Cognitive age as a criterion explaining
senior tourists’ motivations
Ana M. González, Carmen Rodrı́guez, Mauro R. Miranda and Miguel Cervantes
Ana M. González, Carmen
Rodrı́guez, Mauro R.
Miranda and Miguel
Cervantes are all based at
the University of Leon,
Leon, Spain.
Abstract
Purpose – The purpose of this paper is to gain a broader knowledge of the concept of cognitive age
and its use as a variable when segmenting the market of people aged over 55.
Design/methodology/approach – A proposal for measuring this variable was developed, the
dimensions used being: actions, interests, feelings, health, thinking and expectations. A personal
survey of 400 individuals aged over 55 who had been involved in some tourist travel in the last year was
undertaken.
Findings – A principal component analysis resulted in the extraction of a single factor labeled
‘‘cognitive age’’. The outcome of the cluster analysis undertaken was the establishment of two
segments, i.e. active livers and stable passives. The technique of multiple correspondence analysis
reflected differences both in motivations for tourism and in the behavior as tourists of the two segments.
Research limitations/implications – It should be pointed out that there were insufficient repetitions of
the methodology to indicate reliably whether it is consistent and that difficulties were encountered in
gathering information from the group investigated.
Practical implications – The results obtained permit it to be stated that cognitive age enriches
knowledge about senior tourists; hence, it seems to be of interest to take it into consideration when
establishing marketing strategies directed towards this group.
Originality/value – After its overview of the various methodologies relating to cognitive age, this
investigation is one of the few applications of this criterion to segmentation of senior citizen tourists
undertaking journeys of longer duration. Furthermore, it is the sole piece of research so far undertaken to
investigate its usefulness in an individualized manner.
Keywords Tourism, Older consumers, Motivation (psychology), Cognition, Consumer behaviour
Paper type Research paper
Introduction
Misapprehensions about the real conditions in which they find themselves at this stage in
their lives often distort the image of senior customers (Dychtwald and Flower, 1989). People
frequently consider them to be dependent, weak, lonely and physically or mentally limited
(see Appendix 1) (Dychtwald and Gable, 1990; Clary, 1991; Grande Esteban, 1993).
However, most reach this age in full possession of all their capacities, and whenever they
think or speak about old age, they are actually referring to a stage still distant in the future, a
fact that is worth stressing. This state of affairs shows that the stereotype is more an
exception than a rule (Vilchez, 1994), since a new generation of older folk has emerged that
is composed of satisfied, self-sufficient individuals not suffering from any serious limitations
(Cooper and Marshall, 1984; Martin et al., 1998).
Received: March 2008
Revised: May 2008
Accepted: July 2008
PAGE 148
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Hence, modifications are taking place in the characteristics of senior citizens. These
changes, together with the well-known aging of the population, form one of the principal
demographic alterations that will affect the tourism industry, justifying interest in this sector of
the market, as senior citizens now often lead a very active form of life. This activity means
INTERNATIONAL JOURNAL OF CULTURE, TOURISM AND HOSPITALITY RESEARCH
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VOL. 3 NO. 2 2009, pp. 148-164, Q Emerald Group Publishing Limited, ISSN 1750-6182
DOI 10.1108/17506180910962159
they can, and do, engage in a range of leisure activities, among which they include travel,
since they have the time and the money needed to enjoy them (Clary, 1991; Hagan and
Uysal, 1993; Lanquar, 1995; Loverseed, 1993, 2000; Viant, 1993; Dunn, 1994; Van Harssel,
1994; Morgan and Levy, 1996; Chazaud, 1997; Mathur et al., 1998; Javalgi et al., 1999;
Bigné et al., 2000; Dann, 2000, 2001; Wang et al., 2005).
Nevertheless, even if people work with the concept of a sector made up of seniors, they
should remember that seniors are not a homogeneous group in terms of demography,
lifestyles and health, or psychological, social and behavioral patterns (Moschis, 1994,
2003). Indeed, they still constitute a market segment that few have investigated,
understanding which is of more and more interest. This interest comes from an academic
perspective, since there is virtually no theoretical framework in existence for research
applying to this age group. Interest also comes from a business perspective, because this is
a group of consumers that is steadily growing in terms of both size and purchasing power.
Their heterogeneity is so extensive that there is not even any consensus as to how to
describe them in the marketing literature. Various different ways of referring to this group are
in use, the most frequent in the last ten years or so being the following:
B
‘‘older market’’ (Sherman et al., 2001; Carrigan et al., 2004);
B
‘‘mature market’’ (Shoemaker, 2000; Moschis et al., 2004; Wang et al., 2005);
B
‘‘50-plus market’’ (Silvers, 1997);
B
‘‘senior market’’ (Reece, 2004); and
B
‘‘maturing market’’ (Whitford, 1998).
