From Boomers to Gen Z: How Generations Differ in Travel Decisions

Abstract

Exploring international travel behavior provides valuable insights into the factors that influence travelers’ decision-making processes and motivations across generational cohorts. This paper examines differences among Slovak residents from four generations—Generation Z, Generation Y, Generation X, and the Baby Boomer generation—in their travel motivations, perceived constraints, and factors influencing travel-related decisions. The study investigates generational differences in three key areas: (1) the perceived influence of various aspects on decision-making when traveling abroad, (2) the perceived restrictiveness of potential constraining factors, and (3) the perceived importance of factors when choosing a vacation. Data were collected through an online questionnaire administered to 265 Slovak respondents between November and December 2025. The hypotheses were tested using Kruskal–Wallis tests. The results indicate that while some factors, such as price and destination safety, are important across all generations, others—such as social media influence, entertainment, and social activities—show statistically significant generational differences. These findings contribute to a better understanding of generational travel behavior and provide practical insights for tourism professionals seeking to tailor marketing strategies, products, and services to the specific preferences of different age cohorts.

1. Introduction

Tourism is a dynamic and continuously evolving phenomenon that plays a significant role in cultural, social, and economic contexts (Kamboj & Sharma, 2016). Understanding why people travel and how they make vacation choices is a central focus of tourism research, as it provides valuable insights for both scholars and industry practitioners (Thi, 2025). Travel behavior encompasses the decision-making processes related to the timing, destination, mode of transport, and activities associated with trips, as well as preferences for destinations and experiences (Ramirez et al., 2021; Barbieri & Sotomayor, 2013).

Motivation is a core component of travel behavior, representing the internal forces that drive individuals to engage in tourism activities (Zhang & Peng, 2014). Research has consistently shown that motivational factors strongly influence travel intentions, travel frequency, and destination choice (Karl et al., 2020; Carvalho, 2022). Additionally, travel motives impact tourists’ perceptions of destination competitiveness and the overall experience (Ban et al., 2025). Despite extensive research, motivation remains a dynamic concept, shaped by multiple factors, including individual preferences, cultural background, socioeconomic status, and life stage (Thi, 2025; J. Crompton, 1979).

Understanding differences in travel motivation and behavior among generations offers valuable insights for the tourism industry. Different generational cohorts—shaped by unique historical, social, and technological contexts—exhibit varying values, preferences, and consumption patterns, which in turn affect travel behavior (Octaviany & Mardiyana, 2024; Ahn et al., 2019). For instance, Generation X, Millennials (Generation Y), and Generation Z differ in their attitudes toward leisure, technology adoption, and destination selection (Jamal & Newbold, 2020; Popșa, 2024). By analyzing these differences, tourism stakeholders can tailor products and marketing strategies to better meet the needs of each group.

Intergenerational differences play a crucial role in scientific analysis, classification, and informed decision-making. Each generation experiences key turning points in its life course, with certain events triggering substantial economic, political, or social transformations. Variations in production methods, shifts in consumption patterns, and their influence on lifestyles leave distinct imprints on individuals living through these periods. Monitoring these impacts and broader social changes is essential for understanding societal trends and making informed projections for the future (Buzlukçu & Şahin, 2021).

The present study focuses on four generational cohorts—Generation Z, Generation Y, Generation X, and the Baby Boomer generation—to examine their travel motivations, perceived constraints, and factors influencing travel-related decisions. Given the variability of motivations and the scarcity of research comparing multiple generations comprehensively, this study aims to address this gap by investigating the following hypotheses:

Hypothesis 1:

There are statistically significant differences among generations (Z, Y, X, and Baby Boomers) in the perceived influence of at least one aspect on decision-making related to travel abroad.

Hypothesis 2:

There are statistically significant differences among generations (Z, Y, X, and Baby Boomers) in the perceived restrictiveness of at least one constraining factor on decision-making related to travel abroad.

Hypothesis 3:

There are statistically significant differences among generations (Z, Y, X, and Baby Boomers) in the perceived importance of at least one factor when choosing a vacation.

While previous research has examined travel motivations and behaviors within individual generations, relatively few studies have systematically compared multiple generations simultaneously, particularly in the context of Slovak travelers. Moreover, existing studies often focus on broad age cohorts or specific groups, leaving gaps in understanding how motivational factors and decision-making patterns differ across Generation Z, Millennials, Generation X, and Baby Boomers. This study addresses this gap by providing a comprehensive, multi-generational analysis of travel motivations and constraints, offering insights that can inform both theory and practical strategies in tourism management.

Building on earlier work (Melnyk & Vašaničová, 2024), which examined personal characteristics such as marital status, parenthood, and generational affiliation in relation to Slovak women’s travel motivations, Vašaničová and Melnyk (2025) focus specifically on generational differences in travel preferences. Their study highlights how cohorts X, Y, and Z differ in international travel behavior, including destination choice, seasonal patterns, transportation, travel companions, planning, and motivation levels. The present study expands this scope by including both women and men and incorporating the Baby Boomer generation. Using new data, it examines generational differences in travel motivations and preferences more broadly.

2. Literature Review

This literature review is divided into two subsections to provide a comprehensive understanding of the topic. Section 2.1 focuses on the psychological and social factors that influence individuals’ travel choices. Section 2.2 discusses how generational cohorts differ in their travel behavior and decision-making, highlighting the relevance of age and life stage in tourism research.

2.1. Travel Motivation and Behavior

Tourist motivation has been a central topic in tourism research for decades (Carvalho, 2022), as motivation and decision-making underpin the demand for tourism services (Ram, 2024). Motivation is generally understood as an internal psychological force that drives individuals to pursue specific goals or activities (Zhang & Peng, 2014). In tourism, motivation influences not only the decision to travel but also destination selection, frequency of travel, and perceptions of the travel experience (Karl et al., 2020; Ban et al., 2025). Travelers make decisions for many different reasons, some rational and others emotional. The complex web of underlying social and emotional drivers often collides with the more considered, rational impulses, which can make it difficult to understand traveler motivations (Amadeus IT Group, 2025). Tourist behavior is not always based on conscious thought and decision-making; therefore, more realistic and practical management strategies are required (Hsu & Huang, 2008). Jang and Wu (2006) viewed affective states as stimulators of travel intentions and argued that tourists are guided by emotional needs related to pleasure-seeking and actual behavior.

