At Home or Abroad,Does Our Behavior Change? Examining How Everyday Behavior Influences Sustainable Travel Behavior and Tourist Clusters

Abstract

Considering the evolution of climate change and recognizing that the tourism industry is among the key contributors to this evolution, this study aims to clarify how researchers and practitioners can understand better what the triggers to the adoption of a sustainable behavior are while on holidays. Various studies have been conducted on the sustainable tourist, pointing to numerous characteristics but as of yet, not achieving an agreement as to what the profile of this type of tourist is. Through a study on a sample of Canadian tourists, this article aims to identify whether a sustainable consumer type can be identified, how those consumers differ in their everyday sustainable behavior, and whether daily life behaviors continue when traveling. By investigating indicators such as altruism, frugality, and pro-ecological behavior, the study both identifies the underlying structure of sustainable behavior and brings a new insight into which elements permeate or not when traveling.

Keywords

sustainable tourism motivations pro-ecological behavior frugality altruism

Introduction

Sustainable travel has become a major concern because of the impact it has on the environment (Gehlert, Dziekan, and Gärling 2013), and it is increasingly unavoidable for 21st-century consumers to ignore some of the negative impacts of their behavior. The tourism industry has long recognized that “sustainable tourists” were the most desirable tourists as they have the least environmental impacts and a higher spending power than the average tourist (Dodds, Graci, and Holmes 2010; Hansla et al. 2007; Nickerson, Jorgenson, and Boley 2016; Pulido-Fernández and López-Sánchez 2016; Buffa 2015). The so-called sustainable tourist is more likely to “fulfil all triple bottom line measures” (Nickerson, Jorgenson, and Boley 2016, p. 176), enhancing the local economy, as well as supporting the local environmental and social initiatives. Moreover, if tourist destinations become more sustainable, tourists may be willing to travel there at a higher cost and be more inclined to participate in behaviors that preserve their environment and culture. This outcome can also find its echo when considering the residents at a tourism destination. As Yu, Chancellor, and Cole (2011) rightly point out, residents’ attitudes toward sustainable tourism can influence tourism policy and policy makers, and destination managers could benefit from understanding these attitudes (Sirakaya, Ekinci, and Kaya 2008).

Nonetheless, where sustainable tourists come from and whether they will actually pay more is undecided. In fact, there is limited work done on consumers’ behaviors in their day-to-day life and whether they transpose to their behaviors when traveling. As a result, existing literature brings confusion to the understanding of the green traveler, and more studies need to be conducted to clarify whether a link can be drawn between everyday attitudes toward the environment and actual behavior while on holidays. The confusion in existing literature might come from the fact that the green attitude cannot be considered across the whole population, but rather specific segments exist that are more sensitive to environmental issues than others. Sensitivity to sustainable issues evolves along a continuum from highly concerned to not concerned at all. In addition, most studies link attitudes to intentions (such as willingness to pay) but not to actual behavior. It is essential that existing knowledge on tourist behavior now move beyond intentions to measure actual behavior when consumers are traveling.

Is There a Green Traveler?

A number of theories have been put forward to try to explain and understand purchase intentions relating to potentially green consumers such as the theory of planned behavior (TPB), the theory of reasoned action (TRA), and environmentally responsible behavior (ERB). The theory of planned behavior proposes that people’s underlying belief structure determines their intentions, subjective norms, and perceived controls. Testing models of TPB, Kalafatis et al. (1999), using both UK and Greek consumers, found that attitudes, subjective norms, perceived control, self-identity, and past behavior were all strong predictors of a person’s behavioral intentions. A more recent study by Paul, Modi, and Patel (2016) found that consumers who are highly concerned about the environment have more positive outlooks on purchasing greener products. Although dated, Kinnear, Taylor, and Ahmed (1974) researched ecologically concerned consumers, that is, ERB in Canada exploring if there was a relationship between socioeconomic and personality characteristics of consumers with a key focus on ecological concern. Through their study, they found that there may be an ecologically concerned segment for marketers to target.

Researchers developed a similar reasoning when it comes to the potential green traveler. First of all, green travelers appear to have distinctive socioeconomic profiles. Tourists who display higher commitments to sustainability clearly have higher income or education levels (Juvan and Dolnicar 2016; Buffa 2015; Ramchurjee and Suresha 2015; Shamsub and Lebel 2012; G. Miller et al. 2010; Shamsub and Lebel 2012). Buffa (2015) also identified that sustainability indicators and ethical tour operators attracted younger people, even if profits benefiting local community were not as important.

Looking beyond socioeconomic profiling, Dolnicar (2010) found that “residents and tourists indicate that environmental concern, altruism, feeling morally obliged to behave in an environmentally friendly manner, age and regional identity are the best predictors of the segment of people who behave in an environmentally friendly way at home” (p. 718). Dolnicar (2010) also found income and moral obligation to be strong predictors of segment membership. Further research discusses how underlying environmental values are critical to tourist behavior (Perkins and Brown 2012) and therefore tourists are willing to make more efforts to ensure their travel behavior protects (Dolnicar 2006) or respects the environment by paying additional fees (Dodds, Graci, and Holmes 2010).

With regard to how green consumers actually behave while traveling, Bergin-Seers and Mair (2009) identified that green tourists were more likely to partake in sustainable travel behaviors and knowledge searching information. Pulido-Fernández and López-Sánchez (2016) also found that pro-sustainable tourists (one of three clusters: the “reflective tourist,” “unconcerned tourist,” and “pro-sustainable tourist”) were willing to pay more money for a sustainable tourism offering. These authors, however, found that the amount was not much higher than normal. Ramchurjee and Suresha (2015) also identified that willingness to pay did not often translate into actions. Teeroovengadum (2019) investigated sustainable identity as an antecedent to tourists’ sustainable behavior. His study clearly identified that “stronger environmental identity leads directly to more positive ecotourism attitude, greater interest towards ecotourism and a higher willingness to pay a premium” (p. 257). As this study also looks at intentions, this recent work is particularly interesting since it indicates that contemporary consumers increasingly need to align their behavior with their identity. In a world where environmental threats to our planet have become evident, it becomes increasingly difficult to ignore the impacts of one’s own behavior on the environment.

