Impact of Travel Motivation on Tourist’s Attitude Toward Destination: Evidence of Mediating Effect of Destination Image

Abstract

This research aims at exploring the relationship between travel motivation and tourists’ attitude toward a destination. The study also aims at assessing the mediating role played by destination image between travel motivation and tourists’ attitude toward destination. Data for the study has been collected from tourists visiting Ladakh (Jammu and Kashmir state of India) during the month of July to September (N = 350). Utilizing two theoretical lenses, that of the theory of image and theory of planned behavior, findings of the study revealed positive relationship between tourists’ travel motivation and their attitude toward the destination, which is mediated by destination image. Furthermore, this study contributes by signifying that tourism marketers need to make every possible effort to enhance travel motivation of tourists, so as to build positive image and favorable attitude of tourists toward the destination.

Keywords

travel motivation destination image tourists attitude emerging markets

Introduction

The hospitality and tourism industry has become an important sector in many countries as a source of foreign exchange. This sector also helps in mitigation of balance of payment deficit and problem of unemployment and also contributes significantly toward income, saving, investment, and economic growth (Enzenbacher, 2019; Thrassou, Vrontis, & Bresciani, 2014; Vrontis, Bresciani, & Giacosa, 2016). Tourists’ travel motivation has been an important area of research since the 1960s and a central point to understand tourist behavior (Jango & Wu, 2006). Understanding why people travel and what factors influence their behavioral intention to visit a destination is beneficial for tourism planning and marketing (McGuiggan, Emerson, & Glaser, 1995). Nesbit (1973) identified four reasons for visiting a destination; namely, personal business travel, government or corporate business travel, visiting friends and relatives, and vacation travel for pleasure. Among these, vacation travel for pleasure is the most researched area. Studies undertaken to explore vacation travel for pleasure identified a number of factors such as experience of novelty, knowledge enhancement, getting relax, practice of good shopping (Huang & Hsu, 2009), self-esteem and social recognition, escape from routine, enhancement of social bounding, learning/discovering, experience thrill and excitement (Hung & Petrick, 2011), knowledge and adventure, economic concern, personal safety, destination information, travel arrangement, destination features, family and friends, leisure and relaxation, religious and cultural considerations, and travel bragging (Mutinda & Mayaka, 2012). It is under this context then that this study contributes in several ways as discussed below.

There is lack of consensus among researchers with respect to the dimensions of tourists’ travel motivations as these differ with respect to different destinations and tourists’ sociodemographic characteristics. Earlier studies have explored two dimensions/factors of travel motivations, that is, push and pull factors (Said & Maryono, 2018; Sato, Kim, Buning, & Harada, 2018). In addition, Crompton (1979) identified nine dimensions of travel motivation, that is, self-evaluation and exploration, relaxation, feeling of prestige, doing inconceivable things, enhancement of relationship, social interaction, cultural reasons, and experience loyalty. Though many researchers have measured travel motivations with these dimensions, there has been a lack of validation (qualitatively or quantitatively) of the same. The present study validates the nine-dimension scale of travel motivations in an emerging market context, that is, an Indian setting. Moreover, many studies have explained the relationship between travel motivation and destination image (Beerli & Martin, 2004; Martin & Bosque, 2008); between travel motivation and tourist’s attitude toward destination (Lam & Hsu, 2004, 2006; Lee, 2009); between destination image and tourists’ attitude toward destination (Kim & Stepchenkova, 2015; Veen & Song, 2014). However, research about the impact of aforementioned nine dimensions of travel motivation on destination image as well as tourists’ attitude toward destinations remains underexplored. Furthermore, not many (various data bases like Emerald, Elsevier, EBSCO, Springer, Sage, Wiley-Blackwell, JSTOR, and Taylor & Francis have been searched) has examined destination image as a mediator between travel motivations and tourists’ attitude toward destination. Therefore, the purpose of this study is to validate the travel motivations’ construct and explore the direct as well as indirect relationship between travel motivation and tourist’s attitude toward the targeted location through destination image. Furthermore, the nature of tourists contacted (our respondents) include both national as well as international, that expands the scope of this study. Additionally, this study has also identifies practical implications for the Indian state of Jammu and Kashmir tourism department particularly and tourism marketers in general. In summary, the existing study improves our knowledge within the domain of travel motivation, tourist’s attitude toward destination, and destination image by validating these constructs. The contribution of this study further lies in empirically validating the nine-dimension construct of travel motivation and inclusion of destination image as a mediator while investigating the relationship between travel motivation and tourists’ attitude toward destination.

In what follows this research article is organized in eight parts. In the next section, we present the rationale of the study followed by research questions, Conceptual Framework, Hypotheses Development, Research Design and Methodology, and Data Analysis. We then, put forth the Discussion and Conclusion as well as Theoretical and Managerial Implications of the Study. Finally, in the last part of the study, we identify the Limitations of the Study and propose future lines of research in this area.

Rationale and Context of The Study

As discussed above, tourism is a popular activity in modern life and is contributing significantly toward the economic development. This sector has potential to make several economic and sociocultural contributions. Key contribution among them being national integration and creation of opportunities through economic linkage at destination. Ladakh has been opened for tourism in 1974. There after the flow of tourists, both foreigners and domestic, has increased year after year. For instance, in 2009, 79,087 visitors visited Ladakh including 30,570 foreigners and 48,517 of domestic tourists (Pelliciardi, 2010). Whereas in 2016, around 235,698 tourists visited Ladakh including 38,005 foreigners and 197,693 domestic tourists (Greater Kashmir, 2017). But academically, tourism sector of the area has remained unexplored from a research point of view. Ladakh is emerging as popular tourist destination for both foreign as well as domestic tourists. So, there is a need to explore and identify the factors, which motivate and attract tourists to visit Ladakh, which will help in effective planning and framing strategies for better management of tourism. Based on this rationale and context, we formulate the following two research questions:

Research Question 1: Do travel motivations help in building positive destination image and tourists’ attitude toward destination?

Research Question 2: What is the role played by destination image between travel motivation and tourists’ attitude toward destination?

Conceptual and Theoretical Framework

Travel Motivation

Travel motivation is deeply rooted in Maslow’s hierarchical needs; namely, physiological, safety, belonging, self-esteem, and self-actualization (Chon, 1989). However, in addition to Maslow’s hierarchical needs, tourists’ travel motivation comprises two more needs; that is, aesthetic and knowledge-based needs. The first three human need (physiological, safety, and belonging) are classified as tension reducing, while the remaining four (i.e., self-esteem, self-actualization, aesthetic, and knowledge) are referred to as inductive arousal-seeking motives (Mill & Morrison, 1985). According to Wu (2015), travel motivation are desires of a person, such as to relieve pressure, to enjoy natural environment, to experience beautiful scenery, and to learn, which forces an individual to undertake a vacation for pleasure. However, according to the tourism literature and related models of travel destination choice and decision-making process, the decision of tourist to visit a particular destination involves the concept of Push and Pull motivation (Crompton, 1979). This concept explains that people are pushed away from their home by some innate forces and pulled toward particular destination/destinations by some external forces (Mutinda & Mayaka, 2012). Push factors are the sociopsychological motivations that predispose people to travel. Most push factors originate from intrinsic desires of human beings (Awaritefe, 2004). On the other hand, pull factors are those that attract people to a specific destination once the decision to travel has been made. They include tangible and intangible resources of a specific destination that pull people to realize their needs of travel experiences (T. Z. K. Hsu, Tsai, & Wu, 2009). The push motivations have been useful in explaining the desire for travel, while the pull motivation helps illustrate the actual destination choice (Baloglu & Uysal, 1996).

