Search results

Purpose – This chapter examines the need, and possibilities, for social science research that is grounded in the life sciences.

Design/methodology/approach – The chapter starts with the observation that the social sciences have been tied far too closely to models and concepts in the physical sciences, which has both limited and distorted research findings. The predominant models used in much of social science cannot meet the challenges we face. Examining issues in political science in particular, the author demonstrates the value of a biopolitical perspective for political science research and policy analysis relevant to the challenges we face.

Findings – Studies about human issues should be based on research that considers humans as part of the evolving biological world. Key biopolicy research areas illustrate the value and flexibility of life science models and data. Political science can and should provide important insights to our understanding of socio-political issues and options, but to succeed the discipline must abandon mechanistic models of human nature and motivation and return to an understanding based in the life sciences.

Practical implications (if applicable) – The discussion analyzes the overall strengths and weaknesses of the proposal to adopt a biopolicy approach, and concludes that obstacles, though real, can be overcome. There are opportunities for substantial contributions to social science.

Social implications (if applicable) – Failure to integrate political science with a life sciences perspective will mean a continuation of disciplinary work that is largely irrelevant or inadequate to emerging issues and problems.

Original/value of chapter – The value of this chapter is to highlight the need for a reexamination of the mechanistic models as well as the disciplinary boundaries that control most social science, and political science in particular. It examines widely recognized issues and challenges facing Western societies (and global communities) to illustrate that a life sciences perspective is essential to both analysis and policy options. It is an important consideration for academics (teachers and students) policy researchers, and policy makers as well.

The purpose of this study is to identify the factors that contribute to the successful implementation and management of sustainable innovation in research-intensive sectors such as the life sciences industry.

The study was conducted through a combination of two methods. The first was qualitative interviews of 21 sustainability experts and leaders in the life sciences industry who were responsible for implementing sustainable innovation. They were selected through nonprobabilistic purposive sampling. The second method was thematic content analysis using the MAXQDA software.

The study identified that successful implementation of sustainable innovation in research-intensive firms begins with the alignment of the executive vision for sustainability with the business objectives of the research-intensive firm. Furthermore, implementation of sustainability practices is identified as a function of organizational reconfigurations that facilitate purposeful inflow and outflow of ideas and knowledge between internal firm resources and external stakeholders, anchored by the objectives of the research-intensive firm.

The study explicated factors only within life sciences industry based on qualitative interviews. The study offers scope for cross-sector quantitative evaluation.

To the best of the authors’ knowledge, this study is among the first studies to systematically delineate the underlying factors that govern successful implementation of sustainable innovation in research-intensive industries, through integration of the resource-based view and stakeholder theory and thereby provide a framework for research-intensive organizations to implement sustainable innovation practices.

Business accelerators have recently received increasing attention as important cogs in business ecosystem development. However, their exact role in the ecosystem is not yet well known, especially outside the IT sector. The purpose of this study is, therefore, twofold: to determine the position of life science accelerators in the business ecosystem and the attributes of support for companies and to identify key features of the life science accelerators that contribute to the change in business ecosystems.

The authors offer an exploratory case study of five life science business accelerators and analyze the main factors affecting the companies and the whole business ecosystem. The authors build upon the scarce literature on business accelerators and consider a new type of accelerator that specializes in life science projects and study its role in the transformation and evolution of the life science industry.

The authors have defined the role and key parameters of life science accelerators that influence the existing business ecosystems: (1) cooperation with other regions and countries, (2) development of entrepreneurial skills among participants of the business accelerators program and (3) a project on demand-based approach.

The key parameters of the life science accelerators allow to concentrate these efforts on the activities that are most demanded by the market. Business accelerators can increase the created value for other program participants.

Life science innovation is a complex domain of professional work including scientific know-how, regulatory expertise, and commercialization and marketing skills. While the investment in basic life science research has soared over the last decades, resulting in a substantial growth in scientific know-how, the life science industry (and most notably pharmaceutical companies) unfortunately reports a meagre innovative output. In order to counteract waning innovation productivity, new organizational initiatives seek to better bridge and bond existing life science resources. The purpose of this paper is to report a case study of bio venture hub initiative located in a major multinational pharmaceutical company.

