A policy dimension required for technology roadmapping: Learning from the development of emerging wind energy industry in China

Innovation policies play an important role throughout the development process of emerging industries. However, existing policy studies view the process as a black-box, and fail to understand the policy-industry interactions through the process. This paper aims to develop an integrated technology roadmapping tool, in order to facilitate the better understanding of policy heterogeneity at the different stages of new energy industries in China. Through the case study of Chinese wind energy equipment manufacturing industry, this paper elaborates the dynamics between policy and the growth process of the industry. Further, this paper generalizes some Chinese specifics for the policy-industry interactions. As a practical output, this study proposes a policy-technology roadmapping framework that maps policy-market-product- technology interactions in response to the requirement for analyzing and planning the development of new industries in emerging economies (e.g. China). This paper will be of interest to policy makers, strategists, investors, and industrial experts. © 2011 IEEE.

A policy dimension required for technology roadmapping: Learning from the emergence of Chinese wind turbine industry

Innovation policies play an important role throughout the development process of emerging industries in China. Existing policy and industry studies view the emergence process as a black-box, and fail to understand the impacts of policy to the process along which it varies. This paper aims to develop a multi-dimensional roadmapping tool to better analyse the dynamics between policy and industrial growth for new industries in China. Through reviewing the emergence process of Chinese wind turbine industry, this paper elaborates how policy and other factors influence the emergence of this industry along this path. Further, this paper generalises some Chinese specifics for the policy-industry dynamics. As a practical output, this study proposes a roadmapping framework that generalises some patterns of policy-industry interactions for the emergence process of new industries in China. This paper will be of interest to policy makers, strategists, investors and industrial experts. Copyright © 2013 Inderscience Enterprises Ltd.

Facilitation of learning induced by both random and gradual visuomotor task variation.

Motor task variation has been shown to be a key ingredient in skill transfer, retention, and structural learning. However, many studies only compare training of randomly varying tasks to either blocked or null training, and it is not clear how experiencing different nonrandom temporal orderings of tasks might affect the learning process. Here we study learning in human subjects who experience the same set of visuomotor rotations, evenly spaced between -60° and +60°, either in a random order or in an order in which the rotation angle changed gradually. We compared subsequent learning of three test blocks of +30°→-30°→+30° rotations. The groups that underwent either random or gradual training showed significant (P < 0.01) facilitation of learning in the test blocks compared with a control group who had not experienced any visuomotor rotations before. We also found that movement initiation times in the random group during the test blocks were significantly (P < 0.05) lower than for the gradual or the control group. When we fit a state-space model with fast and slow learning processes to our data, we found that the differences in performance in the test block were consistent with the gradual or random task variation changing the learning and retention rates of only the fast learning process. Such adaptation of learning rates may be a key feature of ongoing meta-learning processes. Our results therefore suggest that both gradual and random task variation can induce meta-learning and that random learning has an advantage in terms of shorter initiation times, suggesting less reliance on cognitive processes.