1988
DOI: 10.1016/0160-7383(88)90085-0
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Multidimensional scaling and tourism research

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Cited by 47 publications
(18 citation statements)
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“…Fenton and Pearce (1988) describe the aim of MDS, 'to reduce data so as to make them more manageable and meaningful, and at the same time to identify if there is any inherent underlying structure within the data' (p. 237). In MDS the relationships between variables are plotted as points within a graphical space; the closer together the points, the closer the relationship-and vice versa.…”
Section: Methodsmentioning
confidence: 99%
“…Fenton and Pearce (1988) describe the aim of MDS, 'to reduce data so as to make them more manageable and meaningful, and at the same time to identify if there is any inherent underlying structure within the data' (p. 237). In MDS the relationships between variables are plotted as points within a graphical space; the closer together the points, the closer the relationship-and vice versa.…”
Section: Methodsmentioning
confidence: 99%
“…With MDS, one may analyse any kind of similarity or dissimilarity matrix, in addition to correlation matrices. Fenton and Pearce (1988) also argued that MDS was in many ways more user friendly than factor analysis. MDS has been used quite extensively for commercial products but its use in tourism reseacrh has been limited (Chandra and Menezes 2001).…”
Section: Location-basedmentioning
confidence: 97%
“…MDS is a set of techniques used to analyse similarities in data that produce spatial or geometric representations of complex objects [3][4][5]. MDS had its origin in behavioural sciences for its help in understanding judgements of individuals (as preference, or relatedness) concerning elements in a set of objects [6][7][8]. Nowadays, MDS is used with a large variety of real data, such as biological taxonomy [9][10][11][12], finance [13,14], marketing [15], sociology [16], physics [17], geophysics [18][19][20], communication networks [21,22], biology and biomedics [23,24], among others [25,26].…”
Section: Introductionmentioning
confidence: 99%