Whose perceptions are reality? Revealing the Gap between real demographic profile of visitors and tourism providers’ perceptions of this profile
Abstract The aim of this research paper is to investigate the existence of discrepancies or gaps between the actual demographic profile of visitors and providers’ estimate of this profile within the context of a tourism destination. This study is the first in marketing literature to investigate such a gap. A modified gap analysis is used to measure and interpret the results. Results highlight the importance for providers of acknowledging visitors’ most observable and measurable variables, such as demographic characteristics, in order to develop sustainable destination strategies. This gap analysis may prove to be an extremely useful tool for destination marketing managers in charge of the market segmentation and the destination marketing strategy. Keywords: Demographic segmentation, Modified gap analysis. Track: Tourism Marketing
1. Introduction The importance of market segmentation as a basis for developing a destination marketing strategy is widely acknowledged (e.g. Bieger & Laesser, 2002; McCleary & Uysal, 1995, Tkaczynski, Rundle-Thiele, & Beaumont, 2008) and there has been a distinguished body of researches into tourism destination segmentation research (Frochot, 2005; Johns & Gyimothy, 2002). This paper investigates the gap between the demographic profile of destination visitors and providers’ estimate of this profile, using a modified gap analysis. The implicit assumption of this investigation is that the possession of spherical knowledge of destination visitors’ profile by local destination stakeholders is crucial for the successful operation, sustainability, and long-term viability of the destination.
2. Literature review 2.1 Tourism market segmentation research Tourism researchers acknowledge that market segmentation is a widely accepted strategic marketing tool in tourism industry (Hanlan, Fuller, & Wilde, 2005). Middleton (2001) suggests that segmentation in tourism research may be defined as a process of dividing a total market, such as all tourists, into manageable sub-groups. The basic idea underlying tourism market segmentation is to identify or define groups of tourists who are similar with respect to the construct of primary interest, for instance, travel behaviour, travel motives and patterns of expenditure (Dolnicar, 2006). Market segmentation research has a long history in tourism research (Bieger & Laesser, 2002; Kastenholz, Davis, & Paul, 1999; Cha, McCleary, & Uysal, 1995). Both a priori (Mazanec, 2000) or commonsense (Dolnicar, 2004) and post-hoc (Myers & Tauber, 1977) or a posteriori (Mazanec, 2000) or data-driven (Dolnicar, 2004) segmentation studies have frequently been undertaken to gain an in-depth understanding of the tourism market in order to improve the possibilities of targeting marketing activities towards attractive sub-markets. The merits and limitations of two key approaches to market segmentation (see Dolnicar, 2004, 2006; Kara & Kaynak, 1997; Wind, 1978) highlight the number of subjective decisions inherent in typical studies (Hoek, Gendall & Esslemont, 1996; Everitt, 1974). 2.2 Demographic segmentation research In reviewing the tourism marketing literature, demographic (e.g. Burnett & Baker, 2001; Juaneda & Sastre, 1999; Galley & Clifton, 2004), psychographic (e.g. Baloglu & Uysal, 1996; Cha, et al., 1995), geographic (Bonn, Joseph, & Dai, 2005; Moscardo, Pearce, & Morrison, 2001) and behavioural characteristics (Bonn, Furr, & Susskind, 1999; Kastenholz, Davis, & Paul, 1999) are the most frequently used segmentation bases. Researchers use these bases either singularly (e.g. Kim & Lee, 2002; Reece, 2004; Simpson & Bretherton, 2004) or in combination (e.g. Baloglu & Shoemaker, 2001; Bojanic & Warnick, 1995; Court & Lupton, 1997; Dolnicar & Fluker, 2003; Etzel & Woodside, 1982; Morrison, Hsieh, & O’Leary, 1994) to develop tourist profiles for chosen destinations. In particular, there has been an emphasis on psychographic and behavioural segmentation in the recent tourism literature (e.g. Frochot, 2005; Simpson & Bretherton, 2004) as these segmentation variables are more able to predict tourist behaviour (Johns & Gyimothy, 2002). Finally, whilst most segmentation studies have collected visitor data using quantitative data via questionnaire surveys (e.g. Baloglu &
Shoemaker, 2001; Dolnicar & Fluker, 2003), there are few cases where qualitative research has been utilised (Laws, Scott, & Parfitt, 2002; Scott & Parfitt, 2005). Within the broad areas of tourism segmentation it is widely acknowledged that demographic segmentation is the most common approach to market segmentation for destination marketing (Tkaczynski, et al., 2008). Demographic segmentation categorises visitors by variables such as age (Anderson & Langmeyer, 1982), gender, family life cycle (Fodness, 1992), income (Juaneda & Sastre, 1999), occupation, education, religion, race, nationality (Bowen, 1998) and socio-economic status (Gartner, 1996; Morrison, Braunlich, Cai, & O’Leary; 1996). Generally, sociodemographic variables have been considered as quite usable, since they are easy to assess (Lawson, 1995) and inexpensive, while segments based on demographics are easy to form (Moriarty & Reibstein, 1986; Bonoma & Shapiro, 1983; Griffith & Pol, 1994) and measure (Brayley, 1993; Bowen, 1998). However, they have also been identified as inadequate (even poor) determinants of tourist behaviour (e.g. Baloglu & Brinberg, 1997; Kastenholz, 2002; Gitelson & Kerstetter, 1990; Cha, et al., 1995; Morrison, Braunlich, Cai, & O’Leary, 1996; Johns & Gyimothy, 2002). But, they are still more objective and measurable than the unobservable variables. These are some of the primary reasons that indicate why these variables have been widely used as bases for segmentation by tourism researchers and practitioners. 