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Today, the importance of the Randstad agglomeration is often discussed in terms of the economic coherence between its four largest cities. This is remarkable when several leading authors argue that the economic importance of cities is strongly determined by economic networks between cities worldwide. This discrepancy stems from the fact that limited empirical research exists on corporate networks. Furthermore, the relative importance of cities within various studies is based on different functional types and spatial scales of data, making the results incomparable. Therefore, in this paper, the relative importance of the four largest Randstad cities is explored within three independent, comparative networks (top 100 global firms, top 100 European firms, and top 100 Dutch firms). Employing network analysis techniques, this paper evaluates the local, supra-regional and global importance of the four Randstad cities within the three independent networks. The results show that the relative importance and network structures of these four cities are highly dependent on the economic size and locality of the initial headquarters and that Amsterdam proves to be the most important Randstad city in all three scales of corporate networks. [ABSTRACT FROM AUTHOR]

With rapid urbanisation, the demand for office floor space also increases. Although high-rise buildings are very common in urban areas, study of the rent for different stories in such buildings is relatively rare. Liu (1988) and Grimaud (1989) separately applied agglomeration economies to study the density variation in urban areas. However, these studies assumed that the floor rent in the same building is the same for each story. Such an assumption about floor rent may not fully reflect actual floor rent and, from the perspectives of theoretical completeness and practical usefulness, formulation for different floor rents in high-rise buildings, and their effect on urban density variation should also be considered. This research note extends Ogawa and Fujita’s locational potential function (1980) into two dimensions: flat dimension and story dimension. The modification of the locational potential function is then applied to revise Liu’s model. Finally, the office distribution in a CBD (central business district) is then discussed. [ABSTRACT FROM AUTHOR]