Changes in innovation styles - comprehensive study of the changes in innovation styles to identify the causes and effects of different influencing factors and capabilities to create a general innovation pattern.

An investigation in innovation management and entrepreneurial management is conducted in this thesis. The aim of the research is to explore changes of innovation styles in the transformation process from a start-up company to a more mature phase of business, to predict in a second step future sustainability and the probability of success. As businesses grow in revenue, corporate size and functional complexity, various triggers, supporters and drivers affect innovation and company's success. In a comprehensive study more than 200 innovative and technology driven companies have been examined and compared to identify patterns in different performance levels. All of them have been founded under the same formal requirements of the Munich Business Plan Competition -a research approach which allowed a unique snapshot that only long-term studies would be able to provide. The general objective was to identify the correlation between different factors, as well as different dimensions, to incremental and radical innovations realised. The 12 hypothesis were formed to prove have been derived from a comprehensive literature review. The relevant academic and practitioner literature on entrepreneurial, innovation, and knowledge management as well as social network theory revealed that the concept of innovation has evolved significantly over the last decade. A review of over 15 innovation models/frameworks contributed to understand what innovation in context means and what the dimensions are. It appears that the complex theories of innovation can be described by the increasing extent of social ingredients in the explanation of innovativeness. Originally based on tangible forms of capital, and on the necessity of pull and technology push, innovation management is today integrated in a larger system. Therefore, two research instruments have been developed to explore the changes in innovations styles. The Innovation Management Audits (IMA Start-up and IMA Mature) provided statements related to product/service development, innovativeness in various typologies, resources for innovations, innovation capabilities in conjunction to knowledge and management, social networks as well as the measurement of outcomes to generate high-quality data for further exploration. In obtaining results the mature companies have been clustered in the performance level low, average and high, while the start-up companies have been kept as one cluster. Firstly, the analysis exposed that knowledge, the process of acquiring knowledge, interorganisational networks and resources for innovations are the most important driving factors for innovation and success. Secondly, the actual change of the innovation style provides new insights about the importance of focusing on sustaining success and innovation ii 16 key areas. Thirdly, a detailed overview of triggers, supporters and drivers for innovation and success for each dimension support decision makers in putting their company in the right direction. Fourthly, a critical review of contemporary strategic management in conjunction to the findings provides recommendation of how to apply well-known management tools. Last but not least, the Munich cluster is analysed providing an estimation of the success probability of the different performance cluster and start-up companies. For the analysis of the probability of success of the newly developed as well as statistically and qualitative validated ICP Model (Innovativeness, Capabilities & Potential) has been developed and applied. While the model was primarily developed to evaluate the probability of success of companies; it has equal application in the situation to measure innovativeness to identify the impact of various strategic initiatives within small or large enterprises. The main findings of the model are that competitor, and customer orientation and acquiring knowledge important for incremental and radical innovation. Formal and interorganisation networks are important to foster innovation but informal networks appear to be detrimental to innovation. The testing of the ICP model h the long term is recommended as one subject of further research. Another is to investigate some of the more intangible aspects of innovation management such as attitude and motivation of mangers. IV

Strength grading of sawn timber in Europe: an explanation for engineers and researchers.

This paper is a concise explanation of the normative background to strength grading in Europe, addressing important aspects that are commonly misunderstood by structural engineers and timber researchers. It also highlights changes that are being made to the standards to: incorporate requirements of the construction products regulations; add improvements to the system to accommodate the latest knowledge and technology; and widen the application of the standards. Where designs need to be optimised, there is an opportunity to use the system more intelligently, in combination with the latest technology, to better fit design values to the true properties of the timber resource. This can bring a design enhancement equivalent to effort improving other aspects of the structure, such as connectors and reinforcement. Parallel to this, researchers working on other aspects of structural improvement need to understand what grades really mean in respect of the properties of the timber, in order to correctly analyse the results of testing. It is also useful to know how techniques used in grading can assist with material properties characterisation for research. The amount of destructive testing involved in establishing machine grading settings and visual grading assignments presents a barrier to greater use of local timber, and diversification of commercial species, so it is important that any researcher assessing the properties of such species should consider, from the outset, doing the research in a way that can contribute to a grading dataset at a later date. This paper provides an overview of what is required for this.