Destination Image

Destination image has been an important area of study since the early work of Boulding (1956) and Martineau (1958), who proposed that human behavior depends on image rather than reality. Myers (1968) proposed the “theory of image,” which suggests that the world is a psychological and distorted representation of objective reality residing and existing in the mind of individuals. In terms of “destination image,” Lawson and Baud-Bovy (1977) defined it as the expression of all knowledge, impressions, prejudices, and emotional thoughts a person or group of persons has/have of a particular object or place. Thus, “tourism destination image” can be defined as the perception of tourists’ regarding certain characteristics of the destination, such as perception about tourism infrastructure, hospitality atmosphere, unique cultural attraction of the destination, and so on (Cardoso, Araújo Vila, de Araújo, & Dias, 2019; Chen & Tsai, 2007). Furthermore, it has been conceptualized as a multidimensional construct comprising of both organic image and induced image. Organic image is an image of the destination formed on the basis of organic sources of information, such as newspaper, magazines, books, movies, school courses, family and friends, and so on. However, induced image is an image of the destination formed on the basis of induced sources, such as travel broachers, travel agent, and travel guide books (Gunn, 1972).While making a travel destination decision, tourists’ base their final choice of their travel destination (Björk & Kauppinen-Räisänen, 2017; Ozek & Ferraris, 2018) on the basis of organic and induced source of information, wherein the influence of organic image is perceived and argued to be higher as compared with induced image (Gunn, 1972).

Tourists’ Attitude Toward Destination

Attitude is a predisposition created by learning and experience, to respond in a consistent way toward something and this predisposition may be favorable or unfavorable. In tourism, attitude is tourists’ predisposition or feelings toward a vacation destination and tourism services of the destination, which is based on perception of tourism products and attributes of the destination (Bresciani, Thrassou, & Vrontis, 2015; Mountinho, 1987; Sanchez-Cañizares & Castillo-Canalejo, 2015). Theoretically, we further utilize the “theory of planned behavior” (Ajzen, 1991), wherein we contextualize and examine how tourist’s attitudes describes the psychological tendencies expressed by positive or negative evaluation of their engagement in certain behavior. The “theory of planned behavior,” deals with the nature of behavior-specific factors that are designed to predict and explain human behavior in specific contexts (Ajzen, 1991), wherein perceived behavioral control, together with behavioral intention, can be used directly to predict behavioral achievement. It is therefore the view of an individual toward a particular behavior, which depends on barriers and benefits of that behavior (Foster, 2014). Furthermore, it comprises cognitive, affective, and behavioral components (Vincent & Thompson, 2002 ). The cognitive response is the evaluation made on the basis of information and knowledge about the destination, the affective response is evaluation of the destination made on the basis of feeling and emotions of the tourists (Seo & Yun, 2015; Toudert & Bringas-Rábago, 2019) and the behavioral component is a verbal indication of the tourist with regard to their visit to the destination (Akdag, Guler, Dalgic, Benli, & Cakici, 2018).

Attitude predisposes a person to act or perform in a certain manner (Lee, 2007; Sparks, 2007). It is in this context then that one can argue that the thinking of tourists with respect to visit a particular destination will reflect in evaluation of his or her visit to the destination in terms of enjoyable–unenjoyable, positive–negative, fun–boring, pleasant–unpleasant, and favorable–unfavorable (Lam & Hsu, 2004).

Hypotheses Development

Figure 1 represents the conceptual framework and accordingly the hypotheses have been framed. The model evaluates the relationship between travel motivation and destination image as well as between destination image and tourist’s attitude toward destination.

Figure 1

Theoretical Framework

Travel Motivation and Destination Image

Travel motivation is an individual’s internal desires and attributes of a destination, which make him or her undertake a vacation to a particular destination. As discussed above, it has been classified into push and pull motivation (Mutinda & Mayaka, 2012). Push motivation is internal to an individual and comprises psychological, physical, social, and seeking/exploration (T. Z. K. Hsu et al., 2009). Among these four push factors psychological and social factor for visiting a destination has moderate and positive effect on affective component of destination image (Baloglu & McCleary, 1999; Beerli & Martin, 2004). On the other hand, pull motivation is extrinsic to an individual that emerge as a result of attractiveness of the destination arising from mass publicity or promotion about the tangible and intangible attributes of a destination and thereby contributing to an image of that destination (Kassean & Gassita, 2013). Baloglu and McCleary (1999) had identified positive effect of stimulus (pull factor) and personal factors (push factor) on destination image. However, in relation to stimulus factors, many studies have found a significant effect of variety and type of information on perceived image of a tourist destination (Beerli & Martin, 2004; Jalilvand, Samiei, Dini, & Manzari, 2012). Furthermore, Martin and Bosque (2008) found significant difference in image of destination among tourists with different travel motivation.

Beside tourism, researchers in other sectors have also identified motivation as an important factor of perception. Bruner and Goodman (1947) in their experimental study found positive effect of motivation on perception. This relationship was further refined by Balcetis and Dunning (2006), after a series of experimental work they concluded that in an environment of uncertainty and ambiguity, people form a perception, which facilitates their motivation positively. More simply, it means that individuals who had not actually visited a particular destination in the past form a perception about that destination on the basis of their motivation to visit that destination. On the basis of above studies, we can posit that travel motivation positively affect destination image (Perception) of the tourist, and thus our first hypothesis is as follows:

Hypothesis a1: Travel motivation of tourists significantly affects destination image.

Hypothesis o1: Travel motivation of tourists does not significantly affect destination image.

Travel Motivation and Tourists’ Attitude Toward the Destination

Attitude has been defined by Fishbein and Ajzen (1975) as learned predisposition to respond in a consistently favorable or unfavorable manner with respect to a given object. Theoretically, Ajzen (1991) identified a condition necessary to arose or modify an attitude. He also suggested that motivation precedes attitude and the former may influence the latter. Within the field of tourism, very few studies have investigated the relationship between travel motivation and tourists’ attitude (e.g., C. H. C. Hsu, Cai, & Li, 2010; Huang & Hsu, 2009; Lam & Hsu, 2004). Lam and Hsu (2004) applied theory of planned behavior in a tourism context to explain the relationship between travel motivation and tourists’ attitude toward a destination. According to them, tourists’ attitude toward a destination is determined by his or her behavioral belief about the push and pull motivations to travel. They further concluded that higher the behavioral belief of push and pull motivation, the more positive and favorable will be the tourists’ attitude toward the destination. Researchers have also applied the expectation motivation and attitude model to better understand the relationship between travel motivation and tourists’ attitude (C. H. C. Hsu et al., 2010, Wong, Cheung, & Wan, 2013), wherein they revealed positive impact of travel motivation on tourists’ attitude toward visiting the destination. Huang and Hsu (2009) found significant effect of novelty and relaxation motivation on tourists’ attitude toward revisiting Hong Kong, as a destination. However, the effect of knowledge motivation was insignificant, which was because, after visiting a particular destination people acquire ample knowledge about that destination, and the knowledge factor does not remain a motivation for them any more to visit that particular destination. Based on these arguments, we formulate our second hypothesis as follows:

Hypothesis a2: Travel motivation has significant effect on tourists’ attitude toward the destination.