The same vagueness affects the thresholds adopted as the boundary for old age, since
authors fix its onset at anywhere from 50 up to 65 years of age. This vagueness highlights the
relevance of discussions about taking chronological age as a variable when analyzing this
market. The questioning of chronological age arises because numerous studies confirm that
seniors identify themselves as being younger than that age, rejecting the characteristics
typically related to their chronological age and manifesting behaviors influenced by an age
differing from that which calculations using their birth certificates would give (Havighurst and
Albrecht, 1953; Tuckman and Lorge, 1954; Blau, 1956, 1961; Kutner et al., 1956; Phillips,
1956, 1957, 1961; Tuckman and Lavell, 1957; Jyrkilä, 1960; Tuckman et al., 1961; Zola, 1962;
Rosow, 1967, 1974; Guptill, 1969; Barak et al., 1981). These studies back up the claims
various authors make that traditional socio-demographic criteria are not sufficiently
explanatory in view of the growing personalization of individual consumption patterns in
developed economies (Lambin, 1995; González Fernández and Bello Acebrón, 2002).
Cognitive age as a criterion for tourist market segmentation
Trends in measurement of cognitive age
When it comes to analyzing and proposing strategies for more mature consumers, people
increasingly commonly accept that self-perceived age should replace chronological age.
This age is a component of the self-images people have and as a construct authors term it
‘‘cognitive age’’ (Barak et al., 1981; Barak and Stern, 1986; Dychtwald and Flower, 1989;
Moschis et al., 1993).
In the 1950s scholars made the first attempts to measure cognitive age by means of a very
simple method – that of just asking the interviewees to what age category they thought they
belonged. This technique is called a single-item scale (Blau, 1956), and the responses to it
differ from one study to another, although the commonest categories are young,
middle-aged and seniors. Its chief defects are the lack of knowledge of the concepts that
people have of each age category, the influence of negative stereotypes of seniors present
in society (which may bias responses; Rosow, 1974), and lastly the fact that it is a
measurement handling a complex phenomenon in an overly simplistic way (Stephens,
1991). Table I shows the main pieces of research work that use this sort of scale.
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Table I Application of cognitive age scales: single item and semantic differential
Author
Year
Scale
Sector/age group
Comments
Guptill
1969
Semantic differential
Sociology; 55 to 87
Notes the aspects most significant in
measuring age identification
Kastenbaum et al.
1972
Personal agea
Gerontology; 20 to 69
Studies the relationship between
chronological age and the concepts of
personal, interpersonal and
consensual age
Baum and Boxley
1983
Single item
Psychology; 74.5 (average age)
Suggests that being involved in some
personal activity is related to feeling
younger
Guiot
2001b
Personal age (modified)
Consumer behavior; 20 to 75
Analyzes the use of cognitive age when
segmenting the mature women’s
clothing market
Note: aThis scale is the scale on which Barak and Schiffman (1980) base their scale. It is a scale derived from the age decade scale
Later, another scale came into use, the semantic differential scale (Guptill, 1969; George
et al., 1980; Mutran and George, 1982), originally consisting of 50 bipolar adjectives
(Osgood and Suci, 1955). This scale has evolved into simpler versions, permitting evaluation
of self-perceived age by means of a calculation of the distance between the opinion people
have about themselves and their opinions with respect to the other two reference points (see
Table I). Apart from the difficulty of administering this type of test, it has little empirical
underpinning, a fact worthy of highlighting. George et al. (1980) further stress this aspect,
recommending the development of models allowing a description of the causes and
consequences of age identification.
Finally, the most widely accepted scale emerged, termed the ‘‘age decade scale’’ (Barak
et al., 1981), and using as its base the personal age concept of Kastenbaum et al. (1972). Its
measurement looks at four dimensions, relating to:
1. the age people feel they are;
2. the age they think they look;
3. the age that reflects their pattern of actions; and
4. the age that their interests show.
All these are dimensions evaluated in decades of age. Once the figures for each of the
dimensions listed are available, calculation of the cognitive age simply involves taking the
arithmetic mean of the set. This scale constitutes the basis for major contributions and
innovations to the system for measuring cognitive age in recent work (Guiot, 1999, 2001a, b;
Barak et al., 2001; Catterall and Maclaran, 2001; Gwinner and Stephens, 2001; Sherman
et al., 2001; Szmigin and Carrigan, 2001a). Table II lists applications of this methodology.
