911 resultados para low and medium-low technology industries


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Publication suspended, Nov. 25 through Dec. 1922, Nov. l933 through June 1934.

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Issues for 1920-1948 called also v. [1]-29.

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"OTA-BP-H-16 December 1982" - v.2.

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"December 16, 1983; HG2401 U.S.C."

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"Serial CCC."

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Previous ed. entered under: United States. Bureau of the Census.

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The generic pharmaceutical value chain model has been employed to describe both the global pharmaceutical and biotechnology industries till now. This research investigates the organisational value chain in Australian biotechnology companies in order to assess the appropriateness of the pharmaceutical value chain to small-and medium-sized biotechnology companies. The main theme of the research is: Can a generic model of the organisational value chain be defined for the biotechnology industry? Emanating from the literature, two research propositions were developed. RP1: there are eight major definable elements/activities of the organisational value chain for the biotechnology industry. RP2: Coverage of the elements in the biotechnology value chain ranges from focused to broad. A multiple case study methodology was used to explore these propositions. To develop a number of case studies, data was collected from senior managers of small and medium Australian biotechnology companies using an interview instrument, as well as from publicly available documentation and through observation. The results were analysed using cross-case comparisons. The results showed that an aggregation of the value chains of each organisation can be reduced to these eight definable elements that constitute the biotechnology value chain: basic research, applied research, development, verification and validation, prototype development, clinical trials, manufacturing and marketing. However, the findings also indicate that these major elements of the value chain need to be further reduced into sub-activities or sub-tasks to cater for the unique differences between biotechnology companies. Generally, the findings were consistent with the literature. However, a wider sampling, including international biotechnology organisations should be studied. The major contribution of this research is in the development of a value chain model, including general sub-tasks, for the Australian biotechnology industry.

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A firm's competitive strategy and innovation processes are strongly influenced by, and must be responsive to, its competitive environment. This is nowhere more strongly evident than in the high technology industries. In the present work, case studies of biotechnology new ventures are presented. These studies illustrate how an initial market entry strategy of parallel competition (through creative imitation) has enabled several biotechnology start-ups to reduce their mortality risk. We coin the term ''parallel bridge'' to describe this strategy. The parallel bridge provides early cash flows which support research and development and provide time for new ventures to develop core competencies, including a capacity to produce second and third horizon products that will sustain longer term competitiveness.

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At a broad level, it has been shown that different institutional contexts, policy regimes and business systems affect the kinds of activities in which a nation specialises. This paper is concerned with the way in which different national business systems affect the nature of participation of a nation in the knowledge economy. The paper seeks to explain cross-national variations in the knowledge economy in the Australia, Denmark and Sweden with reference to dominant characteristics of the business system. Although Australia, Denmark and Sweden are all small wealthy countries, they each have quite distinctive business systems. Australia has been regarded as a variant of the competitive business system and has generally been described as an entrepreneurial economy with a large small firm population. In contrast Sweden has a coordinated business system that has favoured large industrial firms. The Danish variant of the coordinated model, with its well-developed vocational training system, is distinguishable by its large population of networked small and medium size enterprises. The three countries also differ significantly on two dimensions of participation in the knowledge economy. First, there is cross-national variation in patterns of specialisation in knowledge intensive industries and services. Second, the institutional infrastructure of the knowledge economy (or the existing stock of knowledge and competence in the economy, the potential for generation and diffusion a new knowledge and the capacity for commercialisation of new ideas) differs across the three countries. This paper seeks to explain variations in these two dimensions of the knowledge economy with reference to characteristics of the business system in the three countries.

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Air Traffic Control Laboratory Simulator (ATC-lab) is a new low- and medium-fidelity task environment that simulates air traffic control. ATC-lab allows the researcher to study human performance of tasks under tightly controlled experimental conditions in a dynamic, spatial environment. The researcher can create standardized air traffic scenarios by manipulating a wide variety of parameters. These include temporal and spatial variables. There are two main versions of ATC-lab. The medium-fidelity simulator provides a simplified version of en route air traffic control, requiring participants to visually search a screen and both recognize and resolve conflicts so that adequate separation is maintained between all aircraft. The low-fidelity simulator presents pairs of aircraft in isolation, controlling the participant's focus of attention, which provides a more systematic measurement of conflict recognition and resolution performance. Preliminary studies have demonstrated that ATC-lab is a flexible tool for applied cognition research.