The Efficacy of Sustainability Values in Predicting Travelers’ Choices for Sustainable Hospitality Businesses

Abstract

Sustainability studies suggest that travelers’ decisions to support sustainable production and to consume sustainable hospitality and tourism services are functions of those travelers’ values. This study examined the efficacy of the sustainability value (SV) scale in predicting potential travelers’ choices for sustainable hospitality businesses using a partially mediated structural equation model. Data from a panel of 1,202 recent travelers in North America suggest that SVs predict an individual’s choice for sustainable hospitality businesses. The effect of those values, however, is partially mediated by the travelers’ environmental behaviors. Based on the respondents’ attitudes and behavior, they were grouped into an environment-supporting group called “strong-sustainers” and an environment-neutral group termed “centrists-sustainers.” Extending these findings to the market, hoteliers could offer targeted sustainability messages for the proposed “strong-sustainer” traveler, who would be more likely to purchase a “green” room, and likewise customize communications to the “centrist-sustainer” travelers, for whom an environmental message carries no weight.

Keywords

sustainable tourism sustainability values “green” consumers

The notion of sustainability has gained widespread acceptance in the hospitality industry as part of a strategy to encourage a “green consumer.” Actual findings relating to that theoretical consumer are scarce, and few studies have examined potential travelers’ values as a source of motivation for booking a room in a sustainable hotel or purchasing sustainable services from another hospitality business. Based on the premise that values are antecedents to attitudes and behaviors (Fishbein and Ajzen 1972; Spash 2002), the sustainability value (SV) scale used in this study was developed based on the values described in the Millennium Declaration of the United Nations (UN). This document makes specific references to universal values such as freedom, equality, solidarity, tolerance, respect for nature, and shared responsibility (see Exhibit 1). Similar values are also expressed by The Earth Charter (2000), The World Summit on Sustainable Development (2002), and the Global Scenario group (Raskin et al. 2002). These are declared as the fundamental values of sustainability (Leiserowitz, Kates, and Parris 2006, 418). Despite their importance, little is known about the nature of hospitality consumers’ SVs. Thus, this article aims to understand the role of SVs in predicting potential travelers’ choices for sustainable hospitality businesses. Our study (1) determines the SVs of potential travelers, (2) assesses the extent to which SV scale predicts choices for sustainable hospitality facilities (CSHF), and (3) uses SVs to segment the potential travel market using a factor-cluster segmentation approach.

Exhibit 1:

Definitions of Sustainable Development Values.

Sustainable development values	Definitions
Freedom	Men and women have the right to live their lives and raise their children in dignity, free from hunger and from the fear of violence, oppression, or injustice. Democratic and participatory governance based on the will of the people best assures these rights.
Equality	No individual and no nation must be denied the opportunity to benefit from development. The equal rights and opportunities of women and men must be assured.
Solidarity	Global challenges must be managed in a way that distributes the costs and burdens fairly in accordance with basic principles of equity and social justice. Those who suffer or who benefit least deserve help from those who benefit most.
Tolerance	Human beings must respect one another, in all their diversity of belief, culture, and language. Differences within and between societies should be neither feared nor repressed, but cherished as a prec ious asset of humanity. A culture of peace and dialogue among all civilizations should be actively promoted.
Respect for nature	Prudence must be shown in the management of all living species and natural resources, in accordance with the precepts of sus tainable development. Only in this way can the immeasurable riches provided to us by nature be preserved and passed on to our descendants. The current unsustainable patterns of production and consumption must be changed in the interest of our future welfare and that of our descendants.
Shared responsibility	Responsibility for managing worldwide economic and social development, as well as threats to international peace and security, must be shared among the nations of the world and should be exercised mul tilaterally. As the most universal and most representative organization in the world, the United Nations must play the central role.

Source: D.A. Shepherd, Valya Kuskova, and Holger Patzelt, “Measuring the values that underline sustainable development: The development of a valid scale.” Journal of Economic Psychology 30, no. 2 (2009):

Source. Shepherd, Kuskova, and Patzelt (2009).

Literature Review and Hypotheses Development

Values play a significant role in explaining specific beliefs and behavior and can be used as predictors for other outcome variables, notably, attitudes or behavioral intentions (Stern 2000; Stern and Dietz 1994). An analysis of countless supplementary definitions finds that value systems generally include the following five common features: (1) concepts or beliefs, (2) about desirable end states or behaviors, (3) that transcend specific situations, (4) guide selection or evaluation of behavior and events, and (5) are ordered by relative importance (Allport 1966; Maslow 1959; Rokeach 1973; Schwartz 1992; Schwartz and Bardi 2001). As one example, Schwartz’s (1992) value theory identifies the following ten broad values according to the motivation that underlies each of them: achievement, benevolence, conformity, hedonism, power, security, self-direction, stimulation, tradition, and universalism. We apply these values as part of our hypothesis development, as explained below.

