Relationships among Hedonic and Utilitarian Factors and Exogenous and Endogenous Influences of Consumer Behavior in Tourism

Customer experience is gaining more and more attention from researchers. Particularly in tourism, this experiences may be determined by hedonic or utilitarian factors. However, there are other influences, both exogenous and endogenous, that may impact consumer behaviors in tourism. Thus, in this article, we explore the receptivity of consumers in terms of certain types of influences, exogenous and endogenous, to hedonic and utilitarian factors related to a tourism package. To examine these research questions, we employ exploratory factor analysis, confirmatory factor analysis, and structural equation modelling on a sample of 150 tourists from Europe and North America.
JEL ClassificationM31, M10

This work was supported by the strategic grant POSDRU/159/1.5/S/133255, Project ID 133255 (2014), cofinanced by the European Social Fund within the Sectorial Operational Program Human Resources Development 2007-2013.

Full Article

1. Introduction

Researchers have long focused on the aspects that determine certain decisions from consumers, in certain environments, and with certain motivators that are emphasized in the marketing messages. To fully understand consumers’ pattern of choice, it is important to explore different explanations for consumer behavior meant to offer a better understanding of the interplay between a consumer’s functional goals and experiential preferences within the decision context.

Consumption with a hedonic dimension is oriented towards a consumer’s pleasure that is motivated by fun and fantasy. Otherwise, a consumption with an utilitarian dimension implies achieving certain goals, fulfilling certain needs, or accomplishing functional tasks (Hirschman and Holbrook, 1982). Hedonic value is more subjective and personal than its utilitarian counterpart because it stems from a need for fun and playfulness rather than from a need to engage in task completion (Ryu et al., 2010). Consumer researchers have increasingly begun to investigate consumer choice based on distinctions that involve the purchase and consumption of goods for pleasure versus for more utilitarian and instrumental purposes (Vinerean, 2013).

In this study, we explore the receptivity of consumers in terms of certain types of influences, exogenous and endogenous, to hedonic and utilitarian factors related to a tourism package. More specifically, these influences may further determine certain utilitarian factors (i.e., achieving some functional and practical benefits) or hedonic factors (i.e., experiential benefits involving emotional responses or fantasies) related to a tourism package. We will examine the relationships between these elements by modeling the structural equations related to them, and the corresponding stages of establishing the accuracy of the sample, through exploratory factor analysis and confirmatory factor analysis.

2. Literature Review

2.1.Utilitarian and Hedonic Factors

Consumer value classifications are represented as the dichotomization of utilitarian and hedonic values (Babin et al., 1994; Bridges and Florsheim, 2008). More specifically, to illustrate this dichotomization, Hirschman and Holbrook (1982) described consumers as either “problem solvers” or in terms of consumers seeking “fun, fantasy, arousal, sensory stimulation, and enjoyment.”

Utilitarian value has dominated much of the research conducted in the area of consumer behavior (Bloch and Bruce 1984). Utilitarian consumer behavior has been described as task-oriented and rational (Batra and Ahtola 1990) in that customers’ functional utility is dependent on whether their consumption needs, which inspire the shopping trip, were met successfully (Babin et al. 1994). With regard to utilitarian motivations, Babin et al. (1994) note that people are concerned with efficiency and achieving a specific end when they shop. By focusing on utilitarian motivators or factors, consumers will emphasize the objective, tangible, attributes of products, such as: price, infrastructure, accommodation of the tourism outlet.

Although consumption activities are influences by both utilitarian and hedonic factors (Babin et al., 1994), Holbrook and Hirschman (1982) noted that conventional research up until the early 1980s had given less importance to the hedonic component of the consumption experience. Babin et al. (1994) introduced two types of shopping values by developing a scale measuring both hedonic and utilitarian values obtained from the pervasive consumption experience of shopping. Their research showed that there are various dimensions of hedonic and utilitarian for shopping value and that they are connected to a number of important consumption variables (Ryu et al., 2010).

Babin et al. (1994) developed a value scale that assessed consumers’ evaluations of a shopping experience along the dimensions of:

– utilitarian value: instrumental, task-related, rational, functional, cognitive, and a means to an end;

– hedonic value: reflecting the entertainment and emotional worth of shopping; non-instrumental, experiential, and affective.

