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Universities face incredibly difficult, complex decisions concerning the degree to which they participate in the process of commercializing research. The U.S. government has made an explicit policy decision to allow funded entities to obtain patents and thereby has encouraged participation in the commercialization of federally funded research. The Bayh-Dole Act enables universities to participate in the commercialization process, but it does not obligate or constrain them to pursue any particular strategy with respect to federally funded research. Universities remain in the driver's seat and must decide carefully the extent to which they wish to participate in the commercialization process.The conventional view of the role of patents in the university research context is that patent-enabled exclusivity improves the supply-side functioning of markets for university research results as well as those markets further downstream for derivative commercial end-products. Both the reward and commercialization theories of patent law take patent-enabled exclusivity as the relevant means for fixing a supply-side problem – essentially, the undersupply of private investment in the production of patentable subject matter or in the development and commercialization of patentable subject matter that would occur in the absence of patent-enabled exclusivity.While the supply-side view of the role of patents in the university research context is important, a view from the demand side is needed to fully appreciate the role of patents in the university research context and to fully inform university decisions about the extent to which they wish to participate in the commercialization process. Introducing patents into the university research system, along with a host of other initiatives aimed at tightening the relationship between universities and industry, is also (if not primarily) about increasing connectivity between university science and technology research systems and the demands of industry for both university research outputs (research results and human capital) and upstream infrastructural capital necessary to produce such outputs.In this chapter, I explore how university science and technology research systems perform economically as infrastructural capital and explain how these systems generate social value. I explain how the availability of patents, coupled with decreased government funding, may lead to a slow and subtle shift in the allocation of infrastructure resources.

Contemporary literature reveals that, to date, the poultry livestock sector has not received sufficient research attention. This particular industry suffers from unstructured supply chain practices, lack of awareness of the implications of the sustainability concept and failure to recycle poultry wastes. The current research thus attempts to develop an integrated supply chain model in the context of poultry industry in Bangladesh. The study considers both sustainability and supply chain issues in order to incorporate them in the poultry supply chain. By placing the forward and reverse supply chains in a single framework, existing problems can be resolved to gain economic, social and environmental benefits, which will be more sustainable than the present practices.

The theoretical underpinning of this research is ‘sustainability’ and the ‘supply chain processes’ in order to examine possible improvements in the poultry production process along with waste management. The research adopts the positivist paradigm and ‘design science’ methods with the support of system dynamics (SD) and the case study methods. Initially, a mental model is developed followed by the causal loop diagram based on in-depth interviews, focus group discussions and observation techniques. The causal model helps to understand the linkages between the associated variables for each issue. Finally, the causal loop diagram is transformed into a stock and flow (quantitative) model, which is a prerequisite for SD-based simulation modelling. A decision support system (DSS) is then developed to analyse the complex decision-making process along the supply chains.

The findings reveal that integration of the supply chain can bring economic, social and environmental sustainability along with a structured production process. It is also observed that the poultry industry can apply the model outcomes in the real-life practices with minor adjustments. This present research has both theoretical and practical implications. The proposed model’s unique characteristics in mitigating the existing problems are supported by the sustainability and supply chain theories. As for practical implications, the poultry industry in Bangladesh can follow the proposed supply chain structure (as par the research model) and test various policies via simulation prior to its application. Positive outcomes of the simulation study may provide enough confidence to implement the desired changes within the industry and their supply chain networks.

How do ego-networks evolve? How does such evolution affect firms’ innovation output? This chapter uses a longitudinal sample of firms in the biotechnology industry to address these questions. We use social network theory to develop a model of the structure and dynamics of firms’ interorganizational research collaboration ego-networks. Using novel longitudinal methods, this chapter demonstrates how research collaboration ego-networks in the biotechnology industry change over time and how this evolution affects focal firms’ subsequent innovative output. The model is tested on a sample of 482 biotechnology firms over a span of 17 years (1990–2006). The results indicate the significant impacts of ego-network size, ego-network growth, and the inclusion of new members in the ego-network on the innovation output of biotechnology firms. Our results also suggest that enlarging ego-networks by adding new and diverse members presents significant management challenges.

Growth in scientific production and productivity over the 20th century resulted significantly from three major countries in European science – France, Germany, and the United Kingdom. Charting the development of universities and research institutes that bolster Europe’s key position in global science, we uncover both stable and dynamic patterns of productivity in the fields of STEM, including health, over the 20th century. Ongoing internationalization of higher education and science has been accompanied by increasing competition and collaboration. Despite policy goals to foster innovation and expand research capacity, policies cannot fully account for the differential growth of scientific productivity we chart from 1975 to 2010.

Our sociological neo-institutional framework facilitates explanation of differences in institutional settings, organizational forms, and organizations that produce the most European research. We measure growth of published peer-reviewed articles indexed in Thomson Reuters’ Science Citation Index Expanded (SCIE).

Organizational forms vary in their contributions, with universities accounting for nearly half but rising in France; ultrastable in Germany at four-fifths, and growing at around two-thirds in the United Kingdom. Differing institutionalization pathways created the conditions necessary for continuous, but varying growth in scientific production and productivity in the European center of global science. The research university is key in all three countries, and we identify organizations leading in research output.