Travelers’ needs and desires are changing. By understanding travel motivations and responding accordingly, the tourism industry has the opportunity to strengthen customer loyalty through more personalized and creative offerings (Amadeus IT Group, 2025). Motivation is multifaceted and can include desires for exploration, novelty, relaxation, social interaction, and cultural enrichment (Venkatesh, 2006). Moreover, motivations are context-dependent and may vary across life stages, cultural backgrounds, and socio-economic conditions (J. Crompton, 1979; Thi, 2025).

There is a general perception that tourism can directly or indirectly contribute to increased well-being. Traveler motivation is closely linked to well-being and satisfaction (Iacob et al., 2025). Motivations such as relaxation, cultural enrichment, or adventure contribute to overall life satisfaction and can influence repeat travel behavior.

2.2. Generational Theory and Travel Behavior

The concept of a generation, rooted in generational theory, was popularized in the United States by Strauss and Howe (Li et al., 2013). While generational differences in consumer behavior are widely recognized, their impact on tourism remains relatively underexplored (Gonda & Rátz, 2023). Generational theory provides a framework for understanding differences in travel behavior across age cohorts. Generations are groups of individuals who share birth years and formative experiences that shape their values, attitudes, and behaviors (Popșa, 2024). Generational characteristics are influenced by historical, social, political, and technological contexts, which affect their consumption patterns and lifestyle preferences (Moscardo & Benckendorff, 2010; Raunio, 2014). Because members of a generation are born within a similar time frame, they experience comparable social events and external influences during their formative years, which contribute to the development of shared life experiences and common perspectives (Li et al., 2013). Generations are linked by shared experiences, life events, and ultimately shared values. Even if these links are not always strong, they remain significant. Values create an opportunity to link decisions within a generational framework, reinforcing the idea that there are differences between generations while emphasizing the internal similarities that influence the decision-making of members of the same generation (Törőcsik, 2016). Understanding generational patterns offers an important framework for interpreting the differing needs, values, and expectations of contemporary populations (Gorenak et al., 2025).

When analyzing generational differences, it is important to distinguish between generational effects, age effects, and period effects: (i) generational effects reflect differences between cohorts born in the same period; (ii) age effects refer to changes associated with chronological aging; (iii) period effects describe influences that affect all age groups at a specific point in time (Ralph, 2017). Although this study adopts a generational cohort framework, it is important to acknowledge the methodological challenge of distinguishing between age, period, and cohort effects. Given the cross-sectional nature of the data collection (November–December 2025), it is not possible to fully disentangle whether observed differences are attributable to life-stage characteristics (age effects), shared formative experiences (cohort effects), or broader socioeconomic conditions at the time of data collection (period effects). Therefore, the results are interpreted primarily as generational cohort differences grounded in generational theory, while recognizing that some variation may also reflect age-related life cycle influences. The generational cohorts (according to Dimock, 2019; Popșa, 2024; Rojas, 2024; Beytes, 2024) most relevant to contemporary tourism studies are as follows:

• Greatest generation—born between 1901 and 1927;
• Silent generation—born between 1928 and 1945;
• Baby boomers—born between 1946 and 1964;
• Generation X—born between 1965 and 1980;
• Millennials—born between 1981 and 1996;
• Generation Z—born between 1997 and 2012;
• Alpha—born between 2013 and 2024.

Cottrell (2025), Makarevicius et al. (2025), McCrindle (2025), and Askinasi (2025) later expanded this categorization by introducing Generation Beta, defined as individuals born from 2025 onward.

Travel behaviors within each generational cohort reflect distinctive patterns influenced by a variety of factors (Jamal & Newbold, 2020). Liu et al. (2024) emphasize that examining generational differences is crucial for understanding travel behavior, highlighting the value of adopting a generational perspective in tourism research. Such differences may manifest in the purposes of travel, ranging from commuting to social or leisure trips, as well as in perceptions of physical and natural environments, including considerations of safety and sustainability. Additionally, the historical, cultural, socioeconomic, and technological contexts experienced by each generation significantly shape their mobility and travel patterns (Circella et al., 2016).

Differences between generations influence travel preferences, destination choices, and leisure behavior. For example, Millennials and Generation Z are typically more technologically adept and socially connected, while Baby Boomers may prioritize comfort, security, and cultural experiences (Octaviany & Mardiyana, 2024; Jamal & Newbold, 2020). Differences in motivational priorities among generations may therefore have important implications for both tourism marketing and policy, as understanding these distinctions enables more targeted and effective engagement strategies.

3. Materials and Methods

This section describes the study design, research sample, data collection procedures, and the statistical methods employed to analyze generational differences in travel-related decision-making.

3.1. Research Sample

This study employed a quantitative, cross-sectional research design based on primary data collected through an online questionnaire. The target population consisted of Slovak residents aged 18 years and older who had prior experience traveling abroad. Data were collected between November and December 2025. A non-probability convenience sampling method was applied. The questionnaire was distributed electronically via social media platforms and email networks, and participation was voluntary and anonymous.

Because a non-probability sampling approach was used, the research sample cannot be considered statistically representative of the entire Slovak population. However, the dataset allows for the examination of generational differences in factors influencing international travel decision-making.

The research sample consisted of 265 respondents. Participants were classified into generational groups based on their year of birth as follows: Baby Boomers (aged 61–79, born 1946–1964), Generation X (aged 45–60, born 1965–1980), Generation Y (aged 29–44, born 1981–1996), and Generation Z (aged 18–28, born 1997–2007).

The youngest respondent was 18 years old, while the oldest was 72. The average age of respondents was 36 years old (median = 35; standard deviation = 13,1715).

Table 1. Generational distribution of respondents by gender.

	Gender
Generation	Female	Male	Total
X	71 (26.79%)	23 (8.68%)	94 (35.47%)
Y	50 (18.87%)	56 (21.13%)	106 (40.00%)
Z	31 (11.70%)	13 (4.91%)	44 (16.60%)
Baby Boomers	15 (5.66%)	6 (2.26%)	21 (7.93%)
Total	167 (63.02%)	98 (36.98%)	265 (100%)

shows the frequencies and percentages of respondents by gender across individual generational groups. Of the total 265 respondents, 7.93% (21) belonged to the Baby Boomer generation, 16.60% (44) to Generation X, 40% (106) to Generation Y, and 35.47% (94) to Generation Z. This distribution reflects the generational classification applied in the study.

