1. Introduction
To adapt their tourist offers to different consumer segments, the tourist intermediary industry has faced multiple challenges. As differences and inequalities in travelers’ experiences have become more widely recognized in recent years [
1,
2], awareness of the need to address variables that can influence travel decisions has increased [
3]. There are numerous existing research studies addressing aspects related to tourist consumer behavior and their decision-making processes [
4,
5,
6,
7]. The sociodemographic attributes of tourists are essential factors in decision-making processes, and motivations for travel are explained mainly by a series of indicators, including age, gender, marital status, educational level, employment status, and income level [
5,
8].
Understanding consumer interests from a gender and age perspective is considered crucial in the design and marketing of tourist products [
9]. These are, therefore, essential variables that the travel agency industry should consider. However, they remain insufficiently explored in the literature. Research on the influence of gender in the tourism sector has mainly focused on aspects related to gender consumption and how the travel of men and women qualitatively differs [
10], discrimination against women [
11], gender-based job insecurity [
12], gender inequality in occupying managerial and technical positions [
13], gender wages [
14], women’s role in local tourism development [
15], gender stereotypes and sexist attitudes in the context of tourism [
16], or women’s economic empowerment [
17], among others. Research in the tourism sector has highlighted the importance of examining travelers’ interests from a gender perspective and despite women being significant participants in the tourism industry, they are still under-represented [
18]. In this sense, existing tourism research related to understanding travelers’ interests from a gender perspective, considered fundamental in terms of tourism marketing in the subsector of travel agencies, is limited and virtually unexplored [
19,
20,
21]. Thus, the male perspective is predominant, creating a gender bias by integrating female behavior into the dominant behavior pattern [
21,
22,
23], resulting in a gender perspective in the design and marketing of tourist products and services offered by travel agencies not being recognized and integrated, leading to travel agencies implementing gender-blind marketing strategies, which could result in consumer dissatisfaction. Age is a key variable to be considered because, among other aspects, the needs and preferences of travelers can vary considerably throughout their life due to changes in personal circumstances, belonging to a particular generational population, and the natural ageing process of human beings [
24,
25,
26].
The aim of this article is to examine the differences generated by the gender and age variables of consumers of Spanish travel agencies when choosing travel and tourist destinations. This research applies a quantitative descriptive statistical approach to analyze travel preferences. A questionnaire targeting 879 individuals who had purchased through Spanish travel agencies formed the basis for data collection. A non-probabilistic convenience sampling method was employed, yielding balanced gender representation. The findings shed light on the differences generated by the gender and age variables of the behavior of consumers in travel agencies. It emphasizes the benefits that travel agencies can gain by implementing marketing strategies from a gender and age perspective, as opposed to adopting marketing approaches without a specific focus. This research is particularly interesting to marketing specialists in the travel agency industry, as it allows them to delve into the needs, tastes, and preferences of new consumer profiles. By segmenting their customers appropriately and effectively, businesses can customize their products and services to meet the needs of different age groups better. This can lead to an improved consumer experience, greater satisfaction, and increased long-term loyalty.
3. Methodology
Given the characteristics of this research, we have chosen to develop an explanatory quantitative methodology using an ex post facto approach from the perspective of the descriptive branch of statistics. To test the hypotheses presented, we used a questionnaire directed at individuals over 18 years of age who had made purchases using a Spanish travel agency, both from physical and virtual channels, allowing us to contextualize our study within the national context. A total of five questions were specifically designed (two nominal dichotomous closed-ended questions, one numerical interval-scale polytomous close-ended question, one nominal-ordinal polytomous open-ended question, and one nominal polytomous open-ended question) to gather basic information about the subjects that would allow us to draw a traveler profile based on individuals’ sociodemographic characteristics and their general travel preferences. These five questions were related to gender, age, preferences when traveling (culture, relaxing, exploring new destinations, nature, entertainment, visiting family, friends, and relatives, food experiences, attending concerts and shows, sports, or learning languages), preferences for international or domestic travel, and preferred destination type (beach, mountain, cities, inland destinations, or others).