With respect to the research mentioned previously, an overview of three pieces of work
specifically in the field of tourism and using the age decade scale is of particular relevance
to the current investigation. These are the studies by Cleaver and Muller (1998), Mathur et al.
(1998) and Szmigin and Carrigan (2000).
The research by Cleaver and Muller (1998) verifies the theoretical connection between
cognitive age and reasons for traveling as a new way of segmenting the tourism market. In
this instance the age decade scale uses only two dimensions out of the original four, i.e. age
felt and activities common to the age group (felt and activities), and measurement of the
motives for vacation travel is by means of nine items adapted from Beard and Ragheb (1980,
1983). According to the results of this work, several reasons for traveling and personal
values are associated with the two cognitive age variables considered. Tourism products
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Table II Applications of the age decade scale
Author
Year
Sector/age group
Comments
Barak and Schiffman
1980
Consumer behavior (hair care); 55 þ
Barak and Gould
1985
Barak
1987
Nelson and Smith
1988
Barak and Rahtz
1990
Chua et al.
1990
Goldsmith and Heiens
1992
Wilkes
1992
Van Auken and Barry
1995
Johnson
1996
Villanueva Orbáiz
1997
Barak and Rahtz
1999
Szmigin and Carrigan
2000
Szmigin and Carrigan
2001
Gwinner and Stephens
2001
Catteral and Maclaran
2001
Barak et al.
2003
Goulding and Shankar
2004
Mathur and Moschis
2005
Ramos Soler
2005
Eastman and Iyer
2005
The variable ‘‘cognitive age’’ yields data that cannot
be obtained exclusively from the use of chronological
age
Women as consumers of leisure; 30-69 Considers six concepts of age: chronological,
cognitive, ideal, youthfulness, discrepancy and
disparity
Gerontology; 30-69
Confirms the reliability and validity of the variable
cognitive age. Investigates the area researched by
Kastenbaum et al. (1972) in greater depth
Consumer behavior (advertising for the Combines the concepts of cognitive age and
elderly); 55 and above
cooperation, highlighting differences within the
overall grouping of seniors
Generic; 60 and above
Examines two measures of age – cognitive age and
youth – and their relationship with a set of
characteristics
Consumer behavior; 55 and above
Examines the relationship between the predictors for
successful aging and cognitive age
Gerontology; 21-92
Validates two hypotheses: the greater the
chronological age, the smaller the proportion of it
represented by subjective age; and the greater the
variability in perceptions of the age of people in their
thirties
Consumer behavior (fashion); 60-79
Measurement properties of cognitive age and its
relationship with specific variables
Generic; 55-90
Studies the validity of the construct cognitive age by
means of three methods: semantic differential, Likert
and proportionality (ratios)
Consumer behavior; 18-87
Cognitive age can be a key variable in marketing
travel, recreation, leisure and other related services
Consumer behavior; 50 þ
Cognitive age strengthens and improves analyses of
the behavior patterns of seniors
Generic; 60-94
Examines two specific dimensions: ‘‘perceived
youthfulness’’ and ‘‘feeling old’’. Uses four concepts
of age: chronological, cognitive, perceived
youthfulness and feelings of being old
Consumer behavior (holiday
The study could not validate the hypothesis that
destinations); 50-90
innovatory behavior by consumers is linked to their
perception of their age
Consumer behavior; 50-75
Study of the perception and use of time by seniors,
together with how this influences their purchasing
habits
Consumer behavior; 55-91
Coherence of cognitive age as a criterion explaining
consumer behavior
Behavior of the elderly; 50 and above Argues that age and aging are socially structured,
hence attitudes towards aging are not fixed but
changing
Behavior; 20-59
Compares satisfaction with internal age in four
different cultures in Asia and Africa. This
measurement is the difference between the cognitive
age and the desired age of individuals
Consumer behavior; 30-40
Examines the cultural movement of ‘‘rave’’ festivals
and the influence of cognitive age on the migration of
people from groups of higher ages towards such
events
Consumer behavior; 18-92
A replication and extension of the work by Wilkes
(1992). Factors influencing self-perception and
behavior
Advertising; 65 and above
Studies self-perceived age and life-style as criteria
for segmentation and application to advertising
Internet; 65-85
Seniors with the lowest cognitive ages are more likely
to use the internet in comparison with those with
higher cognitive ages;
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that offer adventure, excitement or challenges are more likely to be attractive to seniors who
feel like, or wish to act like, younger folk.