3.2. Instrument Development and Measurement Approach

The questionnaire was developed specifically for the purposes of this study, drawing on commonly discussed dimensions in tourism and consumer behavior literature (e.g., price sensitivity, destination safety, authenticity, social influence, and relaxation). Given the exploratory nature of the research and the focus on comparing perceived importance and influence of clearly defined aspects, each factor was operationalized as a single-item measure rated on a 6-point Likert scale (0–5).

The use of single-item measures is considered appropriate when constructs are concrete, unambiguous, and easily understood by respondents (e.g., price, safety, comfort), particularly in exploratory studies aiming to compare mean differences across groups rather than to develop latent measurement models. In this study, the primary objective was to assess perceived influence and importance of distinct travel-related aspects rather than to construct multidimensional latent variables.

Because the study did not aim to model latent constructs composed of multiple indicators, reliability measures such as Cronbach’s alpha and exploratory factor analysis were not applied. Instead, content validity was ensured through careful formulation of items based on relevant tourism literature and consultation during questionnaire preparation to ensure clarity and conceptual relevance.

3.3. Methods

The research hypotheses were tested using the Kruskal–Wallis test, with a significance level set at 0.05. This nonparametric test was selected because the data did not meet the assumption of normal distribution, making parametric tests inappropriate. In addition, the analysis involved comparisons among more than two independent groups, namely the generational cohorts. Following a significant Kruskal–Wallis test, we used multiple comparisons of mean ranks for all groups to identify which specific group pairs differed. This procedure calculates pairwise comparisons of average ranks and applies a Bonferroni adjustment to the p-values to control for multiple comparisons.

For all significant Kruskal–Wallis tests, we additionally computed eta-squared (η²) as a measure of effect size to indicate the proportion of variance in the dependent variable explained by generational group membership. This provides a practical interpretation of the magnitude of observed differences, supplementing statistical significance. Effect sizes were calculated using the formula

$${\eta }^2={\displaystyle \frac{H-k+1}{n-k}}$$

(1)

where H is Kruskal–Wallis test statistic, k is number of groups, and n denotes total sample size. Following commonly used thresholds, η² values of 0.01, 0.06, and 0.14 were interpreted as small, medium, and large effects, respectively (Cohen, 1988).

Data processing and statistical analysis were conducted using Gretl (2025a) for statistical computations and Microsoft Excel for data preparation.

4. Results

This section presents the findings of the study, organized into two main sections for clarity and coherence. Section 4.1 provides a detailed analysis of participants’ responses, highlighting key trends, patterns, and descriptive statistics that offer insight into the research context. Section 4.2 evaluates the proposed hypotheses to determine whether the observed data support or reject each hypothesis. These sections provide a comprehensive understanding of the study outcomes and form the basis for the subsequent discussion and interpretation.

4.1. Results of the Questionnaire Survey

Participants were asked to indicate the extent to which various aspects influenced their decision-making related to travel abroad, using a Likert scale ranging from 0 (no influence) to 5 (highest influence).

Table 2. Descriptive statistics for aspects influencing travel decision-making.

Aspects	0	1	2	3	4	5	Mean	Median	Std. Dev.
Price	5 (1.89%)	5 (1.89%)	17 (6.42%)	51 (19.25%)	71 (26.79%)	116 (43.77%)	3.9849	4	1.1654
Weather and climate conditions	9 (3.40%)	8 (3.02%)	25 (9.43%)	61 (23.02%)	86 (32.45%)	76 (28.68%)	3.6415	4	1.2573
Quality of accommodation	8 (3.02%)	17 (6.42%)	35 (13.21%)	66 (24.91%)	75 (28.30%)	64 (24.15%)	3.4151	4	1.3180
Food and gastronomy options	11 (4.15%)	22 (8.30%)	37 (13.96%)	64 (24.15%)	78 (29.43%)	53 (20%)	3.2642	3	1.3674
Cultural and historical monuments	16 (6.04%)	20 (7.55%)	29 (10.94%)	57 (21.51%)	68 (25.66%)	75 (28.30%)	3.3811	4	1.4826
Digital availability of services	31 (11.70%)	23 (8.68%)	42 (15.85%)	62 (23.40%)	74 (27.92%)	33 (12.45%)	2.8453	3	1.5205
Recommendations from family/friends	23 (8.68%)	35 (13.21%)	57 (21.51%)	68 (25.66%)	52 (19.62%)	30 (11.32%)	2.6830	3	1.4398
Ratings and reviews from other travelers	17 (6.42%)	16 (6.04%)	37 (13.96%)	66 (24.91%)	76 (28.67%)	53 (20%)	3.2340	3	1.4109
Social media	60 (22.64%)	49 (18.49%)	45 (16.98%)	55 (20.75%)	31 (11.70%)	25 (9.43%)	2.0868	2	1.6148
Suitability of destination for photography	99 (37.36%)	54 (20.38%)	34 (12.83%)	36 (13.58%)	24 (9.06%)	18 (6.79%)	1.5698	1	1.6194
Environmental sustainability	107 (40.38%)	62 (23.40%)	45 (16.98%)	31 (11.70%)	14 (5.28%)	6 (2.26%)	1.2491	1	1.3480

Note: The scale ranges from 0 (no influence) to 5 (highest influence). Std. dev. denotes standard deviation.

summarizes the descriptive statistics for each aspect, including the relative frequencies and percentages of respondents’ answers.

The aspect “price” received the highest influence rating among respondents, with 43.77% assigning it the maximum score of 5, indicating that it has the greatest impact on vacation decision-making. In total, 116 respondents rated “price” as the most influential aspect. The mean score for this aspect was 3.98, the highest among all selected aspects, with a median value of 4. The factors “weather and climate conditions”, “quality of accommodation”, “food and gastronomy options”, “cultural and historical monuments”, and “ratings and reviews from other travelers” also received relatively high evaluations, with mean scores exceeding 3, indicating a substantial impact on vacation-related decision-making. In contrast, “suitability of destination for photography” and “environmental sustainability” were rated the lowest among all examined factors, suggesting minimal influence on decisions related to travel abroad. These aspects were assigned a score of 0 by 37.36% and 40.38% of respondents, respectively. The factor “social media” received a moderate evaluation, with a mean score of 2.09 and a median of 2, reflecting an average level of influence.

The next question assessed constraining factors in relation to decision-making about traveling abroad. The question was formulated using a Likert-type scale ranging from 0 to 5, where 0 indicated “not at all restrictive” and 5 indicated “mostly restrictive.”

Table 3. Descriptive statistics for constraining factors restricting travel decision-making.

Factors	0	1	2	3	4	5	Mean	Median	Std. Dev.
Financial costs of travel	6 (2.26%)	19 (7.17%)	22 (8.30%)	51 (19.25%)	58 (21.89%)	109 (41.13%)	3.7472	4	1.3709
Availability of time for travel	16 (6.04%)	14 (5.28%)	24 (9.06%)	51 (19.25%)	65 (24.45%)	95 (35.85%)	3.5849	4	1.4773
Health status	70 (26.42%)	50 (18.87%)	30 (11.32%)	34 (12.83%)	27 (10.19%)	54 (20.38%)	2.2264	2	1.8878
Family responsibilities	72 (27.17%)	41 (15.47%)	43 (16.23%)	41 (15.47%)	29 (10.94%)	39 (14.72%)	2.1170	2	1.7734
Language barrier	113 (42.64%)	48 (18.11%)	44 (16.60%)	35 (13.21%)	11 (4.15%)	14 (5.28%)	1.3396	1	1.4914
Political situation of the destination	46 (17.36%)	35 (13.21%)	45 (16.98%)	60 (22.64%)	31 (11.70%)	48 (18.11%)	2.5245	3	1.6958
Destination safety	11 (4.15%)	15 (5.66%)	47 (17.74%)	44 (16.60%)	53 (20%)	95 (35.85%)	3.5019	4	1.4695
Work-related restrictions	67 (25.28%)	28 (10.57%)	42 (15.85%)	44 (16.60%)	36 (13.58%)	48 (18.11%)	2.3698	2	1.8220
Restrictions due to studies	164 (61.89%)	21 (7.92%)	19 (7.17%)	20 (7.55%)	12 (4.53%)	29 (10.94%)	1.1774	0	1.7662
Distance and length of travel	72 (27.17%)	35 (13.21%)	53 (20%)	50 (18.87%)	24 (9.06%)	31 (11.70%)	2.0453	2	1.6795
Tourist traffic	38 (14.34%)	29 (10.94%)	65 (24.53%)	50 (18.87%)	44 (16.60%)	39 (14.72%)	2.5660	3	1.5937
Administrative requirements	67 (25.28%)	46 (17.36%)	62 (23.40%)	54 (20.38%)	15 (5.66%)	21 (7.92%)	1.8755	2	1.5208

Note: The scale ranges from 0 (not at all restrictive) to 5 (mostly restrictive). Std. dev. denotes standard deviation.

presents the descriptive statistics for each constraining factor, including the frequencies and percentages of respondents.

According to the responses received from respondents, the factor “financial costs of travel” has the highest level of restrictiveness in decision-making related to travel abroad. The majority of respondents (41.13%) rated this constraining factor as 5 (mostly restrictive), with a mean score of 3.74 and a median score of 4. Among the most restrictive factors are “availability of time for travel” and “destination safety”. Both factors were most frequently rated as 5 (mostly restrictive) by 35.85% of respondents. Both factors have a mean scores higher than 3.5 and a median scores of 4. The factors with the highest concentration of responses at 0 (no at all restrictive) are “restriction due to studies”, rated as 0 by 61.89% of respondents, and “language barrier”, rated as 0 by 42.64% of respondents. The low restrictiveness of “restriction due to studies” can be explained by the small proportion of Generation Z respondents in the sample who are still studying. The low restrictiveness of the “language barrier” may be explained by the fact that most respondents have knowledge of foreign languages. Other factors with the highest concentration of responses at 0 (no at all restrictive) include “health status” (26.42%), “family responsibilities” (27.17%), “work-related restrictions” (25.28%), “distance and length of travel” (27.17%), “administrative requirements” (25.28%). These factors therefore exhibit the lowest level of restrictiveness on decision-making related to travel abroad. Moderate levels of restrictiveness were observed for the constraining factors “political situation of the destination” and “tourist traffic”. The most common rating for the “political situation of the destination” was 3, reported by 22.64% of respondents, with a mean score of 2.52 and a median score of 3. In the case of “tourist traffic”, the most frequent rating was 2, reported by 24.53% of respondents.

The following question was similar in nature to the previous one. Respondents were asked to rate the importance of selected factors when choosing a vacation using a Likert scale from 0 to 5. On this scale, 0 represented “not at all important” and 5 represented “mostly important”.

Table 4. Descriptive statistics for factors important in choosing a vacation.

Factors	0	1	2	3	4	5	Mean	Median	Std. Dev.
Comfort	3 (1.13%)	12 (4.53%)	29 (10.94%)	58 (21.89%)	70 (26.42%)	93 (35.09%)	3.7321	4	1.2347
Authentic experience	9 (3.40%)	10 (3.77%)	12 (4.53%)	48 (18.11%)	75 (28.30%)	111 (41.89%)	3.8981	4	1.2860
Enrichment through culture	14 (5.28%)	17 (6.42%)	20 (7.55%)	65 (24.53%)	67 (25.28%)	82 (30.94%)	3.5094	4	1.4278
Relaxation	3 (1.13%)	11 (4.15%)	17 (6.42%)	44 (16.60%)	68 (25.66%)	122 (46.04%)	3.9962	4	1.1991
Entertainment	13 (4.91%)	24 (9.06%)	40 (15.09%)	64 (24.15%)	53 (20%)	71 (26.79%)	3.2566	3	1.4699
Personal Growth	43 (16.23%)	45 (16.98%)	36 (13.58%)	59 (22.26%)	39 (14.72%)	43 (16.23%)	2.5094	3	1.6826
Social activities	40 (15.09%)	61 (23.02%)	42 (15.85%)	48 (18.11%)	41 (15.47%)	33 (12.45%)	2.3321	2	1.6262

Note: The scale ranges from 0 (not at all important) to 5 (mostly important). Std. dev. denotes standard deviation.

presents the descriptive statistics for each factor, including the frequencies and percentages of responses.

The majority of the suggested factors had a concentration of responses at 5, indicating that these factors were very important to respondents when choosing vacation. The factors included “relaxation” (46.04%), “authentic experience” (41.89%), “comfort” (35.09%), “enrichment through culture” (30.94%), and “entertainment” (26.79%). Although all of these factors were rated at the highest importance level of 5 (mostly important), the frequency of responses shows that “relaxation” and “authentic experience” were considered the most important. Both factors had a median score of 4 and a mean score of 3.90 and 3.99, respectively. The factor “personal growth” received moderate ratings, with the most common score being 3, reported by 22.26% of respondents, with a mean score of 2.51 and a median score of 3. The factor “social activities” was the only one among all factors with a concentration of responses at the lower end of the scale. The most frequent rating was 1, reported by 23.02% of respondents, indicating that this factor was less important when choosing a vacation compared to the others.

4.2. Hypotheses Testing

Table 5. Results of the Kruskal–Wallis test for Hypothesis 1.

Aspects	MR Z	MR Y	MR X	MR BB	H	p-Value	η2
Price	144.1	132.7	121.7	108.2	5.799	0.1218
Weather and climate conditions	122.8	137.5	149.0	122.4	4.682	0.1966
Quality of accommodation	129.0	135.4	136.9	130.7	0.524	0.9135
Food and gastronomy options	124.0	140.7	140.0	119.6	3.538	0.3159
Cultural and historical monuments	133.0	127.0	138.8	151.1	2.185	0.5348
Digital availability of services	137.1	135.2	126.1	117.6	1.639	0.6506
Recommendations from family/friends	143.3	126.3	137.5	111.4	4.492	0.2130
Ratings and reviews from other travelers	141.8	126.2	138.5	116.5	3.428	0.3302
Social media	157.6	120.1	126.1	102.8	16.894	0.0007 ***	0.053
Suitability of destination for photography	146.5	123.3	138.1	110.6	7.078	0.0694
Environmental sustainability	134.1	127.4	145.8	129.2	2.0297	0.5663

Note: MR means mean rank; Z, Y, X, and BB denote Generations Z, Y, X, and Baby Boomers; H denotes test statistics; *** indicates significance at the 0.1% level.

presents the results for Hypothesis 1. The Kruskal–Wallis test revealed significant differences among generations for the aspect “social media” (p < 0.001). This indicates that generational cohorts differ in the perceived influence of social media on decision-making related to travel abroad. Generation Z had a higher mean rank (MR) compared to Generations Y, X, and Baby Boomers, indicating a stronger perceived influence of social media on their travel-related decisions. The effect size, as measured by η² (0.053), indicates a medium effect according to Cohen’s (1988) thresholds, suggesting that generational group membership explains approximately 5.3% of the variance in social media influence. For all other aspects, no significant differences were observed. This indicates that the examined generational cohorts show similar patterns in their decision-making regarding these aspects, whether they are perceived as highly influential or minimally influential. It also suggests that these aspects are either similarly important or similarly unimportant across all generations.

Table 6. Siegel and Castellan post hoc test (Hypothesis 1).

Aspect	Z vs. Y	Z vs. X	Z vs. BB	Y vs. X	Y vs. BB	X vs. BB
Social media	0.0033 **	0.1473	0.0183 *	1.0000	1.0000	1.0000

Note: Z, Y, X, and BB denote Generations Z, Y, X, and Baby Boomers; * indicates significance at the 5% level and ** at the 1% level.

presents the results of the Siegel and Castellan post hoc test for Hypothesis 1, comparing the perceived influence of social media on travel decision-making between generational pairs. The test indicates that Generation Z differs significantly from Generation Y (p = 0.0033) and from Baby Boomers (p = 0.0183), with Generation Z perceiving social media as more influential (MR = 157.6—see in Table 5). No significant differences were observed between Generation Z and Generation X (p = 0.1473), or among any other generational pairings (all p ≥ 0.05). These results clarify that the significant Kruskal–Wallis effect for social media is primarily driven by the stronger perceived influence among Generation Z compared to the older generations.

Table 7. Results of the Kruskal–Wallis test for Hypothesis 2.

Factors	MR Z	MR Y	MR X	MR BB	H	p-Value	η2
Financial costs of travel	140.7	134.6	115.0	128.1	3.832	0.2802
Availability of time for travel	133.5	152.1	121.2	59.4	28.996	0.0000 ***	0.100
Health status	131.6	129.4	136.2	150.7	1.515	0.6789
Family responsibilities	129.8	135.2	146.6	107.5	4.110	0.2499
Language barrier	133.5	119.9	158.9	142.9	9.329	0.0252 *	0.024
Political situation of the destination	123.5	130.6	155.8	139.7	5.755	0.1241
Destination safety	130.6	127.0	142.9	153.1	3.126	0.3727
Work-related restrictions	126.5	145.0	150.0	66.0	22.261	0.0001 ***	0.074
Restrictions due to studies	177.2	114.9	103.7	87.9	66.802	0.0000 ***	0.244
Distance and length of travel	144.1	128.1	130.5	112.8	4.085	0.2524
Tourist traffic	127.7	138.7	128.0	138.2	1.353	0.7166
Administrative requirements	146.7	122.2	138.2	115.5	6.707	0.0819

Note: MR means mean rank; Z, Y, X, and BB denote Generations Z, Y, X, and Baby Boomers; H denotes test statistics; * indicates significance at the 5% level, and *** at the 0.1% level.

presents the results of the Kruskal–Wallis test for Hypothesis 2, which examined generational differences in the perceived restrictiveness of various factors on decision-making related to travel abroad. Significant differences among generations were found for the following factors: availability of time for travel (p < 0.001; η² = 0.100, medium effect), language barrier (p = 0.025; η² = 0.024, small effect), work-related restrictions (p < 0.001; η² = 0.074, medium effect), and restrictions due to studies (p < 0.001; η² = 0.244, large effect). These effect sizes indicate that generational group membership explains a meaningful proportion of the variance in most restrictive factors, particularly for restrictions due to studies, while the impact of the language barrier is comparatively modest.

The significance of these factors can be explained by age-related characteristics of the respondents. Younger respondents are more likely to be studying, while older respondents are more likely to be working. This affects the availability of time for travel and exposure to work-related restrictions. The restrictions due to studies factor reflects the higher impact of academic obligations on younger generations. Generational differences in the language barrier may relate to foreign language proficiency, familiarity with digital translation tools, or willingness to travel abroad without full language competence.

For the remaining factors—financial costs of travel, health status, family responsibilities, political situation of the destination, destination safety, distance and length of travel, tourist traffic, and administrative requirements—no statistically significant differences were observed. This indicates that these factors were perceived similarly in terms of restrictiveness across all generational cohorts.