Once the initial questionnaire was drafted, it underwent a critical review by a group of experts following the recommendations of Cabero and Barroso [
59]. Three university professors, two directly related to the field of travel intermediation and the third connected to market research, collaborated to examine the structure, content, clarity, and appropriateness of the questions based on the criteria of unambiguity, relevance, and importance proposed by Tejada [
60]. After receiving suggestions from the experts, the instrument was restructured, and brief descriptions were added to address each dimension and guide subjects on the appropriate procedure for answering the questions. Finally, before the definitive application of the questionnaire, a pilot test was conducted based on the instructions of Casas et al. [
61]. We had a group of 30 consumers of products marketed through travel agencies, and data from this test revealed certain problems related to the understanding of specific questions, which were appropriately addressed.
A non-probabilistic convenience sampling procedure [
62] was used because we had a census of consumers that met the necessary characteristics for the aim of the analysis. We did not consider weighting the sample as there was a high degree of homogeneity, and there was no significant mismatch. The questionnaire was administered online, with the sample accessing a self-administered questionnaire using the SurveyMonkey online platform (
www.surveymonkey.com, last accessed on 20 March 2020). It was distributed via email with the collaboration of various national retail and wholesale travel agencies, who sent it to their customer databases so that respondents could anonymously answer and contribute to this research. The questionnaire was available for seven weeks, from 13 January 2020 to 2 March 2020, and the sample obtained included 879 consumers of tourist products marketed by Spanish travel agencies in 2019. The sample was constituted by 44.25% men and 55.75% women. In relation to age groups, the most prominent being 21 to 29 years (27.30%) followed by the group of 18 to 20 years (26.62%), the groups of 30 to 39 years (15.02%), 40 to 49 years (16.04%), and 50 to 59 years (12.63%) have intermediate values, and the group aged 60 or older stands out for its limited presence (2.39%).
Subsequently, the data were coded and entered into IBM SPSS (Statistical Package for Social Sciences) version 26.0 for the corresponding statistical analysis. To assess the reliability of the questionnaire, Cronbach’s alpha internal consistency index was used to identify items that might make a low or no contribution to the overall internal consistency of the questionnaire [
63]. Results exceeding 0.700 were obtained, precisely 0.887, indicating that the instrument has an appropriate level of reliability and is suitable for applying statistical inference techniques. To present the possible differences, Cross-Tabulation tables have been carried out and, in this case, the appropriate statistic to determine if the differences are significative is the Chi-Square (χ
2) test. This choice was made because it is always best to deal with qualitative categorical variables.
4. Results
This section is structured by exploring two hypotheses related to the potential differences generated by gender and age on consumers of travel agencies on various travel-associated variables. To better understand the consumer profile, we examined the following questions related to destination choice: What are their preferences for relaxation, culture, etc.? Do they prefer international or domestic travel? What types of destinations do they prefer, such as beaches, mountains, etc.?
The segmentation of potential destinations, as proposed in Hypothesis 2, is based on the contribution of Varela et al. [
64] who argue that in the planning of the tourism sector, a common goal is to assess the demand for specific types of destinations. They suggest categorizing the population into homogeneous segments or groups based on their preferences for hypothetical destinations, which will facilitate the effective implementation of marketing strategies. It is important to note that Varela et al. [
64] did not consider the age factor.
4.1. Contrasting Hypothesis 1
To test the null hypothesis that claims that gender does not imply differences in the main travel interests, we conducted a Chi-Square (χ
2) test to determine the possible association between two qualitative categorical variables. When working with empirical data, it is common for them to violate the assumption of normality and recommend considering this aspect in any study, as many statistical procedures require, or work better if this assumption is met, directly influencing the inferences and estimates of the results obtained [
65]. Therefore, since the sample size available is large and has significant statistical potential (n = 879), we follow the recommendations of these authors. As a preliminary step to data processing, it was checked for normality using the Kolmogorov–Smirnov statistical test. A 95% confidence interval and a statistical significance level of a p-value of less than 0.05 (
p < 0.05) were used. Values obtained below 0.05 (
p < 0.05) would imply not assuming the normality assumption. The data obtained show a significance value of
p < 0.001 (
Table 1), which leads us to accept the absence of normality and forces us to apply non-parametric tests. In this case, the Pearson Chi-Square (χ
2) test was used to analyze the consumer profile and the categorical variables of gender and the main travel interests.
