Today, there is almost no field of science that does not take advantage of information technologies. Geography is no exception and is becoming innovative and advanced more than ever. Value proposition of every business model seeks to solve customer problems and satisfy their needs. Spatial modelling on the other side assists users in the process of decision-making and helps them solve any type of spatial problem. Since 2009 location data from millions of people, holding devices in their hands is being accumulated and analyzed every day, hour, minute. One of the greatest sources of data today are not the geospatial datasets of the companies, but the ordinary people. Crowds now have the power to capture, store and even analyze spatial data and all that could be explained by one word, which emerged just 12 years ago – crowdsourcing. This changed in an amazing way even the most traditional business models, created new ones and shaped whole industries.
It is believed that we are now living in the times of the Fourth Industrial Revolution. Klaus Schwab has associated it with the “second machine age” in terms of the effects of digitization and AI on the economy (Schwab, 2016). Disruptive business models using Geospatial Technologies are emerging to provide powerful spatial knowledge to their customers.
The power of global connectivity and its consequences for all people around the world are reshaping the whole understanding of how our planet is going into the future (Khanna, 2016). Spatial analysis, modelling and mapping are now shifted by a new and more precise term – location intelligence (LI).
LI is an emerging methodology for turning location data into business outcomes, helping businesses solve their most complex questions and challenges (Torre & Giraldo, 2017). It plays an increasingly important role for organizations and businesses by providing accessible insight into where things happen, why they happen, and what the next best move is.
LI is believed to be the driver of significant changes in the geospatial industry. The main building blocks of that process are:
- Mastering big data: satellites, sensors, crowdsourcing data are shifting the industry from “where-to-find-data” to “how-to-analyze-it” paradigm. Big data from sensors (Internet of Things or IoT) and Big data from people (Internet of People or IoP) combined form the last huge idea for the World Wide Web – Internet of everything or IoE;
- Tailoring location analysis to better serve different industries, public bodies or projects;
- No direct costs for hardware improvement due to the usage of cloud computing services and analysis;
LI has a direct connection with Business Intelligence (BI) and is believed to be the next big shift for companies, handling huge amounts of location data.
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