2.3. Towards a modified gap analysis in demographic characteristics measurement This paper investigates the gap between the demographic profile of visitors and providers’ estimate for this profile using a modified gap analysis. The implicit assumption of this investigation is that the possession of market knowledge by local destination stakeholders is crucial for the successful operation, sustainability, and long-term viability (Atuahene-Gima, 2005; Avlonitis & Gounaris, 1997) of the destination. Parasuraman et al. (1985) identified five gaps where customers’ expectations and performance evaluations were interpreted by providers. Brown and Swartz (1989) expanded the Gaps Model to include a gap which reflect the differences between customers’ experiences and providers’ perceptions of customer experiences (i.e., Gap = customer perceptions – providers’ estimate of customer perceptions). Brown and Swartz (1989) study medical care services and put professionals (doctors) to answer according to what they believe that customers would answer and afterwards they compare the results with the evaluation of visitors themselves for the experience of service. Apart from subjects that measure diagnostic practices, the grades of visitors are higher than the level that the doctors expect that customers would answer. Despite the recognition of the last gap from many authors in service marketing (see Candido & Morris, 2000), only one study examined this gap ever since, doing this in tourism trade sector (Vogt & Fesenmaier, 1995). Vogt and Fesenmaier (1995) in their study find that service providers (retailers ) do not understand the level at which customers evaluate their experience and tend to underrate the customer experience, confirming thus Brown and Swartz’s (1989) research results. This paper investigates this gap in relation to the demographic profile of visitors, a notion that have never been examined before. Discrepancies between the perception of tourism providers concerning the demographic profile of destination visitors and the actual profile of visitors is the focus of the study. By empirically testing this gap the purpose of this study is doubleedged: on the one it sheds more light on the importance for providers of acknowledging visitors’ most observable and measurable variables, such as demographic characteristics, and on the other hand it constitutes an effective marketing tool helping destination marketers in the task of market segmentation and the destination marketing strategy.
Schematically, the following equation depicts this gap: Gap = visitors’ demographic profile – providers’ estimate of tourists’ demographic profile
3. The Study In order to examine the extent which visitors’ actual demographic profile and providers’ perceptions of this profile coincide or not, research formulated the main research hypothesis (Ho: there is no difference between tourists’ destination experience and providers’ estimate of tourists’ experience). 3.1 Research methodology Data was collected from visitors and service providers in the tourism destination of Olympia, throughout two separate survey efforts. Olympia is one of the most famous and visited destinations in Greece for international tourists. A multi-stage sampling scheme adopted to approach the sampling elements (i.e., tourists), during the field research figures in the following two-level stage units: first stage units were the opening hours of the destination’s main attractions (Archaeological Site and Museum), whereas second stage units comprised of the people that visited the archeological attractions. On the other hand, the local Chamber of Commerce provided lists of destinations’ services provided that constituted the sampling frame. After the completion of the questionnaire phase correlations were run to investigate possible random discrepancies (i.e., year-to-year fluctuations) of the data. According to the results the sample proved representative of destination visitors’ population. 3.2 Questionnaire design This study departs from previous studies (Brown & Swartz, 1989; Vogt & Fesenmaier, 1995) by not using the SERVQUAL scale for the gap measurement. Instead, it employs performance only measures due to the disadvantages of the disconfirmation approach in tourism (Dorfman, 1979; Crompton and Love, 1995; Yuksel & Rimmington, 1998) and destination studies (Kozak & Rimmington, 2000). Each provider completed a questionnaire largely identical to that the customer completed. In some parts of the questionnaire, statements were transformed from the customer’s to the employee’s perspective. 3.3 Measurement The measurement scales for this study were developed based on five demographic variables: nationality (U.K, French, German, Greek, Italian, other), gender (male, female), visitors’ age (15-18, 19-29, 30-39, 40-49, 50-59, more that 60+), visitors’ level of education (primary education, secondary, university students, university graduates and postgraduates), and finally visitors’ monthly income (less than 800, 800-1499, 1500 – 3000, more than 3.000 euros).