The data obtained by applying the Chi-Square (χ
2) test allow us to conclude that the gender variable implies differences in the main travel interests (
Table 2). With a p-value of less than 0.05, it is possible to assume the existence of heterogeneity between the male and female in the main travel interests. It is noteworthy that 45.10% of women seek to explore new destinations, compared to 36.8% of men. Second, 21.3% of men prefer relaxation travel, while 17.10% of women prefer this, according to the analyzed data (
Table 3).
Therefore, the null hypothesis that claims that gender does not imply differences in the main travel interests can be rejected, and it can be stated that gender implies significant differences in the main travel interests, accepting Hypothesis 1.
4.2. Contrasting Hypothesis 2
This section analyzes Hypothesis 2, and the two sub-hypotheses into which it is broken down. As in the previous subsection, it was checked for normality and the results of the Kolmogorov–Smirnov tests for normality between the group of the variables age and preference in terms of the travel distance (national or international) (
Table 4) and between the group of the variables age and preference in terms of the type of destination (beaches, mountains, cities, inland, or others) (
Table 5) confirm the absence of normality, with p values of less than 0.05. Since the assumption of normality was rejected, Chi-Square (χ
2) tests were performed. The Chi-Square (χ
2) tests contrasts the null hypothesis, explaining that the categorical variable age groups are not related and do not exhibit any association with the travel distance preference and with the preferences for the type of destination.
By conducting the Chi-Square (χ
2) tests (
Table 6), the existence of heterogeneity among age groups and their preferences regarding the travel distance, whether national or international, has been identified (
p < 0.05). Consequently, we can reject the null hypothesis and state that there is diversity among age groups (accepting Hypothesis 2.1). Preferences vary, with young people preferring international destinations, such as the 18–20 age group (30.8%), the 21–29 age group (25.8%), and the 30–39 age group (27.3%), or both (between 53.3% and 56.1%), while the older age groups prefer national destinations, such as the 50–59 age group (52.3%) and the 60 or more group (38.1%) (
Table 7).
Hypothesis 2.2 considers heterogeneity in the preferences for the type of destination, such as sun and beaches, mountains, cities, and inland, among others, in relation to age groups. In the Chi-Square (χ
2) tests, a
p-value of 0.378 (not significant at 0.05) was observed, which leads us to reject Hypothesis 2.2. This suggests that age groups do not imply differences in the preferences for the type of destination (
Table 8) and, therefore, the differences indicated in
Table 9 cannot be considered significant.
To describe and analyze the variables of the travel distance preference and preferences for the type of destination regarding age groups, a box and whisker plots were created, and these plots allow us to evaluate the first, second, and third quartiles, the median corresponding to the second quartile, or the fiftieth percentile (p50).
After creating the box and whisker plots that relate the variable of the age groups to the variable of the travel distance preference (
Figure 1), we can see that the highest median (p50) corresponds to the choice of national destinations (40–49 age group). In the other two cases, the median is in the 21–29 age group. It can be stated that there is an absence of symmetry, except for the box corresponding to international destinations, where the median is reasonably centered. The
Figure 1 contains no outliers that distort or bias the information corresponding to the previously mentioned tables.
The box and whisker plots that relate the variable of age groups to the variable of the preferences for the type of destination (
Figure 2) show uniformity in the medians corresponding to the 21–29 age group in choosing beach destinations, mountain destinations, and city destinations. Additionally, the median for inland destinations corresponds to the 40–49 age group. The median corresponding to other destinations is also associated with young individuals. Above the 75th percentile (p75), whiskers were found in all the boxes except for the one corresponding to inland destinations. Below the 25th percentile (p25), whiskers were found in the boxes of inland destinations and other destinations. Finally, it should be noted that a lack of normality was found, except for the box of inland destinations and the box corresponding to other destinations, with a relatively symmetrical distribution of the median.
