The paper has targets to evaluate impacts from science and technology (S&T) to economic development of Red River Delta area through interactive relations between indicators reflecting S&T activities. The evaluation is based on integrated approaches and selections of related factors. | JSTPM Vol 2, No 4, 2013 45 PRELIMINARY EVALUATION OF IMPACTS FROM SCIENCE-TECHNOLOGIES TO ECONOMIC DEVELOPMENT OF RED RIVER DELTA AREA Tran Anh Tuan Institute of Regional Research and Development, MOST Abstract: The paper has targets to evaluate impacts from science and technology (S&T) to economic development of Red River Delta area through interactive relations between indicators reflecting S&T activities. The evaluation is based on integrated approaches and selections of related factors. Particularly in this paper, the research team conducted the separate evaluations of S&T factors from many other factors. By using iterative functions for identification of these relations, the study helps to identify the rate of impacts from these factors and then to identify orientations to adjust them in order to enhance the effectiveness of economic development. Keywords: Evaluation of impacts; Science and technology; Economic development; Red River Delta. Code: 13122701 1. General introduction There exist, up to now, very few research works related to evaluations of impacts from S&T to economic development. Some of them deal only with global views and qualitative assessment of the matter, rather than quantitative assessment. They did not yet indicate the way the actual S&T activities impact the economic development and the rate of these impacts. In order to have a full picture of S&T activities and economic development of Red River Delta area, various indicators may be listed out and they can be presented in absolute or average figures. Every indicator reflects one or few aspects of S&T activities or economic development. The full picture should be based on analysis of many, as more as possible, various indicators which reflect all the aspects of the research problem. From another side, however, a large number of indicators would make the problem too complex and then the analysis may be spread out. Many indicators might be overlapping, not easy to be collected in .
