Location Data Analytics in the Business Value Chain: A Systematic Literature Review

• Main Authors: Luis E. Ferro-Diez, Norha M. Villegas, Javier Diaz-Cely
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Business data processing; business value chain; location analysis; location context; location intelligence; machine learning
• Online Access: https://ieeexplore.ieee.org/document/9252938/

Context information has become a significant asset to optimize the value obtained from information systems. Location is an important type of context information that refers to the place in which an event occurs. In business environments, the implementation of location-based analytics systems to aid decision making processes is of paramount importance for business development. However, after an exhaustive literature review, we found that researchers and practitioners still lack a comprehensive characterization of location-based data analytics systems that have been effectively applied to business processes. This paper presents the results of a systematic literature review (SLR), in which we characterized a total of 168 location-based and business oriented analytics solutions that were published between 2014 and 2019. To conduct this SLR we defined three characterization dimensions: business aspects, through which we identified value chain business processes or activities that may be benefited with the proposed solution; data source, which allowed us to report on the data used in each of the studies; and data analytics, through which we report on the analytics techniques and validation strategies implemented by the studied approaches. The contribution of our SLR is twofold. First, it provides business and data analytics practitioners with a comprehensive catalog of location-based data analytics approaches that could be applied to improve value generation, at different levels, along their businesses' value chains. And second, it provides researchers with a complete landscape of recent advancements and open challenges in the field.