5. Discussion
In this analysis, gender implies significant differences in the main travel interests, accepting Hypothesis 1. McGehee et al. [
66] state that women are more inclined than men to travel to visit family and friends, as also observed in our research results. Gozalova et al. [
67] highlight a greater interest from male audiences in sports tourism destinations, coinciding with the results of our investigation. Andreu et al. [
43] obtained results similar to those of our research after identifying five customer segments based on their sociodemographic characteristics and travel patterns (calm and relaxed tourists, getaway-seeking tourists, active tourists, leisure-seeking tourists, and scattered tourists); they concluded that women’s motivations to travel were more substantial than men’s and stated that active tourists, leisure-seeking tourists, and scattered tourists were mainly male, while tourists looking for getaways and relaxation were more represented among females. Our research results are in line with Vespestad and Mehmetoglu’s [
68] investigation when affirming that women prefer cultural activities. When considering entertainment and attending concerts and shows as travel interests, our results coincide with those of Kruger and Saayman [
69] when stating that men attend more events than women. Furthermore, our research indicates that female travelers, if compared to male, have a higher environmental awareness and approach to nature, an idea that is also confirmed by Li [
70] when stating that women may be more inclined toward experiences that foster a deep connection with nature, such as eco-friendly activities, wildlife encounters, or serene landscapes. As in our study results, other research also indicates that females tend to demonstrate a more positive attitude and motivation towards learning a language [
71,
72].
However, the results of this study differ from those obtained by Jönsson and Devonish [
73], who studied the gender factor and its influence on the motivations that lead individuals to visit the destination of Barbados. The researchers identified four general blocks of main motivations for tourists, which are culture, pleasure/fantasy seeking, relaxation, and physical activity. They also identified 14 individual motivation items distributed across these general blocks. After analyzing the data, the researchers concluded that gender does not significantly influence tourists’ motivations for visiting the destination. Suttikun et al. [
74] studied the motivations of tourists visiting Bangkok (Thailand) and concluded that the gender factor does not significantly influence individuals’ motivations for traveling to Bangkok, and Lin et al. [
75], based on a multiple regression analysis of data obtained from 443 tourists in Taiwan, also affirm that gender does not significantly influence travel interests. These results differ from those obtained in our research when considering the item “explore new destinations” in which women are the majority with 41.5% compared to 36.8% achieved by men. When considering women and men’s interest on food experiences when traveling, Matalas et al. [
76] conclude that women tend to be more motivated to taste local food, dine at specific facilities, and spend more on food during trips compared to men; these results differ from those obtained in our study with 2.8% of men versus 0.4% of women interested in culinary experiences when traveling.
It is worth remembering that, among the different variables that explain tourist behavior, motivation is considered one of the most relevant factors because it constitutes the driving force behind each type of behavior [
77]. Multiple scholars have investigated travel motivation from the perspective of different fields, such as psychology and social sciences [
78]. Chen and Zhou [
79], after conducting a bibliometric analysis of 1675 scientific publications made between 1990 and 2019 related to emerging research trends in motivation in travel and tourism, concluded that the most prominent motivations are related to tourists’ preferences and personal values.
In relation to the age groups differences, Hypothesis 2.1 is accepted, referring to the existence of differences in the choice of national or international destinations, but Hypothesis 2.2 is rejected. This suggests that age groups do not imply differences in preferences for the type of destination (beaches, mountains, cities, inland destinations, or others). In the literature, it is evident that individuals need to make decisions related to their choice of destination based on the geographical distance from their usual place of residence [
80]. Additionally, sociodemographic factors such as the age of the traveler can influence the attributes of a destination that attract tourists [
81]. In this regard, Lee et al. [
82] demonstrated in their research that age influences push factors in a specific way, concluding that older tourists showed a more significant attraction to natural and cultural resources. Likewise, older individuals evaluate certain pull factors, such as access to destination facilities and information or easy access to natural, historical, and educational resources, differently than younger tourists evaluate these factors.