Table 8. Siegel and Castellan post hoc test (Hypothesis 2).

Factor	Z vs. Y	Z vs. X	Z vs. BB	Y vs. X	Y vs. BB	X vs. BB
Availability of time for travel	0.5201	1.0000	0.0004 ***	0.1473	0.0000 ***	0.0142 *
Language barrier	1.0000	0.4147	1.0000	0.0271 *	1.0000	1.0000
Work-related restrictions	0.5347	0.5607	0.0064 **	1.0000	0.0001 ***	0.0002 ***
Restrictions due to studies	0.0000 ***	0.0000 ***	0.0000 ***	1.0000	0.8343	1.0000

Note: Z, Y, X, and BB denote Generations Z, Y, X, and Baby Boomers; * indicates significance at the 5% level, ** at the 1% level, and *** at the 0.1% level.

presents the results of the Siegel and Castellan post hoc test for Hypothesis 2, comparing the perceived restrictiveness of significant factors between generational pairs. For availability of time for travel, significant differences were observed between Generation Z and Baby Boomers (p < 0.001) and between Generation Y and Baby Boomers (p < 0.001), with Generation Y also differing from Generation X at a lower significance level (p = 0.014). The mean ranks (in Table 7) show that Generation Y (MR = 152.1) and Generation Z (MR = 133.5) perceive time availability as more restrictive than Generation X (MR = 121.2) and especially Baby Boomers (MR = 59.4). This indicates that younger generations consider limited time a greater constraint when planning travel abroad.

For the language barrier, the only significant difference was between Generation Y and Generation X (p = 0.027). The mean ranks (in Table 7) suggest that Generation X (MR = 158.9) perceives language issues as more restrictive than Generation Y (MR = 119.9), while Generation Z (MR = 133.5) and Baby Boomers (MR = 142.9) fall in between, indicating relatively smaller generational differences overall.

For work-related restrictions, significant differences were observed for Generation Z vs. Baby Boomers (p = 0.006), Generation Y vs. Baby Boomers (p < 0.001), and Generation X vs. Baby Boomers (p < 0.001). The mean ranks (in Table 7) reveal that Baby Boomers (MR = 66.0) perceive work-related obligations as less restrictive than younger generations.

For restrictions due to studies, Generation Z differed significantly from all other generations (all p < 0.001). The mean rank (in Table 7) for Generation Z (MR = 177.2) is much higher than for Generation Y (MR = 114.9), Generation X (MR = 103.7), and Baby Boomers (MR = 87.9), reflecting the higher impact of academic obligations on younger respondents.

Table 9. Results of the Kruskal–Wallis test for Hypothesis 3.

Factors	MR Z	MR Y	MR X	MR BB	H	p-Value	η2
Comfort	138.5	134.4	119.3	130.2	2.108	0.5504
Authentic experience	139.1	132.7	119.6	135.5	2.181	0.5356
Enrichment through culture	146.5	119.2	130.0	148.9	7.797	0.0504
Relaxation	132.5	136.8	130.8	121.1	0.913	0.8224
Entertainment	163.5	135.4	85.7	83.6	42.401	0.0000 ***	0.151
Personal Growth	143.3	135.4	116.1	110.2	5.978	0.1127
Social activities	155.0	122.5	124.7	105.1	13.457	0.0037 **	0.040

Note: MR means mean rank; Z, Y, X, and BB denote Generations Z, Y, X, and Baby Boomers; H denotes test statistics; ** indicates significance at the 1% level, and *** at the 0.1% level.

presents the results of the Kruskal–Wallis test for Hypothesis 3, which examined generational differences in the perceived importance of factors when choosing a vacation. Significant differences were found for entertainment (p < 0.001; η² = 0.151, large effect) and social activities (p = 0.003; η² = 0.040, small effect). This indicates that generational membership explains a substantial portion of the variance in entertainment preferences, while the effect on social activities is smaller. The mean ranks indicate that entertainment was rated highest by Generation Z (MR = 163.5), while social activities also showed the highest ratings among Generation Z (MR = 155.0). These results suggest that younger generations place greater importance on entertainment and social activities when choosing a vacation, possibly reflecting their preferences for leisure, social interaction, and engaging experiences.

Enrichment through culture (p = 0.0504) was a borderline factor. Although not statistically significant, the p-value suggests a potential trend, with mean ranks showing some variation across generations (MR Z = 146.5, MR Y = 119.2, MR X = 130.0, MR BB = 148.9), indicating partial convergence in perceived importance among the generational cohorts.

The remaining factors—comfort, authentic experience, relaxation, and personal growth—were not statistically significant, indicating that these factors are perceived similarly in importance across all generations.

Table 10. Siegel and Castellan post hoc test (Hypothesis 3).

Factor	Z vs. Y	Z vs. X	Z vs. BB	Y vs. X	Y vs. BB	X vs. BB
Entertainment	0.0579	0.0000 ***	0.0000 ***	0.0018 **	0.0282 *	1.0000
Social activities	0.0165 *	0.1831	0.0420 *	1.0000	1.0000	1.0000

Note: Z, Y, X, and BB denote Generations Z, Y, X, and Baby Boomers; * indicates significance at the 5% level, ** at the 1% level, and *** at the 0.1% level.

presents the results of the Siegel and Castellan post hoc test for Hypothesis 3, which compares the perceived importance of entertainment and social activities between generational pairs.

For entertainment, significant differences were observed between Generation Z and Generation X (p < 0.001) and between Generation Z and Baby Boomers (p < 0.001). Additionally, significant differences were found between Generation Y and Generation X (p = 0.001) and between Generation Y and Baby Boomers (p = 0.028). Although the difference between Generation Z and Generation Y (p = 0.058) did not reach the 5% significance level, the results indicate that younger generations perceive entertainment as more important when choosing a vacation compared to older generations. The mean ranks (in Table 9) indicate that Generation Z (MR = 163.5) perceives this factor as most important, followed by Generation Y (MR = 135.4), Generation X (MR = 85.7), and Baby Boomers (MR = 83.6).

For social activities, significant differences were observed between Generation Z and Generation Y (p = 0.017) and between Generation Z and Baby Boomers (p = 0.042), indicating that Generation Z places greater importance on social activities than older generations. No significant differences were found between the remaining generational pairings (all p ≥ 0.05).

To enhance clarity,

Table 11. Summary of hypotheses and results.