According to Arnold and Reynolds (2003), there are six dimensions of hedonic buying:

· Adventure – shopping for stimulation, adventure, and the feeling of being in another world;

· Social – socializing with friends and family;

· Gratification – stress relief, alleviating negative mood, treating oneself;

· Idea – keeping up with trends, seeing new products and innovations;

· Role – enjoyment derived from shopping for others;

· Value – seeking sales, discounts, bargains.

Hedonic approaches to the design and promotion of tourism products are necessary because consumers can generally obtain the core benefits of the products from different organizations.

Hedonic consumption implies the multisensory, fantasy, and emotional aspects of consumers’ interactions with products. Moreover, hedonic motivators are subjective and experiential, as consumers may rely on a product to meet their needs for excitement, self-confidence, or fantasy.

2.2. Endogenous and Exogenous Influences of Consumer Behavior

For this research, we will study how endogenous and exogenous influences may have an impact on consumer behavior in tourism. Consumers are generally influenced by other people around them, their past experience, or by marketing information they may encounter in mass media and internet. In both sources of information and influence of tourism package, the credibility of the source is a vital element in persuasiveness that is more than often based on the source’s perceived intentions, and we will address these aspects.

In terms of endogenous influences, we will explore past personal experiences with a particular tourism package, input from friends and family.

Consumers tend to hold certain brand or company attitudes because of a brand’s or company’s utility. When a product has been useful or been helpful in the past, their attitude toward it tends to be favorable. Therefore, consumers may use past personal experiences as a baseline or indicators when considering a certain hotel chain or tourism agency, both in terms of hedonic aspects (entertainment, customer care, etc.) and in terms of utilitarian aspects (price, facilities, etc.).

The consumer’s previous experience with the product or a tourism organization has a major impact on the credibility of the marketing message that might further impact the subsequent behavior or attitude of consumers. Fulfilled product-related experiences tend to increase the impact of credibility of future marketing messages, whereas unfulfilled product claims or disappointing experiences tend to reduce the credibility (Schiffman and Kanuk, p.285).

Peer and reference groups fall into many groupings. For example, there are primary groups, which are composed of those people a particular consumer sees most often: friends, family, close colleagues, and there are secondary groups, which consist of people the consumer may encounter occasionally (Blythe, 1997, p.99). The credibility of the peer and reference groups is high because the consumer already has contact and trust for the friend or family member he/she is consulting about a tourism package.

In this research, we will focus on primary groups, and how friends and family might influence a consumer’s predisposition to a tourism package and how this influence might related to the hedonic and utilitarian factors associated with it. This grouping is important from a marketing perspective for a product with a high emotional dimension (i.e. a holiday) because consumers tend to choose friends who think in similar ways and have similar interests, and the family is probably the most powerful in influencing consumer decision making.

The exogenous influences we will examine in this article will be mass media and internet. Mass communication is highly used to influence consumer behavior, in general, and in tourism, in particular through marketing outlets, such as television, newspapers, magazines, etc. consumers today have more media options than ever before in the new forms of media (such as the Web) and traditional media in new forms (such as online editions of well-established newspapers), but there is no single answer as to which medium has the most influence on consumer behavior.

The credibility of the commercial source is more problematic and usually is based on a composite evaluation of its reputation, expertise, and knowledge and that of the medium a particular tourism organization uses to advertise its products.

3. Research Hypotheses

Based on the literature framework, we propose a set of six hypotheses, adjusted to understand consumer behavior in tourism, as follows:

H1. Hedonic factors influence the utilitarian factors a consumer may experience in his/her decision-making process.

H2. Endogenous influences have an impact on consumers’ perception of exogenous influences.

H3. Exogenous influences have an impact on the hedonic factors associated with a consumer’s tourism purchase.

H4. Exogenous influences have an impact on the utilitarian factors associated with a consumer’s tourism purchase.

H5. Endogenous influences have an impact on the hedonic factors associated with a consumer’s tourism purchase.

H6. Endogenous influences have an impact on the utilitarian factors associated with a consumer’s tourism purchase.

These six hypotheses of the research model are also presented in Figure 1.