4. Results Univariate analysis and chi square tests were performed to evaluate the difference in means between tourists' and providers perceptions. A total of 268 usable questionnaires (response rate of 71%) were collected from the visitors of the destination under study over the course of two months. On the other hand, the service provider self-completion survey
achieved a 76.5% response rate or 95 usable questionnaires. The demographic characteristics of visitors along with providers’ perceptions of these variables are presented in Table 1 (see Appendix). Table 1 demonstrates that the majority of tourists that visit the destination is British and French (1 out of 3 visitors), of both genders, young, aged from 19 to 29 (32.5%), university graduates and postgraduates (50.4%) and of middle-up monthly income (1500-3000 euros). However, tourism providers believe that destination visitors are British, of both genders, older people aged from 40 to 50 (30.5%), college graduates (45%) and of the lowest monthly income (less than 800 euros). These differences are pictured in Graph 1.
Graph 1. Demographic Profile of Destination Visitors and Providers’ estimate of visitors’ profile
Visitors’ actual demographic profile Providers’ estimate of visitors’ profile
Finally, Chi-square and tests provided support the gap in providers’ perceptions of tourists profile and actual profile (Table 2).
Table 2. Chi-square statistics and Fisher's exact test (2-sided)
Differences between visitors' demographic profile and providers’ perceptions of this profile Nationality Sex Age Education Income (monthly) .001 .000 .000 Chi-square .000 .076 Fisher's exact test (2-sided)
5. Discussion This study investigates the gap between the perception of tourism providers concerning the demographic profile of destination visitors and the actual profile of visitors portrayed in the study. Research hypothesis was verified almost in its total, as only one of the five partial hypotheses was rejected (that about visitors’ gender). Results show that the majority of visitors of the destination are young, British and French (one out of three), of both genders, hold a university degree and their monthly income ranges from 1.500 – 3.000 euros. On the other hand, results show a false estimation of tourism professionals for the majority of demographic characteristics of visitors (with the exception of gender). Namely, tourism professionals hold the perception that destination visitors are uneducated, poor and older that they really are. Consequently, we could detect a major ‘under-estimation’ of visitors’ educational and income level. The aforesaid finding is of particular importance for Marketing researchers and practitioners, considering both the significance of demographic characteristics for the buying behavior of consumers, and the extensive use of those characteristics in market segmentation and the identification of distinctive market segments/target groups. An example that reflects the impact of this gap can be traced in connection to destination visitors’ age. According to providers’ estimations visitors of the destination are senior people. This perception leads destination marketing managers to the delivery of tourism offerings and services adjusted to senior visitors. The existence of a pleonasm of jewellery shops in the destination – product that traditionally target older visitors (Turner & Reisinger 2001) - argues in favour of the finding of the study. On the other hand, younger visitors’ traditionally spend more on music or multimedia tourism applications, books and gifts for others (Kim & Littrell, 2001). This example clearly demonstrates the fact that false perceptions might lead to ineffective decision making for marketing in terms of segmentation, positioning and marketing mix formulation. To conclude, results highlights that tourism providers’ misconceptions about the demographic characteristics of the destination visitors might have serious impact on the planning and delivery of the tourism service and experience.
6. Conclusion and Implications The purpose of the present study was to provide an effective marketing segmentation tool for a better understanding of customer’s demographic profile by empirically testing it in the context of a tourism destination. This study is the first in marketing literature to investigate such a gap. Overall, results provide strong support for the notion of this gap analysis. More specifically, findings indicate that discrepancies between providers’ perceptions concerning the demographic profile of visitors and the actual profile of visitors might have serious impact on the planning and delivery of the destination experience. Moreover, this gap analysis might constitute an effective marketing tool helping destination marketers in the task of market segmentation and the destination marketing strategy. Surveying both visitors and providers on a regular basis, as part of gap analysis, is an excellent tool to show different ways on how tourism managers are able to reach each target market with a suitable range of offerings and propose an integrated solution to customer needs and wants (Buhalis, 2000). In conclusion, there is of course a strong need for further and more detailed evaluation of the nature, structure and dynamics of this gap (e.g. the degree of "closeness to customers", and the need for the inclusion in measurement of all types of employees involved in delivering the service and the imperative of measuring the totality of the customer’s experience).
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Table 1. Demographic Profile of Destination Visitors and Providers’ estimate of visitors’ profile (frequencies and ranking) Demographic categories Nationality UK French German Greek Italian Other Gender Female Male Age 19-29 30-39 40-49 50-59 15-18 Education University graduate Postgraduate College graduate University Student Basic Monthly Income More than 3000 euros 1500 - 3000 800-1499 Less than 800 euros Visitors (%) Rank Providers (%) Rank
18.4 15.8 13.2 13.2 10.2 29.1
1 2 3 3 5 6
18.9 32.6 14.7 3.2 17.9 12.6
2 1 4 6 3 5
32.5 22.8 17.9 16.0 4.5
1 2 3 4 5
9.8 29.3 30.5 25.6 4.9
4 2 1 3 5
27.2 25.3 22.2 20.6 4.7
1 2 3 4 5
15.7 0 44.9 9.0 30.3
3 5 1 4 2
41.9 26.5 17.2 14.4
1 2 3 4
26.7 21.1 37.8 14.4
3 4 2 1