Hypothesis	Supported/Rejected
1: There are statistically significant differences among generations (Z, Y, X, Baby Boomers) in the perceived influence of at least one aspect on decision-making related to travel abroad.	Supported for social media. Rejected for all other aspects.
2: There are statistically significant differences among generations (Z, Y, X, Baby Boomers) in the perceived restrictiveness of at least one constraining factor on decision-making related to travel abroad.	Supported for availability of time, work-related restrictions, language barrier, and restrictions due to studies. Rejected for all other constraining factors.
3: There are statistically significant differences among generations (Z, Y, X, Baby Boomers) in the perceived importance of at least one factor when choosing a vacation.	Supported for entertainment and social activities. Rejected for comfort, relaxation, authentic experience, personal growth, and enrichment through culture.

presents a summary of all tested hypotheses, indicating which were statistically supported or rejected based on the results of the Kruskal–Wallis tests.

It is important to note that the study sample consists exclusively of 265 Slovak respondents, collected through an electronic questionnaire, which may limit the representativeness of the findings. The use of online data collection may have favored digitally active individuals and younger cohorts, potentially contributing to the uneven distribution of respondents across generational groups (e.g., 94 respondents from Generation Z and 21 from the Baby Boomer Generation). Although the Kruskal–Wallis test is robust to unequal group sizes, the relatively small number of Baby Boomer respondents may reduce statistical power and limit the stability of comparisons involving this cohort. Therefore, the findings should be interpreted with caution, particularly when drawing conclusions about older generations.

Furthermore, as the study focuses exclusively on respondents from Slovakia, the results reflect the specific socio-economic, cultural, and historical context of this country. Generational identities and travel behavior are shaped by nationally embedded experiences; therefore, the observed patterns may not be directly generalizable to other cultural or economic environments. Broader generalization would require comparative cross-national research.

5. Discussion

The results of this study provide clear evidence that generational differences influence travel decision-making, perceived constraints, and vacation preferences among Slovak respondents, supporting all three hypotheses.

The findings both confirm and extend the existing literature on generational differences in tourism decision-making and preferences (Glover, 2009). Consistent with previous research by Ivancsóné Horváth et al. (2025), price remains a key factor influencing travel decisions across generations. In our study, 43.77% of respondents rated price as the most influential factor, emphasizing that financial considerations continue to play a dominant role. This aligns with prior findings suggesting that affordability strongly affects vacation choices.

The study also confirms the growing role of digitalization and social media in travel decision-making, consistent with Ivancsóné Horváth et al. (2025). Notably, generational differences were evident in the influence of social media: Generation Z perceived social media as significantly more influential than Generation Y and Baby Boomers, while Generation X showed intermediate levels of influence. This pattern mirrors previous research suggesting that younger cohorts rely heavily on visual and digital content in forming travel intentions, whereas older cohorts place greater weight on trust and personal recommendations.

Regarding motivational factors, the results support the works of J. L. Crompton and McKay (1997) and Jang et al. (2009), demonstrating that novelty, relaxation, and authentic experiences remain important determinants of vacation choices. “Relaxation” and “authentic experiences” emerged as the highest-rated factors across generations, reflecting the continued importance of both affective and experiential motivations in travel behavior. Interestingly, entertainment and social activities were rated significantly higher by Generation Z compared to older generations. This finding supports Kamboj and Sharma’s (2016) assertion that younger travelers prioritize thrills, novelty, and engaging experiences, while also revealing a generational divergence in social and recreational preferences.

Consistent with Kamboj and Sharma (2016), who noted that Generation Y is particularly inclined to travel and is influenced by factors such as the digital revolution, financial instability, and safety concerns, our results highlight both continuities and extensions of these patterns. While financial costs emerged as the most restrictive factor across generations, confirming the enduring impact of economic considerations, digital influences showed clear generational differences. Generations Z and Y reported a stronger influence of social media on travel decision-making than older cohorts, reflecting the continuing role of the digital revolution in shaping travel behavior. Additionally, younger generations placed greater importance on entertainment and social activities, indicating that their leisure motivations extend beyond traditional factors like relaxation or cultural enrichment. These findings suggest that, while external and personal factors continue to shape tourism decisions, the way these factors are weighted varies across generational cohorts, with younger travelers increasingly prioritizing digital engagement and experiential forms of leisure, thereby echoing and updating the trends identified by Kamboj and Sharma (2016).

Our findings also resonate with Benkendorff and Moscardo (2009), who highlighted distinctive travel preferences among Generation Y. Consistent with their results, younger generations in our study—particularly Generation Z and Y—demonstrated a stronger emphasis on entertainment, social activities, and novel experiences compared to older cohorts, reflecting their interest in escape, excitement, and engaging leisure opportunities. While we did not specifically examine travel in family groups, the patterns of motivation and perceived constraints in our data—such as prioritizing relaxation and authentic experiences—suggest that life stage and personal circumstances continue to influence travel choices, aligning with previous claims about Generation Y’s travel behaviors. Overall, these findings confirm that younger travelers have distinctive motivational profiles and support the notion that novelty and experiential engagement remain central to their decision-making processes.

With regard to restrictive factors, the results add nuance to the generational differences identified by Reizenwitz (2019). Younger generations, particularly Generation Z, were more affected by time constraints and academic obligations, while older generations experienced fewer such limitations. This highlights that life stage and responsibilities may be as influential as generational cohort characteristics in shaping travel decisions.

Consistent with research emphasizing safety concerns among Millennials (Yousaf et al., 2018) and environmental awareness among Generation Y (Pham & Hwang, 2021), destination safety was perceived as moderately restrictive, particularly among younger generations. However, environmental sustainability had a surprisingly low influence on travel decision-making. This contrast may reflect either a generational shift in prioritization or sample-specific characteristics, suggesting that while awareness exists, it may not yet translate into behavioral decision-making for international travel. The relatively low importance of factors such as suitability for photography and environmental sustainability may indicate an emerging gap between expressed environmental concern and actual travel priorities, echoing debates in the literature about the difference between stated attitudes and behavior (Pham & Hwang, 2021).

This study provides empirical support for established generational trends while offering updated insights into how price sensitivity, digital influence, safety considerations, and generational motivations interact to shape contemporary travel behavior. The findings have practical implications for tourism marketers seeking to tailor offers to generational preferences and for policymakers aiming to understand how constraints such as cost, time, and safety affect international travel decisions.