Another contribution in relation to the field of tourism is the work by Mathur et al. (1998). Their
research incorporates two additional dimensions, ‘‘health’’ and ‘‘thinking’’, alongside the
original four of the age decade scale. This study relates to the concept of new-age elderly of
Schiffman and Sherman (1991), contrasting with the traditional elderly. The study attempts to
identify the new-age segment as a market within the overall group comprising the old, to
pinpoint the values that may distinguish the two groups of elderly and to spot the principal
needs and lifestyles of older consumers. In its definition of cognitive age, six dimensions are
used to elicit an age decade: ‘‘I feel’’, ‘‘I look’’, ‘‘My health is’’, ‘‘I do most things’’ and ‘‘I
think’’, all followed by the phrase ‘‘as though I am in my . . . ’’, and ‘‘My interests are mostly
those of a person in his/her . . . ’’. The results indicate that the cluster of new-age elderly have
as characteristics their greater independence, their desire to be more in control of the
situation and their greater satisfaction with life than is the case for traditional elderly. The
findings also reveal that more advantageous way of achieving segmentation of the seniors
market for travel is the use of variables related to these values.
Investigations by Szmigin and Carrigan (2000) find it is not possible to validate the central
hypothesis of the study, i.e. the idea that consumers with lower cognitive ages would be
more likely to show innovatory behavior. They adopted the four dimensions of the scale as
proposed by Barak (1987) and measured innovatory behavior by consumers by means of
the Domain-Specific Innovativeness Scale of Goldsmith and Hofacker (1991), which shows
itself to be valid and reliable in previous applications (Goldsmith and Flynn, 1992; Goldsmith
et al., 1993). After comparison of the outcomes from the two scales, the results would
indicate that there is no significant relationship between cognitive age and innovatory
behavior on the part of consumers.
Proposal of a model for measuring cognitive age
In view of the small number of specific contributions to the tourism market by investigative
projects using cognitive age, together with the need to widen understanding of the concept
in question, still rather limited among those studying marketing, this research project aims at
establishing a model for measurement and validating it in the sector concerned.
From an overview of information referring to scales and their use, the age decade scale
emerges as having most extensive fine-tuning over the course of time and hence is the scale
with the most testing (see Table III). The model proposed here envisages modifications to the
original version by Barak et al. (1981). It is somewhat similar to the proposals of Mathur et al.
(1998) and of Clark et al. (1999), but even so has substantial adjustments relative to them. In
the first place, the scale suggests incorporation of the dimension termed ‘‘expectations’’,
justifying this inclusion by the fact that many of the ideas that other dimensions reflect
(actions, interests, feeling, health and thoughts) depend on the expectations people have
from life, hence influencing these perceptions. In this way the tool gains a more dynamic
character, with some reflection of the perspectives on life each individual reveals. Secondly,
elimination of the dimension termed ‘‘appearance’’ seems necessary. This omission is the
outcome of a considerable body of literature, in which there are a number of references
indicating its extreme closeness to chronological age, and because it reflects more of a
social aspect, while cognitive age attempts to grasp an internal belief (Barak et al., 1981;
Barak, 1987; Schiffman and Sherman, 1991; Goldsmith and Heiens, 1992; Wilkes, 1992;
Villanueva Orbáiz, 1997; Barak, 1998; Clark et al., 1999; Barak et al., 2001; Guiot, 2001a, b).
Thus, the scale of measurement for cognitive age proposed in this research has as its basis
the use of six items reflecting each of the following dimensions:
1. actions;
2. interests;
3. feelings;
4. health;
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Table III Modified applications of the age decade scale
Author
Year
Sector/age group
Comments
Montepare and Lachman 1989
Gerontology; 14-83
Shows that the subjective age identified varies from
adolescence through to old age, changing systematically.
As chronological age increases, women show a greater
discrepancy between real and subjective age
Mathur et al.
1998
Consumer behavior (travel and
leisure); 55 and above
Investigates the values and lifestyles of the senior citizen
sector and their likely potential for the travel and leisure
market
Cleaver and Muller
1998
Consumer behavior
(psychological motives for
traveling); 56-93
Associates self-perceptions of seniors with the reasons for a
journey and personal values. Uses a two-dimensional scale
Clark et al.
1999
Behavior of mature women; 55
and above
Physical activity can be used as a method for improving and
maintaining health and satisfaction with life. The cognitive
age shown reflects this fact
Sherman et al.
2001
Consumer behavior; 55 and
above
Comparison of the habits of two groups of seniors and the
influence of sex. Verification of the validity and reliability of
the NAVO scalea
Wei
2005
Consumer behavior; 20 and
above
Investigates socio-demographic aspects and cognitive age
in relation to innovatory behavior by consumers
Notes: aNew-Age Value Orientation (NAVO) scale. This scale is a set of characteristics drawn up by Mathur et al. (1998) and Sherman et al.
(2001) to distinguish traditional seniors from ‘‘new-age’’ seniors
5. thinking; and
6. expectations.
These are items that endeavor to define the age group to which individuals believe they
belong.
In respect of the age threshold for consideration in this study of seniors, after a review of the
published literature the decision was to cover people aged 55 years and above, in the light
of the satisfactory results numerous authors obtain in this way (Barak et al., 1981; Javalgi
et al., 1999; Moschis, 1992, 1996, 2003; Marı́n Vidal, 1993; Viant, 1993; Gibson, 1995;
Ortega Martı́nez, 1989; Cai, 1997; Dunne and Turley, 1997; Mathur et al., 1998; Bai et al.,
1999; Faranda and Schmidt, 1999; Shoemaker, 2000; Hsu and Lee, 2002; Reece, 2004;
Wang et al., 2005).
Research method
Objectives, hypotheses and sample design
This work goes further into the concept of cognitive age and its use in segmenting the market
composed of people aged 55 years and above, as also to relate it to motivations and
behavior in respect of tourism. There are also a set of more precise objectives closely linked
with the principal aim:
B
analysis of the cognitive age of tourists;
B
grouping of individuals into segments as a function of their cognitive ages;
B
study of the relationship between the cognitive age of individuals and their motivations for
tourism by segments; and
B
an investigation of tourist behavior on long-duration journeys of each segment.
The hypotheses adopted for the research are the following:
H1.
Significant differences occur between the cognitive age and the chronological age
of seniors.
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H2.
Different cognitive ages highlight the existence of varying motivations for tourism
among seniors.
In light of the objectives noted above, the study performed a personal survey of individuals
aged 55 years of age and above who had undertaken some tourist travel in the last year. This
did not just sample individual households, but also leisure centers for seniors, because there
is one in each of the zones into which the city analyzed is divided and also because they
bring together high concentrations of the population under study. The technical details of the
study are specified in Table IV.
The study uses a questionnaire with four sections:
1. habits regarding tourism involving long-duration journeys, i.e. destination, type of
accommodations used, type of transport, corporation organizing the journey and specific
reasons for each of the journeys referred to;
2. motivations for tourism;
3. cognitive age; and
4. demographic and socio-economic characteristics.
Hypothesis testing
To attain the aims of the current piece of research, various multi-variable statistic techniques
were used. Firstly, principal component analysis was the technique that rendered down the
information from the six dimensions going to make up cognitive age, measured in
accordance with the model proposed. The outcome is the extraction of a single factor
explaining approximately 82 percent of the total variance, consequently labeled ‘‘cognitive
age’’, as it clearly represents that variable very accurately. The figures for the statistics
justifying the analysis described are noteworthy, being 0.93 for Kaiser-Meyer-Olkin and
2,503,640 for Bartlett’s test.
In relation to analysis of the validity and reliability of the cognitive age scale being proposed,
the value for Cronbach’s a reaches 0.95. This figure indicates an excellent level of internal
consistency for the scale and corroborates the relevance of the new dimension included in
the scale.
Since one of the objectives of the investigation is to segment the market by using the
cognitive age variable, cluster analysis in accordance with Ward’s method was used, the
variable for differentiating individuals being the cognitive age factor emerging from the prior
analysis. The results emerging clearly show a distinction between two groups within the
sample. One of these reaches a total of 223 subjects, termed ‘‘active livers’’, presenting a
large majority of individuals whose cognitive ages are lower. The other group, amounting to a
total of 177 individuals, are those people termed ‘‘stable passives’’, their cognitive ages
being higher, while this group also has a much larger percentage of subjects who feel as old
as their real age.
Table IV Technical details of study
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45,851 people of both sexes, aged 55 years and above and living in Leon, a
Spanish city
Sample
400 people aged over 55 having undertaken some form of travel for tourist
purposes during the previous 12 months
Technique
Personal survey in the form of a structured questionnaire
Sampling procedure
Multi-stage random sampling with proportional assignment by district, sex
and age
Sampling error
5 percent (p ¼ q ¼ 50)
Confidence level
95.50 percent (K ¼ 2s)
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Once this natural grouping emerges, validation of it is necessary. The technique in use is
discriminant analysis. An application of this method also serves to check the first hypothesis,
that there are significant differences between the cognitive age and the chronological age of
seniors.
