks, and dynamic properties such as resilience and information diffusion. The Italian resort island of Elba is used as a case study allowing comparison of the communication network of tourist organizations and the virtual network formed by the websites of these organizations. The study compares the parameters of these networks to networks from the literature and to randomly created networks. The analyses include computer simulations to assess the dynamic properties of these networks. The results indicate that the Elba tourism network has a low degree of collaboration between members. These findings provide a quantitative measure of network performance. In general, the application of network science to the study of social systems offers opportunities for better management of tourism destinations and complex social systems.

The purpose of this article is to contribute to our stock of knowledge about who uses networks, how they are used, and what contribution the networks make to advancing the scientific enterprise. Between 1985 and 1990, the Survey of Income and Program Participation (SIPP) ACCESS data facility at the University of Wisconsin‐Madison provided social scientists in the United States and elsewhere with access through the electronic networks to complex and dynamic statistical data; the 1984 SIPP is a longitudinal panel survey designed to examine economic well‐being in the United States. This article describes the conceptual framework and design of SIPP ACCESS; examines how network users communicated with the SIPP ACCESS project staff about the SIPP data; and evaluates one outcome derived from the communications, the improvement of the quality of the SIPP data. The direct and indirect benefits to social scientists of electronic networks are discussed. The author concludes with a series of policy recommendations that link the assessment of our inadequate knowledge base for evaluating how electronic networks advance the scientific enterprise and the SIPP ACCESS research network experience to the policy initiatives of the High Performance Computing Act of 1991 (P.L. 102–194) and the related extensive recommendations embodied in Grand Challenges 1993 High Performance Computing and Communications (The FY 1993 U.S. Research and Development Program).

This study aims to introduce a method based on link analysis to investigate the structure of the R&D support infrastructure associated with science parks in order to determine whether this webometric approach gives plausible results.

Three science parks from Yorkshire and the Humber in the UK were analysed with webometric and social network analysis techniques. Interlinking networks were generated through the combination of two different data sets extracted from three sources (Yahoo!, Bing, SocSciBot).

These networks suggest that institutional sectors, representing business, universities and public bodies, are primarily tied together by a core formed by research institutions, support structure organisations and business developers. The comparison of the findings with traditional indicators suggests that the web‐based networks reflect the offline conditions and policy measures adopted in the region, giving some evidence that the webometric approach is plausible to investigating science park networks.

This is the first study that applies a web‐based approach to investigate to what extent the science parks facilitate a closer interaction between the heterogeneous organisations that converge in R&D networks. This indicates that link analysis may help to get a first insight into the organisation of the R&D support infrastructure provided by science parks.

This chapter focuses on the treatment and characterization of networks as an emerging discipline. Networks are defined. The authors call out and explain the importance of network domains, network geographies and topologies, network behaviors, network nodes, network links, relationships and flows, and network messages. While network sciences provide a strong foundation for research and analysis, the authors note the lack of knowledge networks. This chapter highlights the need to expand coverage to include knowledge networks.