04_How Destination Image and Evaluative Factors Affect Behavioral Intentions

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Tourism Management 28 (2007) 11151122

Research article

How destination image and evaluative factors

affect behavioral intentions?

Ching-Fu Chen, DungChun Tsai

Department of Transportation and Communication Management Science, National Cheng Kung University, 1, Ta-Hsueh Rd. Tainan, 701, Taiwan, ROC

Received 1 November 2005; accepted 17 July 2006

Abstract

Differing from the previous studies, this study proposed a more integrated tourist behavior model by including destination image and

perceived value into the qualitysatisfactionbehavioral intentions paradigm. The structural relationships between all variables with

respect to different stages of tourist behaviors were investigated in the study. The results show that destination image have both direct

and indirect effects on behavioral intentions. In addition, the path destination image-trip quality-perceived value-satisfaction-

behavioral intentions appears evident in this study.

r 2006 Published by Elsevier Ltd.

Keywords: Destination image; Trip quality; Perceived value; Satisfaction; Behavioral intentions

1. Introduction

Tourism has been seen as the driving force for regionaldevelopment. Successful tourism can increase destinations

tourist receipts, income, employment and government

revenues. How to attract the tourists to revisit and/or

recommend the destination to others is crucial for the

success of destination tourism development.

From the perspective of tourist consumption process

(Ryan, 2002; Williams & Buswell, 2003), tourist behavior

can be divided into three stages: pre-, during- and post-

visitation. More specifically, tourist behavior is an aggre-

gate term, which includes pre-visits decision-making, on-

site experience, experience evaluations and post-visits

behavioral intentions and behaviors. It has been generallyaccepted in the literature that destination image has

influence on tourist behaviors (Bigne, Sanchez, & Sanchez,

2001; Fakeye & Crompton, 1991; Lee, Lee, & Lee, 2005).

The tourist behaviors include the choice of a destination to

visit and subsequent evaluations and future behavioral

intention. The subsequent evaluations include the travel

experience or perceived trip quality during the stay,

perceived value and overall satisfaction while the futurebehavioral intentions include the intention to revisit and

the willingness to recommend. There has been a great body

of studies focusing on the interrelationship between

quality, satisfaction and behavioral intentions (Backman

& Veldkamp, 1995; Baker & Crompton, 2000; Cronin,

Brady, & Hult, 2000). However, in recent years perceived

value has been emphasized as the object of attention by

researchers in tourism (Kashyap & Bojanic, 2000; Murphy,

Pritchard, & Smith, 2000; Oh, 1999, 2000; Petrick, 2004;

Petrick & Backman, 2002a, b; Petrick, Backman, & Bixler,

1999; Petrick, Morais, & Norman, 2001; Tam, 2000). Some

studies even argued that the measurement of satisfactionmust be in conjunction with the measure of perceived value

(Oh, 2000; Woodruff, 1997) and perceived value plays the

moderating role between service quality and satisfaction

(Caruana, Money, & Berthon, 2000). Furthermore, per-

ceived value involves the benefits received for the price paid

(Zeithaml, 1988) and is a distinctive concept from quality

and satisfaction. Empirical research also reveal that the

positive impact of perceived value on both future

behavioral intentions and behaviors. Hence, perceived

value, quality and satisfaction all have been shown to be

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0261-5177/$ - see front matterr 2006 Published by Elsevier Ltd.

doi:10.1016/j.tourman.2006.07.007

Corresponding author. Tel.: +886 6 2757575x53230;

fax: +8866 2753882.

E-mail addresses: [email protected] (C.-F. Chen),

[email protected] (D. Tsai).
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good predictors of future behavioral intentions (Baker &

Crompton, 2000; Bojanic, 1996; Cronin et al., 2000;

Petrick, 2004; Tam, 2000).

By understanding the relationships between future

behavioral intentions and its determinants, destination

tourism managers would better know how to build up an

attractive image and improve their marketing efforts tomaximize their use of resources. Hence, the purpose of the

study is twofold. The first is to construct a more integrated

model of tourist consumption process by including

destination image and perceived value into the quality

satisfactionbehavioral intention paradigm. The second is

to examine the relationships between destination image and

evaluative factors (i.e. trip quality, perceived value and

satisfaction) in their prediction of future behavioral

intentions.