Overall, if those studies point to the existence of a more sustainable consumer, the likeliness of those consumers translating their attitude into actual behavior appears to be rather weak. Since most studies focus on the link between attitude and intentions, rather than attitude and behavior, it is difficult to get a clear picture of actual behaviors.

Attitude–Behavior Gap

Several authors have clearly pointed to the difficulty for tourists, no matter how environmentally concerned they might be, to translate their attitude into sustainable vacation behavior. For instance, D. Miller, Merrilees, and Coghlan (2015) measured tourists’ pro-ecological behavior in four key categories including recycling, green transport use, sustainable energy/material use, and green food consumption. The authors found that if tourists had a positive environmental attitude while at home, they only engaged in environmentally conscious actions when traveling if it was convenient.

Ramchurjee and Suresha (2015) identified that varying levels of education and low perceived benefits of protecting the environment meant that even if tourists are aware of their behavioral impact on the environment, they are not necessarily prepared to put their environmental beliefs into action for positive change when visiting destinations. More worryingly, Juvan and Dolnicar (2014) focused on cognitive dissonance and the attitude–behavior gap by investigating consumers who actively engage in environmental protection. Their study revealed that although respondents were involved with environmental organizations where their daily tasks were to organize environmental protection or conversation, their behavior while traveling resulted in different outcomes. The results of this study have shown that even though tourists may be participating in ethically responsible behavior (ERB) at home, tourists were less environmentally conscious while traveling. Budeanu (2007) also noted that consumers’ choice to participate in sustainable travel behavior was low in comparison to their high positive attitudes toward the topic. Gössling (2018) investigated to which extent tourists learn about sustainability from their contacts with different cultures and destinations that they visit, suggesting that they can enhance their ability to travel responsibly when they understand their impacts. The author, however, found that tourists’ perceptions of the term “indulgence” when discussing impacts at home differed from behavior when traveling, where they indulged in clean towel services and bed sheet changes daily. These results in unsustainable travel behavior show a gap between behavior at home and behavior while traveling.

Understanding the Attitude–Behavior Gap

There may be a number of reasons for the attitude–behavior disconnect, and two of the more prominently discussed are the topics of self and that of cost. Hibbert et al. (2013) explored the social context of the “self” when interviewing respondents as to why they travel. Many explained that they wanted to travel to destinations that would benefit their future self, either through social or personal status. If they are more involved with their behavior resulting in “status,” they are less likely to be aware of the environmental impacts their traveling contributes to. Kroesen (2013) classified tourists into integration, ignorance, denial, necessity, guilt, and indulgence/fatalism when asked about their viewpoints toward air travel and climate change. From this study, attitude–behavior inconsistency was prevalent when respondents were asked if they were aware of their consumption and also what their actions were to offset these impacts. Hibbert et al. (2013) declare that as tourists are becoming increasingly mobile, this attitude–behavior gap increases, where their behavior at home does not correlate with their behavior abroad. These authors discuss the different selves that a person can have in different situations, where when they are at home they feel differently than when traveling. This could account for the attitude–behavior inconsistency.

In relation to cost, Hansla et al. (2007) and Dodds, Graci, and Holmes (2010) found that tourists said they are willing to pay more for sustainable tourism offerings. Pulido-Fernández and López-Sánchez (2016), however, found that tourists desired more sustainable tourism, but that the rise of price required to increase sustainability offerings deterred tourists. Therefore, cost is deemed a key inhibitor in regard to sustainable travel where travelers are aware of the impact of their behavior in a destination but do not consider their participation in them and seem un-interested in adopting sustainable lifestyles or supporting responsible tourism products (Budeanu 2007).

The low support from tourists to adapting to sustainable tourism has become one of the main barriers to selling such products. If there is no demand for sustainable products while traveling, businesses will not incorporate them in their product offerings. Understanding the behavior gap and raising awareness to these issues can help change the way tourists behave. Understanding why some travelers undertake “pro-sustainable” tourist actions has become increasingly difficult to explore because of the lack of studies (López-Sánchez and Pulido-Fernández 2017). Juvan and Dolnicar (2014) suggest that it is hard to appreciate actual tourists’ behavior, as many studies are not measured on their behavior but on their willingness to participate in sustainable tourism. Subsequently, Juvan and Dolnicar (2016) outlined that more observational studies of tourists were needed in order to measure the actual behavior of a sustainable product. Lu, Dogan, and Del Chiappa (2014) also encourage researchers to investigate sustainable behavior antecedents if the industry wants to change ecotourism participation. Hibbert et al. (2013) did explore the attitude–behavior gap but did not address all social, economic, and environmental aspects of current behavior. These authors postulated that a greater understanding of the potential pro-sustainable behavior can only be understood if one looks deeper into the attitudes and actual behaviors of a traveler, namely, the behavior of a resident at home and then also when traveling.

The authors of this article want to move beyond the intention measures traditionally used in previous studies in order to evaluate much more accurately sustainable behavior. The originality of this paper lies in its capacity to measure both sustainable behavior at home and compare it to sustainable vacation behavior. One way to explore this link is to investigate the sustainable behavior in a finer approach, notably by investigating its key pillars. In 2010, Corral-Verdugo et al. invited researchers to measure more accurately the construct of sustainable behavior by looking at its main structure. Sustainable behaviors are organized actions reported to protect both the natural and the human resources. In correspondence with this characterization, at least three sets of behavior are mentioned as “sustainable” actions in terms of their effects on the sociophysical environment: pro-ecological actions; frugal, or austere, patterns of consumption; and altruistic behaviors. Based on Corral-Verdugo et al.’s work, the current study aims to investigate how those three components can act as explanatory variables in sustainable behavior.

Pro-ecological behavior is “conscious actions performed by an individual so as to lessen the negative impact of human activities on the environment and to enhance the quality of the environment” (Sawitri, Hadiyanto, and Hadi 2014, p. 28). It includes any action that aims to preserve our environment, ranging from recycling to composting (Kaiser 1998). As Corral-Verdugo et al. (2012) point out, the main objective of pro-ecological behavior is to reduce human impact on the planet with clear and concrete actions.