Figure 1. Conceptual model of the research

4. Research Methodology

4.1. Measurement and Research Instrument

All the constructs examined in this research are newly formed and were studied in the survey according to Table 1.

Table 1. The operational definition of the variables

Dimension Operational definition
Utilitarian motivators - 1 -2 -3 -4 -5 Accommodation 1 2 3 4 5
- 1 -2 -3 -4 -5 Availability of tourist information 1 2 3 4 5
- 1 -2 -3 -4 -5 Infrastructure 1 2 3 4 5
- 1 -2 -3 -4 -5 Price 1 2 3 4 5
Hedonic motivators - 1 -2 -3 -4 -5 Things to do 1 2 3 4 5
- 1 -2 -3 -4 -5 Customer Care 1 2 3 4 5
- 1 -2 -3 -4 -5 Scenery 1 2 3 4 5
- 1 -2 -3 -4 -5 Places to Eat 1 2 3 4 5
- 1 -2 -3 -4 -5 Family friendly facilities 1 2 3 4 5

4.2.Sample and Data Collection

The data collection implied a primary research, via various online social networks as respondents filled out an online survey from February 22 to April 18, 2010. A web-based consumer survey was used for the data collection. The present research uses as a method the pilot survey, for which the sample is small (150 respondents), not statistically representative and not determined based on an established formula, but rather using a convenience sample technique.

The online survey generated 150 usable questionnaires. Table 2 presents the profile of the respondents that enjoy travelling.

Table 2. Respondents’ profile

Frequency Percentage
Sex Male 62 41.3%
Female 88 58.7%
Total 150 100.0%
Country Australia 1 0.7%
Austria 9 6.0%
Belgium 3 2.0%
Canada 20 13.3%
Croatia 2 1.3%
Denmark 3 2.0%
Finland 1 0.7%
France 15 10.0%
Germany 22 14.7%
Holland 2 1.3%
Hungary 1 0.7%
Italy 10 6.7%
Malta 1 0.7%
Norway 2 1.3%
Portugal 4 2.7%
Spain 9 6.0%
Sweden 2 1.3%
Switzerland 3 2.0%
United Kingdom 17 11.3%
United States of America 23 15.3%
Total 150 100.0%
Age <20 years old 8 5.3%
20-34 years old 84 56%
35-50 years old 44 29.3%
51-64 years old 12 8%
>65 years old 2 1.3%
Total 107 100.0%

5. Data Analysis

5.1. Exploratory Factor Analysis

The exploratory factor analysis (EFA) technique was used to reduce the number of scales assigned to each elaborated online behavior dimension. Nonetheless, before applying this statistical analysis, we examined the reliability of the scales through Cronbach’s alpha coefficient, for which we aimed to achieve a score higher than 0.70 (Cronbach, 1970) to ensure that the dimensions explored in this research are eligible. Table 3 shows that we obtained scores between 0.836 and 0.949 for all four scales, thus the data can be analyzed through multiple techniques because the scales are appropriate for examination.

Table 3. Descriptive statistics

Scale Cronbach’s Alpha for the scale Item Statistics
Item Mean Std. Deviation
Utilitarian Factors .949 Accommodation 2.34 2.987
Availability of tourist information 2.25 2.925
Infrastructure 2.03 2.487
Price 2.35 3.039
Hedonic Factors .934 Things to do 1.97 2.869
Customer care 1.73 2.709
Scenery 2.21 2.674
Places to eat 1.64 2.853
Family friendly facilities 1.41 2.871
Endogenous Influences .836 Previous personal experience 5.45 1.895
Influence of family/Friends 4.95 1.623
Exogenous Influences .883 Mass media 4.07 1.687
Internet 4.39 1.779

As a rotation method for the EFA, we used the oblique technique, Promax, because it allows the factors to correlate and it diminishes interpretability. Also, by using this rotation method, the variables of the research were examined for the relationships between each factor and the corresponding variables, by removing the relationships that might be shared by multiple factors.

Moreover, we used the Maximum Likelihood method for extracting the factors of the research as this method minimizes the potential differences that may appear among factors. Also, this method is most commonly used for samples that are further assessed in AMOS for confirmatory factor analysis and structural equation models, which are the analysis techniques we will be using in this research.

