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Analysing the Effect of Tourist Satisfaction on Tourist Revisit Intentions

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Sambodhi ISSN No. 2249-6661
UGC Care Journal Vol.- 44 No. 1, January To March (2021)

Analysing the Effect of Tourist Satisfaction on

Tourist Revisit Intentions
Shugufta Showkat 1, Danish Mehraj 2, Dr. Reyaz A. Qureshi3*
1,2
Research Scholar, Department of Management Studies, University of Kashmir, Srinagar, J&K.
3*
Assistant Professor, Tourism & Hospitality Management, Department of Management Studies,
University of Kashmir, Srinagar, J&K.

(*Corresponding Author: dr.riyaz@yahoo.co.in)

Abstract: The purpose of this study is to provide an insight about the impact of Tourist Satisfaction on Tourist
Revisit Intentions, taking Jammu and Kashmir, India as a unit of analysis. The research design was cross-sectional.
Data were collected from various tourist destinations in Jammu and Kashmir, India. The proposed model was tested
using structural equation modelling with a sample size of 500 respondents. The findings suggest that tourist
satisfaction was found to have significant positive effects on revisit intention. An understanding of these
mechanisms can help governments to create appropriate policies to support the sustainable development of tourism
and promote their tourism industries by fostering tourist satisfaction.

Keywords: Tourist Satisfaction, Revisit Intentions, Structural equation modelling.

INTRODUCTION

Tourism has become a crucial commercial market in many developing countries in recent years through the creation
of associated employment, changes in the living conditions of local residents, and financing for the growth of other
industries (Sharpley, 2000; Tao & Wall, 2009). Developing countries are seeking to improve and diversify their
tourism offerings in order to attract international tourists (Hau & Omar, 2014). Tourism is also important to these
nations, and a growing number of studies are focusing on the growth of tourism. Among other things, the
satisfaction of tourists and the intention to revisit them are considered vital to ensure the success of every
destination (Prayag, 2009; Quintal & Polczynski, 2010; Seetanah et al., 2020).

Tourist satisfaction is one of the most commonly researched variables in tourism and hospitality literature.
Specialized literature shows, from this viewpoint, the main role of tourist satisfaction at the time of choosing a
tourist destination(Reza Jalilvand et al., 2012). Achieving tourist satisfaction in this regard could contribute to a
prosperous tourism industry. In fact, given the main role of satisfaction in a tourist destination, it has been
repeatedly argued that, on the one hand, the feeling of satisfaction encountered by the tourist in a destination would
be a powerful precedent for recommending or returning to a destination (Alegre & Garau, 2010; Soleimani &
Einolahzadeh, 2018). In other words, satisfaction is an explicit precedent for a place's tourist satisfaction. The
results demonstrate from this viewpoint that such allegiance may be affective, cognitive or conative in nature(Khan
et al., 2013; Mohammad, 2014).

It has been shown that multiple variables can yield optimum levels of satisfaction; in a way, they are directly related
to the tourist and, on the other hand, to the destination's environment (Obonyo et al., 2012). In tourism literature, it
has also been argued that satisfaction can be the product of the value perceived in the location by the tourist( Chen
& Chen, 2010; Dayour & Adongo, 2015). Similarly, emotional satisfaction, the perception of the image of the
destination or the perception of the nature of the facilities offered in the destination can be accomplished as a result
(Sukiman et al., 2013).Overall, satisfaction can be the product of the relation with the different attributes of the
tourist destination, together with the tourist's optimistic expectations.

In this respect, the key components for deciding tourist satisfaction would be the advantages perceived in the
place(Metin Kozak & Rimmington, 2000). Nevertheless, while there is comprehensive literature that analyses
satisfaction, there is no final consensus on which variables decide a destination's tourist satisfaction (Chi & Qu,
2008).