The total number of values people consider in connection with a decision is relatively small, and thus a study of values is an economically efficient approach for describing and explaining similarities and differences in people’s actions (Rokeach 1973). In this regard, Schwartz (2006) proposed a cultural-values theory out of the need to account for individual differences in value priorities and their effects on attitudes and behavior across cultures. Schwartz derived value dimensions for comparing cultures by considering three critical issues that confront all societies: (1) to what extent a person is embedded into a group, (2) how to preserve the social fabric, and (3) how to relate to the natural and social world. The theory postulates three bipolar dimensions that represent alternative resolutions to each of the three problems: embeddedness versus autonomy, hierarchy versus egalitarianism, and mastery versus harmony. In summary, values are cognitive demonstrations of the important human goals or motivations with which people must transfer to coordinate their behavior (Bilsky and Schwartz 1994) and also underlie value orientations (patterns of basic beliefs), which influence attitudes and behavioral intentions and behaviors (Vaske and Donnelly 1999).

Studies of the relationship between values and tourist behavior in the hospitality and tourism literature have been scarce. Pizam and Calantone (1987) provided the seminal work relating tourist behavior to personal values. A few authors have followed using varying value scales, for example, Rokeach Value Survey (Rokeach 1973), List of Values (Kahle 1983), and Values and Lifestyles (Mitchell 1983). Dalen (1989) looked at value orientations on the cultural level by segmenting the Norwegian population according to personal values: traditional idealists, modern idealists, traditional materialists, and modern materialists. Dalen suggested that this typology could be applied to the field of tourism and could account for different types of tourist behavior. A subsequent study that empirically applied the typology to Norwegian tourists concluded personal values provide powerful explanations of tourism behavior (Mehmetoglu et al. 2010).

During the turn of the new millennium, the UN (2000, 2) declared that a set of “certain fundamental values are essential to international relations of the century.” Values in sustainable development have also been articulated by various governmental agencies, nongovernmental organizations, and environmental groups, although the Millennium Declaration of the UN was the only one to put forth a specific set of declared values. Shepherd, Kuskova, and Patzelt (2009, 254) provided a stepping stone for future research in this area by creating a scale with which to measure SVs, but even then they argue that there is “need for multiple scales to measure the values that underlie sustainable development.” The values they specified are freedom, equality, solidarity, tolerance, respect for nature, and shared responsibility. Thus, we offer the following hypothesis to be tested.

Hypothesis 1a (H1a): SVs predict choices of potential travelers for sustainable hospitality businesses.

Environmental Values and Behaviors

Research has shown a link between individuals’ values and their expressed environmental concern and behaviors (De Groot and Steg 2006; Stern et al. 1995). While varying theoretical contexts have been used, most research has focused on Schwartz’s self-transcendence (combination of universalism and benevolence) and self-enhancement values (combination of power and achievement; Nordlund and Garvill 2002; Schultz and Zelezny 1999; Stern et al. 1999). Karp (1996) suggested that values of self-transcendence were positively correlated with self-reported environmental behavior (EvB), whereas self-enhancement values were negatively correlated with environmental attitudes and self-reported behavior. While the direct relationship between values and EvB is weak, a norm-activation model using Schwartz’s universalism (altruism) has provided an explanation for actions in the bulk of the literature. Many studies have applied that model to EvB (e.g., Dunlap and Van Liere 1978; Guagnano, Stern, and Dietz 1995; Hopper and Nielsen 1991; Stern, Dietz, and Black 1986). Research has also concluded that values play a role in specific situations when they are activated by a set of altruistic concerns, and these value types have a positive relationship with proenvironmental attitudes and behavior (Hansla et al. 2008; Schwartz and Rubel-Lifschitz 2009). This approach comprises values such as equality, social justice, and peace on earth, and is based on feelings of moral obligation, personal norms, and the ascription of personal responsibility for carrying out the altruistic behavior (Corraliza and Berenguer 2000; Hedlund 2011). In that context, Nielson and Ellington (1983), Hopper and Nielsen (1991), and Vining and Ebreo (1992) found that support of recycling could be predicted by Schwartz’s altruism model. However, Guagnano, Stern, and Dietz (1995) did not find that Schwartz’s model was always predictive of EvB intentions. They contend that Schwartz’s model interacts with external conditions, and that the attitude–behavior relationship is a curvilinear function resulting from the interaction of personal variables and external conditions. In this scenario, when external surroundings impede behavior, the altruistic values are not valid in the prediction of a behavior. Social norms are one such external influence on attitudes and behavioral intentions. As defined in the theory of reasoned action (Fishbein and Ajzen 1972) and the theory of planned behavior (Ajzen and Driver 1991), social norms are those put forth by one’s significant others and backed by their approval or disapproval of one’s actions. A person sometimes must weigh these social norms against the desire to fulfill self-interest (see Ajzen and Driver 1991; Bryan, Fisher, and Fisher 2002; Kaiser and Gutscher 2006). Extending this contradiction, Stern and Dietz (1994) and Stern (2000) broadened the model to include environmental attitudes and behavior. They contend that three different value orientations may affect beliefs related to EvB: an egoistic orientation (the person himself or herself), a social-altruistic orientation (people in general), and a biospheric value orientation. Several other studies have found that proenvironmental beliefs, intentions, and behavior appear to be positively related to altruistic or biospheric values and negatively to egoistic values (Stern, Dietz, and Guagnano 1998; Van Vugt, Meertens, and Van Lange 1995).