Hypothesis 1: Individuals who demonstrate higher levels of pro-ecological behavior in their everyday behavior will display a more sustainable travel behavior.

Hypothesis 1a: The relationship between pro-ecological behavior and sustainable travel behavior will remain constant no matter the cluster membership.

Frugality is a notion that is regaining attention in light of modern living conditions and their impact on the planet and the recognition of overconsumption limits. Evans (2011, p. 552) proposes that

to be frugal is to be moderate or sparing in the use of money, goods and resources with a particular emphasis on careful consumption and the avoidance of waste. At the level of practice, it is worth thinking of frugality as a moral restraint on consumption and a form of resistance to the alleged excess and profligacy of consumerism.

Frugality is characteristic of consumers who attempt to make changes to the ways in which they live associated to a lower income or, as Evans and Abrahamse (2009) suggest, to develop a more environmentally friendly lifestyle. Frugal behavior involves necessarily reducing one’s consumption and also a more equitable use of products.

Hypothesis 2: Individuals who demonstrate higher levels of frugality in their everyday behavior will display more sustainable vacation behavior.

Hypothesis 2a: The relationship between frugality and sustainable travel behavior will remain constant no matter the cluster membership.

Far from potentially reflecting egoistic motives, the notion of altruism aims to benefit other human beings and is an integral part of human nature (Fehr and Fischbacher 2003; Piliavin and Charng 1990). Altruism is connected to the desire to make active choices in one’s life but in relation to other human beings, which ultimately contributes to the sustainability cause. Altruism is considered as being a fundamental component of pro-ecological motivations. Schultz (2001) demonstrated that altruistic individuals perceive to have more control and display a higher propensity to make sacrifices, behaving pro-ecologically is clearly identified as a moral issue for those individuals.

Hypothesis 3: Individuals who demonstrate higher levels of altruism in their everyday behavior will display a more sustainable holiday behavior.

Hypothesis 3a: This relationship between altruism and sustainable travel behavior will remain constant no matter the cluster membership.

Finally, considering that existing literature has identified that different segments of consumers might be identified depending on their green behavior, the present study aims to investigate if such a segment exists and then test the first three hypothesis across those segments. This article, therefore, aims to build on existing literature by Kaiser (1998) and López-Sánchez and Pulido-Fernández (2016); it also aims to investigate travel behavior and its connection to tourist clusters and everyday behavior as it pertains to the work of Juvan and Dolnicar (2016), Passafaro et al. (2015), and Corral-Verdugo et al. (2010, 2012). Beyond looking to understand how travel behavior differs by the type of tourist, this study aims to understand the role that the everyday behaviors of altruism, pro-ecological behavior, and frugality play in tourist decisions around sustainable travel behavior, ensuring a social, economic, and environmental lens was included.

Hypothesis 4: Consumers can be segmented according to their sustainable travel behavior.

Hypothesis 4a: Different segments of travel behavior will display varying levels of pro-ecological behavior

Hypothesis 4b: Different segments of travel behavior will display varying levels of frugality

Hypothesis 4c: Different segments of travel behavior will display varying levels of altruism

Research Method

Using a multimethod approach though the application of clustering and structural equation modeling, this study looks to understand sustainable tourist clusters as well as how everyday behavior might lead to sustainable travel behavior.

To begin, a survey was constructed asking questions pertaining to tourist demographics, travel and sustainable travel behavior, and everyday sustainable tendencies measured through altruism, pro-ecological behavior, and frugality (Corral-Verdugo and Pinheiro 2004; Corral-Verdugo et al. 2010, 2012; Kaiser 1998). Drawing on the work of Kaiser (1998), who was arguably the first author to construct a measure of ecological behavior considering both (a) the difficulty of the behavior and (b) the susceptibility of the behavior to influence and constraint, questions pertaining to pro-ecological behavior were asked, such as “I wait until I have a full load before doing laundry,” “I collect and recycle used paper,” and “I point out un-ecological behavior to someone.” Frugality was assessed using the construct developed by Corral-Verdugo et al. (2012), asking questions such as “I do not buy a new car if my old one is still functioning,” and “I wear the same clothing from past season.” The construct of altruism was measured using questions such as “I donate clothing to poor people,” “I help elders or the handicapped cross the street,” and “I donate blood when required,” as developed by Corral-Verdugo et al. (2010, 2012). Lastly, the measures of travel behavior and sustainable travel behavior were measured by asking questions such as “I chose tourism companies which proactively protect the environment,” “I have made the decision not to travel to destinations where I believe the local culture is not respected” and “Tourists have a responsibility to do what they can to protect the environment,” being derived from the work of López-Sánchez and Pulido-Fernández (2016), Juvan and Dolnicar (2016), and Passafaro et al. (2015). Those questions pertaining to the first three aforementioned constructs were measured using five-point Likert-type scales, similar to their asking in Corral-Verdugo et al. (2012), while those questions that comprise sustainable travel behavior were measured using seven-point scales, as was undertaken in the work by López-Sánchez and Pulido-Fernández (2016).

The survey was administered to a panel of 1,242 Canadian travelers, over the age of 18, who had traveled at least once in the past year. While surveys were collected from the 1,242 panelists, questions pertaining to their recent travel behavior provided them the opportunity to select not applicable. To allow for a complete data set with no extraneous responses such as not applicable, any respondent to indicate not applicable to a previous travel question were removed from the data, resulting in a total sample size of 783. This abides by the issue that Kostadinova (2016) noted, being that situational factors need to be considered (individual related factors and context related or situational factors), with all relevant questions including a not applicable or opt-out response option.

The completed survey sample was first analyzed to determine if clusters exist, for example, a type of tourist. Second, differences in cluster demographics and travel behavior were examined. Third, the ability of the proposed model to explain the variance in sustainable travel behavior was tested through SEM. Lastly, to determine if the model holds true for each of the different clusters, SEM by cluster analysis was employed. Each step in this analysis has been broken down sequentially into the headings—Cluster Analysis, Cluster Demographics, SEM, and SEM by Cluster, which is presented in the Findings section.