Although our results did not show significant generational differences in the importance of environmental sustainability in travel decision-making, other studies have documented generational contrasts in environmental attitudes and sustainable travel behavior. For example, research on international visitors in New Zealand found that Generation Z was more likely than older generations to belong to segments characterized by higher environmental concern and engagement in sustainable practices such as resource saving and buying local food, indicating that eco-behavior patterns can differ by cohort in some contexts (Prayag et al., 2025). Similarly, studies in consumer behavior research outside tourism have found that younger cohorts often display stronger environmental concern than older cohorts, with Generation Z and Generation Y showing higher levels of environmental sensitivity than Generation X, suggesting intergenerational variation in environmental orientation in broader consumption contexts (e.g., Wang & Wu, 2024). Our finding of no significant generational difference in the perceived importance of environmental sustainability in vacation choice may reflect the complexity of sustainability motivations rather than a rejection of generational differences per se. Integrating sustainability attitudes with behavioral and contextual variables in future work may offer a more nuanced understanding of how generational identity interacts with pro-environmental travel preferences.

Additionally, industry research highlights that younger travelers experience financial pressure differently than older cohorts, adapting travel patterns in response to affordability and flexibility constraints, whereas older adults are less constrained by cost and may prioritize comfort and reliability (Mintel, 2026). In the case of our Slovak sample, the absence of significant differences for many constraints may reflect shared structural realities and homogenized travel priorities, wherein common influences such as cost and safety are similarly salient across cohorts.

While the current study found significant generational differences for only a limited set of factors, this pattern aligns with findings in the existing literature suggesting that generational effects do not necessarily manifest uniformly across all domains of travel behavior. For example, research on tourism consumer behavior has repeatedly demonstrated that some travel attributes show significant variation among age cohorts, while others remain similar across generations, highlighting both differences and important similarities (e.g., no differences in core travel drivers) (Li et al., 2013). A recent study of Slovak travelers further confirms that certain structural or situational factors, such as transportation choices or companion preferences, may be influenced more by practical considerations than by generational identity per se (Vašaničová & Melnyk, 2025). Similarly, research on travel satisfaction suggests that fundamental travel experiences such as satisfaction and perceptions of safety maintain their importance across generations, indicating universal motivational underpinnings that transcend cohort membership (Olsson et al., 2020). These theoretical and empirical insights support the interpretation that null generational differences in aspects such as price sensitivity, destination safety, comfort, and relaxation likely reflect shared tourism priorities across cohorts, rather than measurement noise alone. At the same time, it remains important to acknowledge potential measurement and sample limitations in this study, suggesting that future research further refine conceptual measures to explore both universal and cohort-specific determinants of travel behavior.

6. Conclusions

This study provides valuable insights into how generational differences influence decision-making, motivations, and constraints related to traveling abroad, based on a sample of Slovak respondents. While some factors, such as price, quality of accommodation, and destination safety, appear to remain consistently important across all generations, other aspects—such as the influence of social media, entertainment preferences, and the perceived restrictiveness of time and academic obligations—clearly vary among generational cohorts. These findings contribute to the growing body of research on generational differences in international travel and highlight the importance of considering generational characteristics when analyzing tourism behavior.

From a scholarly perspective, this study contributes to the theoretical development of generational theory by empirically examining how generational identity shapes travel decisions and motivations. The results refine our understanding by identifying which dimensions of travel behavior are more strongly influenced by generational affiliation. Specifically, younger generations—Generations Z and Y—place greater importance on entertainment, social activities, and digital sources of information, while older generations show more uniform decision-making patterns and rely less on social media. Conversely, factors such as price, destination safety, and relaxation are perceived similarly across generations, suggesting that some aspects of travel behavior are shaped more by situational or practical considerations than by generational identity alone. These findings underscore the differential explanatory power of generational theory across dimensions of travel behavior, particularly in the context of international tourism.

Practically, the study offers actionable insights for tourism businesses in the areas of product development, marketing, and consumer segmentation. Understanding that Generation Z highly values entertainment, social engagement, and social media–driven information can guide the design of experiential, shareable, and interactive travel offerings. Generation Y’s focus on authentic experiences, relaxation, and flexible travel arrangements suggests opportunities for tailored off-peak promotions, culturally immersive trips, and self-guided packages. For older generations, maintaining trust, reliability, and structured planning remains important, which can inform the design of all-inclusive and well-organized travel experiences. By aligning marketing content, communication strategies, and service offerings with these generational preferences, tourism businesses can enhance customer engagement, satisfaction, and conversion across diverse traveler segments.

From a managerial perspective, these findings can inform generationally targeted strategies, including the development of digital tools, social media campaigns, and experience-based packages. For example, integrated planning platforms, real-time personalization, and interactive social experiences are likely to resonate strongly with Generation Z, while flexible booking platforms and off-peak offers may better serve Generation Y. Recognizing generational differences in constraints, such as time availability and academic obligations, also enables more strategic demand planning and service design, ensuring that products are accessible and appealing to each cohort.

While this study offers meaningful insights, several limitations should be considered. The sample consists exclusively of Slovak respondents, which may limit the generalizability of the findings to other cultural or geographical contexts. Future research could examine generational differences across countries, compare travel preferences by gender, or explore how additional demographic variables—such as income, education, and family structure—interact with generational identity. Additionally, employing mixed-methods and longitudinal approaches could provide deeper and more dynamic insights into evolving generational trends in travel behavior.

While this study applies a generational cohort framework to examine differences among Generation Z, Generation Y, Generation X, and the Baby Boomer Generation, it is important to acknowledge the methodological complexity associated with distinguishing cohort effects from age and period effects. Given that the data were collected cross-sectionally between November and December 2025, the observed differences may reflect not only shared formative experiences that characterize generational cohorts, but also life-stage characteristics (e.g., student status, family responsibilities, retirement) and broader socio-economic or geopolitical conditions present at the time of data collection. As age, period, and cohort effects are inherently interrelated, the present study does not claim to isolate pure generational effects in a strict causal sense. Rather, the findings are interpreted within the framework of generational theory, emphasizing cohort-based patterns while recognizing that some differences may also be influenced by life-cycle and contextual factors. Future research employing longitudinal or repeated cross-sectional designs would allow for a more precise separation of these effects and further validation of the cohort-based interpretations.

Given the use of single-item measures in this study, future research should consider applying multi-item constructs accompanied by reliability and validity testing to strengthen the methodological rigor and measurement accuracy of the findings.