ARTICLE IN PRESS JID: PATREC [m5G;June 23, 2015;20:19] Pattern Recognition Letters 000 (2015) 1–10 Contents lists available at ScienceDirect Pattern Recognition Letters journal homepage: www.elsevier.com/locate/patrec Promoting consensus in the concept mapping methodology: An application in the hospitality sector ✩ Albert Fornells a,∗ , Zaida Rodrigo a , Xari Rovira c , Mónica Sánchez d , Ricard Santomà a , Francesc Teixidó-Navarro a,b , Elisabet Golobardes b a Research Group in Hospitality, Tourism and Mobilities, School of Tourism and Hospitality Management Sant Ignasi, Universitat Ramon Llull. Av. Marquès de Mulhacén 40–42, Barcelona 08034, Spain b GR-SETAD, La Salle, Universitat Ramon Llull. Av. Quatre Camins 30, Barcelona 08022, Spain c ESADE Business School, Universitat Ramon Llull. Av. Pedralbes 62, Barcelona 08034, Spain d Universitat Politècnica de Catalunya. UPC-Barcelona Tech., Jordi Girona, 1–3, Barcelona 08034, Spain article info Article history: Available online xxx Keywords: Concept mapping methodology Qualitative reasoning techniques Consensus measures Excellence in hospitality abstract The concept mapping methodology aims to respond to the non trivial task of conceptualising abstract thoughts by means of a focus group composed by experts from the studied domain. The approach defines a set of general steps that allow experts to lead the generation of ideas, group the ideas in a conceptual map of interrelated concepts using clustering multidimensional scaling and clustering techniques, analysing the quality of the conceptual maps and deciding on a final interpretation. In this sense, this final decision is not trivial because clustering techniques provide a set of potentially conceptual maps so experts must select the one that fits best according to their opinion. For this reason, we present the global index of consensus as an indicator for filtering the most suitable clustering solutions using qualitative reasoning. It promotes the con- sensus of experts opinions and ensures objectivity in the final interpretation. The index outperforms three of the most well-known clustering validation indexes in a case study focused on the meaning of excellence in the hospitality industry. This work presents the global index of consensus as an indicator for filtering the most suitable clustering solutions using qualitative reasoning that promotes the consensus of experts’ opinions, which is one of the key aspects in the concept mapping methodology. The index outperforms three of the most well-known clustering validation indexes in a case study focused on the meaning of excellence in hospitality. © 2015 Elsevier B.V. All rights reserved. 1. Introduction The concept mapping methodology aims to respond the chal- lenge of guiding a group of experts in the objective representation of thoughts, ideas or abstract concepts based on promoting their agree- ment regarding what they consider most relevant in consensus [1,35]. Thus, this method is used to offer clarity and develop a model or spec- ify a conceptual framework and it has been successfully applied in education, social research and management science fields to create conceptual frameworks based on specific aspects [26]. The method- ology defines a set of general steps using qualitative and quantitative data to determine a conceptual map of interrelated concepts [27]. Giving a specific topic study through a set question, a focus group composed of experts in this domain generate ideas related to this ✩ This paper has been recommended for acceptance by Lledó Museros. ∗ Corresponding author. Tel.: +34 932522890. E-mail address: albert.fornells@tsi.url.edu (A. Fornells). topic using brainstorming. Next, the focus group have to group and weight the ideas in categories based on their point of view. This information is converted into knowledge using data mining tech- niques [37], which are applied to identify shared patterns between the opinion of the experts using multidimensional scaling and clus- tering techniques. It is important to highlight that clustering tech- niques often return more than one possible solution where each one represents a clustering configuration that groups elements in a spe- cific way. Therefore, the last step is to validate and select the most suitable clustering configuration based on the criteria of the group of experts. Although one of the main benefits of this approach is its flexibility and adaptability, the amount of data that has to be anal- ysed may hinder the tasks of experts because the selection of the best clustering configuration is non trivial and they have to review all the results following the subjective premise “does it make sense to you?” [35], which may compromise the objectivity of the approach. This paper presents the global index of consensus (GIc) to help experts in selecting the most suitable clustering configuration based http://dx.doi.org/10.1016/j.patrec.2015.05.013 0167-8655/© 2015 Elsevier B.V. All rights reserved. Please cite this article as: A. Fornells et al., Promoting consensus in the concept mapping methodology: An application in the hospitality sector, Pattern Recognition Letters (2015), http://dx.doi.org/10.1016/j.patrec.2015.05.013