Findings

Overall Demographics

In this study, there was a fairly equal representation of respondents by gender (females, 46%), with most of the respondents born in Canada (77%) and not identifying as a visible minority (78%). Most of the respondents were educated with either a college diploma (25%), university undergraduate degree (38%), or graduate degree (38%). A fairly equal distribution of 10-year age ranges was collected between 18 and 65 years of age, with 13% of respondents being older than 65 years. When traveling, almost half of the respondents (40%) travel in all seasons, travel with their partner or spouse (50%), frequently travel to visit friends and family, and stay in hotels or resorts. While the sample was fairly representative of the Canadian tourist based on age, the sample was younger and more highly educated than the general Canadian traveler (see Table 1).

Table 1.

Population and Sample Population.

Variable	Population	Sample
Gender, %
Female	47	46
Male	53	54

Age, %
18–19 years	4	5
20–34 years	29	19
35–44 years	17	20
45–54 years	20	23
55–64 years	17	18
≥65 years	13	15

Education, %
Less than high school	9	1
High school	17	15
College diploma	47	25
University undergraduate degree	19	39
University graduate degree	8	20

Note: Population statistics were derived from Statistics Canada (2019) travel survey of residents in 2010.

Cluster Analysis

Questions for travel behavior were used to understand the different clusters that might exist in regard to sustainable travel behavior. To derive these clusters, the data were first tested for normality using the skewness and kurtosis tests, each of which found the individual question responses to fall below the ±2 limits. Next, all 23 questions were run through a two-step cluster analysis to determine the number of clusters that should be investigated in order to acquire a silhouette measure of cohesion and separation (SMCS) of fair or better. This analysis resulted in identification of three clusters that achieved a “fair” rating on the SMCS. A k-means cluster analysis was then run, setting the number of clusters to three. The outcome of this cluster analysis, along with the questions that were used in deriving the analysis is presented in Table 2 below. An ANOVA was run to investigate if there were significant differences between the clusters as it pertains to respondent answers to travel behavior, along with testing the differences between each of the clusters through the use of a Bonferroni post-hoc test (see Table 2). The respondent demographics of each cluster can also be found in Table 3. Although the overall sample had 783 respondents, 48% fell in cluster 1, 36% in cluster 2, and 16% in cluster 3 (see Table 3).

Table 2.

Clusters Based on Travel Behavior.

	Mean Scores			ANOVA Significance	Differences			n
	C1: Typical Tourist	C2: Economical Tourist	C3: Sustainable Tourist	ANOVA Significance	C1 to C2	C1 to C3	C2 to C3
Purchase locally owned accommodations.	2.38	2.87	4.13	0.000	−0.49***	−1.75***	−1.26***	781
Purchase locally grown food and/or drink.	2.99	3.88	4.24	0.000	−0.90***	−1.26***	−0.36***	782
Purchase anything but chain food (e.g., McDonald’s).	2.65	1.88	3.86	0.000	0.77***	−1.20***	−1.98***	782
Purchase locally made arts and crafts	2.56	3.35	4.09	0.000	−0.79***	−1.53***	−0.74***	783
Seek out a company’s environmental or fair-trade policy.	2.12	2.34	4.06	0.000	−0.22*	−1.95***	−1.72***	783
Walk or cycle instead of taking motorized transportation at the destination (taxi or renting a car).	2.87	3.45	4.18	0.000	−0.57***	−1.31***	−0.74***	783
Don’t rent a private car.	2.47	2.18	4.03	0.000	0.29**	−1.56***	−1.85***	783
Opt for a different destination that did not need flying to.	2.40	2.21	4.03	0.000	0.18p	−1.64***	−1.82***	782
Purchase carbon offsets to mitigate your carbon footprint.	1.92	1.45	3.91	0.000	0.48***	−1.99***	−2.46***	783
Use public transportation (i.e., bus, subway, or tram).	2.65	3.11	4.12	0.000	−0.46***	−1.47***	−1.01***	783
Adapt your dress style to meet the expectation of local people at the destination.	2.42	3.34	3.98	0.000	−0.93***	−1.57***	−0.64***	783
Go to places mostly locals go to (or very few tourists).	2.59	3.31	4.11	0.000	−0.72***	−1.52***	−0.80***	783
Eat local foods and specialties in locally owned restaurant (instead of international food in known branded places).	2.88	3.96	4.12	0.000	−1.09***	−1.24***	−0.16	783
Stay in your hotel to relax.	2.61	2.55	3.89	0.000	0.06	−1.28***	−1.33***	782
Try using the local language (if not your first language).	2.34	3.40	4.00	0.000	−1.07***	−1.66***	−0.60***	783
Intentionally interact with locals.	2.63	3.81	4.00	0.000	−1.18***	−1.37***	−0.19	783
Don’t keep the air conditioning or heater on when you leave the room.	2.69	2.00	3.72	0.000	0.69***	−1.03***	−1.72***	783
Turn off the lights when you leave your accommodation.	3.59	4.82	4.11	0.000	−1.23***	−0.52***	0.71***	782
Bring and use a refillable water bottle.	2.89	4.16	4.03	0.000	−1.27***	−1.14***	0.13	783
Don’t ask for a plastic bag when shopping.	2.43	2.04	3.80	0.000	0.38***	−1.37***	−1.76***	782
Don’t take more food than you needed at a buffet.	2.27	1.64	3.72	0.000	0.63***	−1.45***	−2.08***	783
Don’t take more than one shower per day.	2.17	1.66	3.63	0.000	0.51***	−1.47***	−1.97***	783
Participate in your hotel’s reuse towel program.	2.68	4.35	3.83	0.000	−1.67***	−1.16***	0.52***	783

Note: The questions were adapted from López-Sánchez and Pulido-Fernández (2016), Juvan and Dolnicar (2016), and Passafaro et al. (2015), using the scale 1 = never, 2 = rarely, 3 = sometimes, 4 = most of the time, 5 = always.

***

Significant at p <0.001; **significant at p <0.01; *significant at p <0.05. Significance was set at p <0.1.

