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This article aims at contributing to the development of a Marxist theory of the production of knowledge, and in particular of natural sciences and techniques (NST), under capitalism. It rejects the double critique that the labor theory of value has become obsolete under modern capitalism and that Marx’s theoretical structure cannot accommodate mental production. The paper starts with two preliminary sections. First, some relevant aspects of dialectics as a tool of social research are submitted. Then, notions such as Information Society or Service Society are debunked. On this basis, the production of individual and of social knowledge is inquired into and the conditions for knowledge production to be production of (surplus) value are analyzed. Next, the question is tackled as to why and how this knowledge (and in particular NST) is functional for the interests of the capitalist class, even though in a contradictory way. Several examples are provided. Particular attention is paid to the computer and to biotechnology and genetic engineering. The most common objections against the thesis of the class determination of knowledge are dealt with. It is argued that class determination of knowledge can explain why the science and techniques developed in one society and by one class can be used in other societies and by other classes. Examples are provided of trans-class and trans-epochal elements of knowledge. Finally, the last section submits that a radically different type of NST can originate only from a radically different type of society, based on radically different production relations.

This chapter attempts to theorize the role of knowledge in the determination of the value of commodities. This draws from the South Korean controversy on the value and price of information commodities such as computer software and digital music. One group of writers has argued that the value of software copies (=commodities) is contributed by the labor time expended to produce the source code (=knowledge) in a piecemeal fashion. For another group, the source code has nothing to do with the production of the value of copies given that the source code is unnecessary for the (re)production of copies, and thus the value of software copies is approximately zero and its price is a high monopoly price. Both approaches are flawed. In the case of the former, no value can actually be transferred from the source code to copies because no changes are made to the source code before or after the production of copies. In case of the latter, knowledge is viewed as having nothing to do with value production. On the basis of this critique, an alternative view is put forward, in which knowledge plays an important role in value production by determining the productivity and/or complexity of labor. Knowledge “virtually intensifies” labor. It is also argued that intellectual property rights should be theorized in a way to refine and reproduce the role of knowledge – the virtual intensification of labor – at more complex and concrete levels of analysis.

This chapter offers a complementary view to the “quality of knowledge” perspective whereby citations to academic articles are a result of efficient market processes. The chapter suggests that any academic research can be seen through the prism of two types of knowledge networks – production and usage. Author(s) of papers are located in these two networks and their absolute and relative position in these networks can help the diffusion of the focal research. The hypotheses are tested on a dataset of 1,085 papers published in the top five management journals between 1993 and 1997. Results suggest that controlling for attributes of a paper, the position occupied by author(s) in the usage networks and production networks contributes substantially to future citations received by a paper in these five journals. However, under conditions of extreme prominence in the usage network, increases in prominence in the production network dampen increase in future citations. Similarly under conditions of extreme prominence in the production network, increases in prominence in the usage network dampen increase in future citations. Implications of these results are discussed in the context of knowledge creation, dissemination, and recognition efforts of authors.

The authors explore the emergence of altmetrics and Open Access (OA) publishing and discuss why their adoption in the management field lags behind other fields such as life sciences. The authors draw on the status literature to discuss the knowledge production and consumption underpinned by the ‘Impact Factor’ metric and high-status ‘Toll Access’ journals and their implications. The authors explain the rise of altmetrics and OA publishing and their implications on the production and consumption of knowledge. The authors then examine the current situation, challenges and offer reflections on the management field’s progression towards a more open research regime in the digital era.

This chapter argues that neoliberal governmentality in immunization relocates the Turkish state's position regarding vaccine and immunization policies. Neoliberalism is often discussed in the context of privatization, performance, and effectiveness separately. However, more attention should be paid to the set of strategies that are employed in public policy processes to manage populations in terms of immunization, while intertwining power with knowledge. Following Foucault's concept of governmentality and taking it further within the context of biopolitics, this chapter focuses on different knowledge practices regarding vaccine and immunization policies in Turkey. In doing so, this case study applies a post-structural analysis to examine vaccine production, vaccine know-how, and immunization policies inscribed in policy documents as a form of knowledge practice. The analysis sheds light on the reflexive transformation of the concept of biopolitics, which is moving from state-oriented knowledge practices toward a neoliberal governmentality of immunization.

