First-Time Versus Repeat Travellers: Perceptions of the Destination Image of Thailand and Destination Loyalty

1. Introduction

Many destinations worldwide rely heavily on tourists’ future behavioural intention, which is frequently conecptualised as loyalty (Afshardoost & Eshaghi, 2020). Hence, comprehending the complex relationship between cognitive and affective image is vital for understanding tourists’ observations of a destination (Woosnam et al., 2020). Consequently, tourism destination strive to increase first-time and repeat travellers to their attractions (Rather et al., 2022).

Cognitive image is travellers; knowledge and beliefs regarding a destination. Affective image relates to travellers’ emotions regarding the features of a destinations (Woosnam et al., 2020). The affective and cognitive images are crucial in constructing travellers’ travel decisions and destination-linked behaviour (Guo & and Pesonen, 2022). Perceptions tend to be influenced by experiences, general impressions, and cultural backgrounds (Zou & Yu, 2022). Cognitive and affective images interplay to affect the intent of first-time travellers to endorse a destination and the revisit intention of repeat travellers, and constitute destination loyalty (Lu et al., 2023). Several researchers have investigated the effects of destination image on first-time and repeat visitor behaviours (Lu et al., 2023; Qu et al., 2025; Yoo & Katsumata, 2022).

Destination loyalty integrates travellers’ revisit intention and endorsement intention regarding the destination and is a major marker of its long-term success (C. Li et al., 2023). Frequently, first-time travellers are inspired by novelty (eager for new or different experiences), which creates their travel-connected inspirations and experiences (Y. Zhang et al., 2021). Contrastingly, loyalty (contingent on service quality, brand relationships, and memorable experiences) influences repeat travellers (Tabaeeian et al., 2023). Loyalty and novelty increase travellers’ satisfaction, encourage revisits, and generate word-of-mouth (WOM) that is facourable (Serra-Cantallops et al., 2020).

Thailand has a good climate, beautiful beaches, cultural heritage richness, hospitality that is warm, and all-year tourism potential (Mustafa et al., 2020). The arrival of travellers has ranked Thailand among the top 10 most liked countries worldwide, where there were 39.8 million tourist entries in 2024 (United Nations World Tourism Organization [UNWTO], 2024). Furthermore, Thailand is the leading destination in Southeast Asia. Studies on the Thailand and travellers’ destination loyalty are limited (Erawan, 2020). Therefore, comprehending the effects of tourist’ perceptions of the features of Thailand (cognitive image) and emotional experiences (affective image) on their intent to revisit or endorse Thailand (destination loyalty) is crucial for maintaining its long-term economic and competitive success in global tourism (Duong et al., 2024).

This study bridged the above gap in knowledge through the cognitive-affective-behavioural (CAB) model and investigated the interplay between cognitive, affective, and behavioural processes. This study investigated the cognitive and affective component differences in repeat and first-time travellers’ observations of the destination image of Thailand, and included their intent to revisit or recommend it. Data were obtained from international travellers. Multigroup analysis (MGA) was done with partial least squares-structural equation modelling (PLS-SEM). The MGA is an advanced analytical method that evaluates the differences between sub-groups within identical models (Troiville et al., 2025). Most of the results were interpreted based on a single-population analysis. This study presented a significant methodological contribution as it examined direct and indirect effects across different groups. The results provides valuable understandings for tailoring strategies by destination marketing organisations and policymakers and increasing the appeal of Thailand to varied visitor sectors.

2. Literature Review

2.1. The CAB Model

The CAB model defines the interactions between cognitive, affective, and behavioural processes to comprehend and forecast human behaviour (Lifshitz, 2020). The model underlines the role of the cognitive dimension in affecting behaviour. Simultaneously, the model recognizes that emotion mediates decision-making (X. Zhou et al., 2023). The model tests the supposition of rational decision-making (S. Li et al., 2022) and is used in marine environmental protection (Lin & Tsao, 2023), smart tourism technology (Chang, 2022), and consumer behaviour (Q. Zhang et al., 2024). Nevertheless, its use in tourism destination is limited. In this study, the framework examined tourists’ travel intentions concentrating on cognitive and affective factors (Wang et al., 2020). The CAB model was used to combine the destination image of Thailand and enhance the understanding of international tourists’ behaviours regarding revisiting and recommendation.

2.2. Destination Image

Destination image is defined as “a set of impressions, ideas, expectations, and emotional thoughts an individual has of a specific place” (Stylos et al., 2016, p. 42). Destination image includes the cognitive image (assesses destination qualities) and the affective image (indicates emotional responses or inspirations) (Casali et al., 2021; Fu & Timothy, 2021; Stylidis, 2022). Cognitive and affective images are involved in determining tourists’ perceptions and intent to visit, revisit, or endorse a destination (X. Zhou et al., 2024). The interaction between these dimensions emphasises the effects of rational assessments and emotional connections (M.-S. Kim et al., 2018). The destination perceptions of tourists are frequently formed by integrating cognitive and affective aspects (Afshardoost & Eshaghi, 2020; Guo & and Pesonen, 2022), which forms and inclusive overview that influences their overall view. Positive experiences (meaningful links) enhance connections to destinations and encourage positive impressions (Wu et al., 2021).