Table 3.

Respondent Demographics by Cluster.

Variables		Mean Scores				n
Variables		All	C1: Typical Tourist	C2: Economical Tourist	C3: Sustainable Tourist	n
Female		45.98	39.41	54.74	45.60	783
Born in Canada		77.14	76.68	78.60	75.20	783
Identifies as a visible minority		22.25	24.40	14.74	33.06	782

Education
	Less than high school	0.89	0.80	1.05	0.80	783
	High school	15.33	15.55	17.89	8.80	783
	College diploma	25.29	24.40	30.53	16.00	783
	University undergraduate degree	38.44	42.36	31.93	41.60	783
	University graduate degree	19.41	16.09	17.89	32.80	783
	Prefer not to say	0.64	0.80	0.70	0.00	783
Age, years
	18–24	4.60	5.09	3.51	5.60	783
	25–34	19.16	17.69	10.18	44.00	783
	35–44	20.31	25.20	13.33	21.60	783
	45–54	22.61	21.72	23.51	23.20	783
	55–64	17.50	16.89	24.21	4.00	783
	65–74	12.77	9.12	22.46	1.60	783
	75–84	2.04	2.68	2.11	0.00	783
	≥85	0.38	0.27	0.70	0.00	783
	Prefer not to answer	0.64	1.34	0.00	0.00	783
Income
	<$30,000	7.92	8.31	7.37	8.00	783
	$30,000–$49,999	17.37	16.09	18.25	19.20	783
	$50,000–$69,999	21.58	22.79	21.05	19.20	783
	$70,000–$99,999	23.50	22.79	23.51	25.60	783
	$100,000–$149,999	14.81	15.82	10.18	22.40	783
	≥$150,000	6.00	6.70	6.32	3.20	783
	Prefer not to answer	8.81	7.51	13.33	2.40	783
Season of travel
	Winter	19.80	20.38	15.44	28.00	783
	Spring	9.96	12.33	7.37	8.80	783
	Summer	25.16	27.08	18.25	35.20	783
	Fall	4.60	3.75	6.32	3.20	783
	All Seasons	40.23	36.46	52.28	24.00	783
	Company while traveling
	Alone	18.01	18.77	14.39	24.00	783
	Partner/Spouse	50.06	43.97	65.26	33.60	783
	Family	24.52	27.88	14.74	36.80	783
	Friends	6.64	8.58	5.26	4.00	783
	Colleagues	0.64	0.54	0.35	1.60	783
	Other	0.13	0.27	0.00	0.00	783
When you travel, how frequently do you take the following types of trips?
	Business	2.11	1.99	1.78	3.22	770
	All-inclusive resort	2.78	2.74	2.49	3.56	774
	Cruise	2.17	2.09	1.89	3.05	765
	Travel for a festival/event	2.43	2.30	2.15	3.40	767
	Visit friends and family	3.38	3.29	3.26	3.92	774
	Short break, i.e., city break	3.13	3.00	2.99	3.86	765
	Tour package	2.45	2.34	2.13	3.46	766
When you travel for vacation, in what type of accommodation do you most commonly stay?
	Hotel/resort	3.69	3.62	3.57	4.18	781
	Hotel/resort (all inclusive)	2.91	2.84	2.64	3.74	778
	Holiday homes/apt	2.17	1.92	1.96	3.40	776
	Home sharing (e.g., Airbnb)	1.97	1.73	1.72	3.22	775
	Bed-and-breakfast	2.16	1.91	1.95	3.36	776
	Timeshare/own cottage	1.85	1.72	1.48	3.10	774
	Hostels	1.79	1.65	1.38	3.15	774
	Family and friends	2.88	2.80	2.74	3.47	779

Number of respondents in each cluster		783	373	285	125

Cluster Demographics

Utilizing the results of the ANOVA pertaining to the differences in travel behavior and demographics between clusters, researchers were able to classify three clusters; Typical Tourist, Economical Tourist, and Sustainable Tourist. The name and details of the characteristics are presented in Table 4.

Table 4.

Cluster Names and Descriptions.

Cluster Name	Cluster Characteristics
Cluster 1: Typical Tourist (TT)	• This cluster is a more generic tourist. They do care about some elements of sustainability but their position is not as strong as the other clusters.• They are not really ready to adapt to local populations, nor do they care much for locally owned accommodation.• They are average earners, have no age identification, and more likely to be male.• Overall, a group that still needs to be sensitized to sustainability and could be influenced as they are the group most likely to travel with friends.
Cluster 2: Economical Traveler (ET)	• This cluster is not necessarily sensitive to the environmental discourse (carbon, flying, renting . . . ), but are sensitive to actions: they project their sustainable behavior into concrete acts that they can master and operate (turn lights off, use a refillable water bottle, etc.)• This general attitude fits, overall, with their fairly high scores on frugality and pro-ecological behavior. Less so on altruism.• They are slightly less educated and older people, which might indicate a generational effect here.
Cluster 3: Sustainable Tourist (ST)	• This cluster is keen on localhood and very sensitive to ongoing messages about sustainability (grand ideas such as fair trade, walking, not flying, carbon offsets).• Their commitment to sustainability reflects in their everyday life; they are clearly aiming to put their money where their mouths are especially when it comes to caring for others around them in society (altruism)• Their sustainable intellectual thirst is also shown through some of the variables of the pro-ecological behavior (read about environmental issues, talk with friends about environmental problems, etc.)• Their sustainable travel behavior matches their attitude• They are clearly very sensitive to the sustainable message and feel that they have to “be good” through their consumption choices.• This group is composed of significantly more visible minorities than clusters 1 and 2, they are better educated, younger (66% falling between 25 and 44 years of age), and they earn significantly higher incomes (>50% earning >$70,000).

Differences in cluster membership

Utilizing the clusters, the research looked to examine if there were significant differences in the responses to questions that were collected pertaining to the constructs of pro-ecological behavior, frugality, altruism, and sustainable travel behavior. As can be seen in Table 5, all questions pertaining to each construct were found to have different responses based on respondent cluster membership. For all questions pertaining to Altruism, Cluster 3 respondents are more likely to indicate higher incidence of altruistic behavior, while Cluster 1 respondents typically indicate lower, but mid-range, frequencies. This also holds true for most questions pertaining to pro-ecological behavior. In contrast, clusters two and three trade-off between having the highest indication of frugality, while cluster 1 is still seen as having a more modest tendency toward frugality.