Schultz (2001) used confirmatory factor analytic procedures and found strong evidence for the distinction between egoistic, biospheric, and altruistic concerns. This basic three-factor structure supports the notion that values underlie environmental concerns and an environmental worldview. Results have also shown that egoistic and biospheric environmental concerns are significantly correlated with Schwartz’s values scale. Self-transcendent values and altruistic concerns have also been found to have a positive correlation, whereas self-enhancement has been correlated negatively with biospheric and altruistic concerns. Schwartz, Sagiv, and Boehnke (2000) found self-transcendent values (particularly universalism) correlated positively with macro-level environmental worries.

Due to parsimony, most studies of individual environmental values use surveys rather than direct observations of environmentally consequential behavior. Values are most commonly related to either (1) self-reported behaviors (e.g., “Do you usually recycle newspapers?”), (2) behavioral intentions (e.g., “Would you be willing to sign a petition in favor of stricter environmental protection?”), or (3) other measures that express concern for the environment. Thus, an important limitation of the literature we have just discussed is that few studies examine actual behavior. It is well established that the link between self-reported behavior or behavioral intentions and actual behavior is far from perfect. Another limitation is that the relationship between values and behavior can be dependent on the type of value(s) being examined. A growing and important area of research examines the relationship of values to stated willingness to pay or otherwise make sacrifices to protect the environment (e.g., “How much would you be willing to pay to protect watershed X from development?”). Finally, many studies simply link values to expressions of proenvironmental attitudes. Although it has been suggested that consumers’ attitudes toward environmentally responsible practices are critically important in service industries (Choi et al. 2009; Hsieh 2012), little research has been done in this area. To address this gap, we offer the following hypotheses.

Hypothesis 1b (H1b): EvBs (recycling and environmentally active behavior) affect choices of potential travelers for a sustainable hospitality business.

Hypothesis 2 (H2): SVs predict choices of potential travelers for sustainable hospitality businesses indirectly via EvB. Hence, the choice of a sustainable hospitality business is partially mediated by EvB of travelers.

Method

Data Collection and Measures

We studied a panel of 1,202 recent North American travelers randomly drawn from a purchased list of Wilkins Research Service, an online research company. We asked them to complete a fifteen-minute web-based survey. Respondents had to have taken a round-trip of 200 miles lasting at least twenty-four hours outside their home region in the prior twelve months. Quota targets were placed on a best-efforts basis to ensure proportionate representation for age, gender, ethnicity, income, region, and education. The data show that the samples were a close approximation of the general traveling population with the exception of race (see Exhibit 2). This issue is typical of panel studies and is thus a drawback of using panel data.

Exhibit 2:

Sample Profile: Descriptive Statistics.