2. Conceptual background and hypotheses

Destination image is defined as an individuals mental

representation of knowledge (beliefs), feelings and overall

perception of a particular destination (Crompton, 1979;

Fakeye & Crompton, 1991). Destination image plays two

important roles in behaviors: (1) to influence the destina-

tion choice decision-making process and (2) to condition

the after-decision-making behaviors including participa-

tion (on-site experience), evaluation (satisfaction) and

future behavioral intentions (intention to revisit and

willingness to recommend) (Ashworth & Goodall, 1988;

Bigne et al., 2001; Cooper, Fletcher, Gilbert, & Wanhill,

1993; Lee et al., 2005; Mansfeld, 1992). On-site experience

can be mainly represented as the perceived trip qualitybased upon the comparison between expectation and

actual performance. However, the influence of destination

image on after-decision-making behaviors has been ne-

glected in previous studies except for Bigne et al. (2001)

and Lee et al. (2005). Following the marketing perspective,

Lee et al. (2005) argued that individuals having a favorable

destination image would perceive their on-site experiences

(i.e. trip quality) positively, which in turn would lead to

greater satisfaction levels and behavioral intentions.

The first four hypotheses, therefore, would be:

H1. The more favorable the destination image, the higher

the perceived trip quality.


the overall satisfaction.


the perceived value.

H4. The more favorable the destination image, the more

positive the behavioral intention.

As aforementioned, service quality has been recognized

as the antecedent of satisfaction and behavioral intentions

in a service setting. In addition, the research by Bigne et al.

(2001) and Lee et al. (2005) also ascertained that higher trip

quality could lead to both higher satisfaction and more

positive behavioral intentions in general.

The fifth and sixth hypotheses, therefore, would be:

H5. The higher the trip quality, the higher the overall

satisfaction.

H6. The higher the trip quality, the more positive the

behavioral intention.

Quality, perceived value and satisfaction have been

recognized as the antecedents of behavioral intentions

(Kashyap & Bojanic, 2000; Petrick, 2004; Tam, 2000; Tian-

Cole, Crompton, & Willson, 2002). However, the relation-

ships between these antecedents are arguable. Based upon

different assumptions, Petrick (2004) classified the relation-

ship quality, perceived value and satisfaction into three

models, i.e. the satisfaction model (quality-value-

satisfaction), the value model (quality-satisfaction-

value) and the quality model (the relationship betweensatisfaction and value is uncertain). The empirical result

shows in favor of the satisfaction model. In other words,

perceived value plays a moderating role between quality

and satisfaction. The evidence is inherent to Caruana et al.

(2000) and Hellier, Geursen, Carr, and Rickard (2003). In

addition, perceived value may be a better predicator of

repurchase intentions than either satisfaction or quality

(Cronin et al., 2000; Oh, 2000).

The last four hypotheses, therefore, would be:

H7. The higher the trip quality, the higher the perceived

value.

H8. The higher the perceived value, the higher the overall

satisfaction.

H9. The higher the perceived value, the more positive the

behavioral intention.

H10. The higher the overall satisfaction, the more positive

the behavioral intention.

The conceptual model of the study is shown as Fig. 1.

Each of the model components is defined as follows:

Behavioral intention: the visitors judgment about the

likeliness to revisit the same destination or the willingness

to recommend the destination to others.

Overall satisfaction: the extent of overall pleasure or

contentment felt by the visitor, resulting from the ability of

the trip experience to fulfill the visitors desires, expecta-

tions and needs in relation to the trip.

Perceived value: the visitors overall appraisal of the net

worth of the trip, based on the visitors assessment of what

is received (benefits), and what is given (costs or sacrifice).

Trip quality: the visitors assessment of the standard of

the service delivery process in association with the trip

experience.

Destination image: the visitors subjective perception of

the destination reality.