Table 5.

Altruism, Pro-ecological Behavior, Frugality, and Sustainable Travel Behavior by Cluster.

Construct	Question	Mean Scores
Construct	Question	C1:– Typical Tourist	C2: Economical Tourist	C3: Sustainable Tourist
Altruism:Please indicate the frequency at which you undertake the following actions^a	Donate clothing to poor people	3.24	3.65	4.08
	Assist a person in need on the street	2.87	3.16	4.05
	Contribute financially, such as to the Red Cross	2.77	3.10	3.75
	Visit the sick at hospitals/homes	2.08	2.07	3.46
	Help elders or the handicapped crossing the street	2.66	3.08	3.75
	Guide people asking for directions	3.32	3.90	4.10
	Provide some money to the homeless	2.47	2.69	3.76
	Participate in fund collection rallies	2.35	2.45	3.66
	Donate blood when required	2.13	2.04	3.35
	Cooperate with colleagues	3.24	3.94	3.98

Pro-ecological behavior:Now please indicate the frequency at which you undertake the following actions^b	Wait until have a full load before doing laundry	3.66	4.19	4.18
	Drive on highway at speeds under 100 kph	2.84	2.86	3.78
	Collect and recycle used paper	3.82	4.66	4.20
	Point out unecological behavior to someone	2.58	2.88	3.78
	Do not buy prepared food	2.98	2.74	3.66
	Buy products in refillable packages	2.92	3.31	3.79
	Buy seasonal produce	3.49	4.14	4.03
	Do not use a clothes dryer	3.71	3.94	4.08
	Read about environmental issues	2.91	3.38	3.92
	Talk with friends about environmental problems	2.70	3.18	3.95
	Do not use chemical insecticides	2.26	1.78	3.38
	Turn down air conditioning when leaving place	3.50	4.35	4.06
	Look for ways to reuse things	3.41	4.27	4.04
	Encourage friends and family to recycle	3.21	3.94	4.09
	Conserve gasoline by walking or bicycling	2.87	3.52	3.95

Frugality:Finally, please indicate the frequency at which you undertake the following actions^c	Do not buy a new car if old one is still functional	3.39	4.12	4.00
	Wear the same clothing from a past season	3.85	4.62	4.08
	Do not buy jewelry	3.15	3.54	3.68
	Do not buy shoes	3.52	3.94	2.32
	Do not buy more food than needed	3.17	3.58	2.22
	Do not use earnings for buying clothing	3.78	4.42	2.60
	Always eat meals at home	3.41	3.88	3.92
	Rather walk than drive	2.83	3.38	3.89
	Reuse notebooks and papers	3.06	3.89	3.88
	Live lightly even when affording luxuries	3.17	3.85	3.91

Sustainable travel behavior:Please indicate your level of agreement with the following statements^d	I chose tourism companies that proactively protect the environment	4.05	4.59	5.80
	I have made the decision not to travel to destinations where I believe the local culture is not respected	4.07	4.69	5.71
	Tourists have a responsibility to do what they can to protect the environment	4.91	6.22	5.91
	I have paid extra for travel products that have lower negative impacts on the environment	3.82	4.12	5.47
	I have paid more for environmentally responsible or sustainable tourism	3.61	3.62	2.58
	I have decided not to stay at accommodations that were not certified to be sustainable or eco or green-labeled.	3.69	3.78	5.26
	I have paid more for a tour or accommodation that claimed it was socially responsible and/or eco-friendly	3.62	3.74	5.36
	Rather than visit a place where tour operators exploit local workers, I preferred not to go on holiday	3.75	4.14	5.34

Note: n = 783, all clusters were significantly different at p <0.000.

Questions adapted from Corral-Verdugo et al. (2010); 5-point scale (1 = strongly disagree to 5 = strongly agree).

Questions adapted from Kaiser (1998); 5-point scale (1 = strongly disagree to 5 = strongly agree).

Questions adapted from Corral-Verdugo and Pinheiro (2004); 5-point scale (1 = strongly disagree to 5 = strongly agree).

Questions adapted from López-Sánchez and Pulido-Fernández (2016), Juvan and Dolnicar (2016), and Passafaro et al. (2015); 7-point scale (1 = strongly disagree to 7 = strongly agree).

Structural Equation Model

Using the questions asked of respondents and drawing on the work of Corral-Verdugo and Pinheiro (2004), Corral-Verdugo et al. (2010, 2012), Kaiser (1998), López-Sánchez and Pulido-Fernández (2016), Juvan and Dolnicar (2016), and Passafaro et al. (2015), we tested the influence of everyday behaviors of altruism, pro-ecological behavior, and frugality on the likelihood to travel sustainably. To begin, the four aforementioned constructs were evaluated for internal reliability, the results of which are presented in Table 6. The initial questions that comprised the four constructs showed reasonable Cronbach’s alpha, but after running a factor analysis on each construct, select questions were eliminated from each construct if they had loadings less than 0.6 to improve internal cohesion. In the end, the constructs altruism, pro-ecological behavior, frugality, and sustainable travel behavior were each measured by 7, 8, 5, and 6 questions respectively. The Cronbach’s alphas are presented in Table 6 below.

Table 6.

Construct Reliability.