Characteristics	Canada/USA
Sample size (N)	1,202
Female (%)	50.5%
Income distribution
Below $19,999	8.38%
$20,000-$49,999	32.63%
$50,000-$79,999	25.75%
$80,000-$99,999	11.28%
$100,000 and above	15.77%
Refused	6.19%
Age distribution
18-24	7.88%
25-34	18.36%
35-44	18.26%
45-54	27.45%
55-64	18.86%
65 years of age or older	0.18%
Ethnic composition of the sample
White	84.03%
African American	3.49%
Hispanic	2.99%
Some other ethnic background	8.48%
Prefer not to answer	1.00%

The data were analyzed using SPSS and AMOS (statistical software packages). First, the factors related to preference for a sustainable hospitality business, universal SVs, and EvBs were obtained using exploratory factor analysis (EFA), which produced six conceptually meaningful SV dimensions, as originally conceptualized by Shepherd, Kuskova, and Patzelt (2009). CSHF was conceptualized as a unidimensional construct consisting of five items: (1) Choosing a hospitality facility that participates in environmental partnerships or certification programs; (2) choosing accommodations that actively recycle materials; (3) looking for environment-friendly service provider signs before making reservations; (4) choosing accommodations that actively promote green practices; and (5) eating in restaurants that provide environment-friendly products. EvB of the potential guests was identified using two general domains, Environmentally Active Behavior, which included “I talk with friends about problems of the environment” and “I read about environmental issues,” and Recycling Behavior, comprising “I look for ways to reuse things” and “I encourage friends and family to recycle” (see Exhibit 3).

Exhibit 3:

Measurement Properties: Standardized Regression Weights (Loadings).

Scale/Item	Path	Domains	Standardized Regression Weights
EvB: Environmental Behavior	<—	SV: Sustainability Values (α = .92)^a	.421
CSHF	<—	SV: Sustainability Values	.213
Freedom	<—	SV: Sustainability Values	.581
Solidarity	<—	SV: Sustainability Values	.922
Shared Responsibility	<—	SV: Sustainability Values	.883
Respect for Nature	<—	SV: Sustainability Values	.816
Equality	<—	SV: Sustainability Values	.846
Tolerance	<—	SV: Sustainability Values	.833
CSHF	<—	EvB: Environmental Behavior (α = .96)^a	.548
Recycling Behavior (RecycleBehv)	<—	EvB: Environmental Behavior	.876
Environmental Active Behavior (EnvActivism)	<—	EvB: Environmental Behavior	1.032
People need only make minor changes to their current consumption out of respect for nature	<—	Respect for Nature3	.846
Current patterns of production only require minor adjustments to protect the welfare of the natural environment	<—	Respect for Nature2	.843
Sometimes some natural resources need to be sacrificed for important developments	<—	Respect for Nature1	.767
To a certain extent, the natural environment will look after itself to the benefit of future generations	<—	Respect for Nature4	.785
Choose accommodations that actively promote green practices to their guests, shareholders, vendors, and to the public	<—	CSHF (SusChoiceHos; α = .93)^a	.816
Choose tourism/hotel facilities that participate in environmental partnerships or certification programs such as ISO 9000	<—	CSHF (SusChoiceHos)	.883
Choose accommodations that actively recycle materials	<—	CSHF (SusChoiceHos)	.861
Eat in restaurants that provide environment-friendly products/facilities (i.e., low toxicity, organic foods, or locally produced goods)	<—	CSHF (SusChoiceHos)	.808
Look for environment-friendly service provider signs before making reservations	<—	CSHF (SusChoiceHos)	.882
The nations that foster economic development the most deserve greater access to its benefits	<—	Equality2	.826
People who contributed the most to economic development deserve greater access to its benefits	<—	Equality1	.701
Those citizens most responsible for economic prosperity should receive more of the resulting benefits	<—	Equality3	.892
I talk with friends about problems of the environment	<—	Environmental Active behavior9	.845
I have pointed out unecological behavior to someone	<—	Environmental Active behavior5	.782
I buy products in refillable packages	<—	Environmental Active behavior6	.740
I read about environmental issues	<—	Environmental Active behavior8	.823
I encourage friends and family to recycle	<—	Recycling Behavior12	.901
I look for ways to reuse things	<—	Recycling Behavior11	.711
In some instances, parents must expect that they and their children will experience feelings of hunger	<—	Freedom1	.527
Sometimes, the threat of violence is necessary to achieve social good	<—	Freedom2	.687
In some instances, people deserve lower levels of justice	<—	Freedom3	.518
(continued)
If we earn our benefits, then it is not necessary to give others some of our gains	<—	Solidarity1	.809
Just because one faces few burdens from global change does not mean that they must give assistance to those who are more burdened	<—	Solidarity2	.805
We must first address the suffering of our own before helping others with their suffering	<—	Solidarity3	.734
We are responsible when members of our immediate society do not tolerate cultural differences but are not responsible for the behavior of members of distant societies	<—	Shared Responsibility3	.711
A civilized nation must accept responsibility for improving the welfare of its less fortunate citizens but is not responsible for the welfare of another nation’s citizens	<—	Shared Responsibility2	.848
We are responsible for assuring that people within our society have their rights for freedom maintained but we are not responsible for these rights for people in other societies	<—	Shared Responsibility1	.764
Each civilized nation should focus on ending injustices in its own borders and not influence other nations in their efforts	<—	Shared Responsibility4	.770
Peace within societies invariably begins with promoting the society’s traditional way of life	<—	Tolerance2	.765
There are some people’s beliefs that do not deserve respect	<—	Tolerance1	.678
In some cases, it becomes necessary to repress differences across societies	<—	Tolerance3	.655