Researchers continue to seek understanding of industrialization as a state managed process. How to create and implement new industries based on advanced knowledge is on the policy agenda of many advanced nations. Measures that promote these developments include national capacity building in science and technology, the formation of technology transfer systems, and the establishment of industrial clusters. What these templates often overlook is an analysis of use. This chapter aims to increase the understanding of the processes that embed new solutions in structures from an industrial network perspective. The chapter describes an empirical study of high-technology industrialization in Taiwan that the researcher conducts to this end. The study shows that the Taiwanese industrial model is oversimplified and omits several important factors in the development of new industries. This study bases its findings on the notions that resource combination occurs in different time and space, the new always builds on existing resource structures, and the users are important as active participants in development processes.

In this paper, we present and apply a new framework – the Poles of Production for Producers/Poles of Production for Users (PFP/PFU) model – to empirically study how one particular group of academic scientists has responded to neoliberal changes in science policy and funding in Canada. The data we use are from a qualitative case study of 20 basic health scientists affiliated with a research-intensive university in a large Canadian city. We use the PFP/PFU model to explore the symbolic strategies (the vision of scientific quality) and practical strategies (the acquisition of funding and production of knowledge outputs) scientists adopt to maintain or advance their own position of power in the scientific field. We also compare similarities and differences among scientists trained before and after the rise of neoliberal policy. The PFP/PFU model allows us to see how these individual strategies cumulatively contribute to the construction of dominant and alternate modes of knowledge production. We argue that the alignments and misalignments between quality vision and practice that scientists in this study experienced reflect the symbolic struggles that are occurring among scientists, and between the scientific and political field, over two competing logics and reward systems (PFP/PFU).

One common feature of different variants of participatory and action research is rejection of technocratic, undemocratic elements in science and inquiry, aiming to break the dominance of traditional academic views of science. These variants open up broader participation of people, and emancipate knowledge creation for the production of actionable knowledge with transformative potentials. The purpose of this chapter is to recognize and clarify a striving for knowledge democracy in these explicit or implicit democratizing ambitions and tendencies in the sense of broadening the participation of concerned parties in research and development work on open and equal terms. This recent concept, still in the process of formulation, has been proposed as a global mobilizing and unifying thinking for distributed networks and movements for participatory oriented research. The concept and movement had an initial embedding in the First Global Assembly for Knowledge Democracy in June 2017, Cartagena, Columbia. The purpose of the chapter is to elaborate on the meaning of knowledge democracy as a vision for the participatory and action research community. Particularly I will distinguish between different orientation to knowledge democracy, and the character of the logic of a more, open, democratic and coproductive science that can be a carrier of it.

This chapter is about the production, diffusion and use of knowledge seen in an economic perspective. Fundamental distinctions between tacit and explicit knowledge and between know-how, know-why, know-what and know-who are related to distinctions between public/private and local/global knowledge. It is argued that the idea of the economy as being knowledge based is misleading and that we have moved into a learning economy where interactive learning is a key to economic performance of firms, regions and nations. This is one reason why a narrow economic perspective is insufficient. When it comes to understand industrial dynamics in the learning economy it is necessary to bring in other disciplines than economics in the analysis.

This chapter provides an overview of the findings and chapters of a thematic volume in the International Perspectives on Education and Society (IPES) series. It describes the common dataset and methods used by an international research team.

The chapter synthesizes the results of a series of country-level case studies and cross-national and regional comparisons on the growth of scientific research from 1900 until 2011. Additionally, the chapter provides a quantitative analysis of global trends in scientific, peer-reviewed publishing over the same period.

The introduction identifies common themes that emerged across the case studies examined in-depth during the multi-year research project Science Productivity, Higher Education, Research and Development and the Knowledge Society (SPHERE). First, universities have long been and are increasingly the primary organizations in science production around the globe. Second, the chapters describe in-country and cross-country patterns of competition and collaboration in scientific publications. Third, the chapters describe the national policy environments and institutionalized organizational forms that foster scientific research.

The introduction reviews selected findings and limitations of previous bibliometric studies and explains that the chapters in the volume address these limitations by applying neo-institutional theoretical frameworks to analyze bibliometric data over an extensive period.