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The use of geolocation technologies is an opportunity for businesses dedicated to retail the city of Manizales can approach their customers and offer different promotions, discounts, advertising and better and improve the customer experience, using its location. However, to ensure the proper design of a marketing strategy of proximity, it is necessary to know the factors that influence the acceptance that will have the use of this technology in users or end consumers, ensuring that stores in the city can offer appropriate services. Through the use of the UTAUT2 model an exploration of those factors that influence the adoption and use of this technology is made using a PLS-SEM model. The results confirm that the variables hedonic motivations, performance expectation, effort expectation and price are statistically significant for users. The use of this technology brings a better experience for and to the customer, providing added value to the final product.

Geomarketing has become a critical domain for most of companies dealing with retailing and services for the three last decades. Usually, retail and service companies utilize geomarketing to make decisions about store location, trade area delineating, and customer plotting. Little by little new applications have emerged from mapping uses dealing with prices, merchandising, and promotion (advertising, direct marketing, sales promotion, salesforce management). Spatial consumer behavior is now considered of paramount importance either within the store or outside as competition is sometimes growing fiercely in markets, on the one hand, and customers are more and more mobile, on the other hand. But the true revolution appears suddenly with smartphones and touch pads which enable to develop both a real mobile marketing (m-marketing) and location-based marketing. With this device, any consumer can be positioned anywhere, anytime to send him/her messages as she/he can keep informed about products and prices, and purchase opportunities; meanwhile, this consumer may either buy from anywhere or at any time. Mapping is no more the only way to manage decisions in a spatial context in marketing. Hence, many concepts should be considered or reconsidered: spatial commodity, ubiquity, proximity, and so on. And new methods emerge to better control space in markets and to be sure to keep in touch with customers even though this last intention should be limited for privacy reasons. That is the reason why geomarketing should be enlarged to spatial marketing.

Interlinking of spatio-textual entities is an open and quite challenging research problem, with application in several commercial fields, including geomarketing, navigation and social networks. It comprises the process of identifying, between different data sources, entity descriptions that refer to the same real-world entity. In this work, we focus on toponym interlinking, that is we handle spatio-textual entities that are exclusively represented by their name; additional properties, such as categories, coordinates, etc. are considered as either absent or of too low quality to be exploited in this setting. Toponyms are inherently heterogeneous entities; quite often several alternative names exist for the same toponym, with varying degrees of similarity between these names. State of the art approaches adopt mostly generic, domain-agnostic similarity functions and use them as is, or incorporate them as training features within classifiers for performing toponym interlinking. We claim that capturing the specificities of toponyms and exploiting them into elaborate meta-similarity functions and derived training features can significantly increase the effectiveness of interlinking methods. To this end, we propose the LGM-Sim meta-similarity function and a series of novel, similarity-based and statistical training features that can be utilized in similarity-based and classification-based interlinking settings respectively. We demonstrate that the proposed methods achieve large increases in accuracy, in both settings, compared to several methods from the literature in the widely used Geonames toponym dataset.

The author considers an important problem of using the Huff model for obtaining quantitative estimates of trade turnover of the shopping center. The aim of the article is to identify the actual limitations of the specified model, which when conducting a practical assessment of potential trade turnover of large objects of commercial real estate in a significant way affect the quantitative results of the calculation and the quality of the conclusions. In accordance with the goal, the author solved the following tasks

Galois lattices are tightly connected to Formal Concept Analysis as they generate a concept hierarchy that helps structuring and clustering closed frequent item sets. When used in Data mining, such a structure can help dealing with large data sets which are very common in such a context. Constructing Galois Lattices is one of the most complex problems in FCA. Our work focuses on the generation process of the Galois Lattice which is based on a parallel distributed approach relying on a CORBA infrastructure. This contribution is part of our global framework aimed at spatial association rules discovery for geomarketing purposes destined to a telecom operator. We will adopt a generation method of association rules that exploits the same concept lattice formerly used to process the closed frequent item sets and which is inspired from the minimal generator concept. The architecture is Manager/Agent based where the agent may encapsulate different concept generation methods given that these ones respect the same concept interfaces.

Today small and medium-sized enterprises (SMEs) play a key role in the economy and are considered the engines of global economic growth. In today’s environment of mature economies, stagnant markets and fierce competition, consumers are increasingly informed and demanding personalized treatment and products and services that meet their needs. In this context, SMEs can remain in the market, and maintain a competitive advantage, if they are able to respond to customers’ needs in a timely manner. That is possible if supported by the appropriate information systems and information technologies. Actually, many SMEs are far from accessing all the available data, because they have neither the knowledge nor financial capacity to acquire tools that allow you to extract knowledge from your internal and external databases. However, is possible by combining a database that provides behavioral information from your prospects and combining that data with the spatial information of those customers. This joint allows a comprehensive analysis that is possible through the use of segmentations techniques, which supports marketing campaigns in an effective way, promoting visibility in the market, and allowing acquiring or maintaining a strategic positioning, using inexpensive tools.

We study the problem of computing isochrones in static and dynamic road networks, where the objective is to identify the boundary of the region in range from a given source within a certain amount of time. While there is a wide range of practical applications for this problemi¾źe.i¾źg., urban planning, geomarketing, visualizing the cruising range of a vehicle, there has been little research on fast algorithms for large, realistic inputs, and existing approaches tend to compute more information than necessary. Our contribution is twofold: 1 We propose a more compact but sufficient definition of isochrones, based on which, 2 we provide several easy-to-parallelize, scalable algorithmic approaches for faster computation. By extensive experimental analysis, we demonstrate that our techniques enable fast isochrone computation within milliseconds even on continental networks, significantly faster than the state-of-the-art.