Note. All factor loadings are significant at the p < .001 level. CSHF = choice of sustainable hospitality facility; EvB = environmental behavior; SV = sustainability values.

Cronbach’s alpha reliabilities are provided.

The analysis of the measurement model indicated the presence of two second-order factors: SVs and EvB (see also in Exhibit 3). To establish internal consistency and validity of the constructs, we obtained composite reliabilities and validity measures during the development of the measurement model and used fit indices and modification matrices to improve the fit of the model. Convergent and discriminant validity of the factors was examined and a structural model depicting partial mediation was tested to examine the relationship between SVs, EvB, and choice for a sustainable hospitality business (CSHF).

We next applied K-means cluster analysis by calculating factor scores for each major construct using an imputation method. These scores were used to group the respondents, allowing us to compare the clusters on each of the SVs using the simultaneous method of multiple discriminant analysis (MDA). The dependent variable was the cluster membership and the independent variables were factor scores on six domains making up the SVs. To validate our cluster solutions, we performed significance tests that compared clusters on the theoretically relevant criterion of the respondents’ environment-friendly behaviors. Moreover, a classification matrix was constructed to validate the results of the clusters. To determine whether statistically significant differences existed between the clusters, chi-square tests and multivariate analysis of variance (MANOVA) were used where appropriate.

Findings

Validity and Reliability of the Measures

Because the SV scale is relatively new, we could find scant evidence about its validity and reliability beyond the original study by Shepherd, Kuskova, and Patzelt (2009). Our analysis supported the reliability and validity of the three scales comprising this tool. A confirmatory factor analysis using the maximum likelihood estimator of AMOS 20 and the covariance matrix as the input was used to test the measure’s convergent and discriminant validity (see Exhibit 4). The model’s three domains, CSHF, EvB, and SVs, have high reliability coefficients and display excellent convergent and discriminant properties (average variance extracted [AVE] for EvB, .92; CSHF, .72; and SV, .67). The three scales’ measurement properties indicate the factor loadings are high and statistically significant (p < .05), satisfying the criteria for convergent validity. In addition, the Cronbach’s alpha reliabilities of the measurement scales (α_EvB = .96, α_CSHF = .93, α_SV = .92) exceed Nunnally and Bernstein’s (1994) recommendation.

Exhibit 4:

Reliability and Validity Analysis.

	CR	AVE	MSV	ASV	EvB	CSHF	SV
EvB	.96	.92	.41	.29	.96
CSHF	.93	.72	.41	.30	.64	.85
SV	.92	.67	.20	.19	.42	.44	.82

Note. According to Hair et al. (2010), the thresholds for these values are as follows: Reliabilities (CR) must be above .7 (CR > .7), for convergent validity CR > AVE and AVE > 0.5; for discriminant validity, MSV < AVE and ASV < AVE (see Hair et al. 2010). CR = composite reliability; AVE = average variance extracted; MSV = maximum shared squared variance; ASV = average shared squared variance; EvB = environmental behavior; CSHF = choice of sustainable hospitality facility; SV = sustainability values.

The structural model’s overall fit was determined initially by examining the χ² statistic (χ²_(416df) = 1,482), which together with the associated probability value were statistically significant (p < .001). This finding suggests the potential for an inadequate fit; however, the sample size and model complexity can influence the χ² statistic, and rejecting a model based only on this result is insufficient (Jöreskog and Sörbom 1996). Thus, we extended our analysis to include root mean square error of approximation (RMSEA), goodness of fit index (GFI), adjusted goodness of fit index (AGFI), normed fit index (NFI), and critical fit index (CFI), per Hu and Bentler (1999).Exhibit 5 shows the structural equation model results and the fit indices.

Exhibit 5:

Results of Structural Equations Analysis.