Few studies explicitly compare across time, space, and different levels of analysis. We show how important European science has been to overall global science production and productivity. In-depth comparisons, especially the organizational fields and forms in which science is produced, are crucial if policy is to support research and development.

In academia, assessment is often narrow in its focus on research productivity, its application of a limited number of standardised metrics and its summative approach aimed at selection. This approach, corresponding to an exclusive, subject-oriented concept of talent management, can be thought of as at odds with a broader view of the role of academic institutions as accelerating and improving science and scholarship and its societal impact. In recent years, open science practices as well as research integrity issues have increased awareness of the need for a more inclusive approach to assessment and talent management in academia, broadening assessment to reward the full spectrum of academic activities and, within that spectrum, deepening assessment by critically reflecting on the processes and indicators involved (both qualitative and quantitative). In terms of talent management, this would mean a move from research-focused assessment to assessment including all academic activities (including education, professional performance and leadership), a shift from focus on the individual to a focus on collaboration in teams (recognising contributions of both academic and support staff), increased attention for formative assessment and greater agency for those being evaluated, as well as around the data, tools and platforms used in assessment. Together, this represents a more inclusive, subject-oriented approach to talent management. Implementation of such changes requires involvement from university management, human resource management and academic and support staff at all career levels, and universities would benefit from participation in mutual learning initiatives currently taking shape in various regions of the world.

This chapter explores the development and the role of accounting for research quality in Australia’s Excellence in Research for Australia (ERA) assessment exercise. It tracks the progress of performance measurement systems from quantitative to qualitative measurement within the Australian higher education sector since 1970, leading up to the implementation of a formal ERA in 2010, and its subsequent iterations in 2012, 2015, and 2018. Although only a part of the ERA submissions, now certain published research outputs provide the primary evidence for research quality to most ERA panels and are a significant driver of the final rating awarded. Before the authors assess the 2018 exercise, they will examine the ever-changing role of journal publications as a vehicle for academic research output.

The social science research community in higher education in the United Kingdom constitutes the largest group of staff covered by any of the six research councils. Over 25% of the people entered in the 2001 Research Assessment Exercise (RAE) had a social science base. This chapter examines the way the pattern of social science research in the UK has been affected by, mainly, the RAE, the interpretations and strategic implementations that flow from it, and the funding allocations it informs. It draws on my own previous work, and that of others across a range of social science disciplines, as well as a small survey of active researchers conducted in late 2004/early 2005 as processes were set in train for the 2008 exercise. The critique of a process based mainly on peer review provides food for thought for those in Australia, where a research quality assessment exercise is in prospect. Paradoxically, the UK may be moving, after 2008, to an approach close to the one being abandoned in Australia.

This chapter outlines the circumstances in South Africa (SA) that led to the evolution of the profession of research management and administration (RMA) in the country. The public higher education (HE) sector has undergone significant change since 1994, and the RMA profession has struggled to keep abreast. However, through its national professional society, SARIMA, a concerted effort is being made to facilitate and advance the RMA pipeline.

SARIMA was instrumental in developing the Professional Competency Framework for SA and is now focussed on creating awareness and providing development opportunities for RMAs to meet the requirements.

RMA in SA is proliferating as the public HE sector expands in response to growing demands and deliberate interventions by the government.

Recent literature on nonprofit boards of directors has extensively investigated the composition, role, responsibilities, and characteristics of boards. Given the growing number of studies on nonprofit boards, which added new impulse to the debate on the role and characteristics of these players, it is time to analyze the state of the art and systematize the current knowledge. On the other hand, despite the presence of some literature reviews, a research comparing the debate among the nonprofit, private, and public sectors is still lacking. Using Gabrielsson and Huse’s (2004) framework, we wanted to identify factors that can influence research on nonprofit boards and compare our results with existing studies on private and public sector.

We conduct a systematic literature review, selecting empirical articles published in international scientific journals from 1992 to 2012.

We found similarities and differences in relation to research on boards among sectors. As a common result, we found that evolutionary studies still remains a neglected area in all of three realms. Finally, whereas input–output studies prevail in the private sector and contingency studies prevail in the public sector, behavioral studies prevail in the nonprofit sector, demonstrating, also, that the sector itself can make a difference in the board’s research.

This literature review provides some suggestion for further research on boards for all of three sectors. For example, we suggest complementing research on boards on all three sectors, especially in relation to evolutionary studies.

This paper fills the need to clarify the status of research on nonprofit boards, in order to address scholars in the understanding of the phenomenon.

Since the 1980s, US universities have greatly increased attention given to innovation and entrepreneurship out of a genuine commitment to enhancing American competitiveness. Although regional innovation and entrepreneurship can be enhanced by universities in multiple ways, the primary metrics of “success” remain patenting, licensing rates, and university spin-outs. While these metrics can be a useful proxy for the entrepreneurial university they tend to understate the many important contributions universities, including non-research intensive universities, make to their regional economies. In this chapter, we introduce a framework of capabilities that are essential to nurturing ecosystems of innovation and entrepreneurship at the regional level. We then describe the varied ways in which universities can support the development of these capabilities. Finally, we provide a framework of metrics, which can more comprehensively capture the value that universities represent to innovation and entrepreneurship in their regions.