With the intention of pointing up the differences between the two variables, i.e. cognitive age
and chronological age, and to facilitate checking that the first is superior to the second,
calculation of various statistics for discriminant analysis are necessary. Both Wilks’s l
(Table V) and Box’s M (Table VI) show higher values for cognitive age as opposed to
chronological age, which gives positive support for the first hypothesis. With respect to the
canonical discriminant functions, more than 80 percent of the function visibly explains the
differences between the groups, but this figure does not show the same forecasting capacity
in relation to chronological age.
A look at the results of the classification shows that the percentage of individuals correctly
classified reaches an optimum level of 100 percent in the case of the use of cognitive age for
analyses (Tables VII and VIII). Comparison of these results with the distributions of
chronological ages of individuals by segments makes demonstrates clearly that percentage
of individuals correctly classified decreases substantially, since the cognitive ages differ
significantly from the chronological (Table IX).
Next, the ways in which different perceptions of age in relation to motivations for tourism
manifest themselves were subjected to analysis. These ways are measured by means of a
set of statements deriving from the research by Beard and Ragheb (1980) and Kabanoff
(1982) (see Table IV). To this end, the technique of multiple correspondence analysis, with
application to each group separately for the 12 active formats reflecting reasons for involving
in tourism, is the choice. The intention is to enrich the description of these groups and
emphasize their motivations in an independent way, since the factors emerging from the
application of this analysis are different for each of the segments. This selection also permits
checking of a second hypothesis, that different cognitive ages make it plain that there are
Table V Tests of equality for group averages. cognitive age/chronological age
Cognitive age
Birth year
Wilks’s l
F
gl1
Gl2
Significance
0.34
0.66
780.82
206.01
1
1
398
398
0.00
0.00
Table VI Results from Box’s M test: cognitive age/chronological age
Box’s M
Approximately
gl1
gl2
Significance
Cognitive age
Chronological age
2.21
0.92
1
458508.50
0.34
0.92
2.21
1
458508.46
0.14
Note: Confirms the null hypothesis that the population covariance matrices are the same
Table VII Self-values: cognitive age/chronological age
Cognitive age
Chronological age
Function
Eigenvalue
Percentage
of variance
Accumulated
percentage
Canonical
correlation
1
1
1.96a
0.52a
100.00
100.00
100.00
100.00
0.81
0.58
Note: aThis analysis uses the first canonical discriminant functions
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Table VIII Results of classificationa,b: cognitive age
Predicted grouping
1
2
Ward method
Original
Count
Percentage
Cross-validationa
Count
Percentage
Total
1
2
1
2
223
0
100.00
0.0
0
177
0.0
100.00
223
177
100.00
100.00
1
2
1
2
223
0
100.00
0.00
0
177
0.00
100.00
223
177
100.00
100.00
Notes: aCorrectly classifies 100.00 percent of the original grouped cases; bcorrectly classifies 100.00
percent of the grouped cases validated by cross-validation
Table IX Results of classificationa,b: chronological age
Predicted grouping
1
2
Ward method
Original
Count
Percentage
Cross-validationa
Count
Percentage
Total
1
2
1
2
187
56
83.90
31.60
36
121
16.10
68.40
223
177
100.00
100.00
1
2
1
2
187
56
83.90
31.60
36
121
16.10
68.40
223
177
100.00
100.00
Notes: aCorrectly classifies 77.00 percent of the original grouped cases; b correctly classifies 77.00
percent of the grouped cases validated by cross-validation
varying motivations for tourism among seniors. The results show that for the active livers
segment, four motivational factors emerge that explain more than 60 percent of the variance:
getting acquainted with new people, breaking with routine, traveling for health and the
pleasure of becoming acquainted with new places or things. In contrast, the four
motivational factors that are relevant for the stable passives segment, explaining nearly 70
percent of the variance, are: cultural novelties, personal development, shared relaxation and
isolated challenge (see Appendix 3). Analysis of the factorial maps obtained would permit
observation of the relationship between cognitive age and motivations for tourism.
Interpretation of the different ways of responding to motivations in the various factorial maps
for the two segments permits the observation that the group termed ‘‘active livers’’ presents
as the principal characteristic motivating their journeys the possibility of facing challenges,
combined with a certain degree of standoffishness. In fact, they show no interest in traveling
in an organized group, or in getting acquainted with other people or cultures at their
destinations. Furthermore, they consider travel to be necessary for maintaining their health
and balance. For them travel may well be just one more activity to which they are
accustomed, which interests them, and which they enjoy.
