Elsevier

Tourism Management

Volume 32, Issue 4, August 2011, Pages 890-901
Tourism Management

Examining the effect of novelty seeking, satisfaction, and destination image on tourists’ return pattern: A two factor, non-linear latent growth model

https://doi.org/10.1016/j.tourman.2010.08.004Get rights and content

Abstract

With many destinations relying on repeat business, intention to revisit has become an important research topic. As revisit intention changes over time, this paper proposes the use of a latent growth curve to model the developmental trajectory of return behavior. The proposed model was tested in two steps in AMOS 16.0 using SEM methodologies to investigate the effects of novelty seeking, destination image and overall satisfaction levels across intent to revisit trajectories using data collected among French, English, and German travelers. Findings indicate that both novelty seeking and low satisfaction among travelers temper immediate intent to return. Conversely, a positive image of the destination enhances both immediate and future intentions to return.

Introduction

With many destinations relying heavily on repeat vacationers to induce visit flow (Gitelson & Crompton, 1984), understanding revisit intent has become important to practitioners and academics alike. A thorough comprehension of revisit intent is particularly important for established travel destinations, where the scope for encouraging further “virgin demand” is limited (Darnell & Johnson, 2001). In recent years, many studies have investigated what causes travelers to make repeat visits. Such studies have identified several antecedents of return intention, including satisfaction (Baker and Crompton, 2000, Kozak, 2001, Petrick et al., 2001, Yoon and Uysal, 2005, Yuksel, 2001), perceived quality (Baker and Crompton, 2000, Chen and Gursoy, 2001, Frochot and Hughes, 2000, Yuksel, 2001), past vacation experience (Alegre and Cladera, 2006, Chen and Gursoy, 2001, Kozak, 2001, Petrick et al., 2001), destination image (Bigne et al., 2001, Milman and Pizam, 1995, Ross, 1993), and cultural difference (Chen and Gursoy, 2001, Reisinger and Turner, 1998).

In the majority of existing studies, the use of intentions to predict actual revisit behavior is directed by the theory of reasoned action (TRA) or the theory of planned behavior (TPB). These viewpoints explain behavioral intentions by representing motivational components of a specific behavior, subsequently denoting the degree of conscious effort that a person will exert in order to perform that behavior (Ajzen, 1991, Fishbein, 1967). In other words, they presume that intention to perform a behavior is the proximal cause of such behavior (Shim, Eastlick, Lotz, & Warrington, 2001). Other studies have examined the relationship between behavioral intention and actual behavior (Quelette & Wood, 1998). Using meta-analytic techniques Sheppard, Hartwick, and Warshaw (1988) reported a mean correlation of 0.53 between behavioral intention and actual behavior, while, in a similar study, Van den Putte (1991) found a mean correlation of 0.62 between the same variables. Both studies indicate that behavior can be reasonably predicted from intention and thus it is generally agreed that understanding behavioral intention is critical in predicting future behavior.

Despite several studies on repeat-visit intention, few researchers have to date addressed the issue of repeat visitation patterns. Feng and Jang (2007) explored the effects of tourists’ novelty seeking and destination satisfaction on revisit intention. Examining three-time interludes within the same model, the authors concluded that satisfaction is a direct antecedent of short-term visits, whereas novelty seeking is a significant antecedent of mid-term revisits. Furthermore, Feng and Jang (2007) determined that short-term, mid-term, and long-term revisit intentions are interrelated. Bigne, Sanchez, and Andreu (2009) considered the effects of variety seeking, satisfaction, and several other antecedents on destination revisit intention. They measured intention at two points in time, the short-run (defined as the next holiday trip) and the long-run (the intention to return to the destination in the distant future). They tested two models for short- and long-run revisit intentions and found the opposite results of Feng and Jang (2007). Indeed, Bigne et al. (2009) found the propensity for variety seeking was a main determinant of a tourist’s intent to return to the same destination for the next holiday. In contrast, the strongest antecedent of revisit intention in the long-term was satisfaction. Although results from both studies offer some insights into the factors affecting tourist revisits at different time stages, the models used in both papers are limited in that they are static and do not incorporate change as a measurable variable. Incorporating change—namely, revisits over time—could be a useful tool for understanding the appropriate time interval for future revisit behaviors.

To address this research gap, the present study uses a latent growth model, which draws upon a set of repeated measures for revisit intention to estimate a developmental trajectory of returns over time. The trajectory is latent in that it was not observed directly, but rather inferred from repeated, observed measures. This technique describes the development trajectory for returns, but also estimates the impact of different predictors (in this case, the destination’s image, visitors’ satisfaction, and visitors’ propensity to seek novel experiences) on its parameters. Such insight could be useful to further verify the effects of various predictors, in particular satisfaction and novelty seeking, on immediate and future intentions to return. This study’s latent growth model was conducted in two steps in AMOS 16.0 using Structural Equation Modeling (SEM). As such, the current study serves a dual purpose. Foremost, it develops insights into a technique to assess change in return intention over time. Furthermore, it explores the effects of possible predictors on revisit behavior patterns to understand individual differences in travel choice over time. The paper begins with a literature review on revisit intent and its determinants. Next, we propose and test a latent growth model using consumer data to explain intention to return. After presenting the findings, this paper provides implications for both industry practitioners and academia. Finally, avenues for further research are proposed.

Section snippets

Revisit intention

An avant-garde study of destination revisit intention dates back to the exploratory work of Gyte and Phelps (1989), who noted that British travelers to Spain show a resurgent intention to return in the future. These early results were refined by Baloglue and Erickson (1998) in their investigation of international repeat visits to Mediterranean destinations, which found that most travelers to a destination are likely to switch to another destination for subsequent trips; but that many do hope to

The proposed hypothetical model

Fig. 1 depicts the latent growth curve model. The hypothesized causal relationships between the different variables are apparent: image  satisfaction  initial status; image  satisfaction  shape factor; novelty  initial status; novelty  shape factor. Initial status and shape factor are, respectively, the intercept and slope of the growth curve over time.

Research methodology

Data was collected using an online questionnaire administered in February 2009 to French, English, and German travelers aged 18 years and older. Survey participants were chosen randomly from panels of respondents that represent each country’s aggregate demographics. Well-established destinations represent the ideal ground to test repeat visitations. Moreover, because destinations close to a traveler’s residence might cause spurious repeat visits (Yim & Kannan, 1999), a screening question

Analysis of results

Latent growth structural equation modeling, using AMOS 16.0 (Ferrer et al., 2004, Schumacker and Lomax, 2004), was implemented to test the set of hypotheses for the effects of destination image, satisfaction, and novelty seeking on the occurrence and development of revisit intentions over the four time periods studied. The latent growth model was analyzed in two steps (Kline, 2004). The first step required analyzing a change model that involves just the repeated measure variable—namely,

Conclusions, discussion, and implications

In the tourism literature, some studies have considered temporal issues in researching revisit intention. These studies have investigated discrepancies in the effects of different antecedents on destination revisit intention measured at different time points. These studies remained static, however, because the cross-sectional nature of each empirical study does not incorporate change as a measurable variable; namely, revisits over time. The present work contributes to the literature as it used

Limitations and further research

As with all research, the current study has several limitations. Firstly tourists’ satisfaction was measured using a single measurement item, which may be a simplistic approach. Using multiple dimensions would be more appropriate and generate more robust findings. Thus, future studies should consider utilizing a model that integrates a multi-variable approach to measuring satisfaction. Technically speaking, using multi-dimensional latent factors for both constructs (i.e., image and

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