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This paper seeks to address the importance of knowledge production and capabilities for the construction industry; and the implications of the challenges associated with their effective exploitation for the construction industry in China.

A thorough review of extant literature and 31 detailed semi‐structured interviews with practitioners from 14 large, medium and small organisations in the UK construction industry. Content analysis was adopted as the analytical approach.

The main triggers of knowledge production in the construction industry are: the need to effectively deal with complex projects; the effective use of new, innovative building materials, systems, services; managing change (both project change and organisational change); coping with the uniqueness of projects; and managing team member interfaces (e.g. consultant‐contractor). Knowledge production is a complex process which can occur through a number of ways (e.g. formal research, reflective practice, transformation and combination of existing knowledge). Organisational culture influences knowledge production both positively and negatively.

This paper addresses the main ways in which knowledge production can benefit construction organisations and can impact positively to organisational innovations. It addresses the role of leadership and culture in knowledge production in organisations. Skilled and competent workforce is key in knowledge production, especially in addressing problem‐solving situations. Appropriate and focused training programmes (e.g. continuing professional development events, other short courses, in‐house programmes‐mentoring, coaching, and job rotation) are important in stimulating approaches for improved knowledge production in organisations. As shortages of skilled personnel are rife in construction in China, organisations need to take the issue of knowledge production more seriously.

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).

The purpose of this research is to investigate the time structure characteristics of collaborative knowledge production behaviors in Q&A (question-and-answer) communities for explicit and tacit knowledge, and systematically investigate the supply side and the demand side of knowledge production.

Taking Zhihu as the research object, using the methods of recurrence plot and recurrence quantification analysis, this paper analyzes the recursive characteristics of the motion trajectories of the three behavioral sequences of questioning, answering, and discussion, qualitatively and quantitatively analyzing the generation and evolution mechanism of explicit and tacit knowledge.

The results show that compared with the demand-side behavior sequence, the supply-side behavior sequence exhibits higher stability, complexity and periodicity. Compared with the tacit knowledge topics, the demand-side behavior sequence of the explicit knowledge topics shows stronger nonlinearity, and the supply-side behavior sequence shows lower complexity.

The research conclusions provide preliminary evidence for the effectiveness of the recurrence plot method in distinguishing different types of knowledge production behaviors and have important application value for the “crowdsourcing” knowledge generation and identification under the knowledge economy and the sustainable development of the socialized question-and-answer community.

The purpose of this paper is to describe the knowledge generation in a cross‐disciplinary group in Norway that developed a new medical device. The aim is to shed light on how knowledge was generated and how the relationships between different communities of practice were mediated. In particular, the paper seeks to examine how material objects and contextual conditions influenced the innovation process.

In this longitudinal case study an innovation process was followed for five years, and the research material was constructed through extensive observations, interviews and document analysis.

The innovation process exhibited different themes in varying degrees of blend throughout the process. First, the practices of constructing the device and ascertaining technical feasibility are described. Then the enacted nature of the work is outlined; how it was significantly dependent on circumstantial factors, but also strongly shaped by the need to ensure clinical usability of the device. Finally, the work to package the innovation and turn it into a commercial product is explored.

In contrast with many previous studies, this study follows large parts of the innovation process, and it emphasises how knowing and practice are a result of networked, and changing, relations between both human and non‐human actors. Rather than one community of practice emerging around the innovation work, what can be called an object‐centred assemblage of communities of practice was seen, which grew and changed according to the changing nature of knowledge needs for the project to continue and succeed. This has interesting implications for the understanding of cross‐disciplinary innovation processes.

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.

Recent changes in the funding and governance of academic research in many OECD countries have altered established authority relationships governing research priorities and judgements. These shifts in the influence of a variety of groups and organisations over scientific choices and careers can be expected to affect the development of different kinds of intellectual innovations by changing the level of protected space they provide researchers and the flexibility of dominant intellectual standards governing the allocation of resources and evaluation of research outcomes. Variations in these features of public science systems influence scientists’ willingness to pursue unusual and risky projects over many years and help to explain cross-national differences in the rate and mode of development of four innovations in the physical, biological and human sciences.

This concluding chapter not only summarises the key discussions and arguments of the preceding chapters but also reflects on organisational, managerial, supervisory, behavioural, social and cultural factors shaping the miners’ reactions to the restructured and formalised deep-level mining work processes and their unofficial job tactic of making a plan (planisa). The chapter provides suggestions on how the positive aspects of planisa could be harnessed and negative aspects addressed towards efficient, productive and safer organisational, managerial, supervisory and operational practices at the rock-face down the mine.

The purpose of this paper is to show why the establishment of “learning organisations” must be a central element of knowledge management – especially in firms operating on markets where product innovation is an important parameter of competition.

The argument straddles and combines insights related to management and organisation theory with an evolutionary economic analysis of the relationship between innovation, learning and knowledge. It is supported by an empirical analysis of survey data on Danish private sector firms. The survey was addressed to all firms in the private urban sector with 25 or more employees, supplemented with a stratified proportional sample of firms with 20‐25 employees.

The analysis shows that firms that introduce several organisational practices, assumed to characterise the learning organisation, are more innovative than the average firm.

The empirical findings are limited to the private sector and do not cover public sector organisations.

The learning organisation characteristics have a positive impact on dynamic performance and there are obviously lessons to be learned from the successful firms operating in turbulent environments that introduce specific organisational characteristics such as job rotation, inter‐divisional teams, delegation of responsibility and reducing the number of levels in the organisational hierarchy.

The paper puts “knowledge management” into the wider concept of “learning economy” and shows how a key element of knowledge management is to enhance the learning capacity of the firm.

The purpose of this study is to contribute to the understanding of the failure of science parks to become a central actor in the knowledge economy and, with the help of new organizational theory, to propose new solutions.

The paper reviews a number of recent studies of science parks and their effect on innovation and economic growth, measured by revenue or survival rate of new firms, but demonstrating no positive result of the parks. The paper then introduces modern organization theory, specializing in analyzing the processes of creating, managing, organizing, and transferring knowledge distributed through a number of networks and other volatile organizations in order to investigate the set‐up of science parks in the knowledge economy.

Using Nonaka's concept of ba as a metaphor for the new tradition in organizational theory, the paper finds very few – if any – signs of these new ways of organizing in traditional science parks. The paper argues that principles from modern knowledge organizations has to be installed in science parks if the parks are to regain the initiative and become an important actor in the new regime of knowledge production. Otherwise, science parks must be viewed as an outdated institution, left over from the industrial society.

The paper proposes a system of certification and quality assessment that might speed up the change in science parks from organizations formed by the industrial society to organizations serving the needs of the knowledge society.

The paper is an original contribution to the theory of science parks and innovation policy. The use of new organizational theory on knowledge management, illustrated by Nonaka's concept of ba, presents a new solution to overcome the traditional thinking on how to organize science parks.

In this article, we analyse how variations in organisational conditions for research affect researchers’ opportunities for changing individual-level or group-level research programmes. We contrast three innovations that were developed in universities and public research institutes in Germany and the Netherlands, which enables comparisons both between organisational settings and between properties of innovations. Comparing the development of three innovations in the two types of organisations enables the identification of links between patterns of authority sharing at these organisations and the opportunities to develop innovations. On this basis, the distribution of opportunities to change research practices among researchers in the two countries can be established.