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While as mature tourist destinations will gain a competitive advantage in an increasingly competitive international
tourism market with developing new destinations through repeated visits (Salleh et al., 2014). Repeat travellers are
a stable destination market and offer free publicity in the form of word-of-mouth reviews to family members and
friends (Breitsohl & Garrod, 2016; Rajesh, 2013). In order to facilitate frequent trips to a destination, it is important
to recognise the determinants of the desire to return. In this way, the variables that affect this attribute will be
changed in order to maximise the probability of return visits (Sangpikul, 2018).

In the literature on tourism, where this topic has been analysed, the choice to revisit a destination is seen as a
dynamic decision involving a variety of interrelated variables (satisfaction with the stay, tourist motivations, prior
experience of the destination, etc.). Repeat holidays at a familiar destination and a declared intention to revisit it,
are two signs of destination loyalty that are often taken into account in literature (Chiu et al., 2016; Ozdemir et al.,
2012; Quintal & Polczynski, 2010a). The main factors that determine a declared intention to revisit a destination
seem to be tourist satisfaction with their stay, specific motivations in choosing a destination and tourist attachment
to it, where the latter can be measured in terms of the repeat visitation (Ozdemir et al., 2012).

In order to overcome these gaps, current research has made a number of contributions to the literature. This research
offers a comprehensive picture of tourism literature by analysing the role of destination attributes in deciding tourist
satisfaction and re-visiting intentions. Since this approach also checks for contingencies, we further deepen our
interpretation, have greater insight and add to the literature on tourism. Finally, the findings of our study offer
empirical support for our recommendations to the tourism regulators.

RESEARCH FRAMEWORK

Tourist Satisfaction

Satisfaction is considered a critical aspect of tourism and can be one of the factors most extensively discussed in
tourism (Chiu et al., 2016; M Kozak, 2003; Salleh et al., 2014). Tourist satisfaction is commonly characterised as
the consumer's reaction to satisfaction or an appraisal of how well a product serves a need(Herle, 2019). In tourism,
satisfaction is the cumulative feelings of enjoyment and the degree to which one derives from visiting a tourist
attraction(Mehmannavaz et al., 2014). The emotional response arising from cognitive reactions to service
encounters, or the disparity between pre-trip perceptions and post-trip experiences will assess tourist
satisfaction(Valle et al., 2006). In other words, tourists are satisfied as they compare previous expectations and after
travel experiences and when feelings of displeasure are the result they are not satisfied(Bagri & Kala, 2015).

Besides, Tourist satisfaction is the customer's feeling that results from engagement or disappointment with a
product/service experience(Antón et al., 2017). Tourist satisfaction is referred to as "the buyer's cognitive state
about the suitability or inappropriateness of the reward received in exchange for the experienced service" (Howard
and Seth, 1969, p. 145). In simpler words, the difference between the understanding of the pre- and post-benefit of a
product/service is tourist satisfaction.In addition to cognitive elements, tourist satisfaction is often measured by
affective elements(Prayag et al., 2017).

The cognitive reactions of customers emerge from the thought side of their mind, while their emotions are
expressed by affective responses. Cognitive and affective aspects also contribute to the assessment of a
product/service by customers(Prayag, 2009). In the tourism industry context, the appraisal of a destination by
consumers is based on both cognitive and affective elements, essentially deciding their satisfaction level(Khan et
al., 2013). When tourist assess the consistency of food and service versus the money they pay, the cognitive
elements come into play, while the affective elements act as customers evaluate the satisfaction, enjoyment and
sense of personal well-being they derive from the experience(M Kozak, 2003).

Revisit intention

Revisit intention has been described in tourism literature as a main research subject. Many researchers conclude that
repeat tourists prefer to remain at a destination longer, indulge in consumer activities more intensively, are more
fulfilled, and propagate favourable word of mouth, thus requiring much lower marketing costs than first-time
visitors(Hung et al., 2016; Quintal & Polczynski, 2010a).The intention to revisit reflects the tendency or plans to
revisit the same place. Since the expense of acquiring a new tourist high relative to maintaining an existing
consumer, service providers are mindful of revisiting tourist expectations (Rittichainuwat et al., 2002).