Construct	Questions	Cronbach’s Alpha
Altruism:Please indicate the frequency at which you undertake the following actions^a	A2. Assist a person in need on the street	0.866
	A3. Contribute financially, such as to the Red Cross
	A4. Visit the sick at hospitals/homes
	A5. Help elders or the handicapped crossing the street
	A7. Provide some money to the homeless
	A8. Participates in fund collection rallies
	A9. Donate blood when required

Pro-ecological Behavior:Now please indicate the frequency at which you undertake the following actions^b	P4. Point out unecological behavior to someone	0.857
	P6. Buy products in refillable packages
	P7. Buy seasonal produce
	P9. Read about environmental issues
	P10. Talk with friends about environmental problems
	P13. Look for ways to reuse things
	P14. Encourage friends and family to recycle
	P15. Conserve gasoline by walking or bicycling

Frugality:Finally, please indicate the frequency at which you undertake the following actions^c	F1. Do not buy a new car if old one is still functional	0.748
	F2. Wear the same clothing from a past season
	F3. Do not buy jewelry
	F9. Rather walk than drive
	F10. Live lightly even when affording luxuries

Sustainable Travel Behavior:Please indicate your level of agreement with the following statements^d	S1. I chose tourism companies that proactively protect the environment	0.888
	S2. I have made the decision not to travel to destinations where I believe the local culture is not respected
	S4. I have paid extra for travel products that have lower negative impacts on environment
	S6. I have decided not to stay at accommodations that were not certified to be sustainable or eco- or green-labeled?
	S7. I have paid more for a tour or accommodation that claimed it was socially responsible and/or eco-friendly
	S8. Rather than visit a place where tour operators exploit local workers, I preferred not to go on holiday

Questions adapted from Corral-Verdugo et al. (2010); 5-point scale (1 = strongly disagree to 5 = strongly agree).

Questions adapted from Kaiser (1998); 5-point scale (1 = strongly disagree to 5 = strongly agree).

Questions adapted from Corral-Verdugo and Pinheiro (2004); 5-point scale (1 = strongly disagree to 5 = strongly agree).

Questions adapted from López-Sánchez and Pulido-Fernández (2016), Juvan and Dolnicar (2016), and Passafaro et al. (2015); 7-point scale (1 = strongly disagree to 7 = strongly agree).

The four constructs, frugality, altruism, pro-ecological behavior, and sustainable travel behavior, were then placed into a structural equation model (SEM) to investigate the relationship between everyday behaviors (frugality, altruism, and pro-ecological behavior) and sustainable travel behavior (see Figure 1). The proposed model was found to not be a good fit as all indices (goodness of fit index, comparative fit index, normed fit index, and root mean square error of approximation) fell below the recommendations made by Awang (2012), Hair et al. (2006), and Hooper, Coughlan, and Millen (2008). After investigating the loadings and the significance of the relationships, it was found that frugality did not significantly influence sustainable travel behavior. Once the insignificant construct of frugality was removed from the model, the model became a good fit, and was able to explain 34.0% of the variance in sustainable travel behavior (see Table 8). As the results in Table 7 show, the average variance extracted (AVE) values were at or above 0.5 (Fornell and Larcker 1981; Hair et al. 2010) and the construct reliabilities were all above 0.8, supporting convergent validity minimums as outlined by Gerbing and Anderson (1992). Beyond being able to explain a third of the variance that goes into predicting sustainable travel behavior, the model also finds that more altruistic and ecologically aware tourists are more likely to travel sustainably (see Figure 1). Furthermore, the model found that pro-ecological behavior has a greater influence on STB than altruism.

Figure 1.

Structural Model (***p < 0.001).

Table 7.

Measurement Model Results.

Construct	Variables	Standard Loadings	Construct Reliability	AVE	CR
Altruism	A2	0.688	0.866	0.49	0.85
	A3	0.664
	A4	0.746
	A5	0.655
	A7	0.716
	A8	0.777
	A9	0.604
Pro-ecological Behavior	P4	0.671	0.857	0.50	0.87
	P6	0.523
	P7	0.471
	P9	0.738
	P10	0.81
	P13	0.614
	P14	0.765
	P15	0.59
Sustainable Travel Behavior	S1	0.797	0.888	0.57	0.89
	S2	0.686
	S4	0.73
	S6	0.755
	S7	0.73
	S8	0.699

Note: AVE = average variance extracted; CR = composite reliability.

Structural Equation Model by Cluster

Following the development of the SEM, the model was investigated for each cluster independently, to determine if it would hold true. As can be seen in Table 8, the model was a good fit for clusters 1 and 2, and met most of the cut-offs when applied to cluster 3. The constructs pro-ecological behavior and altruism also appear to be strong predictors for sustainable travel behavior, with pre-ecological behavior showing the strongest influence in all models.

Table 8.

Goodness of Fit Indices.

	2-Construct Model	Cluster 1: Typical Tourist	Cluster 2:Economical Tourist	Cluster 3: Sustainable Tourist	Acceptable Levels
Df	148	148	148	148
χ²	362.859,p < 0.001	259.776,p < 0.001	204.883,p < 0.001	236.849,p < 0.001
χ²/df	2.452	1.755	1.384	1.600
GFI	0.958	0.937	0.938	0.860	>0.9
AGFI	0.934	0.902	0.903	0.781	>0.9
IFI	0.973	0.965	0.970	0.937	>0.9
CFI	0.973	0.964	0.969	0.937	>0.9
RMSEA	0.043	0.057	0.037	0.070	< 0.08
% of Variance explained (R²)	0.454	0.164	0.345	0.548
SE: A to STB	0.267***	0.118p	0.116	0.281*
SE: PEB to STB	0.473 ***	0.473***	0.528***	0.527***

***

p < 0.001, ** p < 0.01, * p < 0.05.

Note: Df = degree of freedom; GFI = goodness of fit index; AGFI = adjusted goodness of fit index; IFI = incremental fit index; CFI = comparative fit index; RMSEA = root mean square error of approximation; SE = standardized estimates; A = Altruism; PEB = Pro-ecological Behavior; STB = Sustainable Travel Behavior. Cut-off levels used were those recommended by Hooper, Coughlan, and Mullen (2008).

For a breakdown of the results of each hypothesis, see Table 9.

Table 9.

Hypothesis Outcomes.