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3. Methodology

3.1. Questionnaire design

The questionnaire was designed as the survey instrument

including all constructs of the proposed model to

investigate the hypotheses of interest. The questions in

the questionnaire are based on a review of the literature

and specific destination characteristics. The survey instru-

ment was revised and finalized based on feedback from five

tourism experts and a pilot sample of 25 postgraduate

students studying a tourism management program in

Taiwan. Hence, the content validity of the survey instru-

ment was deemed as adequate.1 The questionnaire consists

of five parts. Part 1 of the questionnaire deals with the

measurement of destination image with 20 attributesextracted from previous studies (Baloglu & McCleary,

1999; Beerli & Martin, 2004; Etchner & Ritchie, 1993;

Walmsley & Young, 1998). Part 2 deals with the measure-

ment of trip quality with 20 items covering the five aspects

of attractions, accessibility, amenity, activities, available

packages, and ancillary services (Buhalis, 2000). Part 3

deals with the measurement of perceived value with three

items including time value, money value and effort value

(Bolton & Drew, 1991). Part 4 deals with the measurement

of single-item overall satisfaction and two-item behavioral

intentions (i.e. likeliness to revisit and willingness to

recommend) following Bigne et al. (2001), Sirakaya,

Petrick, and Choi (2004) and Tian-Cole et al. (2002).

Respondents are asked to indicate their agreement level for

each item, for the first four parts on a five-point Likert-type

scale, from strongly disagree ( 1) to strongly agree

( 5). Part 5 presents respondents demographic informa-

tion with seven items, such as gender, age, education level,

occupation, monthly income, travel party, and past

visitation experience via a categorical scale.

3.2. Sample design and data collection

The empirical study was carried out in Kengtin region,

an important and famous coastal destination in southern

Taiwan, during December 2004. Individuals over the age of

18 years and who were visiting the attractions within the

Kengtin region were considered to be the target popula-tion. Applying the convenient sampling technique, a total

number of 500 questionnaires were delivered and 393

usable samples were obtained, resulting in a response rate

of 78.6%.

The respondent profile is summarized as Table 1. The

great majority of the respondents were aged below 34 but

over 15 (72.2%) with a slight majority of female visitors

(57.0%). In all, 75.4% had a university degree or higher

qualification. Student (20.1%), service worker (20.6%) and

clerk worker (20.6%) were the main divisions of occupa-

tion for respondents. The great majority of the respondents

had a monthly income less than NT$40,000, or approxi-

mately $12002 (72.2%), 98.3% were accompanying family

or friends (98.3%), and 80.7% were revisiting Kengtin.

3.3. Data analysis

The data analysis was conducted in two stages. First,

exploratory factor analyses using principal component

method with varimax rotation were conducted on destina-

tion image and trip quality to examine their dimensional-

ities and psychometric properties. On that basis, the

relationships of destination image, evaluative factors (i.e.

trip quality, perceived value and satisfaction), and beha-

vioral intentions were empirically tested using structural

equation modeling (SEM) technique in the second stage.

4. Empirical results

In this study a multi-attribute approach was employed to

measure destination image and trip quality. As mentioned

above, destination image and trip quality were both

measured using a 20-item scale. Employing the principal

components factor analysis, four factors with an eigenvalue

greater than one explained 62.4% of the variance of

destination image scale. Six items with factor loading lessthan 0.5 were removed from the scale. The varimax-rotated

factor pattern implies that the first factor concerns

destination brand (5 items, a 0:819). The second

factor relates to entertainment (4 items, a 0:763).

The third factor consists of characteristics of the nature

and culture (3 items, a 0:659). The fourth factor relates

to sun and sand (2 items, a 0:607). The arithmetic

means of the four multi-item factors were used to build the

construct destination image for subsequent analysis. The

result of the factor analysis for destination image is shown

in Table 2.

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-

H6

-

H8

H9

H3

H4 H2

H5

H1

H10

SatisfactionTrip

quality

Destinationimage

Perceived

value

Behavioral

intention

H7

Fig. 1. The conceptual model of the study.

1The results of scale reliability for the pilot test are destination image

(Cronbach a 0:89), trip quality (Cronbach a 0:83), perceived value

(Cronbach a 0:

91) and behavioral intention (Cronbach a 0:

87). 21 $A33 NT$ at the time of study.

C.-F. Chen, D. Tsai / Tourism Management 28 (2007) 11151122 1117


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Similarly, four factors with an eigenvalue greater than

one explained 60.5% of the variance of trip quality scale

using the principal components factor analysis. Two items

with loading factors less than 0.5 were removed from the

scale. The varimax-rotated factor pattern implies that the

first factor relates to hospitality (7 items, a 0:848). The

second factor relates to attractions (4 items, a 0:748).

The third factor concerns transport (3 items, a 0:769).

