Innovation and export performance:evidence from UK and German manufacturing plants

Using comparable plant-level surveys we demonstrate significant differences between the determinants of export performance among the UK and German manufacturing plants. Product innovation, however measured, has a strong effect on the probability and propensity to export in both countries. Being innovative is positively related to export probability in both countries. In the UK the scale of plants’ innovation activity is also related positively to export propensity. In Germany, however, where levels of innovation intensity are higher but the proportion of sales attributable to new products is lower, there is some evidence of a negative relationship between the scale of innovation activity and export performance. Significant differences are identified between innovative and non-innovative plants, especially in their absorption of spill-over effects. Innovative UK plants are more effective in their ability to exploit spill-overs from the innovation activities of companies in the same sector. In Germany, by contrast, non-innovators are more likely to absorb regional and supply-chain spill-over effects. Co-location to other innovative firms is generally found to discourage exporting.

The determinants of export performance:evidence for manufacturing plants in Ireland and Northern Ireland

The dramatic GDP and export growth of Ireland over the last decade forms a marked contrast with that of its nearest neighbour Northern Ireland. In Ireland, export volume growth averaged 15.5% p.a. from 1991 to 1999 compared with 6.3% from Northern Ireland. Using data on individual manufacturing plants this paper considers the determinants of export performance in the two areas. Larger, externally owned plants with higher skill levels are found to have the highest export propensities in both areas. Other influences (plant age, R&D, etc.) prove more strongly conditional on location, plant size, and ownership. Structural factors (e.g. ownership, industry) explain almost all of the difference in export propensity between larger plants in Northern Ireland and Ireland but only around one-third of that between smaller plants. Significant differences are also evident between plants in terms of their sources of new technology. For indigenously owned plants, inhouse R&D is important. For externally owned plants, R&D conducted elsewhere in the group - typically outside Ireland and Northern Ireland - proves more significant. This external dependency and lower than expected export propensity on the part of small plants in Northern Ireland represent significant policy challenges for the future.© 2006 Scottish Economic Society. Published by Blackwell Publishing Ltd.

Enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty

Modern advances in technology have led to more complex manufacturing processes whose success centres on the ability to control these processes with a very high level of accuracy. Plant complexity inevitably leads to poor models that exhibit a high degree of parametric or functional uncertainty. The situation becomes even more complex if the plant to be controlled is characterised by a multivalued function or even if it exhibits a number of modes of behaviour during its operation. Since an intelligent controller is expected to operate and guarantee the best performance where complexity and uncertainty coexist and interact, control engineers and theorists have recently developed new control techniques under the framework of intelligent control to enhance the performance of the controller for more complex and uncertain plants. These techniques are based on incorporating model uncertainty. The newly developed control algorithms for incorporating model uncertainty are proven to give more accurate control results under uncertain conditions. In this paper, we survey some approaches that appear to be promising for enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty.