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- W2128933163 abstract "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." @default.
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- W2128933163 date "2011-06-06" @default.
- W2128933163 modified "2023-10-02" @default.
- W2128933163 title "Location Intelligence: An Innovative Approach to Business Location Decision-making" @default.
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- W2128933163 doi "https://doi.org/10.1111/j.1467-9671.2011.01253.x" @default.
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