Hypothesis o2: Travel motivation does not significantly affect tourists’ attitude toward the destination.

Destination Image and Tourists’ Attitude Toward the Destination

Chen and Tsai (2007) affirmed previous studies which posits that a tourist’s attitude toward a destination is significantly affected by the image of the destination among tourists. According to Kim and Richardson (2003), destination image affects tourism-related attitudes and behaviors by confirming/reinforcing existing attitudes, creating new attitudes, or by changing the existing perception or attitude. Furthermore, Kim and Stepchenkova (2015) found a significant impact of organic image of destination on tourists’ attitudes toward the said destination. Furthermore, Jalilvand et al. (2012) found a positive and significant impact of destination image on tourist’s attitude toward destination. These arguments signify that the more positive the image of destination among tourists, the more favorable will be their attitude toward the destination, and hence, we formulate and posit our third hypothesis as follows:

Hypothesis a3: Destination image significantly affects tourists’ attitudes toward the destination.

Hypothesis o3: Destination image does not significantly affect tourists’ attitudes toward the destination.

Travel Motivation, Destination Image, and Tourists’ Attitude Toward Destination

Travel motivation is a tourist’s belief about fulfilment of internal desires of travel and experience of certain attributes, which they value and culminates with them visiting a particular destination. Motivation with respect to a particular behavior has been identified as a significant predictor of perception about behavior in tourism as well as other sectors. Specifically, in the context of tourism, Baloglu and McCleary (1999) had identified positive effect of stimulus and personal factors on destination image. Furthermore, image of the destination held by tourists have significant effect on tourist’s attitude toward destination (Kim & Stepchenkova, 2015). With respect to an indirect relationship, Jalilvand et al. (2012) found that information source (stimulus/pull factors) indirectly affects tourists’ attitudes toward destination through destination image. Zhou and Bao (2002), who had investigated process of consumer attitude formation, identified perception as an important mediator between the relationship of motivation and attitude. Therefore, we base and formulate our fourth hypothesis on the above arguments and posit as follows:

Hypothesis a4: Destination image mediates the relationship between travel motivation and tourists’ attitude toward the destination.

Hypothesis o4: Destination image does not mediate the relationship between travel motivation and tourists’ attitude toward the destination.

Research Design and Methodology

In terms of our research design and methodology, to make the research more objective and accurate, following steps have been followed.

Generation of Scale Items

Three constructs, that is, travel motivation, destination image, and tourists’ attitude toward destination have been used in the present study. For operationalizing these constructs, the items have been generated from different sources and processes such as reviewing the existing literature, detailed discussion with the subject experts, relevant academics, and a pilot survey (Table 1). The complete scale is presented in the appendix.

Table 1

Generation of Scale Items

No.	Construct/Dimensions	No. of Items	Source of Information
1	Travel motivation	55	Hanqin and Lam (1999); C. H. C. Hsu et al. (2010); Kozak (2002); Mutinda and Mayaka (2012)
2	Destination image	5	Martin and Bosque (2008)
3	Tourists’ attitude toward the destination	6	C. H. C. Hsu et al. (2010); Lam and Hsu (2004)

Sampling Technique and Data Collection

Nonprobability sampling technique, that is, purposive sampling has been used in the present study as only those peoples were contacted, who were visiting Ladakh as a tourist. To determine the sample size, a pilot survey was conducted on 70 respondents selected conveniently, who visited Ladakh during the month of June. The data collected was analyzed through descriptive statistics, that is, mean, standard deviation, and frequency distribution. Furthermore, formula of Burns and Bush (2005) has been used to decide the sample size.

{n = S}^{2} Z^{2} {/ e}^{2}

where n = sample size, Z = standard error (1.96) associated with the chosen level of confidence, S = variability indicated by an estimated standard deviation, e = amount of precision or allowable error in the sample. After determining the mean and SD from the pilot survey, the sample size was worked out at 254.

The final study has been carried out in our target location Ladakh. The target population for the study consisted of both international and national tourists, who visited Ladakh for tourism purpose. Since the population for the study was unknown, nonprobability sampling technique, that is, purposive sampling has been used for data collection. Data has been collected between July to September, as during this period, the flow of tourists in Ladakh region is high due to compatible weather conditions. For the purpose of data collection, questionnaires were distributed among tourists in the waiting halls of different hotels. Tourists, who visited Ladakh, were requested to spare some of their valuable time to fill the questionnaire presented to them. Those who agreed to cooperate were given the questionnaires with a request to fill and return back the same or latest, the next day. As a precondition, only first-time visitors have been contacted to avoid past experience effect. Four hundred questionnaires were distributed among tourists on their arrival at Ladakh, out of which 342 were returned (response rate = 85%). Furthermore, among the received questionnaires, 63 have been rejected because of incomplete information, which reduced the final number of usable questionnaires, for this study, to 279.

Data Analysis

Exploratory Factor Analysis

Multivariate technique (i.e., exploratory factor analysis) was used for summarizing the data in the study. The objective of using factor analysis is to summarize most of the original information in minimum number of factors. Therefore, principal component analysis along with varimax rotation was used. Factor analysis was conducted separately on all the constructs to comply with conceptual assumption of factor analysis (Hair, Anderson, Tatham, & Black, 2006).

Before conducting factor analysis, “Bartlet-test of sphericity” (BTS), a test for checking the presence of correlation, and “Kaiser’s Measure of Sampling Adequacy” (KMO) test for sampling adequacy were conducted. The result revealed that “KMO” was above (0.50) and value of “BTS” was also away from 0, which justified the application of factor analysis on the data (Hair et al., 2006).

Factors were extracted by using the criteria of Eigenvalue and variance explained. Only those factors were retained whose Eigenvalue is above 1 and cumulative variance explained was above the threshold limit of 50%. While conducting factor analysis, the decision regarding the retention of items for further analysis was made on the basis of factor loadings. Items with factor loading less than 0.50 as well as items that loaded on more than one factor were deleted (Hair, Black, Babin, Anderson, & Tatham, 2007). Factor analysis was applied on the three scales separately. The results are explained below.

Initially, the tourist motivation construct consisted of 55 items, which got reduced to 29 items in nine rounds of factor analysis. The retained items converged under eight factors namely escape, knowledge and places, religion and events, economic, self-realization, safety, relaxation, and natural beauty. Furthermore, these eight factors accounted for about 72% of variation, and Eigenvalue was greater than 1 for all the factors (Table 2).