Past researchers have shown that satisfaction, service conduct, perceived value and potential attraction are the
determinants of the revisit intention (Intan et al., 2018; Quintal & Polczynski, 2010a; Waheed & Hassan, 2016).
Seetanah et al., (2020)reported that every service provider's good reputation improves consumers' ability to re-visit.

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In addition, the purpose of revisiting is informed by the appraisal of prior experience, modern attractions and
advertising resources (Atikahambar et al., 2019).

Based on experience and their level of satisfaction, tourists decide to revisit a certain location. As experience
determines satisfaction, satisfaction directly affects the purpose of revisiting tourists. Quintal & Polczynski(2010)
found out that high tourist satisfaction lowers the desire of a customer to switch, which in turn increases the
intention to revisit. Tourists who are satisfied are likely to reject alternative services and choose to order from the
same service provider. Dissatisfied clients, on the other hand, are more likely to switch to alternatives (Pratiwi et al.,
2018). Many researchers have found that tourist satisfaction is an influential indicator of the intention of revisiting
destination. Many prior findings also show that tourist satisfaction has a positive effect on the intention of revisiting
a destination (N. Chen & Funk, 2010; H. Huang et al., 2015; Julaimi & Talib, 2016; Ramukumba, 2018).

METHODOLOGY

The research design was cross-sectional. A pilot survey was carried out to assess the content validity of the survey
questions. The questionnaire was revised based on the feedback from the pilot survey. The revised questionnaire
was used in the main survey. This study used non probability sampling technique for the formal survey. Among the
non-probability sampling, judgemental sampling was used to gauge the data for the study. For this study the 500
tourists were surveyed over a four-month period at various tourist destinations of Jammu and Kashmir, India.
Elimination of invalid questionnaires resulted in 443 valid questionnaires. According to (Bentler & Chou, 1987;
Lowry & Gaskin, 2014; Mehraj & Qureshi, 2020), samples should be at least five times the number of estimated
parameters, and (Hoogland & Boomsma, 1998) claimed that a sample size in the 200–400 range is the most
appropriate for SEM analysis.

Tourist satisfaction was measured on the basis of quality destination performance. To measure tourist satisfaction,
scales were designed on the basis of the feedback obtained in the qualitative research and by adapting some
instruments used in previous studies (Hye-Rin Lee, 2012; Pizam, Neumann, & Reichel, 1978; Prayag, 2009;
Rajesh, 2013; Valle, Silva, Mendes, & Guerreiro, 2006; Wang & Hsu, 2010). This scale covers twenty-seven items
where tourists were asked to score whether they agreed with different propositions (five-point- Likert scale: 1 =
strongly disagree; 5 = strongly agree). Besides revisit intention was measured on the basis of two aspects namely,
willingness to recommend and intentions.

To measure revisit intention, scales were designed on the basis of the feedback obtained in the qualitative research
and by adapting some instruments used in previous studies (V. Kumar, Pozza, & Ganesh, 2013; Oppermann, 2000;
Valle et al., 2006; Wu, 2016). This scale covers seven items where tourists were asked to score whether they agreed
with different propositions (five-point- Likert scale: 1 = strongly disagree; 5 = strongly agree).

RESULTS

In order to check construct validity, Confirmatory factor analysis, was performed using IBM AMOS version 23.
Multiple model fit indices were used to measure the adequacy of the measurement model, such as χ2 goodness of fit
indices, normed χ2 (CMIN/df<3), a root-mean-square error of approximation (RMSEA<0.08), standardized root-
mean-square residual (SRMR<0.1), comparative fit index (CFI>0.90), goodness-of-fit index (GFI>0.90),
incremental fit index (IFI>0.90) and Tucker– Lewis index (TLI>0.9) (Hooper et al., 2008; Schreiber et al., 2006).
Convergent validity and discriminant validity assessments were conducted by using CR and (Fornell & Larcker,
1981; Hair et al., 2010)criterion, respectively. The measurement model provides an adequate goodness-of-fit index.
The model fit indices for first-order CFA are: χ2=483.3, df=329, CMIN/df=1.469, CFI=0.985, IFI=0.933,
GFI=0.970, SRMR=0.037, RMSEA =0.033.

