The popularity of location empowered devices such as GPS enabled smart-phones has immensely amplified the use of location-based services in social networks. This happened by allowing users to share Geo-tagged contents such as current locations/check-ins with their social network friends. These location-aware social networks are called Location-based Social Networks (LBSN), and examples include Foursquare and Gowalla. The data of LBSNs are being used for providing different kinds of services such as the recommendation of locations, friends, activities, and media contents, and the prediction of user's locations. To provide such services, different queries are utilized that exploit activity/check-in data of users. Usually, LBSN data is divided into two parts, a social graph that encapsulates the friendships of users and an activity graph that maintains the visit history of users at locations. Such a data separation is scalable enough for processing queries that directly utilize friendship information and visit history of users. These queries are called user and activity analytic queries. The visits of users at locations create relationships between those locations. Such relationships can be built on different features such as common visitors, geographical distance, and mutual location categories between them. The process of analysing such relationships for optimizing location-based services is termed Location Analytics. In location analytics, we expose the subjective nature of locations that can further be used for applications in the domain of prediction of visitors, traffic management, route planning, and targeted marketing.In this thesis, we provide a general LBSN data model which can support storage and processing of queries required for different applications, called location analytics queries. The LBSN data model we introduce, segregates the LBSN data into three graphs: the social graph, the activity graph, and the location graph. The location graph maintains the interactions of locations among each other. We define primitive queries for each of these graphs. In order to process an advanced query, we express it as a combination of these primitive queries and process them on corresponding graphs in parallel. We further provide a distributed data processing framework called GeoSocial-GraphX (GSG). GSG implements the aforementioned LBSN data model for efficient and scalable processing of the queries. We further exploit the location graph for providing novel location analytics queries in the domain of influence maximization and visitor prediction. We introduce a notion of location influence. Such influence can capture the interactions of locations based on their visitors and can be used for propagation of information between them. The applications of such a query lie in the domain of outdoor marketing, and simulation of virus and news propagation. We also provide a unified system IMaxer that can evaluate and compare different information propagation mechanisms. We further exploit the subjective nature of locations by analysing the mobility behaviour of their visitors. We use such information to predict the individual visitors as well as the groups of visitors (cohorts) in future for those locations. The prediction of visitors can be used for better event planning, traffic management, targeted marketing, and ride-sharing services.In order to evaluate the proposed frameworks and approaches, we utilize data from four real-life LBSNs: Foursquare, Brightkite, Gowalla, and Wee Places. The detailed LBSN data mining and statistically significant experimental evaluation results show the effectiveness, efficiency, and scalability of our proposed methods. Our proposed approaches can be employed in real systems for providing life-care services. / Doctorat en Sciences de l'ingénieur et technologie / The portal is not showing my complete name. The name (my complete name), I want to have on the diploma is "Muhammad Aamir Saleem". Please correct this issue. / info:eu-repo/semantics/nonPublished

This study focuses on the telecommunication industry, specifically the mobile phone market at the base of the pyramid (BOP). A supply vs. demand stance is taken whereby demographic data offer insight into the demand while the location of telecommunication retail stores constitutes supply. The study furthermore makes extensive use of a GIS (geographical information system) which offers deeper insight into data and different applications thereof. Given the extensive nature of the data used in assessing the national market, a dashboard was developed as part of this research to ease data interpretation. The online map (GIS) and dashboard form an integral part of this report. Literature supports the targeting of the BOP as a viable market given the high volume of people in this market segment. Unconventional methods are, however, required to sustainably cater to this market. The development of multiple channels to target potential consumers has resulted in a dilution of the market in the retail environment. The retail channel however remains important in any company’s strategy to target the BOP. Telecommunication companies can not only benefit from the BOP but also offer benefits to the BOP. The World Bank has reported figures that show a 0.8% increase in GDP for every 10% increase in mobile penetration. Different sources identify the BOP by different income ranges. It became evident, however, that internationally the average applied to identify the BOP is households earning less than USD 3,000 (ZAR 31,440 at an exchange rate of R10.48 / USD) per annum. Although somewhat higher than the international average, the available data dictated that South Africa’s BOP be identified as households earning less than R38,200 per annum for the purposes of this research. Data indicate that 89% of households in South Africa have a mobile phone. By comparing the ownership of existing household goods this research found that of the 11% of households not owning a mobile phone, 6% would be willing to adopt a mobile phone. A tiered approach is followed in assessing the telecommunication opportunity for mobile phones in the BOP. The