Furthermore, with respect to the details for Segment 2, the stable passives, their posture of
indifference to the various motivations proposed requires emphasis, an attitude which links to
the group’s rather inactive profile. They may well travel just for the sake of traveling, showing
some apathy with respect to specific motivations. This behavior is probably due to the taking of
simple decisions not requiring much involvement on their part, as very often they limit
themselves to leisure packages programmed by associations specializing in catering to seniors.
The final part provides a description of the longer-duration journeys made by the two
segments, showing that active livers travel considerably more often than stable passives.
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People in the first group prefer cities, which may be on the coast or inland, while those from
the second visit either cities or towns and villages, but always on the coast. Even
destinations chosen within Spain are different, since active livers prefer the Northern
(Cantabrian) coast, but stable passives the Eastern (Mediterranean) shoreline. As for foreign
destinations, the first segment is the one choosing these primarily. In relation to other
behavioral habits, the groups also show a number of differences. Active livers select higher
price range accommodation, and normally travel in their own vehicles, either as couples or
with their family, their chief reasons for travel being to do something interesting for the family
group or to visit family or friends. However, stable passives mostly take middle to low price
range accommodation and generally travel by bus accompanied by their spouses or in an
organized tour group. The packages on offer from associations which specialize in tours for
seniors in Spain, like the Social Security linked organization called ‘‘Imserso’’, the
local-government-backed set-up called ‘‘Club de los 60’’, and others of a similar nature are
the chief options they take into account when making choices about travel plans.
Conclusions of the research
The intended objective of this research is to gain a deeper knowledge of the concept of
cognitive age and its use as a variable when segmenting the market of people aged 55 years
and above. This objective is of interest, because among the academic community there is an
increasing recognition of the need to understand the heterogeneity of senior consumers. In
fact, a number of academics, upon consideration, indicate that research which introduces this
variable is better for it. Thus, Sherman et al. (2001) conclude that cognitive age is more
effective as an indicator of satisfaction with life than chronological age. Barak and Rahtz
(1999) find that those people who have a lower cognitive than chronological age have higher
self-esteem and greater confidence in their abilities. Furthermore, Chua et al. (1990) state that
those who are cognitively younger show greater satisfaction with life, are more active, and
more socially involved. Likewise, when it comes to the capacity to predict behavior, cognitive
age proves to be superior as compared to the traditional variable, chronological age (Smith
and Moschis, 1984; Sherman et al., 2001). This requires greater awareness of its nature, with
an eye to defining marketing strategies more directed towards such people’s needs and
wishes.
In relation to this reality, segmentation of the seniors market clearly needs to develop along
the same lines. This is the motive for proposing the use of a new criterion for segmentation,
cognitive age, since there are research findings that indicate that the perceptions people
have of their age influence their behavior patterns. In the case of segmentation focusing
specifically on seniors, there is even more justification, because as an individual’s age
increases an ever greater dissociation between real age and the individual’s own perception
of personal age comes into play.
After its overview of the various methodologies relating to cognitive age, this investigation is
one of the few applications of such a criterion to segmentation of senior citizen tourists
undertaking journeys of longer duration. Furthermore, it is the sole piece of research so far to
investigate its usefulness in an individualized manner, not associating it with other variables,
the intention of this approach being to justify its inclusion as standard in questionnaires, as
has traditionally been done with chronological age. Research usually incorporates cognitive
age together with other variables, such as values or lifestyles. Consequently, it does not
discover whether a specific piece of behavior is derived from the individual’s cognitive age
or from the other variables under consideration. In the present piece of work, analysis of
cognitive age is isolated, making possible the demonstration that different cognitive ages
show differing behavior patterns in respect of tourism.
To this end, the work puts forward proposals for measuring this variable, taking as a starting
point the original model for the age decade scale of Barak et al. (1981) and showing some
similarity to the suggestions made by Mathur et al. (1998) and by Clark et al. (1999).
However, this work proposes the omission of the dimension called ‘‘appearance’’. Support
for such an omission comes from an extensive range of literature which offers various
references to indicate the great proximity of this dimension to chronological age. A further
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VOL. 3 NO. 2 2009 INTERNATIONAL JOURNAL OF CULTURE, TOURISM AND HOSPITALITY RESEARCH PAGE 157
adjustment is the inclusion of a new dimension, termed ‘‘expectations’’, as many of the
conceptions reflected in the other dimensions (actions, interests, feelings, health and
thoughts) would seem to depend on the expectations subjects have in life, so that this gives
a more dynamic character to the tool.
