Visitor attractions are found in both urban and rural settings and they constitute
the mainstay of the tourism industry; therefore, it can be assumed that a diverse
group of people will visit attractions of one shape/form or another and that the
visitors’ profile will differ from one type of attraction to the other in terms of
socioeconomic and demographic characteristics. The use of socio-demographic
features is a prevalent and generally accepted basis of segmenting the market
(Kotler and Armstrong, 1991). It is imperative that marketers and managers of
products, including attraction products, understand the socio-demographic
characteristics of their customers in order to judge the market size and spread.
The term socioeconomic status denotes the economic and social position of an
individual as revealed by a number of indicators. The commonly used social
indicators in services management and tourism studies include level of
education and type of occupation. The main economic indicator used in
empirical studies is income; and the commonly employed demographic
indicators are age, gender, marital status and origin. These are often examined
in tourism and related studies to assess consumption patterns and consumer
perceptions of products/services. Jansen-Verbeke (1990), in an investigation of
socio-demographic effects in a shopping context found attitudes towards
shopping, frequency and patterns to be related to visitor characteristics like
age, gender, stage in life cycle and social status. Socio-demographic
characteristics have also been found to affect visitor perception of quality
(Webster, 1989; Iacobucci and Ostrom, 1993; Kelley and Turley, 2001;
Ganesan-Lim, 2008); value (Kumar and Lim, 2008) and satisfaction (Oyewole,
2001; Spinks et al., 2005) and subsequently behavioural intentions.
IPSO MORI’s (2001), study, on behalf of, the Council for Museums, Archives
and Libraries, investigating overall visitation trends, the core visitor market and
the attitudes of visitors towards museums, found that students are the most
likely section of the public to visit museums and art galleries (Table 2.7). One
third of the people sampled in the 25-64 age range (without children) had
visited a museum or art gallery within the study time frame. People age 65 and
above accounted for the largest portion of visits followed by people aged 45-
64; as such, the museum and art gallery product is heavily dependent on middle
aged and senior consumers. The identified managerial implication was the need
for museums and art galleries to evolve through audience development and
marketing generally.
The stage in family life cycle is another demographic indicator used in
empirical studies. The role of children in decision making for the consumption
of leisure and related products cannot be over emphasised. Since the theme
park product has the family market as its main target, this aspect becomes an
imperative one for marketers. McNeal and Mindy (1996), in their study of
Chinese family decision making for leisure time, reported that parents
acknowledged that the children mostly determine what the entire family does
on the weekends, and that families will generally go to places and do things
that provide fun for the children.
Table 2.7 Visit to Museums and Galleries – Life Stage % of UK population % of visitors to museums & galleries Average frequency of visit per annum Estimate d % of all visit Base: All (4,461) % % % % Adults 65+ 19 15 2.97 16 Adults 55-64 11 14 3.10 15 Adults 45-54 11 13 3.22 14
Adults 25-44 (with children aged 5-10)
14 14 2.50 13
Adults 25-34 9 10 3.00 11
Adults 25-44 (with children 4 or under)
12 9 2.55 8
Adults 35-44 5 7 3.20 7
Young adults 16-24 9 9 2.46 7
Adults 25-44 (with children aged 10+)
8 7 2.42 6
Students 4 6 2.49 5
Young adults 16-24 (with children)
7 4 2.53 4
Source: MORI, 2001
Spinks et al’s (2005) research work that investigated the influence of
individual visitor characteristics on satisfaction with tourist attractions revealed
that significant differences exist between satisfaction levels experienced by
visitors of differing origins, genders and age groups. The study also highlights
the need for attraction managers to develop strategic marketing mixes for
different market segments. Conversely, Reisinger and Turner (2002) found less
evidence to suggest that there is a particular need to segment the tourism
market demographically in relation to shopping.
Iacobucci and Ostrom (1993) found that customer’s gender had some effects
on the judgement of core services. Ganesan-Lim et al (2008) developed a
service–based demographic framework for studying service quality perception
based on four service quality dimensions – perceived interaction quality, 93
physical environment quality, outcome quality and system quality. Contrary to
Iacobucci and Ostrom’s (1993) conclusion their findings did not reveal any
significant effect of gender on any of the four service quality dimensions.
Ganesan-Lim et al’s (2008) study also indicated that age had a significant
effect on perceived interaction quality, physical environment quality, outcome
quality and system quality. Mature respondents had significantly higher
perceptions of all four service quality dimensions than their younger
counterparts. Webster’s (1989) study of customer segmentation on the basis of
service quality expectations also revealed that age has a significant effect on all
service quality dimensions in professional service. The study revealed that in
professional service, middle-aged (35-64) respondents placed more importance
on reliability, responsiveness, competence and access. However, this category
of respondents did not place much importance on credibility and tangibility
like older consumers. On the other hand, Webster’s (1989) study failed to
indicate a significant effect for age on 33 out of 34 quality attributes in a non
professional service context, although the results showed a positive relationship
between age and perceived importance of nonprofessional service quality.
The effects of the socio-demographic characteristics on the perception of value
have also been documented. Kumar and Lim (2008), in a mobile service
perception study, found significant differences between Generation Y and the
baby boomers in terms of the effect of perceived economic and emotional
value on satisfaction. The study further revealed that the effect of emotional
value on satisfaction was stronger for Generation Y than baby boomers. In like
manner, economic value had a significant effect on satisfaction for baby
boomers whilst this was not the case for Generation Y.