Table 2

Summary of Exploratory Factor Analysis

Construct (Factor)	M	SD	FL	CFI	EV	VE (%)	KMO
Scales	3.62	0.872				61.533	.765
Travel motivation
Escape	3.85	0.921			3.332	11.490
Esc1	3.84	1.009	0.825	0.709
Esc2	4.19	0.782	0.755	0.621
Esc3	3.68	0.912	0.808	0.681
Esc4	3.71	0.968	0.719	0.658
Esc5	3.81	0.935	0.787	0.669
Knowledge and places	3.97	0.815			3.055	10.533
Se1	4.33	0.740	0.754	0.657
Se2	4.01	0.831	0.836	0.752
Se3	4.27	0.717	0.734	0.653
Dch1	3.75	0.869	0.744	0.672
Dch2	3.48	0.916	0.695	0.703
Religion	2.74	0.973		0.762	3.029	10.444
Rel1	2.66	0.957	0.847	0.837
Rel2	2.79	1.051	0.870	0.794
Rel3	2.67	1.036	0.830	0.527
Dch3	2.86	0.847	0.637
Economic	3.19	0.916			2.679	9.238
Ec1	3.19	0.945	0.876	0.794
Ec2	3.15	0.893	0.935	0.897
Ec3	3.24	0.910	0.916	0.878
Self-actualization	3.62	0.942			2.493	8.595
Self1	3.70	1.004	0.872	0.833
Self2	3.55	0.928	0.883	0.877
Self3	3.60	0.894	0.825	0.768
Safety	3.52	0.867			2.205	7.603
Ps1	3.63	0.818	0.787	0.701
Ps2	3.54	0.911	0.891	0.840
Ps3	3.38	0.856	0.812	0.696
Physical	3.87	0.801			2.201	7.591
Phy2	4.14	0.744	0.696	0.607
Phy4	3.66	0.812	0.777	0.708
Phy5	3.80	0.847	0.789	0.692
Natural beauty	4.24	0.742			1.880	6.483
Dch7	3.92	0.895	0.710	0.588
Dch8	4.21	0.733	0.739	0.671
Dch9	4.59	0.599	0.747	0.627
Destination image
Image	1.527	0.565			2.888	72.197	.808
Img1	1.61	0.609	0.693	0.480
Img2	1.44	0.528	0.899	0.808
Img3	1.55	0.578	0.897	0.804
Img4	1.51	0.545	0.892	0.796
Tourists’ attitude
Attitude	1.63	0.620			3.776	62.938	.854
Att1	1.50	0.559	0.771	0.595
Att2	1.74	0.681	0.752	0.565
Att3	1.69	0.600	0.808	0.653
Att4	1.60	0.617	0.805	0.649
Att5	1.57	0.608	0.821	0.674
Att6	1.70	0.654	0.800	0.640

Note: FL = factor loading; CFI = comparative fit index; EV = Eigenvalue; VE = variance explained; KMO = Kaiser’s Measure of Sampling Adequacy.

Earlier destination image construct consisted of five items. One item got deleted because of low loading (<0.50). The remaining four items converged under single factor explaining about 72% of total variance. Furthermore, Eigenvalue has arrived at 2.88 (Table 2).

The scale measuring attitude toward destination comprised six items. All the items converged under one factor. No item was deleted as all the items have factor loading greater than 0.50. The total variance explained by this construct arrived at 63% with good Eigenvalue (3.776; Table 2).

Scale Validation: Confirmatory Factor Analysis (CFA)

CFA is used to provide a confirmatory test to the measurement theory. It is a way of testing how well measured variable represent a smaller number of constructs. In CFA, researcher has to assign variables to each factor on the basis of preconceived theory. Thus, CFA statistics tell us how our specification of the factor matches reality, that is, the actual data. In the present study, CFA was performed to assess fitness, reliability, and validity of latent constructs. Zero-order factor models have been prepared for single dimension constructs and first-order and second-order model have been designed for multidimension constructs (Hair, Black, Babin, & Anderson, 2009). During CFA, items with standardized regression weights (SRW) less than 0.5 were deleted (Hair et al., 2007). The detailed CFA for the three constructs is to follow next.

Travel motivation. First-order CFA has been applied on 29 items retained after exploratory factor analysis. After applying CFA one item, that is, Esc4, got deleted because of low SRW. The remaining items are loaded adequately on their respective latent construct (SRW > 0.50). The model yielded average fit (χ²/degrees of freedom [df] = 2.122, root mean square residual [RMR] = 0.052, goodness-of-fit index [GFI] = 0.852, adjusted goodness-of-fit index [AGFI] = 0.813, normed fitness index [NFI] = 0.833, comparative fit index [CFI] = 0.903, and root mean. square error of. approximation [RMSEA] = 0.066). Furthermore, all the latent constructs are correlated with each other but are still distinct as the correlation values are less than 0.50, so multicollinearity is not the problem (Tabachnick & Fidell, 2007). Furthermore, second-order CFA has been applied after running first-order factor analysis. All the items are loaded adequately on their respective latent construct with SRW greater than 0.50. On the other hand, only two factors, that is, physical and self-actualization load adequately on the second layer latent construct “travel motivation.” The GFIs are average (χ²/df = 2.330, RMR = 0.073, GFI = 0.830, AGFI = 0.797, NFI = 0.806, CFI = 0.878, and RMSEA = 0.072). Additionally, comparison of first-order and second-order model has been done. The result of χ² test revealed that the two models are significantly different from each other (χ² = 113.281, p < .001). Furthermore, GFIs shows that first-order model is better than the second-order model. Therefore, first-order model has been accepted for further analysis.

Destination image. Zero-order factor model has been designed for four items that have been retained after exploratory factor analysis. All the items loaded adequately on the latent construct (SRW > 0.50). Furthermore, the model yielded good fit indices (χ²/df = 1.941, RMR = 0.005, GFI = 0.993, AGFI = 0.963, NFI = 0.993, CFI = 0.997, RMSEA = 0.060).

Attitude toward destination. In exploratory factor analysis, six items got converged under one factor. After applying CFA, two items got deleted because of low SRW (<.50). The remaining items loaded adequately on their latent construct and yielded excellent goodness-of-model fit (χ²/df = 1.854, RMR = 0.006, GFI = 0.993, AGFI = 0.964, NFI = 0.991, CFI = 0.996, RMSEA = 0.058).

Reliability and Validity

Reliability. The reliability of the scales was assessed through Cronbach’s alpha, which assesses the internal consistency of the scale (Hair et al., 2009). The alpha value for all the dimensions of travel motivation are above threshold limit of (.70) except for natural beauty (α = .660), which is very close to the standardized limit, indicating internal consistency of the scales. Furthermore, the reliability of destination image and tourists’ attitude toward destination scale were also good (.80; Table 3).

Table 3

Reliability and Validity Analysis

Scale	AVE	CR	α
Escape	0.917	0.968	.832
Knowledge and places	0.829	0.952	.832
Religion	0.919	0.932	.860
Economic	0.950	0.987	.919
Self-actualization	0.954	0.805	.891
Physical	0.800	0.965	.756
Natural beauty	0.840	0.865	.660
Safety	0.887	0.953	.807
Destination image	0.851	0.994	.863
Attitude toward destination	0.858	0.960	.838

Note: AVE = average variance; CR = squared correlation.

Before using the inferential analysis, assessed the validity and reliability of the construct with the help of CFA. To provide an assessment of the reliability, convergent, and discriminant validity of the measurement model, CFA was done by using the AMOS 16. Items with SRW less than 0.50 were deleted (Hair et al., 2009). The data have been examined for different types of validity. The detailed discussion is given below.

