Location Intelligence: An Innovative Approach to Business Location Decision‐making

Abstract

AbstractAs 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.