Technology Policy and Co-operative R&D the role of Relational Research Capacity

Evolutionary theories of technological change and industrial dynamics give primary importance to interaction between heterogeneous agents, endowed with complementary assets and competencies. Accordingly, support to co-operative R&D is central to technology policy, as a mean for increasing system connectivity, triggering virtuous cycles of learning and promoting variety. The paper investigates the “chemistry of technological co-operation”, relating its effectiveness and results to the partners’ relational research capacity, i.e. their ability to evaluate, integrate, process and exploit knowledge flows generated by the interaction. A functional specification for the relational research capacity is proposed and its properties are investigated. The formal analysis works as a guideline for the statement of research hypothesis related to the effectiveness of co-operative R&D programmes, to be tested on empirical grounds.Technological co-operation, Innovation, absorptive capacity, competence integration

Knowledge Specialization, Knowledge Brokerage and the Uneven Growth of Technology Domains

Why do certain domains of knowledge grow fast while others grow slowly or stagnate? Two distinct theoretical arguments hold that knowledge growth is enhanced by knowledge specialization and knowledge brokerage. Based on the notion of recombinant knowledge growth, we show that specialization and brokerage are opposing modes of knowledge generation, the difference between them lying in the extent to which homogeneous vs. heterogeneous input ideas get creatively recombined. Accordingly, we investigate how both modes of knowledge generation can enhance the growth of technology domains. To address this question, we develop an argument that reconciles both specialization and brokerage into a dynamic explanation. Our contention is that specializing in an increasingly homogeneous set of input ideas is both more efficient and less risky than brokering knowledge. Nevertheless, specializing implies progressively exhausting available recombinant possibilities, while brokerage creates new ones. Hence, technology domains tend to grow faster when they specialize, but the more specialized they become, the more they need knowledge brokerage to grow. We cast out our argument into five hypotheses that predict how growth rates vary across technology domain

Biotechnology value chains as a case study of the knowledge economy : the relationship between knowledge, space and technology

The overall scope of this thesis is to consider the relationship between knowledge, space and technology in the ‘knowledge economy’ by drawing upon biotechnology value chains as a case study of the knowledge economy. Central to this is the claim that although biotechnology is an internationally distributed sector, it is also concentrated in specific places because those locations provide an advantage through dynamic innovation processes. Such processes are embedded in places because those places have a particular set of knowledge inputs and provide access to other knowledge inputs outwith those places. In this sense, the knowledge economy can be seen as dependent upon different places and scales that all contribute to the innovation process and therefore necessitate relationships within and between different and diverse locations. The major contribution to knowledge that the thesis provides is the development of a new conceptual understanding of innovation processes called the knowledge-space dynamic that focuses on the knowledge and spatial features of the innovation process rather than assuming that the concentration of innovation necessarily entails specific knowledge and spatial characteristics. Consequently the thesis picks apart the current emphasis on certain types of knowledge (e.g. tacit and explicit) to explore the ways in which these are combined in the innovation process and embedded in particular places. Thus the research approach in the thesis adopts a new methdological framework to collect and analyse secondary and primary data that has not been previously undertaken. Overall the thesis conclusion is that the knowledge economy – and especially the biotech industry – may not represent the best method for regional development

Managing the development of valuable intellectual capital : the role of management control

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Technology and Australia's Future: New technologies and their role in Australia's security, cultural, democratic, social and economic systems

Chapter 1. Introducing technology -- Chapter 2. The shaping of technology -- Chapter 3. Prediction of future technologies -- Chapter 4. The impacts of technology -- Chapter 5. Meanings, attitudes and behaviour -- Chapter 6. Evaluation -- Chapter 7. Intervention -- Conclusion - adapt or wither.This report was commisioned by Australian Council of Learned Academies

Challenging the exploration and exploitation dichotomy: towards theory building in innovation management

The conceptual dichotomy between exploration and exploitation, importantly highlighted in March’s (1991) seminal paper, has been widely employed to study innovation management processes and resource allocation decisions in organisations. Despite its extensive usage, the validity of this dichotomy has not been subjected to adequate theoretical scrutiny and empirical support. Therefore, this thesis provides a critical examination of the origins and consequences of exploration and exploitation, and questions this dichotomy especially as pertaining to its application in innovation management. It challenges the taken-for-granted assumption that these two concepts refer to distinct and observable decision-making processes and concludes that this is an assumption largely unwarranted. A systematic literature review about the use of this dichotomy was conducted in the context of innovation management and the findings confirmed that although studies have proposed related notions, such as ambidexterity, as a way to overcome the supposed trade-off between exploration and exploitation. It is confirmed that there has been no attempt hitherto to question the validity of this dichotomy. Also, little empirical evidence was found to suggest that the understanding of managing innovation can be enhanced through a reliance on this dichotomy. Thus, it is argued that the employment of this dichotomy in practices for managing innovation has not been justified and should be investigated directly through empirical evidence. To investigate exploration and exploitation both as performance criteria and internal processes, a mixed-method design that utilises data envelopment analysis (DEA) as quantitative method, and a focus group supplemented by interviews as the qualitative method was relied on. Findings from DEA indicated that exploration and exploitation can be used as criteria for performance evaluation in innovation. However, findings from the qualitative part of the study suggested that in practices for innovation management, exploration and exploitation are not viewed as separated internal processes; hence, this distinction is not featured in decision-making during innovation processes. This means that the classification based on exploration and exploitation is not used for appraisal of activities or projects in managing innovation. It is therefore concluded that the dichotomy of exploration and exploitation is not valid in practices for innovation management and thus its application in theorising innovation should be reconsidered; thus, studies of innovation management should not unquestioningly rely on this dichotomy, because it does not reflect organisational reality. Consequently, this study contributed to innovation management literature by pointing to alternative possible directions, such as ‘problem-solving’, in theorising the processes of innovation management for future studies

the role of relational research capacity

Evolutionary theories of technological change and industrial dynamics give primary importance to interaction between heterogeneous agents, endowed with complementary assets and competencies. Accordingly, support to co-operative R&D is central to technology policy, as a mean for increasing system connectivity, triggering virtuous cycles of learning and promoting variety. The paper investigates the “chemistry of technological co-operation”, relating its effectiveness and results to the partners’ relational research capacity, i.e. their ability to evaluate, integrate, process and exploit knowledge flows generated by the interaction. A functional specification for the relational research capacity is proposed and its properties are investigated. The formal analysis works as a guideline for the statement of research hypothesis related to the effectiveness of co-operative R&D programmes, to be tested on empirical grounds