Introductionhis paper is about the relationship between core competencies and R&D strengths, and the way in which this relationship may be addressed systematically. IT can help by making it possible to analyse quite large volumes of data apparently objectively. But to be effective, it needs to be supplemented by metaphors and visualizations.We start by exploring the relationship between the relatively recent theory of core competencies and the practice of technology management. We show that the theory has strong implications for R&D. Core competencies, technology and R&DWhile there is a substantial literature dealing with technology management, concerted attempts to delineate clearly technology management appear to be R&D Management 28, 1, 1998.Though it is now universally accepted that companies should try to align their R&D activities with their business objectives, achieving this alignment is notoriously difficult in practice. The rise of the core competence framework has been very helpful in creating, and legitimizing, a language in which issues of technical competence and R&D strengths can be followed through to their consequences for competitive advantage. Companies are starting to express their R&D priorities explicitly in terms of core competencies. Without effective IT support, core competence concepts are often applied arbitrarily. This has led to accusations that core competence theory can become yet another battlefield upon which companies play out their internal political battles. Computer-based techniques can help counteract this danger by enabling large volumes of relatively objective data to be collected, then making it possible to analyse and draw out patterns from this data, and finally enabling the data to be represented effectively.It is in this last area of data representation that information technology is now of particular benefit. In order to make the core competence approach sufficiently robust as a basis for decision making, it is necessary to collect and process large volumes of data. However, this data is normally difficult to represent in such a way that managers can assimilate it. In our recent experience, we have come to realize the particular importance of effective representations and metaphors, and have started to shift our own emphasis towards these areas in addition to analysis per se.The paper shows how core competence approaches can support R&D management decision making by exploring the roles of data collection, analysis and representation. Information technology is an integral part of these approaches, and we draw out some generalized lessons for the successful use of IT in decision support.
While business strategy has become synonymous with the search for competitive advantage, the concept of competitive advantage is surprisingly confused.• Often the term is nothing more than a tautology. Successful firms are successful because they have competitive advantage, which in turn cannot be defined in any other way than as a quality that brings about success.• There is also ambiguity as to the locus of competition: whether competitive advantage is a property of firms or of products. This ambiguity creates confusion over the processes by which competition occurs.• Greater distinction and definitional clarity should be made between competition and strategy. Better strategies will result from more accurate pinpointing of the processes of competition, something that is unlikely while competition is simply seen in terms of competitive advantage.
Innovation is said to be the key to future markets, business development and economic growth, yet the concept of innovation remains abstract and ambiguous. This paper suggests any value creation intentions need to recognise that innovation is a context-dependent process which is implicitly and fundamentally informed through the social agendas and consensus of those involved. To inform this social perspective of innovation value creation, we ask, how does the 'sociology of innovation' influence value creation? Using a 'sociology of innovation' standpoint, a qualitative study of participants in Australian bioindustry research and development (R&D) was undertaken to explore how the various sociocontextual frameworks and dominant outcome intentions were involved in value creation in the development of new biotechnological innovations. Through the two themes of context and community, we reveal how value creation was shaped by dynamic social processes involving multiple stakeholders and diverse perspectives of innovation. This research improves our understanding of how those involved in innovation development negotiate a complex social milieu of interpretive schemas to leverage various aspects of value creation. These findings present insights to managers and policy makers seeking to advance innovation value and advantages.
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