Big Data Analytics: The New Boundaries of Retail Location Decision Making-Reference-Cited by-同舟云学术

Big Data Analytics: The New Boundaries of Retail Location Decision Making

Published:2018-10-02 Issue:4 Volume:4 Page:390-408
ISSN:2375-4931
Container-title:Papers in Applied Geography
language:en
Short-container-title:Papers in Applied Geography

Author:

Aversa Joseph¹,Doherty Sean²,Hernandez Tony³

Affiliation:

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

2. Department of Geography and Environmental Studies, Wilfrid Laurier University, Waterloo, Canada;

3. School of Retail Management and Department of Real Estate Management, Ted Rogers School of Management, Ryerson University, Toronto, Canada

Publisher

Informa UK Limited

Subject

Earth and Planetary Sciences (miscellaneous),Urban Studies,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/23754931.2018.1527720

Reference68 articles.

1. How to improve firm performance using big data analytics capability and business strategy alignment?

2. Big Data

3. Social media analytics: a survey of techniques, tools and platforms

4. Beheshti-Kashi, S., and K. D. Thoben. 2014. The usage of social media text data for the demand forecasting in the fashion industry fashion sales forecasting and the predictive power of online. In Dynamics in logistics. Fourth international conference, LDIC, 1–4.

5. Assessing GIS for retail location planning

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