Framework for a Hospitality Big Data Warehouse: The Implementation of an Efficient Hospitality Business Intelligence System

Framework for a Hospitality Big Data Warehouse: The Implementation of an Efficient Hospitality Business Intelligence System

Célia M.Q. Ramos (CEFAGE & ESGHT, University of the Algarve, Faro, Portugal), Daniel Jorge Martins (LARSyS & ISE, University of the Algarve, Faro, Portugal), Francisco Serra (ESGHT, University of the Algarve, Faro, Portugal), Roberto Lam (LARSyS & ISE, University of Algarve, Faro, Portugal), Pedro J.S. Cardoso (LARSyS & ISE, University of the Algarve, Faro, Portugal), Marisol B. Correia (CEG-IST & ESGHT, University of the Algarve, Faro, Portugal) and João M.F. Rodrigues (LARSyS & ISE, University of the Algarve, Faro, Portugal)
DOI: 10.4018/IJISSS.2017040102
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In order to increase the hotel's competitiveness, to maximize its revenue, to meliorate its online reputation and improve customer relationship, the information about the hotel's business has to be managed by adequate information systems (IS). Those IS should be capable of returning knowledge from a necessarily large quantity of information, anticipating and influencing the consumer's behaviour. One way to manage the information is to develop a Big Data Warehouse (BDW), which includes information from internal sources (e.g., Data Warehouse) and external sources (e.g., competitive set and customers' opinions). This paper presents a framework for a Hospitality Big Data Warehouse (HBDW). The framework includes a (1) Web crawler that periodically accesses targeted websites to automatically extract information from them, and a (2) data model to organize and consolidate the collected data into a HBDW. Additionally, the usefulness of this HBDW to the development of the business analytical tools is discussed, keeping in mind the implementation of the business intelligence (BI) concepts.
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1. Introduction

To Sheldon (1989, p. 589) “the information is the true blood of the tourism industry.” Despite having almost three decades, Sheldon’s remark stills as a fact in our days, i.e., travelers, travel agents, hoteliers and stakeholders in the tourism supply chain need broad and trustworthy information. To tourist organizations, an efficient information management will improve the flow of information, the response times to requests from abroad demanders, and the company’s development in an increasingly competitive society, which is heading towards very similar technological bases, in order to ensure their survival (Ramos, Rodrigues, & Rodrigues, 2015b).

In today’s society, the technological bases of the tourism organizations, in general, and of the hoteliers, in particular, make relevant that marketers and managers have access to data intelligence, and make the best use of it (Peter, 2014). In this sense, those professionals have invested heavily in recent years, organizing strong scientific teams, including statisticians and database (DB) experts, well equipped to build and analyse the contents of their Data Warehouses (DW).

However, the exclusive development and use of the hotel’s DW is no longer sufficient to ensure the required competitive advantages (Caldeira, 2012), being necessary to consider the development and use of Big Data Warehouse (BDW) (Di Tria, Lefons, & Tangorra, 2013) architectures, consisting of internal and external data sets (Di Tria et al., 2013; Martins et al., 2015b; Mohanty, Jagadeesh, & Srivatsa, 2013; Ramos, Correia, Rodrigues, Martins, & Serra, 2015a). The concept of BDW refers commonly to the activity of collecting, integrating, and storing large volumes of high velocity data, coming from data sources which may contain both structured and unstructured data (Di Tria et al., 2013). Associated with the concepts of business intelligence (BI), the potentialities related with Big Data are described as technologies that promise to fulfil a fundamental tenet of research in information systems (Schermann et al., 2014), which is to provide the right information, to the right receiver, in the right volume and quality, at the right time (Burke & Hiltbrand, 2011; Ramos et al., 2015a).

Due to the need to survive and to increase competitiveness, hotel marketers are trying to promote their services at travel sites that hold the highest market shares, e.g. Booking or Trivago. This means that the hospitality industry (Chen, Samidjen, Tsai, & Chen, 2013) is using the web as a global vitrine where specialized sites operate, thus providing publicly available information that can be collected into the BDWs with the right technological tools (note, this is not “hacking”). This means generating/retrieving large sets of data, which can be used for hospitality BI purposes, such as, providing a comparison of offers for similar products, or to promote and sell rooms at the best possible price, to the right customers. In essence, hotel managers strive to achieve the best possible revenues but, in order to do it, they need to be in possession of actual and reliable information about their competitive set (e.g., hotels with similar location, facilities, class of service, and number of rooms).

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