Scales and model evaluation

Internal consistency, convergent validity and discriminant validity were investigated to assess the constructs. To
check internal consistency, composite reliability values were examined. All (Table II) were between 0.70-0.90,
which is the satisfactory range (Nunally & Bernstein, 1994). Average variance extracted (AVE) values of the
constructs and factor loadings of the indicators were assessed to check convergent validity. All the AVE
values (Table II) are over the suggested threshold 0.5 (Fornell & Larcker, 1981; Hair et al., 2010).

Besides factor loadings (Table I)are over the suggested threshold 0.6 (Fornell & Larcker, 1981; Hair et al., 2010).

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Table I: Measures of constructs

Factors Statements Item Code Standard

Estimates

Scenery ENVT_1 .815

Lakes /rivers ENVT_2 .887
Climates ENVT_3 .851
Environment Quality of Environment ENVT_5 .905
Quality of Urban Surrounding ENVT_6 .888
Safety & Security ENVT_8 .839
Quality of Roads IA_1 .862
Quality of Accommodation IA_2 .964
Infrastructure & Local Transport IA_3 .980
Accessibility Easy Access to the Area IA_5 .992
Parking Faults IA_6 .649
Tourist info Centers IA_7 .644
Price of meals PRICE_1 .903
Price Price of leisure PRICE_2 .911
Price of shopping PRICE_3 .937
Variety of multiple cuisine FOOD_1 .662
Food Offer of local cuisine FOOD_2 .833
Availability of food FOOD_3 .805
Hospitality of people SC_1 .939
Friendliness of people SC_2 .992
Social & Culture
Customs/traditions SC_4 .808
Diversity of historical attractions SC_5 .821
I would like to come back to this destination in near future IL_1 .694
I would be considering revisiting this destination in near IL_2 .802
Revisit
future
I will revisit this destination next year IL_3 .688
I would recommend this place to my friends IL_4 .686
Recommendation I would say positive things about this destination to others IL_5 .903
I would encourage others to visits IL_6 .916

To satisfy the requirement of the discriminative validity, the square root of a construct’s AVE must be higher than
the correlations between the construct and other constructs in the model (Fornell & Larcker, 1981; Hair et al.,
2010). Table II shows the correlation matrix for the constructs; the diagonal elements have been replaced by the
square root of the constructs AVE. Constructs show adequate discriminant validity since these diagonal values are
higher than the off-diagonal values in the corresponding rows and columns (Hair et al. 2010).

Table II: Construct validity

Construct CR AVE IA ENVT SC PRICE FOOD REVIST RECOM

IA 0.945 0.746 0.864
ENVT 0.947 0.748 0.048 0.865
SC 0.940 0.798 0.182 0.079 0.894
PRICE 0.941 0.841 0.240 0.060 0.243 0.917
FOOD 0.878 0.708 0.171 0.052 0.134 0.086 0.842
REVIST 0.812 0.593 0.238 0.132 0.120 0.137 0.291 0.770
RECOM 0.773 0.532 0.250 0.205 0.072 0.255 0.407 0.196 0.730

Hypothesis testing

In order to measureTourist Satisfaction-revisit Intention relationship, structural equational modelling (SEM) was
used (figure 1).The structural model reveals a good model fit. All the indicators of model fit fall within
the acceptance region. The ratio of Chi-square to df (297.199/168) = 1.76; GFI = 0.901; AGFI = 0.884; NFI =

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0.933; CFI = 0.970; RMR = 0.055; and RMSEA = 0.055, were all significant. The critical ratio of 3.84 for the
specified path (Tourist Satisfaction-revisit Intention), the significant beta coefficient of the specified path (Tourist
Satisfaction-revisit Intention) affirms the positive and significant effect (β=.490***) and R-square of 0.44 affirm the
claim that the revisit intention of tourists is significantly dependent upon the satisfaction with tourist destinations
attributes. Supporting hypothesis that the, development of overall tourist satisfaction positively and significantly
influences revisit intention.