To observe the adequacy of the data, we conducted a Kaiser-Meyer-Olkin Measure of Sampling Adequacy’ (KMO) test and obtained a score of 0.812, which is a very good value that shows the appropriateness of the sample (Field, 2005, p.640).

Table 4 shows the communalities for the scale items we used in this EFA. The results show the accuracy of the newly formed factors because of the high levels of variation displayed after extraction.

Table 4. Communalities

Initial Extraction
Accommodation .882 .921
Things to do .730 .745
Customer care .774 .802
Scenery .704 .664
Places to eat .763 .758
Availability of tourist information .855 .884
Family friendly facilities .743 .788
Infrastructure .660 .648
Price .865 .897
Previous personal experience .596 .677
Influence of family and friends .577 .786
Mass media .668 .650
Internet .676 .999

Further, we explored the total variance for the EFA (Table 5). The criteria used to establish the factors was that each element should have a factor loading greater than 0.7 and Eigenvalues ​​greater than 1 (Field, 2005). Also, the eligibility of the factors can also be observed in terms of the variance explained by each resulted factor, as the variation exceeds 70%, specifically for the analysis the total variance explained is 78.605%.

Table 5. Total Variance Explained for the EFA

Factor Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative % Total
1 5.674 43.650 43.650 1.811 13.931 13.931 4.661
2 2.366 18.203 61.852 5.164 39.726 53.657 4.387
3 1.766 13.585 75.437 1.948 14.984 68.641 1.832
4 1.218 9.366 84.803 1.295 9.964 78.605 1.912
5 .420 3.232 88.035
6 .337 2.594 90.629
7 .293 2.250 92.879
8 .246 1.894 94.773
9 .213 1.636 96.409
10 .165 1.267 97.676
11 .125 .961 98.637
12 .094 .724 99.360
13 .083 .640 100.000

Table 6 presents the results of the EFA, in terms of the pattern matrix obtained for each latent variable that will be further explored. It is noted that all the factor scores surpass the 0.7 level of acceptance and more than that the observable variables gather around the specific latent variables they were meant to examine in the survey.

Table 6. Pattern Matrix of the EFA

Latent constructs Observable variables Factor 1 Factor 2 Factor 3 Factor 4
Hedonic Factors Customer care .896
Family friendly facilities .872
Places to eat .859
Scenery .849
Things to do .812
Utilitarian Factors Accommodation .970
Availability of tourist information .952
Price .937
Infrastructure .769
Exogenous Influences Internet .989
Mass media .783
Endogenous Influences Influence of family and friends .897
Previous personal experience .795

5.2. Confirmatory Factor Analysis

The confirmatory factor analysis (CFA) is used as a preceding step before applying the structural equation model in order to test the proposed measurement model of the research. CFA was applied in Amos software, using a maximum likelihood technique, by allowing all the latent constructs of the model to covariate with each other.

Firstly, we investigated the measurement model that shows a very good and reliable form of the model: χ2 = 85.805, df = 57, p = 0.008, χ2 / df = 1.505, GFI (goodness of fit index) = 0.921, NFI (normed fit index) = 0.950, RFI (relative fit index) = 0.932, CFI (comparative fit index) = 0.982, RMSEA (root mean square error of approximation) = 0.058.

Secondly, to examine a first-order CFA of the research, we evaluated the convergence validity, discriminant validity, and reliability of the data.

Firstly, the measurement model must demonstrate a good fit to the empirical data and meet the recommended minimum requirements for certain indicators. For example, the ratio of chi-square and degrees of freedom should be less than five (Hu and Bentler, 1999), root mean square error of approximation (RMSEA) should be less than 0.10, while the goodness of fit index (GFI), normed fit index (NFI), relative fit index (RFI), and comparative fit index (CFI) should present values greater than 0.9.

