Promoting consensus in the concept mapping methodology: An application in the hospitality sector

• Published in: Pattern recognition letters Vol. 67; pp. 39 - 48
• Main Authors: Fornells, Albert, Rodrigo, Zaida, Rovira, Xari, Sánchez, Mónica, Santomà, Ricard, Teixidó-Navarro, Francesc, Golobardes, Elisabet
• Format: Journal Article Publication
• Language: English
• Published: Elsevier B.V 01.12.2015
• Subjects: 90 Operations research, mathematical programming; 90B Operations research and management science; Classificació AMS; Concept mapping methodology; Consensus measures; Excellence in hospitality; Investigació operativa; Matemàtiques i estadística; Operations research; Optimització; Qualitative reasoning techniques; SEPARATION; VALIDATION; Àrees temàtiques de la UPC; Consensus measures; Concept mapping methodology; Qualitative reasoning techniques; Excellence in hospitality
• ISSN: 0167-8655; 1872-7344
• DOI: 10.1016/j.patrec.2015.05.013

•A new method for improving the concept mapping methodology is presented.•The global index of consensus (GIc) scores the clustering configurations.•GIc is based on qualitative reasoning and it focuses on the experts’ consensus.•A real case application in the Barcelona hospitality industry is presented.•The results show how GIc outperforms some of the most well-known quantitative indexes. [Display omitted] 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 consensus 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.