Business Intelligence Through Personalised Location-Aware Service Delivery

Abstract

Advances in mobile communication and location-based technologies have presented business and decision-makers (such as marketing managers) with a new paradigm for Business Intelligence (BI). It has created a channel for location-aware advertising-defined as targeted advertising initiatives delivered to a mobile device from an identified service provider that is specific to the location of the consumer (Unni & Harmon, 2007). With the increasing popularity of the new generation of Global Positioning Systems (GPS)-enabled smartphones (Bellavista et al, 2008) and their ubiquity, marketers and other service providers are able to utilize this emerging technologies to deliver targeted, tailored (Gauntt, 2008) and personalized services (such advertising) based on consumers' geographical locations (W3C, 2009) and prediction of their needs (Barnes, S. & Scornavacca, 2004), and to reach them through their mobile devices on a geographically targeted basis. As a result, there are now a number of location-aware services that have been classified as-Information and navigations services, emergency assistance, tracking services and network related services (Al-Bayari & Sadoun, 2007). Location aware services means that the application is aware of the current location and can use this information to present, retrieve or filter the information appropriate to the user at a particular position. For example, current offers at restaurants that are within 10 metres could be shown to a user that is out for a night meal with friends and the device can guide them to the destination. Location-Aware Service (from now on referred to as LAS) revenues are expected to increase to about $19 billion by the year 2014 (Kobsa, 2007). Despite its ubiquity and growing popularity, LAS is yet to be fully utilized from BI perspectives for a number of reasons-one of which is users/consumers resistance /unwilling to accept this new pervasive and intrusive means of service delivery. Whilst there are limitations and concerns over indoor location technology and a fragmented location ecosystem, another impending factor is privacy-related user acceptance (Kobsa, 2007) and security/trust related issues. The potential intrusion of privacy is an important concern for users of location-aware services (Kobsa, 2007; Soroa-Joury &Yang, 2009). However, there is a clear presuposition that users with different profiles using different access networks and mobile devices require personalized services that meet their needs at specific locations. Therefore, it is important to investigate how users are responding and how BI can be properly utilized for effective location-aware customer relation management.