Abstract#R##N##R##N#As one of the leading ‘world cities’, London is particularly reliant on sources of foreign direct investment (FDI). In the face of increasing global competition and a difficult economic climate, the capital must compete effectively to encourage and support such investors. Through a collaborative study with London's official FDI promotion agency, Think London, the need for a coherent framework for data, methodologies and tools to inform business location decision-making became apparent. This article discusses the development of a rich environment to explore, compare and rank London's business neighbourhoods. This is achieved through the development and evaluation of a model for location-based decision support. First, we discuss the development of a geo-business classification for London which draws upon methods and practices common in geodemographic neighbourhood classification. A geo-business classification is developed, encapsulating relevant location variables using Principal Components Analysis into a set of composite area profiles. Second, we discuss the implementation of an appropriate Multi-Criteria Decision Making methodology, in this case Analytical Hierarchy Process (AHP), enabling the aggregation of the geo-business classification and decision-makers' preferences into discrete decision alternatives. Finally, we present the results of the integration of both data and model through the development and evaluation of a web-based prototype.
['P. Weber', 'Dave Chapman']
Location Intelligence: An Innovative Approach to Business Location Decision‐making