After the demonstration of the value of the measurement, the outcome of its application is the
establishment of two segments, called ‘‘active livers’’ and ‘‘stable passives’’. Subjects in the
first of these two groups characteristically have a perception of their age lower than its real
value, while those in the second have a cognitive age equal to or greater than their
chronological age. The level of agreement between chronological and cognitive age is very
low. Both motivations for tourism and the behavior as tourists of the two segments reflect these
differences. Thus, active livers seek some degree of isolation and like to meet challenges when
traveling. They see travel as permitting them to maintain an adequate balance in their state of
health and hence they consider it to be a habitual activity, which they enjoy. With respect to their
habits, they show a preference for cities, whether on the coast or inland, outside or within Spain.
Within Spain the Northern coast is one of their favorite destinations, with travel being in their own
private vehicles. They tend to stay in higher price range accommodation, traveling either as
couples or as a family, with the intention of visiting family or friends, but on other occasions with
the aim of doing something that will interest the family group.
Stable passives characteristically express indifference to the various motivations suggested
in the course of this research. They present a somewhat inactive profile, probably due to
taking simple decisions that do not imply much involvement on their part, since very often
they do no more than participate in packaged leisure travel. They visit both cities and smaller
places, as long as they are costal, mostly destinations on the Mediterranean shores of Spain,
and prefer to travel by bus. They usually stay in middle or low price range accommodation,
accompanied by their spouses or in an organized travel group. The packages offered by
associations that specialize in dealing with the elderly, such as Imserso, Club de los 60 and
other similar groups are the principal options they consider when planning travel.
Finally, the results obtained permit the statement that cognitive age enriches knowledge about
seniors as tourists, because Wilks’s l and Box’s M statistics show higher values for this variable
and because more than 80 percent of the canonical discriminant function explains the
differences between groups. This finding demonstrates that the variable is more discriminating
than chronological age and also influences reasons for tourism, highlighting differentiated
behavior patterns. Hence, taking it into consideration when establishing marketing strategies
directed towards this group would seem to be of interest. To take it into account from a
professional angle when establishing marketing strategies, such as market segmentation, as
also when deciding on business actions like defining the tourist service that is to be offered or
which sort of advertising message will be most impactful, would also appear to be useful.
The fact that there may be some defects in the approach taken here should receive some
emphasis. One major limitation relates to the lack of a full methodological framework, as
there is a shortage of repetitions of the methodology that could indicate whether it is
consistent. Another point for highlighting is the chronological age of the group investigated,
since, as this rises, the difficulties in gathering information increase as a consequence of
lack of concentration and problems of understanding, which may sometimes lead to bias in
the data recorded. Moreover, as this work is the first investigation in which the scale
proposed has been used, a great deal still remains to be done in terms of demonstrating and
improving the process of applying it, which underscores the need to carry out future lines of
research so as to gain a deeper awareness of these features. For these reasons, work on the
following lines of investigation would appear to be appropriate:
j
B
to check on the usefulness of cognitive age in association with other types of variable in
the tourism market;
B
to compare the results obtained from its application to other target groups, such as the
young or the middle-aged; and
B
to apply the study, in just the format used here, more extensively, comparing results from
different countries relating to the behaviors and preferences of seniors as tourists.
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Appendix 1: Myths or stereotypes about the elderly
B
They lack purchasing power.
B
Their mental capacities are impaired or they are ailing.
B
They constitute a homogeneous group.
B
They see themselves as old.
B
They are reluctant to try new products or services.
B
They are not physically active.
B
They are uneducated.
B
They are unproductive.
B
They do not represent a substantial market.
Appendix 2: Model proposed for measuring cognitive age
I feel as though I am in my:
I look as though I am in my:
My health is as though I am in my:
I do most things as though I am in my:
I think as though I am in my:
My interests are mostly those of a person in his/her:
Response options: 30s, 40s, 50s, 60s, 70s, 80s, 90s (age groups).
Appendix 3: Items included among motivations for tourism
B
When I travel, I enjoy group activities.
B
For me, traveling is a way to achieve personal enhancement.
B
I travel to get away from daily routine.
B
Traveling so as to get acquainted with other cultures is one of my pleasures.
B
I travel with the aim of learning something new.
B
I am attracted by the challenges that I may face when traveling.
B
When I am on vacation, I want to get away from it all.
B
When I travel, I try to relax from day-to-day stress.
B
What I like best about traveling is getting acquainted with new people and making new
friends.
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B
Traveling should be a way of strengthening family ties.
B
My journeys are important in keeping me fit.
B
I like traveling so as to practice foreign languages.
Corresponding author
Ana M. González is the corresponding author and can be contacted at: amgonf@unileon.es
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