Validity: Face/content validity. It is the extent to which the content of the items is consistent with the construct (Hinkin, 1995). It has been established through existing literature on the subject, discussion with subject experts and bank managers.

Validity: Convergent validity. It refers to the degree to which two measures of constructs that theoretically should be related are in fact related. It tests the extent to which the covariances between the two measures are uniquely explained by the trait factor. Thus, items that are indicators of a specific construct should converge or share a high proportion of variance in common (Hair et al., 2009). Convergent validity got established as all standardized loadings are above 0.50 and variances extracted of the scales are also above 0.7 (Table 3).

Discriminant validity. It tests whether the concepts that are supposed to be unrelated are really unrelated. It has been proved by comparing average variance with squared correlation among different factors (Hair et al., 2009). The average variance extracted for all the factors is higher than the squared correlation, thereby proving discriminant validity of the factors (Table 4).

Table 4

Discriminant Validity

Factors	ESC	KNO & PLC	REL	ECO	SELF	SFT	PHY	NBT	IMG	ATT
ESC	0.912
KNO & PLC	(0.000049).007	0.852
REL	(0.021).148*	(0.119).346**	0.815
EECO	(0.173).417**	(0.026).162**	(0.064).253**	0.966
SELF	(0.126).356**	(0.005).071	(0.088).298**	(0.022).149*	0.617
SFT	(0.179).134*	(0.026).164**	(0.011).108	(0.019).138*	(0.003).057	0.898
PHY	(0.061).247**	(0.047).217**	(0.021).145*	(0.017).132*	(0.103).321**	(0.018).135*	0.928
NBT	(0.035).189**	(0.011).108	(0.024)−.155*	(0.012).111	(0.00003)−.006	(0.0841).290**	(0.086).294**	0.770
IMG	(0.015).123*	(0.031).178**	(0.011)−.109	(0.004)−.070	(0.0068)−.083	(0.068).261**	(0.012).112	(0.124).353**	0.979
ATT	(0.018).135*	(0.029).172**	(0.004)−.065	(0.0009).031	(0.0007).028	(0.043).208**	(0.024).156*	(0.061).248**	(0.394).628**	0.965

Note: ESC = escape; KNO & PLC = knowledge and places; REL = religion; Eco = economic; SELF = self-realization; SFT = safety; PHY = physical; NBT = natural beauty; IMG = destination image; ATT= tourists’ attitude toward destination. Values in bold, on the diagonal axis, represent average variance extracted and values in parenthesis represent squared correlation between the constructs.

p < .01. **p < .05.

Structural Equation Modeling (SEM)

After conducting CFA, the second step in SEM, that is, the structural path model has been analyzed to check various hypothesized relations.

Impact of travel motivation on destination image. Travel motivations are the desires of the tourists and attributes of the destination which makes an individual to take a vacation. Impact of each travel motivation on destination image has been assessed. Furthermore, covariances have been drawn between the independent variables in order to check multicollinearity and covariances are below the limit of 0.50 so multicollinearity is not the issue (Tabachnick & Fidell, 2007). The paths traced that among the eight travel motivation; that is, escape, knowledge and places, religion and events, economic, self-exploration, safety, physical, natural beauty, only four; that is, escape (SRW = 0.22, p < .050), knowledge and places (SRW = 0.23, p < .050), safety (SRW = 0.14, p < .05), and natural beauty (SRW = 0.24, p < .050) have positive and significant impact on destination image. Therefore, the first alternative hypothesis, that is, tourists’ motivation significantly effects destination image is partially accepted, which indicated that null hypothesis “tourists’ motivation does not significantly affect destination image” is rejected.

Impact of travel motivation on tourists’ attitude toward destination. Of all the dimensions of travel motivation, only three dimensions, that is, escape, knowledge and places, and safety, are positively and significantly affecting tourists’ attitude toward the destination. Knowledge and places is the most significant predictor of destination image (SRW = 0.20, p < .50) followed by escape (SRW = 0.16, p < .50) and safety (SRW = 0.15, p < .50). Hence, the alternative Hypothesis 2, travel motivation significantly effects tourists’ attitude toward destination is partially accepted and null hypothesis is rejected, the finding is in-line with C. H. C. Hsu et al. (2010).

Impact of destination image on tourists’ attitude toward destination. Destination image positively contributes to tourists’ attitude toward destination (SRW = 0.70, p < .001). Therefore, the alternative Hypothesis 3, that is, destination image significantly effects tourists’ attitude toward destination is accepted, which means null hypothesis is rejected.

Mediation effect of destination image between travel motivation and destination image. To assess the mediating role of destination image between dimensions of travel motivation and tourists’ attitude toward destination, mediation conditions of Baron and Kenny (1986) has been used in the present study. Those conditions were (a) predictor must have significant effect on the outcome variable, (b) predictor must have significant impact on mediator, (c) the mediator should affect the outcome variable significantly, (d) last, after introducing the mediating variable between the predictor and outcome variable, the direct impact of predictor on outcome becomes insignificant (full mediation). However, if the direct impact decreases then it is considered partial mediation. Furthermore, in order to comply with the aforementioned criteria only those dimensions of travel motivation have been considered in the mediation model, which have significant impact on destination image as well as tourists’ attitude toward destination.

As per earlier analysis there are three common dimensions of travel motivation that are affecting positively destination image as well as tourist’s attitude toward destination. So, when all three, that is, dependent, independent, and mediator were added together the result revealed that destination image fully mediates the relationship between dimensions of travel motivation; namely, escape, knowledge and places, and safety and tourists’ attitude toward destination, as the direct impact of travel motivation dimensions on tourist’s attitude toward destination became insignificant. The goodness-of-model fit is excellent (χ²/df = 2.019, RMR = 0.013, GFI = 0.951, AGFI = 0.913, NFI = 0.939, CFI = 0.968, RMSEA = 0.063). Furthermore, to assess the significance of indirect relationship, Sobel test statistics has been used. The result of Sobel test statistic revealed that travel motivations, that is, escape (SS = 3.304, p < .001), knowledge and places (SS = 2.707, p < .01), and safety (SS = 3.48, p < .001) indirectly affect tourists’ attitude toward destination through destination image.

Discussion and Conclusion

The present study has identified eight factors; namely, escape, knowledge and places, religion, economic, self-realization, safety, and physical and natural beauty, which have been empirically validated with the help of CFA.

With respect to relationship between the constructs, SEM results revealed that among the eight dimensions of travel motivation, only four; that is, escape, knowledge and places, safety, and natural beauty have positive and significant effect on destination image. Hence, the first alternative hypothesis “travel motivations significantly affect destination image” is partially accepted. The study revealed that motivation was key to the tourists to get away from home in order to escape from their mundane boring and busy schedule and to acquire knowledge about the destination, its culture, tradition, and different historical places. Tourists were also motivated by the natural beauty and safety character of the destination, which effected the image of the destination. Furthermore, partial acceptance of the hypothesis may be because of the reason that more than 50% of the respondents’ fall in two age groups; that is, 18 to 27 years (27%) and 28 to 37 years (35%). Descriptive statistics found that religion, economic, self-realization, and physical motivation of respondents in the above two age groups is low as compared with that of respondents in the higher age groups. Furthermore, tourists’ in lower age groups were less oriented toward religion and economic motivation. This reveals that high level of travel motivation for escape, knowledge and places, safety, and natural beauty leads to positive image of destination among tourists.