The fourth consists of the attributes of amenity (4 items,

a 0:763). The arithmetic means of the four multi-item

factors were used to build the construct trip quality for

subsequent analysis. The result of the factor analysis for

trip quality is shown in Table 3.

Reliability for each of the factors was obtained using the

calculation of a Cronbach a coefficient. The Cronbach a

coefficients ranged from 0.85 to 0.61 (see Tables 2 and 3).

Six of the eight factors were above the cut-off criterion of

0.7 recommended by Nunnally (1978) while two were just

below this level, namely, nature and culture (0.66) and

sun and sand (0.61). However, Peterson (1994) suggested

that an a value of 0.6 is the criterion-in-use. Therefore, it

suggests that all factors were well above the criterion-in-

use and thus acceptably reliable.Confirmatory factor analysis (CFA) was then conducted

using LISREL VIII (Joreskog & Sorbom, 1993) with

covariance matrix to test the convergent validity of the

constructs used in subsequent analysis. The fit indices

suggested by Joreskog and Sorbom (1993) and Hair,

Anderson, Tatham, and Black (1998) were used to assess

the model adequacy. Convergent validity of CFA results

should be supported by item reliability, construct reliability

and average variance extracted (Hair et al., 1998). As

shown in Table 4, t-values for all the standardized factor

loadings of the items were found to be significant (po0:01).

In addition, construct reliability estimates ranging from

0.75 to 0.92 exceeded the critical value of 0.7 recommended

by Hair et al. (1998), indicating it was satisfactory. The

average variances extracted for all the constructs fell

between 0.60 and 0.93, and were greater than the value

of 0.5 suggested by Hair et al. (1998). Composite scores for

each construct were obtained from the mean scores across

items representing that construct.

The proposed conceptual model in Fig. 1 was tested by

using the five constructs: namely destination image, trip

quality, perceived value, satisfaction and behavioral inten-

tions. Factors of destination brand, entertainment,

nature and culture and sun and sand were served as

the measurement variables of destination image. Also, factorsof hospitality, attractions, transport and amenity

are used as the measurement variables of trip quality. In

addition, perceived value, satisfaction and behavioral inten-

tions were measured by three, one and two items as

mentioned previously, respectively. Employing the covariance

matrix among 14 measurement items as input, the SEM

analysis was conducted to examine the relationships between

each pair of constructs as hypothesized. The results of SEM

analysis were depicted in Fig. 2. The fit indices of the model

are summarized in Table 5. The overall model indicates that

w2 is 207.7 with 69 degrees of freedom (d.f.) (po0.0001).

Technically, the p-value should be greater than 0.05, i.e.,

statistically insignificant. However, in practice the w2-value is

very sensitive to sample size and frequently results in the

rejection of a well-fitting model. Hence, the ratio of w2 over

d.f. has been recommended as a better goodness of fit than w2

(Hair et al., 1998). A common level of the w2/d.f. ratio is

below 5 (though below 3 is better). The w2/d.f. ratio of the

model is 3.01 (i.e., 207.7/69), indicating an acceptable fit.

Furthermore, other indicators of goodness of fit are

GFI 0.930, RMSEA 0.0716, RMR 0.0015,

NFI 0.972, NNFI 0.975, CFI 0.981, RFI 0.963,

and PNFI 0.737. Comparing these with the corresponding

critical values shown in Table 4, it suggests that the

hypothesized model fits the empirical data well.

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Table 1

Respondent profile

Demographic characteristics Frequency Percentage (%)

Gender

Male 169 43.0

Female 224 57.0

Age

1824 148 37.6

2534 161 41.0

3544 76 19.3

4554 5 1.2

55 and over 3 0.9

Education level

Primary 6 1.2

High school 92 23.4

University 266 67.6

Postgraduate 29 7.8

Occupation

Student 79 20.1

Housework 21 5.3Civil servant 52 13.2

Self-employed 37 9.4

Service worker 81 20.6

Skilled worker 17 4.3

Clerical worker 81 20.6

Other 25 6.5

Monthly income (NT$)a

p2,000,000 108 27.4

20,00140,000 176 44.8

40,00160,000 68 17.1

60,00080,000 16 4.2

X80,001 25 6.5

Travel party

Single 3 0.9

Family 158 40.1

Friends 229 58.2

Tour group 3 0.9

Past experience

First-time visit 76 19.3

Repeated visit 417 80.7

a33 NT$A1 US$.



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Within the overall model, the estimates of the structural

coefficients provide the basis for testing the proposed

hypotheses. As shown in Fig. 2, destination image has a

significantly positive effect on trip quality and behavioral

intentions (g1 0:91, t-value 14.63, po0:01, and

g4 0:37, t-value 2.17, po0:01, respectively) thus sup-

porting H1 and H4. Due to their insignificances on

structural coefficients, however, the hypotheses of destina-

tion image has positive effect on perceived value (H2) and

on satisfaction, (H3) is not supported. The trip quality, as

hypothesized, has a significantly positive effect on per-

ceived value (b1 0:83, t-value 10.92, po:01), thus

supporting H5. Nonetheless, it does not have a significant

effect on both satisfaction and behavioral intentions, thus

rejecting H6 and H7, respectively. In addition, the perceived

value has a significantly positive effect on satisfaction

(b4 0:75, t-value 9.51, po0:01), supporting H8 while it

does not appear to have a significant effect on behavioral

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Table 2

Factor analysis of destination image

Factor/item Factor loading Variance explained (%) Cumulative variance explained (%) Cronbach a

IM1: Destination brand (3.60) 20.19 20.19 0.82

Offers personal safety 0.783

A good quality of life 0.780

Clean 0.718

A good name and reputation 0.647

Hospitable and friendly people 0.521

IM2: Entertainment (3.51) 17.78 37.97 0.76

Good night life 0.760

A good shopping place 0.756

Varied gastronomy 0.744

Exotic 0.574

IM3: Nature and culture (3.92) 12.49 50.46 0.66

Great variety of fauna and flora 0.852

Spectacular landscape 0.658

Unusual ways of life and customs 0.625

IM4: Sun and sand (4.19) 11.91 62.40 0.61

Good weather 0.810Good beaches 0.773

Table 3

Factor analysis of trip quality

Factor/item Factor loading Variance explained (%) Cumulative variance explained (%) Cronbach a

TQ1: Hospitality (3.43) 20.57 20.57 0.85

Price of accommodation 0.761

Prices of activities 0.717

Food and beverage of accommodation 0.707

Services of accommodation workers 0.698

Prices of food & beverage 0.671Safety of activities 0.526

TQ2: Attractions (3.82) 13.57 34.14 0.75

Cleanness of beaches 0.830

Uniqueness of landscape 0.791

Comfort of built environment 0.602

Weather 0.546

TQ3: Transport (3.57) 13.05 47.19 0.77

Accessibility 0.767

Internal transport 0.758

Parking facilities and space 0.713

TQ4: Amenity (3.73) 12.86 60.05 0.76

Food and beverage provision 0.688

General infrastructure 0.676Travel information 0.622

Signs and indicators 0.558



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intentions, not supporting H9. Finally, the satisfaction has a

significantly positive effect on behavioral intentions

(b6 0:54, t-value 7.94, po0:01), supporting H10.

To sum up, an evident path destination image-trip

quality-perceived value-satisfaction-behavioral inten-

tions appears in the estimated model. The results of the

hypotheses testing are summarized in Table 6. Note that

trip quality does not directly, but does indirectly, influence

satisfaction through perceived value as a moderating

variable. This finding confirms the arguments of previous

studies (Caruana et al., 2000; Oh, 2000; Woodruff, 1997).

Table 7 reports the direct and indirect effects of all

variables on visitors behavioral intentions. Both destina-

tion image and satisfaction had direct effects on behavioral

intentions while trip quality and perceived value had

indirect effects on behavioral intentions. Total effect of

destination image on behavioral intentions, i.e., sum of

direct and indirect effect through destination images effect

on trip quality, perceived and satisfaction, was found to be

0.68. In a similar way, the total effects of trip quality,

perceived value and satisfaction on behavioral intentions

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Table 4

Convergent validity

Constructs Items Item reliability Construct reliability Average variance extracted

Factor loadings Standard error Standardized factor loading t-value

Destination image IM1 1.000 0.46 0.75 0.62

IM2 0.903 0.070 0.42 12.97**IM3 0.746 0.060 0.34 12.38**

IM4 0.711 0.065 0.33 10.90**

Trip quality TQ1 1.00 0.42 0.80 0.60

TQ2 0.960 0.065 0.40 14.77**

TQ3 0.929 0.082 0.39 11.26**

TQ4 0.915 0.068 0.38 13.51**

Perceived value PV1 1.00 0.49 0.84 0.76

PV2 1.178 0.078 0.57 15.15**

PV3 1.172 0.078 0.57 14.98**

Behavioral intention BI1 1.00 0.59 0.92 0.93

BI2 1.068 0.040 0.63 26.68**

**po0:

01.