Figure 1: SEM Model

DISCUSSION

The, development of overall tourist satisfaction positively and significantly influences revisit intention. The study is
in line with some previous studies(Hung et al., 2016; Oppermann, 2000b; Um et al., 2006). The findings have made
significant contribution to destination loyalty studies in a number of ways. The results, which were formulated by
the SEM analysis, show the factors which have a significant positive effect on the tourists’ revisit intention to state
Jammu and Kashmir, India. The significant predictors are overall satisfaction, perceived attractiveness on
destination attributes (accommodation, shopping, restaurant & food, and culture of local people), and overall
destination image.

As for the determinants of the intention to return, the main determinant is overall satisfaction, in line with the
findings obtained by Alegre & Cladera, (2006), Yoon &Uysal, (2005), and Kozak,(2001). According to a number of
studies showing that repeat visitors have a higher probability of returning to a destination than first-timers (Shawn
Jang & Feng, 2007; Kozak & Rimmington, 2000; Zhang, Wu, & Buhalis, 2018), this research shows that the
number of previous visits also has a positive impact on intention to return, together with the infrastructure, culture,
quality food and the price/quality ratio. Choosing the destination because of its price has a positive effect on the
intention to return. Those that proved significant were the quality of the accommodation and quality of the
environment. This means that tourists who are motivated by quality declare higher satisfaction levels. Price as a
motivation is also significant, with a positive sign, indicating that tourists motivated by prices have a higher level of
overall satisfaction. The results of the estimated coefficients indicate that satisfaction is more important in
determining the intention to return than the number of previous visits. From the results that were obtained, it is
interesting to note that, quality of infrastructure, culture and quality food and opinions of the price-quality ratio have
a positive effect on the tourist satisfaction.

Implications

Destinations today are facing steep competitions and the challenges are getting greater in the years to
come. Therefore, it is essential to gain a better understanding of why travellers are loyal to a destination and what
drives the loyalty. The results of this study provide theoretical and practical contributions to the service literature
and tourism industry managers. The results help managers to attain a more deeply understanding of
tourist satisfaction and revisit intention. Increasing the support, empathy and efficiency with tourists, managers can
increase their satisfaction and their loyalty to the destination. Tourists’ feedback plays a great role in improving
service quality. Those tourism destinations acting based on market-oriented philosophy should provide services
with higher quality than other destinations in order to succeed. In a tourism destination, tourists are the main factor
and what matters is to attract and satisfy them; therefore, in the competitive atmosphere of tourism destinations,
those which can create more loyalty in their tourists are more successful. As tourism industry is changing every day,
tourism destination managers should investigate and analyse service quality and recognize their strengths and
weaknesses so that they can meet tourists’ increased needs and guarantee their survival because no tourism

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destination is meaningful without tourists. No doubt, mistakes and flaws are inevitable in tourism activities, but the
key point in service activities of tourism is to solve tourists’ problems to attract their attention and loyalty and
consequently their revisit. Therefore, tourism managers working with tourism industry should be instructed to
respect the long-term relationship with tourists and to improve destination image, quality and value. A definite
marketing plan for different sections of tourism destinations is required for tourism industry in state Jammu and
Kashmir; managers of this industry should pay more attention to this issue. Tourists’ needs should be respected and
their expectations should receive enough attention.

Limitations and Scope for Future Research

Based on the above discussion, one of the main limitations of this study was the nature of the research design used
in collecting the data form tourists about satisfaction about tourist destinations of Jammu and Kashmir. Firstly, this
study was cross sectional in nature, future studies can be conducted using longitudinal research design to overcome
biasness. Secondly, this study did not investigate visitors motivations, and their length of stay at the sites, both
being variables identified by researchers to be important variables affecting tourists satisfaction. Thus, future
research should focus on investigating the effects of the length of stay and motivation for visiting the sites on
tourist’s satisfaction with their site experience.

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