first tier assesses the entire market (all households in South Africa) at a municipal level. By including the total market, the opportunity in the BOP is put into perspective. The result was that the total BOP market offers a potential market of R563 million per month through 13.7 simcards. At the other end of the economic pyramid, the ROP offers a market of R2416 million per month through 14.6 million simcards. Thus, even though the BOP offers 48% of the total volume in the market, the value is only 19% of the total market. From a coverage perspective, 42% of BOP households are not covered by a telecom retailer whilst only 27% of the ROP households are not covered. A market of R247 million (through 5.8 million simcards) has been estimated in the BOP opposed to a R379 million market (through 5.8 million simcards) in the ROP. The second tier makes use of a case study to determine the viability of targeting the BOP. Moruleng Mall’s catchment area was analysed within the Moses Kotane municipality that offered a high opportunity as determined in the first tier of analysis. This case study made use of gravity modelling and found that Rustenburg’s retail offering would have limited influence and as such telecom retailers would have to revisit their strategy for the area. A number of shopping centre developments in rural areas were highlighted. Effectively while these developments are taking retail closer to the BOP or rual population, the market is diluted. From a retailer perspective, this makes it difficult to target an entire area through presence in one specific retail node or town. The ultimate finding of this this research suggests that it is in fact possible to target the BOP – however, that it is the ROP located between the BOP households that makes this a viable market. This suggests that it is rather not a question of the viability in targeting the BOP specifically but targeting the more dense rural areas that offer opportunity. / MBA, North-West University, Potchefstroom Campus, 2014

This study focuses on the telecommunication industry, specifically the mobile phone market at the base of the pyramid (BOP). A supply vs. demand stance is taken whereby demographic data offer insight into the demand while the location of telecommunication retail stores constitutes supply. The study furthermore makes extensive use of a GIS (geographical information system) which offers deeper insight into data and different applications thereof. Given the extensive nature of the data used in assessing the national market, a dashboard was developed as part of this research to ease data interpretation. The online map (GIS) and dashboard form an integral part of this report. Literature supports the targeting of the BOP as a viable market given the high volume of people in this market segment. Unconventional methods are, however, required to sustainably cater to this market. The development of multiple channels to target potential consumers has resulted in a dilution of the market in the retail environment. The retail channel however remains important in any company’s strategy to target the BOP. Telecommunication companies can not only benefit from the BOP but also offer benefits to the BOP. The World Bank has reported figures that show a 0.8% increase in GDP for every 10% increase in mobile penetration. Different sources identify the BOP by different income ranges. It became evident, however, that internationally the average applied to identify the BOP is households earning less than USD 3,000 (ZAR 31,440 at an exchange rate of R10.48 / USD) per annum. Although somewhat higher than the international average, the available data dictated that South Africa’s BOP be identified as households earning less than R38,200 per annum for the purposes of this research. Data indicate that 89% of households in South Africa have a mobile phone. By comparing the ownership of existing household goods this research found that of the 11% of households not owning a mobile phone, 6% would be willing to adopt a mobile phone. A tiered approach is followed in assessing the telecommunication opportunity for mobile phones in the BOP. The first tier assesses the entire market (all households in South Africa) at a municipal level. By including the total market, the opportunity in the BOP is put into perspective. The result was that the total BOP market offers a potential market of R563 million per month through 13.7 simcards. At the other end of the economic pyramid, the ROP offers a market of R2416 million per month through 14.6 million simcards. Thus, even though the BOP offers 48% of the total volume in the market, the value is only 19% of the total market. From a coverage perspective, 42% of BOP households are not covered by a telecom retailer whilst only 27% of the ROP households are not covered. A market of R247 million (through 5.8 million simcards) has been estimated in the BOP opposed to a R379 million market (through 5.8 million simcards) in the ROP. The second tier makes use of a case study to determine the viability of targeting the BOP. Moruleng Mall’s catchment area was analysed within the Moses Kotane municipality that offered a high opportunity as determined in the first tier of analysis. This case study made use of gravity modelling and found that Rustenburg’s retail offering would have limited influence and as such telecom retailers would have to revisit their strategy for the area. A number of shopping centre developments in rural areas were highlighted. Effectively while these developments are taking retail closer to the BOP or rual population, the market is diluted. From a retailer perspective, this makes it difficult to target an entire area through presence in one specific retail node or town. The ultimate finding of this this research suggests that it is in fact possible to target the BOP – however, that it is the ROP located between the BOP households that makes this a viable market. This suggests that it is rather not a question of the viability in targeting the BOP specifically but targeting the more dense rural areas that offer opportunity. / MBA, North-West University, Potchefstroom Campus, 2014