Figure 2. Results for the Confirmatory Factor Analysis of the proposed model

Table 7. Confirmatory factor analysis results

Factors CR AVE MSV ASV Endogenous Influences Utilitarian Factors Hedonic Factors Exogenous Influences
Endogenous Influences 0.842 0.727 0.070 0.054 0.853
Utilitarian Factors 0.954 0.838 0.236 0.099 0.190 0.916
Hedonic Factors 0.937 0.750 0.236 0.097 0.235 0.486 0.866
Exogenous Influences 0.886 0.796 0.070 0.031 0.265 -0.153 0.008 0.892

Note: CR= Composite Reliability values, AVE = Average Variance Extracted; The diagonal values (in bold) are the square root of AVE (AVE = )

The CFA is reliable for the proposed model because all the composite reliability (CR) values are greater than the acceptable levels of 0.6 proposed by Bagozzi and Phillips (1991) and 0.7 proposed by the Gefen et al. (2000), as the values range from 0.842 to 0.954 (Table 7).

Convergent validity was assessed in terms of the factor loadings of the confirmatory factor analysis (presented in Figure 2) and the average extracted variance (AVE, Table 7). As observed in Figure, all the elements surpass the 0.7 level of acceptability, as they range from 0.82 to 0.95. Moreover, the AVE values also surpass the 0.5 level, as we obtained scores from 0.727 to 0.838. Therefore, the CFA is in accordance with the convergence condition.

For examining the discriminant validity of the data, we used Fornell and Larcker’s (1981) proposed criterion that the square root of the average variance extracted should exceed the correlation shared by the latent variable with the other constructs of the model.

Discriminant validity was assessed using the criterion recommended by which states that the square root of the average variance extracted should exceed the correlation shared by the latent variable with the other constructs of the model. Table 7 presents the correlations between the constructs and the square root of AVE is displayed on the diagonal of the table. Thus, the condition for discriminant validity is met.

5.3. Structural Equation Model

The structural equation modeling was used to test the hypotheses proposed for the model examined in this paper. The accuracy of structural model was tested in accordance with the criteria established by Hu and Bentler (1999) and developed in Table 8.

Table 8: Model accuracy for the proposed model

Measurement Measurement model result Recommended values
χ2 86.047 (p=0.05, 55df) p ≤ 0.05
χ2 /df 1.564 ≤5
GFI 0.932 ≥0.90
NFI 0.950 ≥0.90
RFI 0.929 ≥0.90
CFI 0.981 ≥0.90
RMSEA 0.051 ≤0.10

Note: χ2 =Chi-square, χ2 /df = ratio of Chi-square and degrees of freedom, GFI = Goodness of fit index, NFI = Normed fit index, RFI = Relative fit index, CFI = Comparative fit index, RMSEA = Root mean square error of approximation.

Thus, the model is fit for further examination and we proceeded to analyze the path coefficients of hypothetical relationships between the latent and observable constructs.

Table 9 reflects information regarding the unstandardized and standardized coefficients estimates, statistical significance, and standard error of each relationship. Figure 3 presents the information about the model in a visual manner. Two hypotheses of the six associated with the proposed model are insignificant.

Table 9: Estimates of hypotheses testing for TAM

Hypotheses Significance Unstandardized Regression Weights Standardized Regression Weights Standard Error Hypothesis Result
H1. HedF→UtilF *** 0.487 0.459 0.068 Confirmed
H2.EndogInf→ ExogInf ** 0.383 0.326 0.102 Confirmed
H3.ExogInf→ HedF 0.527 -0.095 -0.056 0.150 Refuted
H4. ExogInf →UtilF * -0.268 -0.201 0.110 Confirmed
H5. EndogInf → HedF *** 0.468 0.366 0.109 Confirmed
H6. EndogInf → UtilF 0.135 0.190 0.129 0.127 Refuted

*** Significant at a 0.001 level (Two-tailed)

** Significant at a 0.005 level (Two-tailed)

* Significant at a 0.010 level (Two-tailed)

Note: HedF = Hedonic Factors, UtilF = Utilitarian Factors, EndogInf = Endogenous Influences, ExogInf = Exogenous Influencs

Figure 3. Standardized results of the research model

The structural diagram for the proposed model is presented in Figure 3. As shown in Figure 3 and Table 9, the relationship between hedonic factors and utilitarian factors of tourists was significant (β = 0.459, p <0.01), and the linkage endogenous influences and exogenous influences of consumer behavior was also significant (β = 0.459, p <0.05), supporting H1 and H2.

