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Spatial Big Data and Business Location Decision-Making: Opportunities and Challenges

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Regional Intelligence

Abstract

This chapter examines the current state and trajectory of spatial big data and business location decision-making (BLDM) practices amongst major corporations in Canada. The three objectives of the chapter are: (i) to provide a research context for the study of spatial big data (SBD) and associated data science (DS) approaches in business; (ii) to identify the awareness, availability, use, adoption, integration, and development of SBD and DS within BLDM; and (iii) to explore the opportunities and challenges associated with integrating spatial big data into business organizations. The chapter presents qualitative insights from semi-structured interviews with location decision-makers from 24 major business corporations in Canada.

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Authors and Affiliations

  1. Ryerson University, Toronto, ON, Canada

    Joseph Aversa & Tony Hernandez

  2. Wilfrid Laurier University, Waterloo, ON, Canada

    Sean Doherty

Authors
  1. Joseph Aversa
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  2. Tony Hernandez
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  3. Sean Doherty
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Corresponding author

Correspondence to Joseph Aversa .

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Editors and Affiliations

  1. Department of Geography and Environmental Studies, Ryerson University, Toronto, ON, Canada

    Eric Vaz

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Aversa, J., Hernandez, T., Doherty, S. (2020). Spatial Big Data and Business Location Decision-Making: Opportunities and Challenges. In: Vaz, E. (eds) Regional Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-36479-3_11

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