Drawing on institutional work literature, an empirical study based on case study methodology demonstrates that new life science collaborations demand both external and internal institutional work to challenge conventional wisdom, making the legal protection of intellectual properties a key factor in the field and that in turn complicates much firm collaborations. Such institutional work questions existing practices and opens up new pathways in life science innovation work.

The bio hub initiative, which in considerable ways breaks with the traditional in-house and new drug development activities located in enclosed R&D departments and in collaboration with clinical research organizations, demands extensive institutional work and political savoir-faire to create legitimacy and operational stability. Not only are there practical, legal, and regulatory issues to handle, but the long-term legitimacy and financial stability of the bio hub initiative demands support from both internal and external significant actors and stakeholders. The external institutional work in turn demands a set of skills in the bio venture hub’s management team, including detailed scientific and regulatory expertise, communicative skills, and the charisma and story-telling capacities to convince and win over sceptics. The internal institutional work, in turn, demands an understanding of extant legal frameworks and fiscal policies, the ability to handle a series of practical and administrative routines (i.e. how to procure the chemicals used in the laboratory work or how to make substance libraries available), and to serve as a “match-maker” between the bio venture hub companies and the experts located at the hosting company.

The case study provides first-hand empirical data from an unique initiative in the pharmaceutical industry to create novel collaborative spaces where small-sized life science companies can take advantage of the mature firm’s expertise and stock of know-how, also benefitting the hosting company as new collaborations unfold and providing a detailed understanding of ongoing life science innovation projects. In this view, all agencies embedded in institutional field (i.e. what has been addressed as “institutional work” – the active work to create, maintain, or disrupt institutions) both to some extent destabilize existing practise and create new practices better aligned with new conditions and relations between relevant and mutually dependent organizations. The empirical study supports the need for incorporating the concept of agency in institutional theory and thus contributes to the literature on institutional work by showing how one of the industries, the pharmaceutical industry, being strongly fortified by intellectual property rights (i.e. a variety of patents), inhibiting the free sharing of scientific and regulatory know-how and expertise, is in fact now being in the process of rethinking the “closed-doors” tradition of the industry. That is, the institutional work conducted in the bio venture hub is indicative of new ideas entering Big Pharma.

The purpose of this paper is to examine the development of R&D resources in early stage life sciences firms. It looks at how young firms use dynamic capabilities to develop R&D resources.

An in-depth case study approach was used to examine the research questions. It draws on longitudinal data collected from ten life science firms. Data were collected from three rounds of interviews with each case firm. A systematic theme analysis was conducted to analyse the results.

Results from the study indicate that a unique set of past decisions, future opportunities, assets, capabilities, and routines leads to the development of R&D resources. It is evident that scientific breakthroughs, partnership opportunities, the founders’ experience and the firm’s ability to integrate resources and learn from earlier paths are vital to the development of R&D resources.

This study extends the application of the dynamic capabilities framework to early stage life sciences ventures. It also demonstrates that dynamic capabilities can lead to the development of important resources.

The findings from this study provide prescriptive insights for evaluating alternatives on how to develop R&D resources in life sciences ventures.

Life sciences firms are critical to the modern global economy. However, little work examines how young, small life sciences firms develop R&D resources. Moreover, little work uses the dynamic capabilities framework as a lens to holistically examine how small firms develop R&D resources. This study helps to fill those gaps.

The purpose of this paper is to clarify how university‐industry (U‐I) collaboration differs by technology fields in Japan.

An analysis of the research resource allocation in the Japanese national universities in the Japanese national innovation system is followed by the analysis of U‐I collaboration by technology fields. The fields analyzed are life science, information and communication technology (ICT), environment science, nanotechnology and material science, which have been designated as strategically important fields by the Second Japanese Science and Technology Basic Plan. The analysis was conducted in a quantitative way using government data of R&D expenditure, researchers, patent application, joint research, contract research and university spin‐offs.

Some characteristics of U‐I collaboration have been quantitatively found by technology fields. Though the national universities occupy large R&D expenditure shares in life science and nanotechnology/material science in the Japanese national innovation system, their joint research and contract research are fairly active in environment science as well as in life science and in nanotechnology/material science. For university spin‐offs, the national universities are active in life science and ICT.