Hypothesis Number	Relationship	Standardized Path Coefficient
H1a	SV → CSHF	0.21***
H1b	EvB → CSHF	0.55***
H2	SV → EvB	0.42***
Model fit statistics
χ²		1,482.09
df		416
RMSEA		0.05
GFI		0.92
AGFI		0.91
NFI		0.94
CFI		0.95
Variance explained (R²)
EvB		18%
CSHF		44%

Note. H1 = Hypothesis 1; H2 = Hypothesis 2; SV = sustainability values; CSHF = choice of sustainable hospitality facility; EvB = environmental behavior; df = degrees of freedom; RMSEA = root mean square error of approximation; GFI = goodness of fit index; AGFI = adjusted goodness of fit index; NFI = normed fit index; CFI = critical fit index.

***

p < .001.

As shown, the results support the measure’s validity and the proposed partial mediation model. The RMSEA (0.05) is less than .08, and the other GFI indices (GFI = 0.92, NFI = 0.94, CFI = 0.95) suggest the overall model’s predictive ability is good. The second-order factor, SV scale, explains 44 percent of the variance in CSHF and 18 percent of the variance in EvB.

Hypothesis Testing

We have tested the relationships between the constructs in a partially mediated model. SVs are measured by six values, which we found are positively related to the CSHF, as measured by items extracted from the Sustainable Tourism Attitudes Scale (SUSTAS) developed by Sirakaya, Ekinci, and Kaya (2008). Environmental values are measured by two factors that mediate the relationship between SV and CSHF. H1a, which proposes that SV should have a positive relationship with CSHF, was supported (SV = 0.21, p < .001). The results also support H1b (EvB = 0.55, p < .001), suggesting that EvB is positively related to CSHF. Both findings indicate that the two constructs strongly influence CSHF. H1b and H2 suggest that EvB mediates SV’s effect on CSHF. H2 posits that SV is positively associated with EvB. Hence, the study supports H2 (EvB = 0.42, p < .001). Exhibit 5 illustrates the results of the structural equation analysis for a partial mediation model.

According to a close examination of standardized direct effects (see Exhibit 5) and partial effects (not shown), the standardized total (direct and indirect) effect of SV on EvB is .42, meaning that when SVs go up by 1 standard deviation, EvB goes up by 0.42 standard deviations. The standardized total effect of SV on EnvActivism (one of the two first-order factors of EvB) is .434. That is, due to direct (unmediated) and indirect (mediated) effects of SVs on environmentally active behavior, when SV goes up by 1 standard deviation, environmentally active behavior goes up by 0.43 standard deviations. The standardized total effect of SV on recycling behavior is .369. That is, when SVs go up by 1 standard deviation, recycling behavior goes up by 0.369 standard deviations.

The standardized total (direct and indirect) effect of SV on CSHF is .44. That is, due to direct and indirect effects of SV on CSHF, when SV goes up by 1 standard deviation, CSHF goes up by 0.44 standard deviations. The standardized direct effect of SV on CSHF, however, is .21. That is, due to the direct effect of SV on CSHF, when SV goes up by 1 standard deviation, CSHF goes up by 0.21 standard deviations. The standardized indirect effect of SV on CSHF, mediated by EvB, is .23. That is, due to the indirect effect of SV on CSHF, when SV goes up by 1 standard deviation, CSHF goes up by 0.23 standard deviations. The standardized total effect of EvB on CSHF is .548. That is, due to direct and indirect effects of EvB on CSHF, when EvB goes up by 1 standard deviation, CSHF goes up by 0.548 standard deviations (see Exhibit 6).

Identification of Cluster Groups Using SVs

One of the purposes of this study was also to identify relatively homogeneous traveler categories using SVs as segmentation variables. After validating clusters using a holdout sample, our examination of group membership and a dendrogram suggested two meaningful clusters. To determine the importance of each of the six-value factors, we calculated their means in two clusters (see Exhibit 7). The results of the means difference test indicated that all six factors for the two groups were significantly different from each other statistically. The first group placed greater emphasis on all factors compared with the second group. Cluster-1 placed greater value on equality (M = 4.51), solidarity (M = 3.92), tolerance (M = 4.29), freedom (M = 3.10), shared responsibility (M = 3.51), and respect for nature (M = 4.30) than Cluster-2 did. Based on the value attached to these SVs by each cluster, we labeled Cluster-1 (46.7% of the sample) as strong-sustainers and Cluster-2, comprising the remainder of the sample, as centrists-soft-sustainers.