Most developed markets have a very similar demographic profile, experiencing significant growth in the older population and increased life expectancy. This reality positively benefits the tourism demand because having more leisure time and economic resources can contribute to the destigmatization of tourism. To adapt to the ageing population, tourism organizations such as travel agencies must proactively identify and address the needs of this demographic. By designing strategies to cater to their requirements, organizations can improve the experiences of older people and gain a competitive edge. Undoubtedly, it will contribute to the organization’s optimal growth and improved financial results [
83].
Tourism research emphasizes the importance of geographical distance when selecting a travel destination [
84]. While shorter distances are more accessible for any traveler, not all individuals are willing or able to undertake long-distance travel [
85]. The distance a tourist can travel is primarily influenced by the traveler’s income, educational level, age, and gender [
86]. Bao and McKercher [
87] in their research on the destination Bangkok (Thailand) state that long-distance destinations can be somewhat discriminatory, affecting the ability of some people to travel to such destinations. They conclude that travelers from long distances tend to be older and more affluent and consider the destination as one more stop in their journey. In contrast, travelers from short distances are younger, less affluent, and see it as their primary and only destination. Oppermann [
88] demonstrated in his study that the trend for long-distance travel peaks in youth at around twenty years of age and among adults around fifty years of age once their children have become independent. He also noted a negative correlation between age and long-distance travel. However, as You and O’Leary [
89] point out, as the population ages and mobility problems, health issues, and economic capacity decline, long-distance travel begins to decrease. The results we obtained coincide with You and O’Leary [
89], but the disparity of results in the literature forces one to continue working in the future on the relationship between both variables.
While the choice of a tourist destination is a widely researched topic in tourism [
90], there is limited research on the relationship between age and the selection of a specific type of tourist destination in the way we have addressed it. Numerous studies explore the factor of age and its relationship with the selection of activities to be undertaken at the tourist destination [
91], age and consumer behavior when deciding on a tourist destination [
92], or age and the choice of a specific tourist destination based on certain attributes. For example, the study by Mohsin and Ryan [
93] focused on Australia as a destination, and the research carried out by Tomić and Boži [
94] centered on Serbia as a destination.
Companies in the tourism distribution sector should consider that older people constitute a growing and increasingly numerous consumer group with high purchasing potential. However, commercial offers for this demographic group may be limited. Various reasons can contribute to this situation, such as the cult of youth and the specific qualities of this market that attract producers, leading to numerous commercial strategies being directed toward them while neglecting the needs of older individuals [
95].
6. Conclusions
Based on the statistical analysis (through Cross-Tabulations and Chi-Square tests) of the responses of a sample of 879 consumers of tourist products marketed by Spanish travel agencies, two hypotheses related to the differences generated by the gender and age variables of consumers of travel agencies in Spain with various variables associated with travel destination choices were explored. Our hypotheses were related to the preference for different types of travel interests (Hypothesis 1), the choice between national and international destinations (Hypothesis 2.1), and the preference for specific types of tourist destinations (Hypothesis 2.2). Although Hypothesis 2.2 was rejected, this research highlights the importance of considering factors like gender and age in analyzing consumer behavior in the tourism sector.
Our results suggest that men and women have different interests for traveling (Hypothesis 1 was accepted), and age plays a significant role in choosing between national and international destinations (Hypothesis 2.1 was accepted). However, concerning specific types of destinations, age may have no significative difference in this case (Hypothesis 2.2 was rejected). Understanding these dynamics is crucial for tourism companies to develop more effective marketing strategies and offer travel experiences that align with the desires and needs of their customers. It also underscores the need to focus more on the preferences of older travelers, who represent a growing segment with significant purchasing potential, highlighting that they opt more for travel to national destinations, according to this case study. Therefore, this article can provide valuable insights into the tourism sector and help businesses meet the diverse demands of a diversified market.
To further this research and provide greater depth, future investigations should address segmentation among adults over fifty, in addition to repeating the analysis of gender and age in relation to various variables of travel choice in different social contexts. The main limitations of this research are that it is a case study referring to a specific country (Spain) and a specific time (travel contracted in 2019); the analysis tools are perfectly valid, but it is necessary to analyze the relationships between these variables using other multivariate techniques, such as Cluster Analysis, Structural Equation Models, among others.