This paper quantitatively clarifies U‐I collaboration by technology fields showing relative importance of U‐I collaboration by technology fields. The results provide information input to policy makers when they formulate policies to promote U‐I collaboration by technology fields and to corporate managers when they make U‐I collaboration strategies by technology fields as a part of open innovation strategies.

Drawing upon Alfred Sohn-Rethel's work, we argue that, just as capitalism produces abstract labor, it coproduces both abstract mind and abstract life. Abstract mind is the split between mind and nature and between subject/observer and observed object that characterizes scientific epistemology. Abstract mind reflects an abstracted objectified world of nature as a means to be exploited. Biological life is rendered as abstract life by capitalist exploitation and by the reification and technologization of organisms by contemporary technoscience. What Alberto Toscano has called “the culture of abstraction” imposes market rationality onto nature and the living world, disrupting biotic communities and transforming organisms into what Finn Bowring calls “functional bio-machines.”

Nobody concerned with political economy can neglect the history of economic doctrines. Structural changes in the economy and society influence economic thinking and, conversely, innovative thought structures and attitudes have almost always forced economic institutions and modes of behaviour to adjust. We learn from the history of economic doctrines how a particular theory emerged and whether, and in which environment, it could take root. We can see how a school evolves out of a common methodological perception and similar techniques of analysis, and how it has to establish itself. The interaction between unresolved problems on the one hand, and the search for better solutions or explanations on the other, leads to a change in paradigma and to the formation of new lines of reasoning. As long as the real world is subject to progress and change scientific search for explanation must out of necessity continue.

The purpose of this paper is to analyze the different assessments of a particular industry and its ability to innovative, renew and prosper, but also to look into the underlying assumptions that are hiding behind the systemic approaches utilized in these assessments. The point of departure is an empirical puzzle: one group of studies presents a rather optimistic view of the Swedish life science industry and its ability to economize on research, policy and industrial investments. Another group of studies presents much a darker view, questioning the capacity of new companies to reach economic endurance, as well as the possibility of keeping the actually successful companies within the country. At a first sight it appears as if the two groups of studies are resting on a common theoretical ground: all seem to depart from a systemic innovation perspective that challenges the idea of an independent business landscape.

The difference between the assessments becomes comprehensible once the authors allow for a variety of systemic approaches in innovation thinking. The authors propose an ideal-typical distinction between two types of system perspectives; those that view technology as entangled in its environment and those that view technology as disentangled from its environment. The authors use the national innovation system (NIS) and the industrial network (IMP) approaches to exemplify the two perspectives.

An implication of the study is that the term “systemic perspective” is very broad and encompassing, something that in turn points to the importance of being clear about what the authors mean with a system, but also with what the theoretical assumptions focus on and abstract away from.

The ideal-typical distinction between two types of system perspectives; those that view technology as entangled in its environment and those that view technology as disentangled from its environment. The authors use the NIS and the IMP approaches to exemplify the two perspectives.

This paper aims to determine the extent to which graduate student funding portfolios vary across and within engineering, life sciences and physical sciences academic fields for degree recipients. “Graduate student funding portfolios” refers to the percentages of students funded by fellowships, research assistantships, teaching assistantships, personal means and other sources within an organizational unit.

Using data from the Survey of Earned Doctorates data set, the authors analyze doctoral students’ self-reported primary mechanisms of funding across and within academic fields varying along the Biglan taxonomy. The authors used cluster analyses and logistic regression to investigate within-field variation in funding portfolios.

The authors show significant differences in doctoral student funding portfolios across dimensions of the Biglan taxonomy characterizing academic fields. Within those fields, the authors demonstrate considerable variation in funding; institutions cluster into different “modes” of funding portfolios that do not necessarily map onto institutional type or control variables.

Despite tremendous investment in graduate students, there has been little research that can help characterize at the program-level how graduate students are funded, either by internal or external mechanisms. As programs continue to feel the pressures of more limited resources coupled with increasing graduate enrollment demands, investigating graduate student funding at a macro level is becoming increasingly important so programs may better understand constraints and predict shifts in resource availability.