Exhibit 7:

Mean Comparisons of Sustainability Value Domains by Clusters.

Sustainability Value Domains	Cluster 1: Strong-Sustainers (n = 561)	Cluster 2: Centrists-Soft-Sustainers (n = 641)	F Ratio	Significance Level
Freedom (three items)	3.10	2.51	683.0	.001*
Shared responsibility (four items)	3.51	2.37	1,607.6	.001*
Respect for nature (four items)	4.30	3.10	1,265.5	.001*
Equality (three items)	4.51	3.01	1,654.7	.001*
Tolerance (three items)	4.29	3.14	1,563.2	.001*
Solidarity (three items)	3.92	2.63	1,803.9	.001*

Note. Total valid N = 1,202.

Significant at .001 alpha level.

MDA indicated one significant canonical discriminant function (χ² = 1,319.47, p < .001). Both the Wilks’s lambda test and univariate F test enabled us to determine the significance of each of the six SVs’ interpretability of the function. Absolute magnitudes revealed that all six-value factors made a statistically significant contribution to the discriminant function with equality (.327) and shared responsibility (.258) emerging as the most important factors. Statistically significant canonical correlation was moderately high at .82 (p < .001), indicating that the model explained a significant relationship between the functions and the dependent variable. (The square of a canonical correlation indicates the percentage of variance explained by the function, just like the multiple R² does in a regression model.)

The classification matrix of respondents suggests that the attitudinal discriminant functions appear to have done a superb job in classifying strong-sustainers and centrists-soft-sustainers, providing strong evidence for the reliability of this cluster solution. The resulting classifications had a high accuracy rate, with 97.7 percent of strong-sustainers and 99.8 percent of centrists-soft-sustainers correctly classified. These classification rates represented an average of 51.9-percent improvement over a chance determination for Cluster-1 and 46.8-percent improvement for Cluster-2.

Profile of Clusters

Cross-tabulation analysis allowed us to identify a demographic profile of each cluster. Although chi-square analysis revealed that the two clusters were not statistically different from each other based on education level, age groups, or income, we found statistically significant differences between the two clusters based on several EvB variables. This included behaviors such as “I talk with friends about problems of the environment.” In addition to that behavior, Cluster-1 members are more likely to be activists than those in Cluster-2 by pointing out unsustainable behavior to someone, reading about environmental issues, or looking for ways to reuse things. Cluster-1 also seemed to be more concerned about global warming than Cluster-2.

In addition, hard-core strong-sustainers seemed to be more likely to encourage their friends and family to recycle, be concerned about global warming, buy products in refillable packages, and conserve gasoline by walking or bicycling. Consistent with Hsieh’s (2012) observations, these findings suggest that there is a segment of the market that places higher value on SVs and EvBs, as described by the scale items.

Hard-core sustainers are more likely to choose and prefer hospitality companies that employ green and sustainable practices, a finding consistent with that of Hsieh (2012), who cited a survey report by Deloitte’s tourism, hospitality, and leisure research group in 2007 that found 38 percent of business travelers tried to determine whether a hotel was “green” before making their purchase decision. Cluster-1 members are also more likely to look for green certification before making any reservation. One other idiosyncratic difference between the two groups was that Cluster-2 was less interested overall in recreational or touring activities when they travel.

Discussion and Implications

Knowledge about a discrete group of travelers who are supportive of industry sustainability efforts can be valuable to marketers. According to Madrigal and Kahle (1994, 22), values are antecedents to behavior and are important for marketers because of their efficacy in predicting behavior. Researchers can use value constructs in segmenting potential markets for new product and service development and advertising strategies. The SV scale comprised three domains, CSHF, EvB, and SV, all of which demonstrated high reliability (α_EvB = .96, α_CSHF = .93, α_SV = .92) and displayed excellent convergent and discriminant properties (AVE for EvB, .92; CSHF, .72; and SV, .67). These statistics confirm the utility of the SV scale, which is in itself a theoretical contribution to the literature in this area. In a partial mediation model, using structural equation modeling (SEM), our study determined that SVs of potential travelers determine the CSHF directly and also indirectly through their effect on shaping EvB. These factors can be used to segment the potential travel market.

As predicted in our H1a, SVs had a positive relationship with CSHF, and EvB is positively related to CSHF. As respondents’ SVs increase, the probability of their choosing a sustainable business increases. Hence, these values could be used in a cluster analysis that could potentially identify homogeneous groups of people who prefer to stay in sustainable hotels and eat in sustainable restaurants.