With respect to the relationship between tourists’ travel motivation and attitude toward destination, only three factors; that is, escape, knowledge and places, and safety significantly and positively effects tourists’ attitude toward destination. This finding is consistent with Lam and Hsu (2004) study. This may be because of the reason that the majority of tourists’ have high levels of knowledge and place, escape, and safety motivation as average mean values for the mentioned motivations are closer to four on the 5-point scale. This portrays that higher the level of motivation for escape, knowledge and places, and safety for visiting a particular destination, it leads to favorable attitude of tourists toward that destination. Furthermore, knowledge and place motivation emerged as most important factor among all the factors.

SEM result also indicated that destination image had a positive effect on tourists’ attitude toward destination. The study provides evidence that better image of the destination will lead to positive attitude formation. This finding is in line with Jalilvand et al. (2012) study. Results from this study further signifies that an improvement in overall image of a place held by an individual, leads to a positive attitude of tourists toward the destination.

With regard to indirect relationships, destination image is found mediating the relationship between travel motivation dimensions (namely, escape, knowledge and places, and safety) and tourists’ attitude toward destination. It suggests that belief of tourists’ visiting a particular destination leads to a fulfilment of their internal desires of travel and experience of certain attributes which they value, influences their perception about that particular destination positively, this positive perception in-turn then leads to the formation of a favorable attitude toward the said destination.

Empirical and Theoretical Contributions

Overall, this study contributes in the following ways. Empirically, first, this study has added to the existing knowledge domain of travel motivation. The scale of travel motivation, destination image and tourists’ attitude has been validated in an emerging country context, through an Indian tourist destination, Ladakh, in the state of Jammu and Kashmir. Second, this study evaluated the dimension-wise impact of travel motivation on destination image and tourists’ attitude toward the destination, which revealed that out of eight dimensions of travel motivation, natural beauty affects destination images the most. Similarly, knowledge and places affect the tourists’ attitude toward destination the most. Hence, these findings can help future researchers in pursuing this line of inquiry. Third, the present study helped identify the “black box” using destination image to understand travel motivation and tourists’ attitude toward destination relationship. Destination image has been empirically proved as mediator between travel motivation and tourists’ attitude toward destination. Theoretically, this study contributes by dually investigating; first, whether travel motivations help in building “positive destination image” (Gunn, 1972; Myers, 1968) and tourists’ attitude toward this emerging country tourist destination; and second, it explored the role played by destination image between travel motivation and tourists’ attitude toward destination. Additionally, we further utilize the “theory of planned behavior” (Ajzen, 1991), wherein we contextualize and examine how tourist’s attitudes describes the psychological tendencies expressed by positive or negative evaluation of their engagement in certain behavior.

To conclude, we argue that if tourism marketers want to reap the best fruits of travel motivation, they must enhance destination image, which can improve tourists’ attitude toward the destination. We reiterate on the fact that if tourism marketers were to reap the best fruits of travel motivation, they must enhance the destination image, which can improve tourists’ attitude toward the destination. In this context, tourism marketers could hire celebrities as brand ambassadors for promoting Ladakh as a tourists’ destination choice. An interesting example is that of the famous Bollywood actor Aamir Khan, who has showcased Ladakh in his movie “Three Idiots” and thereby immensely increased the popularity for this fairly unknown destination. Furthermore, they could provide online platforms for showcasing Ladakh, through portraying facilities like hotels, guest houses, and so on, as it is well known that such initiatives help improve the destination image.

Practical Implications

This study has several implications which are important for tourism marketers and planners. These are discussed next.

Tourism department and tourism marketers in Ladakh should undertake promotion of events like Sindhu festival, Ladakh festival, and Kargil/Zanskar festival as these festivals are complete showcase the cultural and regional aspects of Ladakh’s custom and tradition. The tourism marketers should also have well-trained and well-educated tourist guides having complete knowledge of historical places, customs, and traditions of Ladakh. Furthermore, the tourism department (Ladakh Tourism) and marketers should motivate people of the region to value and preserve their old culture and tradition for future generations.

The tourism department and the marketers in Ladakh should also provide better facilities (such as better infrastructure, hotel facilities, etc.) to tourists for keeping them motivated to travel. This will lead to upgradation in destination image and foster recommendation given to others to visit the same place, which enhances the belief of potential tourists about fulfillment of their internal needs and experience of certain attributes by visiting Ladakh.

Tourism departments and tourism marketers should also make more efforts to focus on escape, knowledge and places, safety, and natural beauty to attract more tourists and to ensure tourists’ repeat their visit to the destination. Ladakh, as compared with similar tourist destinations across the world, is situated on a high plateau (3,000 m) having lot of potential for adventure tourism, like trekking, river rafting, mountaineering, bike riding, and so on, that can be achieved through strategic advertisement on national as well as international platforms. Such initiatives will have to promote adventure tourism in this region in a better way. Marketers should also advice the government to invest in the infrastructure of the region to cope with these activities. Videos of the same can then be circulated on the social media platform to give a large circulation of the adventure tourism’s opportunity available at Ladakh in order to promote destination image. Furthermore, training should be provided by the tourism department to various tour operators (portrayers, taxi owners/drivers) about how to reach and make the tourists comfortable at Ladakh. Though Ladakh is very beautiful in term of its natural beauty, however, there are weather and locational acclimation challenges that existing tourists face. In this context, proper awareness should be created among the tourists about how to deal with the local weather conditions of Ladakh. The tourism departments of the region will need to promote the natural beauty and safety characteristic of Ladakh so as to build high level of positive image of Ladakh, among potential tourists, which in turn will positively lead to increase in flow of tourists to the region.

In summary, tourism marketers should pay attention to develop a long-lasting cognitive image (quality experience), affective, and unique image of the destination. Cognitive image (quality experience) can be enhanced by developing cognitive aspects of the destination such as providing pleasant and good environment, maintaining beautiful scenery, and maintaining high standard of hygiene and clean environment. Affective image can be improved by creating restful and relaxing atmosphere, maintaining natural beauty and parks situated in the state, use visual recordings (through the medium of movies and television), and so on. Similarly, its unique image can be improved by developing and portraying its local culture and way of life, increasing advertisement of unique craftsmanship and traditional foodstuffs, unique physical appearance, and so on. Tourism marketers/government should also concentrate on designing strategies to upgrade/build hotels, tourist houses, provide hygienic food and drinking arrangements at reasonable price, and improve infrastructure facilities that help improve the tourists’ attitude toward destination.

Limitations and Future Research

All the precautionary efforts were made to ensure the objectivity, reliability, and validity of the study, yet certain limitations were discovered. These limitations can be overcome in future research. First, this study is cross-sectional in nature and in future different ways of conducting similar research will need to be explored. Second, purposive sampling technique has been used in the study, wherein only first time visitors were included in the study. In future, comparative analysis of travel motivations and effect of those motivations on destination image, tourist attitude, among first time and repeated visitors can be assessed. Third, only two outcomes of travel motivation, that is, destination image and tourists’ attitude toward destination, have been studied; other variables (destination loyalty; destination satisfaction) should be considered in a similar context in future research. Last, fourth, our study is geographically limited to the Ladakh region of Jammu and Kashmir (India), it would be interesting in future that other locations of hospitality and tourism be considered, especially from an emerging market perspective, such as India.