Hypothesis	Findings	Result
Hypothesis 1: Individuals who demonstrate higher levels of pro-environmental behavior in their everyday behavior will display a more sustainable travel behavior.	Pro-environmental behavior significantly influences sustainable travel behavior, regardless of cluster membership.	Accepted
Hypothesis 1a: This relationship between pro-environmental behavior and sustainable travel behavior will remain constant no matter the cluster membership.		Accepted
Hypothesis 2: Individuals who demonstrate higher levels of frugality in their everyday behavior will display a more sustainable travel behavior.	Frugality was found to not significantly influence sustainable travel behavior.	Rejected
Hypothesis 2a: This relationship between frugality and sustainable travel behavior will remain constant no matter the cluster membership.		Rejected
Hypothesis 3: Individuals who demonstrate higher levels of altruism in their everyday behavior will display a more sustainable holiday behavior.	Altruism significantly influences sustainable travel behavior, regardless of cluster membership.	Accepted
Hypothesis 3a: This relationship between altruism and sustainable travel behavior will remain constant no matter the cluster membership.		Accepted
Hypothesis 4: Consumers can be segmented according to their sustainable travel behavior.	A k-means cluster analysis derived three separate clusters based on tourists’ previous travel behavior and demographics.	Accepted
Hypothesis 4a: Different segments of travel behavior will display varying levels of pro-environmental behavior	Each cluster showed different levels of pro-environmental behavior, frugality, and altruism.	Accepted
Hypothesis 4b: Different segments of travel behavior will display varying levels of frugality.		Accepted
Hypothesis 4c: Different segments of travel behavior will display varying levels of altruism.		Accepted

Discussion

Previous research has outlined five characteristics of sustainable tourism behavior. First, that income and education influence sustainable behavior (Juvan and Dolnicar 2016; Buffa 2015; Ramchurjee and Suresha 2015). This study found sustainable tourists (the most sustainable cluster), to be typically younger, more educated (74% have a university degree or higher), and in a higher earning category (51% earning more than $70,000, compared to 45% and 40% for the other two clusters). Second, previous studies have questioned whether behavior at home influences behavior when traveling or if traveling instead leads to a type of hedonism that becomes prevalent when on holiday (Juvan and Dolnicar 2014; Ramchurjee and Suresha 2015). This study found that altruism and pro-ecological behavior have positive relationships: the more actions residents did at home, the more they would engage when traveling. Third, Pulido-Fernández and López-Sánchez (2016) assumed that sustainable tourists might not always be willing to pay more, as they found in their study of tourists visiting Spain. Our results, focused on Canadian residents, showed that the sustainable tourist cluster were more willing to pay than typical tourists. Fourth, our results show that there are three distinct types of travelers, refuting results by Bergin-Seers and Mair (2009), who claimed it was questionable if there was actually a green traveler.

Beyond being able to understand the tourist through clustering, this study looked to investigate the ability of frugality, pro-ecological behavior, and altruism to be predictors of sustainable travel behavior. While altruism and pro-ecological behavior were found to be predictors of sustainable travel behavior, the strength of their ability to influence such behavior varied between clusters. Those tourists who were more likely to be sustainable travelers (the ST), and those that were also somewhat supportive of sustainable travel (the ET), were more strongly influenced by pro-ecological behavior and altruism than the general tourist (the TT). This supports the idea that the motivations that influence the sustainable traveler are significantly different from those that motivate the general traveler.

Conclusion

Tourism literature has demonstrated that attitudes and behaviors can influence tourism development. Therefore, an understanding of the tourist in their behavior at home, as well as when they travel, may help predict opportunities to capitalize on sustainability marketing to environmental or social sensitive tourists. This study helps to investigate behaviors as well as attitudes that may help to narrow the attitude–behavior gap that is so prevalent in tourism studies.

This article builds on past work in the pro-environmental area and is unique for a number of reasons. First, this study expands on previous studies as questions went further than solely looking at environmental behaviors (pro-ecological) (Bergin-Seers and Mair 2009; Cheng and Wu 2015; D. Miller, Merrilees, and Coghlan 2015) to also include frugality (economic) and social (altruistic) behaviors. Second, this article examines reported behavior rather than behavioral intentions, thereby providing more reliable information. Third, it looked at day-to-day behavior and the relationship to travel behavior that has not been examined before.

There are also three implications from this study. First, this study showcases that there is a population that seeks out sustainable tourism activities and offerings. Second, that by better segmenting market offerings, one can meet not only tourist demands but also protect the tourist destinations they visit. Finally, this study is not just about tourism offerings, it also justifies the need to focus policies and legislation to increase everyday altruistic and pro-ecological behavioral actions. If we can shift everyday behaviors, we will not only improve sustainable travel behavior, we will also improve the environment and societies in which we live.

Limitations

There are a number of limitations to this study. The survey asked respondents if they took a short break, that is, a city break. It is recognized that a short break could also take place in nature or other areas. Future research should be conducted in different regions to determine appropriate fit and whether factor loadings are the same, to help further refine the cluster analysis. Also, future research should look to incorporate propensity to spend and other related constructs to improve the model’s explanatory power. Although this study started with a sample of more than 1,200, after accounting for the “prefer not to respond” categories, the sample size was drastically reduced. Future research should have a complete choice set. Given the different dynamics that must be taken into consideration for culture, language, and research setting, future research should look to expand its focus to non-Westernized cultures and geographies.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Mark Robert Holmes

Author Biographies

Mark Holmes is an Assistant Professor in the School of Hospitality, Food and Tourism Management, in the Gordon S. Lang School of Business and Economics at the University of Guelph. Holmes conducts research in the areas of sustainable tourism, workplaces and foodservice. Linked in Profile:

Rachel Dodds is a Professor at the Ted Rogers School of Hospitality and Tourism Management at Ryerson University in Toronto, Canada. She has worked in sustainability for the past 20 years and is passionate about change. Her research interests lie in sustainable tourism, over tourism, tourism planning and development. Linked In Profile:

Isabelle Frochot is an Associate Professor at Université Savoie Mont Blanc. Isabelle is specialized in the study of experiential consumption in a tourism context. Isabelle has worked on psychographic segmentation studies (benefit segmentation) and service quality evaluation. Recently she has also developed expertise on the understanding of flow and deconnection as key components of the tourist experience along with proenvironmental behaviour. Isabelle has been the course leader since 2000 of a Master in Tourism Management at the University Savoie Mont Blanc.

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