Our cluster analysis revealed two meaningful groups that attach substantially different importance to the six SVs that we tested. The group we call “strong-sustainers” placed greater emphasis on all six factors compared with the “centrists-soft-sustainers.” Hospitality companies need to use different positioning strategies with regard to sustainability for these two groups, and develop different brand identities and promotional approaches for the two.

One noticeable difference between the two groups was their diverse affinity for tours or activities, particularly relating to the outdoors. Cluster-2, the centrists-soft-sustainers, was not so interested in outside activities. However, when addressing strong-sustainers (Cluster-1), marketers may want to focus their attention on tours that are designed with sustainability in mind, although they are traditional tourism activities. We suggest this in part because members of this cluster like to talk to people about sustainability and encourage others to become more sustainable. Resorts can offer packages that would focus on travelers’ values and propensity to want to participate in several sustainable activities while they travel (e.g., “eco tours” that explore the environmental conditions of an area).

A major challenge will be to design integrated marketing communication (IMC) for these two segments without alienating or confusing either one. This requires choosing highly selective media for both segments. So, for example, we found that recycling is a significant predictor for sustainable hospitality choice. Hospitality companies should emphasize this in their internal (e.g., with posters in the lobby or elevator) and external communications when targeting environmentally concerned segments. Finding those interested in recycling may even be a way to identify potential target markets and the appropriate media to reach them.

With regard to food service, hotels typically use a co-branding strategy for their restaurant operations, in which nationally known brands run their food and beverage operations. Hotels with such an arrangement may need to work with their partners to ensure that they use sustainable practices or select such operations when appealing to environmentally sensitive market. As for a unified marketing effort, marketers need to provide enough information to attract the hard-core sustainers without offending the soft-core sustainers. This could include links to more information, perhaps on a website dedicated to the hotel’s and restaurant’s sustainability commitment. These strategies would support the organization’s efforts to develop deeper relationships with those who are interested in environmental issues.

Our findings raise an interesting question based on the differing environmentally sensitivities of these two groups: Do lodging properties need to offer “green” and conventional rooms to appeal to environmentally sensitive and insensitive markets (similar to smoking and nonsmoking rooms)? If environmentally sustainable features installed by a hotel (e.g., occupancy sensors, low-flow shower heads, and shampoo dispensers) influence guests’ comfort and experience, this might be a viable option.

More critically, another important question relates to pricing: Should the green and nongreen rooms be priced differently? The literature provides mixed evidence for pricing of green rooms (more, less, or the same). Our study seems to make it clear that a substantial group of travelers has no interest in paying for sustainability. The findings of our study also imply that the hotels should provide recycling bins in public areas, in the rooms, and in the back of the house to tangibilize efforts for sustainability and to encourage guests and staff to recycle. Another option would be that a hotel’s recycling sits in the back of the house, but the hotel clearly communicates its procedures to the guests. Hotels can also offer recycled bathroom paper products in the rooms and food and beverage operations. Restaurants would adopt and promote a food waste recycling or composting program. The study also provided some evidence that certain travelers look for green certification, supporting the findings of Millar and Baloglu (2011). In particular, hospitality operations need to have green certification to target hard-core sustainers.

In conclusion, our data indicated that almost half of the market does value sustainability. One of the implications of this finding is that leadership in this area would open up new opportunities and markets for the hospitality industry.

Future research can examine whether the model would behave differently for hotels and restaurants specifically, as our study focused on hospitality businesses in general. The model can also be replicated for different cultural and international markets. Comparison of the model with different nationals and subcultures might be a fruitful research area.

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) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research received funding support from the Caesars Foundation.

Author Biographies

Ercan Sirakaya-Turk is the associate dean for Research, Grants and Graduate Programs at the University of South Carolina (ercan@hrsm.sc.edu). He currently conducts studies related to sustainable tourism and destination branding while teaching advanced research methods and tourism classes.

Seyhmus Baloglu is a professor, assistant dean of research and international programs, and Harrah Distinguished Chair in the William F. Harrah College of Hotel Administration at UNLV (seyhmus.baloglu@unlv.edu). His teaching areas include marketing, international tourism, research methods, and multivariate statistics. His research interests revolve around branding and image development, data mining, customer loyalty, and sustainability in the lodging industry.

Haylee Uecker Mercado is an assistant professor in the Sport and Entertainment Management Department at the University of South Carolina (MERCADOH@mailbox.sc.edu). Her research activities lie in the areas of facility sustainability (design, green practices, and corporate social responsibility) and on marketing of sport to the various Hispanic subcultures.

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