Concluding Summary

In conclusion, this research aimed at exploring the relationship between travel motivation and tourists’ attitudes toward a destination; in this case, the Ladakh region of Jammu and Kashmir (India). The aim of this study was also to assess the mediating role played by destination image between travel motivation and tourists’ attitudes toward destination. Utilizing SEM, we tested our hypothesized relations. We did this through two theoretical lenses: theory of image and theory of planned behavior. Our key findings revealed a positive relationship between tourists’ travel motivations and their attitudes toward the destination, which is mediated by destination image. Overall, this study contributes by signifying that tourism marketers need to make every possible effort to enhance the travel motivation of tourists, so as to build positive images and favorable attitudes of tourists toward the destination.

Footnotes

Appendix

Variables	Items
You came to Ladakh to:
Travel motivation	Escape from your boring environment
	Take break from your busy schedule
	Get away from your home area
	Reduce psychological stress
	Escape from your ordinary life
	Explore yourself
	Know more about yourself
	Have an authentic experience about yourself
	Rest and relaxation
	Refresh yourself emotionally and physically
	Enjoy good weather
	Remain healthy and fit
	Get physically active
	Know about different culture and tradition
	Get knowledge of historical monuments
	Get knowledge about the destination
	Learn new things
	Experience new and different life style
	Visit a place that you have not visited before
	Experience new destination
	Do things which are not possible in any routine life
	Seek adventure
	Seek entertainment
	Spend good time with your family
	To get the family members more close to each other
	To develop love and affection among the family members
	Spend good time with your friends
	To get the friends more close to each other
	To develop love and affection among the friends
	Enhance your social group
	Meet with new peoples
	Attend religious events and festivals
	Gain spirituality
	Get closer to god
Before visiting Ladakh to what extent the following things about Ladakh attracted you toward Ladakh?
	Building and places of historical and archeological importance
	Buildings and places of religious importance
	Sindu Festival/Kala Chakara
	Different and unique atmosphere
	Easy to access
	Hygiene and cleanliness
	Unpolluted environment
	Nice weather
	Outstanding scenery
	Adventure sports and activities
	It suits my household budget
	Reasonable transportation charges
	Reasonable accommodation charges
	It provides value for your holiday money
	The best economic deal
	Good accommodation facility
	Good transportation facility
	Other facilities (Internet, PCO, STD, etc.)
	No civil disturbance
	No terrorism activities
	Low criminal rate
Before your actual visit what was your thinking about Ladakh?
Destination image	As a travel destination Ladakh has a most distinctive character
	Ladakh is a beautiful tourist destination
	Ladakh is an exciting tourist destination
	Ladakh is an interesting tourist destination
	Ladakh is an arousing/touching tourist destination
Tourists attitude toward the destinations	Ladakh is a very good place to visit
	Ladakh is valuable place
	Ladakh is very pleasant tourist destination
	You like Ladakh as a tourist destination
	You have positive attitude toward Ladakh
	Ladakh is a favorable destination to visit

Author’s Note

Vijay Pereira is now affiliated with NEOMA Business School, Reims Campus, France.

ORCID iD

Vijay Pereira

Vijay Pereira (vijay.pereira@port.ac.uk) is an associate professor (International and Strategic HRM) at Khalifa University, Abu Dhabi, UAE. Jeevan Jyoti Gupta (jyotigupta64@rediffmail.com) is an assistant professor at University of Jammu, India. Shabir Hussain (shabir111991@gmail.com) is an assistant professor at the Government Degree College, Leh, Jammu and Kashmir, India.

References

Ajzen

(1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179-211.

Akdag

Guler

Dalgic

Benli

Cakici

A. C.

(2018). Do tourists’ gastronomic experiences differ within the same geographical region? A comparative study of two Mediterranean destinations: Turkey and Spain. British Food Journal, 120, 158-171.

Awaritefe

(2004). Motivation and other considerations in tourist destination choice: A case study of Nigeria. Tourism Geographies, 6, 303-330.

Balcetis

Dunning

(2006). See what you want to see: Motivational influences on visual perception. Journal of Personality and Social Psychology, 91, 612-625.

Baloglu

McCleary

(1999). A model of destination image formation. Annals of Tourism Research, 26, 868-897.

Baloglu

Uysal

(1996). Market segments of push and pull motivations: A canonical correlation approach. International Journal of Contemporary Hospitality Management, 8, 32-38.

Beerli

Martin

J. D

. (2004). Tourist’s characteristics and the perceived image of tourist destinations: A quantitative analysis: A case study of Lanzarote, Spain. Tourism Management, 25, 623-636.

Björk

Kauppinen-Räisänen

(2017). A destination’s gastronomy as a means for holiday well-being. British Food Journal, 119, 1578-1591.

Boulding

K. E.

(1956). The image: Knowledge and life in society. Ann Arbor: University of Michigan Press.

10.

Bresciani

Thrassou

Vrontis

(2015). Determinants of performance in the hotel industry: An empirical analysis of Italy. Global Business and Economics Review, 17, 19-34.

11.

Bruner

J. S.

Goodman

C. C.

(1947). Value and need as organizing factors in perception. Journal of Abnormal Social Psychology, 42, 33-44.

12.

Burns

A. C.

Bush

R. F.

(2005). Marketing research: Online research applications (4th ed.). Upper Saddle River, NJ: Prentice Hall.

13.

Cardoso

Araújo Vila

de Araújo

A. F.

Dias

(2019). Food tourism destinations’ imagery processing model. British Food Journal. Advance online publication. doi:10.1108/BFJ-08-2018-0557

14.

Chen

Tsai

(2007). How destination image and evaluative factors affect behavioral intention. Tourism Management, 28, 1115-1122.

15.

Chon

K. S.

(1989). Understanding recreational traveler’s motivation attitude and satisfaction. Tourist Review, 44(1), 3-6.

16.

Crompton

J. L.

(1979). Motivations for pleasure vacation. Annals of Tourism Research, 6, 408-424.

17.

Enzenbacher

D. J.

(2019). Exploring the food tourism landscape and sustainable economic development goals in Dhofar Governorate, Oman: Maximising stakeholder benefits in the destination. British Food Journal. Advance online publication. doi:10.1108/BFJ-09-2018-0613

18.

Fishbein

Ajzen

(1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Boston, MA: Addison-Wesley.

19.

Foster

(2014). Student destination choices in higher education: Exploring attitudes of Brazilian students to study in the United Kingdom. Journal of Research in International Education, 13, 149-162.

20.

Greater Kashmir. (2017). Retrieved from http://epaper.greaterkashmir.com/epaperpdf/6102017/6102017-md-hr-12.pdf

21.

Gunn

(1972). Vacationscape: Designing tourist region. University of Texas at Austin, TX: Bureau of business Research.

22.

Hair

J. J. F.

Anderson

R. E.

Tatham

R. L.

Black

W. C.

(2006). Multivariate data analysis (5th ed.). Noida, Uttar Pradesh, India: Dorling Kindersley.

23.

Hair

J. J. F.

Black

W. C.

Babin

B. J.

Anderson

R. E.

(2009). Multivariate data analysis (7th ed.). Upper Saddle River, NJ: Prentice Hall.

