Spatial Characteristics of internationally competitive cities

Due to globalization, traditional factors of competitive advantage (e.g. markets, natural resources, and labour) have become highly mobile, thereby permanently transforming the way in which cities and businesses compete for economic development. In this context, innovation became the leading driver of economic development in advanced economies. Because innovation requires continuous and efficient interfacing, businesses in knowledge-intensive industries tend to seek physical proximity to external factors (e.g. complimentary and supporting businesses, markets demands, and highly-skilled workers). Businesses also cluster together to take advantage of factors that are available only in economies of scale (e.g. well-developed infrastructure). As epicentres of agglomeration, cities are uniquely positioned to provide the set of urban amenities necessary for innovation and business growth in a global economy. However, cities are very diverse, as are the amenities that they provide. Consequently, some cities outperform others in attracting innovation-driven, knowledge-intensive industries. This heightens competitiveness between cities as they strive to increase their social and economic development. While many studies have investigated the impact of urban socio-economic characteristics on competitiveness, there is a knowledge gap in the specific study of urban spatial characteristics and their impact on the attraction of Foreign Direct Investment. To help fill the gap, this study was conducted to identify the most relevant urban spatial characteristics to the clustering of Multinational Corporations in mid-sized north-western European cities. The aim was to provide an understanding of which urban spatial characteristics should be prioritized for economic growth in order to guide local and regional policies as well as urban design. A unique methodology was developed to generate proximity data from geographically mapped spatial characteristics in 11 cities, which were then analysed through multiple negative binominal regressions. Findings confirmed that proximity to architectural aesthetics, train stations, well-connected streets, and local service firms all increase FDI clustering. In contrast, proximity to road interchanges, parks, and local hi-tech firms were found to decrease FDI clustering. In the interest of investigating the effect of proximity at the regional level, additional analysis was conducted using proximity data from twin cities. Results confirmed nearness affinity between FDI clusters in a city and architectural landmarks, local firms, and road interchanges in a neighbouring city. This study culminates on a set of recommendation to the city of Rotterdam aimed at improving international attractiveness and competitiveness through urban spatial design.