The linkages among exogenous influences and hedonic factors and utilitarian motivators were both negative, however only the relationship between the exogenous influences (internet and mass media) have a negative and significant effect on the utilitarian factors of tourism behavior (β = -0.268, p <0.10), indicating that the respondents of this study do not trust or have a negative attitude towards the commercial marketing influences that attempt to change their consumption behavior for tourism packages. However, the relationship between this type of external marketing influences and the hedonic value consumer perceive in relation to a holiday was not supported.

Endogenous influences, of previous personal experience and recommendations from friends and family, showed a great influence on hedonic factors (β = 0.366, p <0.001), supporting H5, showing that this positive and significant relationship should be taken into consideration in examining the influences of consumer behavior in tourism. However, H6 was refuted in the context of this research model, because the coefficient calculated for the endogenous influences and utilitarian factors of tourism packages was insignificant.

6. Discussion and Conclusion

6.1. Theoretical Contributions

The major theoretical contribution of this research is to extend the general knowledge on consumer behavior in tourism considering hedonic and utilitarian factors, as well as exogenous and endogenous influences. To fully comprehend consumers’ choosing patterns in relation to tourism services, it is crucial to examine different inputs of consumer behavior that provide a better understanding of the juxtaposition between a consumer’s functional goals and experiential preferences within an emotional decision context.

The purpose of this study was to examine the relationships among hedonic and utilitarian factors and exogenous and endogenous influences of consumer behavior in tourism. In sum, the structural equation model analysis revealed that the proposed model could well predict consumers’ behavioral influences in relation to their hedonic or utilitarian motivators, indicating its applicability in hospitality industries, particularly the tourism industry. The latent constructs, along with other observable variables of the model, indicate acceptable levels of convergent and discriminant validity, as well as reliability of the scales and of the model fit.

Theoretically, this study demonstrates the usefulness of two distinct structures of consumer service value: hedonic and utilitarian factors and their interactions with consumer behavior influences. Clearly, utilitarian and hedonic values are fundamental dimensions that help to the understanding consumers’ evaluations of the consumption experience because they maintain a basic underlying presence across different consumption phenomena.

6.2. Implications for Managers

Practically speaking, the results can help marketers of tourism-related organizations better understand people’s rationale and influences for buying certain tourism packages and how those packages should be portrayed and presented in marketing settings, by emphasizing the hedonic factors. As presented in this paper, exogenous influences that come from marketing sources and target consumer behavior have a negative effect when they are combined with utilitarian motivators. However, consumers have positive and strong responses to exogenous influences that showcase hedonic aspects of the tourism package in marketing frameworks. Thus, tourism organizations should acknowledge and seek to improve customers’ perceptions of both hedonic and utilitarian values in ensuring satisfaction, thereby in turn influencing positive behavior emotions (Ryu et al, 2012).

6.3. Limitations and Future Research Directions

As with any study, there are some limitations to the generalizability of the findings. This research focused only on the tourism industry. Researchers (Chandon et al., 2000) have found that the relative appeal of hedonic as compared to utilitarian value depends on the nature (hedonic or utilitarian) of the product/service, indicating that the role and relative importance of instrumental characteristics versus hedonic aspects may vary across contexts (Ryu et al., 2010). Thus, more research is needed into other segments of this large industry, with a higher level of focus, such as on a particular hotel chain.

Additionally, the use of a convenience sampling technique, although it has been widely and successfully used for research studies, limits the generalizability of the paper’s findings. Thus, future articles should include a broader range of tourists to test the proposed relationships.

Future studies should explore the linkages amongst hedonic and utilitarian motivations and influences in other environments, such as online searching or online tourism social communities, the relationship between motivation and external influences, at the power of pre-existing attitudes and possible previous expectations that may shape tourism experience.


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The Bucharest University of Economic Studies

Lucian Blaga University of Sibiu

Iuliana CETINA
The Bucharest University of Economic Studies

Lucian Blaga University of Sibiu


Simona Vinerean, The Bucharest University of Economic Studies, Romania

Article History

Received: May 5, 2015
Accepted: June 8, 2015
Available Online: June 22, 2015

Cite Reference

Vinerean, S., Opreana, A., Cetina, I., and Dumitrescu, L., 2015. Relationships among Hedonic and Utilitarian Factors and Exogenous and Endogenous Influences of Consumer Behavior in Tourism. Expert Journal of Marketing, 3(1), pp. 17-28

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