24.

Hair

J. J. F.

Black

W. C.

Babin

B. J.

Anderson

R. E.

Tatham

R. L.

(2007). Multivariate data analysis (6th ed.). Upper Saddle River, NJ: Prentice Hall.

25.

Hanqin

Z. Q.

Lam

(1999). An analysis of mainland Chinese visitors’ motivations to visit Hong Kong. Tourism Management, 20, 587-594.

26.

Hinkin

T. R.

(1995). A review of scale development practices in the study of organizations. Journal of Management, 21, 513-524.

27.

Hsu

C. H. C.

Cai

L. A.

(2010). Expectation, motivation, and attitude: A tourist behavioral model. Journal of Travel Research, 49, 282-296.

28.

Hsu

T. Z. K.

Tsai

Y. F.

H. H.

(2009). The preference analysis for tourist choice of destination: A case study of Taiwan. Tourism Management, 30, 288-297.

29.

Huang

S. S.

Hsu

C. H. C.

(2009). Effects of travel motivation, past experience, perceived constraint, and attitude on revisit intention. Journal of Travel Research, 48, 29-44. doi:10.1177/0047287508328793

30.

Hung

Petrick

J. F.

(2011). Why do you cruise? Exploring the motivations for taking cruise holidays, and the construction of a cruising motivation scale. Tourism Management, 32, 386-393.

31.

Jalilvand

M. R.

Samiei

Dini

Manzari

P. Y.

(2012). Examining the structural relationship of electronic word of mouth, destination image, tourist attitude toward destination and travel intention: An integrated approach. Journal of Destination Marketing & Management, 1, 134-143.

32.

Jango

S. S.

C. M. E.

(2006). Seniors’ travel motivation and the influential factors: An examination of Taiwanese seniors. Tourism Management, 27, 306-316.

33.

Kassean

Gassita

(2013). Exploring tourists push and pull motivations to visit Mauritius as a tourist destination. African Journal of Hospitality, Tourism and Leisure, 2(3), 12-27.

34.

Kim

Richardson

S. L.

(2003). Motion picture impacts on destination images. Annals of Tourism Research, 18, 278-291.

35.

Kim

Stepchenkova

(2015). Effect of tourist photographs on attitudes towards destination: Manifest and latent content. Tourism Management, 49, 29-41.

36.

Kozak

(2002). Comparative analysis of tourist motivations by nationality and destinations. Tourism Management, 23, 221-232.

37.

Lam

Hsu

C. H. C.

(2004). Theory of planned behavior: Potential travelers from China. Journal of Hospitality & Tourism Research, 28, 437-461.

38.

Lam

Hsu

C. H. C.

(2006). Predicting behavioral intention of choosing a travel destination. Tourism Management, 27, 589-599.

39.

Lawson

Baud-Bovy

(1977). Tourism and recreational development. London, England: Architectural Press.

40.

Lee

T. H.

(2007). Ecotourism behavioural model of national forest recreation areas in Taiwan. International Forestry Review, 9, 771-785.

41.

Lee

T. H.

(2009). A structural model to examine how destination image, attitude, and motivation affect the future behavior of tourists. Leisure Sciences: An Interdisciplinary Journal, 31, 215-236.

42.

Martin

H. S.

Bosque

I. A. R. D

. (2008). Exploring the cognitive-affective nature of destination image and the role of psychological factors in its formation. Tourism management, 29, 263-277.

43.

Martineau

(1958). The personality of the retail store. Harvard Business Review, 36(1), 47-55.

44.

McGuiggan

Emerson

Glaser

(1995). Can personality be used to predict vacation choice? Proceedings: World Marketing Congress, 7(1), 67-74.

45.

Mill

Morrison

(1985). The tourism system, an introductory text. Upper Saddle River, NJ: Prentice Hall.

46.

Mountinho

(1987). Consumer behavior in tourism. Journal of Marketing, 21(10), 1-44.

47.

Mutinda

Mayaka

(2012). Application of destination choice model: Factor influencing domestic tourists’ destination choice among resident of Nairobi, Kenya. Journal of Tourism Management, 33, 1593-1597.

48.

Myers

J. G.

(1968). Consumer image and attitude. Berkeley: Institute of Business and Economic Research, University of California.

49.

Nesbit

W. R.

(1973). The art of forecasting domestic air travel: A survey assessment and overview. In Fourth Annual Conference Proceedings, the Travel Research Association (pp. 285-290). Salt Lack city, UT: Travel Research Association.

50.

Ozek

Ferraris

(2018). The role of self-awareness and self-efficacy on career decision-making: An innovative perspective. In Innovation and capacity building (pp. 207-229). Cham, Switzerland: Palgrave Macmillan.

51.

Pelliciardi

(2010). Tourism traffic volumes in Leh district: An overview. Ladakh Studies, 26, 14-23.

52.

Said

Maryono

(2018). Motivation and perception of tourists as push and pull factors to visit national park. Web Conferences, 31, 08022. doi:10.1051/e3sconf/20183108022

53.

Sanchez-Cañizares

Castillo-Canalejo

A. M.

(2015). A comparative study of tourist attitudes towards culinary tourism in Spain and Slovenia. British Food Journal, 117, 2387-2411.

54.

Sato

Kim

Buning

R. J.

Harada

(2018). Adventure tourism motivation and destination loyalty: A comparison of decision and non-decision makers. Journal of Destination Marketing & Management, 8, 74-81.

55.

Seo

Yun

(2015). Multi-dimensional scale to measure destination food image: Case of Korean food. British Food Journal, 117, 2914-2929.

56.

Sparks

(2007). Planning a wine tourism vacation: Factors that help to predict tourist behavioral intentions. Tourism Management, 28, 1180-1192.

57.

Tabachnick

B. G.

Fidell

L. S.

(2007). Using multivariate statistics (5th ed.). New York, NY: Allyn & Bacon.

58.

Thrassou

Vrontis

Bresciani

(2014). Strategic reflexivity in the hotel industry: A value-based analysis. World Review of Entrepreneurship, Management and Sustainable Development, 10, 352-371.

59.

Toudert

Bringas-Rábago

N. L.

(2019). Destination food image, satisfaction and outcomes in a border context: Tourists vs. excursionists. British Food Journal, 121, 1101-1115.

60.

Veen

R. V. D.

Song

(2014). Impact of the perceived image of celebrity endorse on tourists’ intention to visit. Journal of Travel Research, 53, 211-224.

61.

Vincent

V. C.

Thompson

W. T.

(2002). Assessing community support and sustainability for ecotourism development. Journal of Travel Research, 41, 153-160.

62.

Vrontis

Bresciani

Giacosa

(2016). Tradition and innovation in Italian wine family businesses. British Food Journal, 118, 1883-1897.

63.

Wong

Cheung

Wan

(2013). A study of travel expectation, motivation, attitude. Contemporary Management Research, 9, 169-186.

64.

C. W.

(2015). Foreign tourists’ intentions in visiting leisure farms. Journal of Travel Research, 68, 757-762.

65.

Zhou

Bao

(2002). Users attitudes toward web advertising: Effects of Internet motivation and Internet ability. NA: Advances in Consumer Research, 29, 71-78.