Annals of Tourism Research, Vol. 32, No. 1, pp. 93–111, 2005 Ó 2005 Elsevier Ltd. All rights reserved. Printed in Great Britain 0160-7383/$30.00
A Neural Network Application
Jonathan Z. Bloom University of Stellenbosch, South Africa
Abstract: The objective of the research is to consider a self-organizing neural network for segmenting the international tourist market to Cape Town, South Africa. A backpropagation neural network is used to complement the segmentation by generating additional knowledge based on input–output relationship and sensitivity analyses. The ﬁndings of the self-organizing neural network indicate three clusters, which are visually conﬁrmed by developing a comparative model based on the test data set. The research also demonstrated that Cape Metropolitan Tourism could deploy the neural network models and track the changing behavior of tourists within and between segments. Marketing implications for the Cape are also highlighted. Keywords: segmentation, SOM neural network, input–output analysis, sensitivity analysis, deployment. Ó 2005 Elsevier Ltd. All rights reserved. ´ ´ Resume: Segmentation du marche: une application du reseau neuronal. Le but de la ´ ´ recherche est de considerer un reseau neuronal auto-organisateur pour segmenter le marche ´ ´ ´ touristique international a Cape Town, en Afrique du Sud. On utilise un reseau neuronal de ` ´ retropropogation pour completer la segmentation en generant des connaissances comple´ ´ ´ ´ ´ mentaires basees sur une relation input–output et des analyses de sensibilite. Les resultats ´ ´ ´ du reseau neuronal auto-organisateur indiquent trois groupes qu’on conﬁrme visuellement ´ en developpant un modele comparatif base sur l’ensemble des donnees d’essai. La recherche ´ ` ´ ´ a montre aussi que le Tourisme Metropolitain du Cap pourrait utiliser les modeles de reseau ´ ´ ` ´ neuronal et suivre la trace du comportement changeant des touristes dans et entre les seg´ ments. On souligne aussi les implications de marketing pour le Cap. Mots-cles: segmentation, reseau neuronal, analyse input–output, analyse de sensibilite, utilisation. Ó 2005 Elsevier ´ ´ Ltd. All rights reserved.
INTRODUCTION Marketing an international tourism destination such as Cape Town in South Africa has never been more dynamic, competitive, and important than it is today. Successful marketing requires careful planning and comprehensive analysis of data and information obtained from tourists that frequent destinations and those that do not. There is no shortcut to establishing a positioning strategy that could deliver a valuable experience to tourists. The ability to identify and serve tourists and create a dialogue with them has become a necessity for destination organizations such as Jonathan Bloom (Department of Business Management, University of Stellenbosch, Matieland, 7602, South Africa. Email ) has a particular research interest in the application of predictive modeling in tourism using artiﬁcial intelligence technology. He spent several years in the private sector assisting destination organizations such as South African Tourism and Cape Metropolitan Tourism to extract more value from the data obtained from market surveys. 93
Cape Metropolitan Tourism (hereafter referred to as Cape Metro Tourism). Managing the tourist relationship has become an essential part of attracting those with speciﬁc proﬁles to a destination. All activities around the tourist ‘‘touch points’’––which aim to identify, attract, and retain the most valuable tourists for a destination and its enterprises––should be considered. The end result is to enhance retention and loyalty and sustain growth from proﬁtable tourists. It is important to determine what it takes to encourage them to purchase the product/service that a destination offers. A need exists to understand their behavior and thus...