-

1=0.83**

(10.92)

-

-(1.03)

4=0.75**

4=0.37**

3=0.13

(0.78)

Destination

image

(14.63)

1=0.91**

Trip

qualitySatisfaction

2=0.04

(0.72)

3=0.20

6=0.54**

(7.94)

Behavioral

intention

(9.51)

5=0.17

(1.74)

Perceived

value

2=0.07

(0.53)(2.16)

**denotes p


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were found to be 0.34, 0.41 and 0.54, respectively. It

indicates that destination image and satisfaction are the

two most important variables to influence visitors

behavioral intentions.

5. Conclusions

This study investigated the tourist behaviors by con-

structing a more comprehensive model considering desti-

nation image, evaluative factors (i.e. trip quality, perceived

value, satisfaction) and behavioral intentions. The struc-

tural relationships between all variables in the study were

tested using data obtained from a visitor questionnaire

survey at Kengtin in southern Taiwan. As Lee et al. (2005)

argued, although broad agreement among scholars regard-

ing the influence of destination image on process, little

empirical research has been done. In addition, the

moderating role of perceived value between quality and

satisfaction has been debatable but frequently neglected inprevious research. This study differs from previous studies

by taking account of destination image and perceived value

in the tourist behavior model.

The structural relationship analysis indicates that

destination image appears to have the most important

effect on behavioral intentions (i.e. intention to revisit and

willingness to recommend). Destination image influences

behavioral intentions in two ways: directly and indirectly.

This finding is consistent with Bigne et al. (2001). In

particular, the path of destination image-trip quality-

perceived value-satisfaction-behavioral intentions ap-

pears evident in this study. Destination image not only

influences the decision-making process but also conditions

after-decision-making behaviors of tourists. In other

words, the influence of destination image is not limited to

the stage of selecting the destination, but also affects the

behavior of tourists in general (Bigne et al., 2001). Hence,

endeavors to build or improve the image of a destination

facilitate loyal visitors revisiting or recommending beha-

viors, thus being critical to the success of destination

tourism development.

Trip quality was found to have an indirect rather than a

direct effect on overall satisfaction as moderated by

perceived value. It implies that unless leading to an

increase in perceived value, trip quality is not guaranteed

to lead to customers overall satisfaction. Subsequently, the

results in positive behavioral intentions would be also

uncertain. Hence, perceived value does play an important

role in affecting the level of satisfaction and future

behavioral intentions of customers. An increase in quality

would generally induce an increase in costs. If a product

with high quality cannot make customers satisfied, how-

ever, the quality in practice is of little use and its induced

cost is wasteful. By better understanding how tourists value

their trip experiences, tourism managers could be able to

device more effective marketing strategies and service

delivery to meet tourists actual needs. Once tourists

perceive their trip experiences valuable, the higher satisfac-

tion would occur and furthermore the benefits of positive

behaviors could be brought out. The issues allowing better

understanding of customers value perception and the role

of perceived value in the relationship between quality and

satisfaction should be addressed and warrant future study.

Acknowledgments

The authors wish to thank Mr. Ting-Yao Wei for his

assistance in data collection and the two referees for their

comments.

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ARTICLE IN PRESS

Table 7

Direct effect, indirect effect and total effect

Path Direct effect Indirect effect Total direct

Image-Trip quality 0.91 0.91

Trip quality-Perceived value 0.83 0.83

Perceived value-Satisfaction 0.75 0.75

Satisfaction-Behavioral intentions 0.54 0.54

Image-Behavioral intentions 0.37 0.31 0.68

Trip quality-Behavioral intentions 0.34 0.34

Perceived value-Behavioral intentions 0.41 0.41



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04_How Destination Image and Evaluative Factors Affect Behavioral Intentions

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