Baloglu and McCleary (1999) described the hierarchical link between cognitive and affective images, where cognitive assessments occurred before emotional responses. Various researchers have examined this relationship and emphasized the effects of cognitive valuations on affective responses. For example, Woosnam et al. (2020) reported that affective perceptions were substantially affected by cognitive images. Lam et al. (2024) established that cognitive and affective heritage images were positively linked. Munanura et al. (2024) established that positive cognitive and emotional states were connected, which improved tourism supports.

2.3. Destination Loyalty

Destination loyalty is widely investigated in tourism and involves attitude and behaviour (J. Zhang & Walsh, 2020). Behavioural loyalty refers to the actions of tourist (destination revisits). Attitudinal loyalty places importance on emotional commitment and an attitude that is positive in relation to a destination (Liu et al., 2016; M. Zhou & Yu, 2022). The post-visit attitudinal loyalty gauges include the intention to endorse and WOM, which are important in tourism (Palau-Saumell et al., 2016). Tourism relies greatly on loyalty as it motivates revisit and endorsement decisions (Kanwel et al., 2019). Furthermore, loyalty relies on trust and perceived experiences, which construct the destination cognitive and affective images and affect loyalty (Al-Ansi & Han, 2019; Stylidis, 2022). Revisits, WOM, and electronic recommendations are characteristics of behavioural loyalty, which is frequently connected to tourist experiences that are positive (Kani et al., 2017; Loureiro et al., 2021; Yadav et al., 2021). Comprehending loyalty-promoting factors can aid destinations in creating more in-depth links with travellers and guaranteeing success in competitive tourism regions.

2.4. Revisit Intention

The retention of current customers is substantially advantageous economically, as gaining new customers can be 5-10 times costlier (Xu et al., 2021). A 5% rise in customers who are loyal can grow profit by 25-85% (Lentz et al., 2022). These principles are related to tourism, where experiences that are positive inspire revisiting. The revisit intention is the predisposition of tourists to return to a destination, which is typically created by their affective and cognitive perceptions (Liao et al., 2021). The effects of destination affective and cognitive images on revisit intention have been underscored in numerous studies. Carvalho (2022) and Rasoolimanesh et al. (2025) reported that cognitive images positively affected the revisit intention. Liang and Xue (2021) highlighted the function of affective images in encouraging revisits. These results underscored the importance of augmenting the rational and emotional characteristics in relation to a destination to inspire revisits.

2.5. Intention to Recommend (WOM)

Positive experiences frequently produce informal endorsements that affect the behaviour of potential tourists (Y.-F. Chen & and Law, 2016). The WOM is “informal communication directed at other consumers about the ownership, usage, or characteristics of particular goods and services” (Westbrook, 1987, p. 261) and is a persuasive tourism tool. The WOM promotes trust and emotional links, which enhance the credibility perception of the source of information (Hayes et al., 2016). Hence, WOM is a persuasive external source of information in tourism, where it constructs the attitudes of tourists (Litvin et al., 2008).

Tourists’ experiences and their destination image perceptions are closely linked. A positive destination image improves satisfaction and intensifies the possibility of endorsing the destination to others (Cubillas-Para et al., 2023). Prayag et al. (2017) determined that perceptions of sustainability substantially improved tourist satisfaction and WOM intent. Furthermore, residents with positive perceptions of events are also likelier to endorse their city (Chen et al., 2018). Tourists who are satisfied are also likelier to share feedback that is positive and inspire visits from other tourists (Manthiou et al., 2017; Prayag et al., 2017).

The WOM-linked behaviours of repeat and first-time travellers differ noticeably. Šagovnović and Kovačić (2020) reported that first-time travellers frequently pursued novelty and assurance, which affected their observations and endorsements. Contrastingly, familiarity and satisfaction promoted loyalty in repeat travellers. Therefore, knowledge of these dynamics can ais destination strategy modification in response to varied visitor sectors and amplify the effects of WOM.

Few studies have investigated the effects of destination affective and cognitive images on loyalty and the revisit or endorsement intent in relation to Thailand. This study addressed the knowledge gap by investigating these connections using the CAB model, where internation tourists’ perceptions were referenced and these dynamics were examined through the following hypotheses (H):

H1: First-time and repeat travellers have significantly differing perceptions of the effects of the cognitive destination image of Thailand on the affective destination image.

H2: First-time and repeat travellers have significantly differing perceptions about the effects of the cognitive destination image of Thailand on the intent to revisit.

H3: First-time and repeat travellers have significantly differing perceptions about the effects of the cognitive destination image of Thailand on the intent to recommend.

H4: First-time and repeat travellers have significantly differing perceptions about the effects of the affective destination image of Thailand on the intent to revisit.

H5: First-time and repeat travellers have significantly differing perceptions about the effects of the affective destination image of Thailand on the intent to recommend.

H6: First-time and repeat travellers have significantly differing perceptions about the cognitive and affective components of the destination image of Thailand and intent to revisit and endorse the destination.

This study extended the CAB model to address international tourists’ perceptions about the affective and cognitive destination images, and behavioural loyalty. Figure 1 illustrates the conceptual model.

3. Methodology

3.1. Instrument Development

The questionnaire survey included sections on the respondents’ demographic characteristics (marital status, gender, education level, age, and monthly income), cognitive and affective image aspects, intent to revisit, and intent to recommend. All constructs were measured using a Likert scale of five points [1 (“strongly disagree” to 5 (“strongly agree”)]. Cognitive and affective image were measured using a three-item and five-item scale, respectively adapted from Casali et al. (2021), Jeong and Holland (2012), Kim et al. (2021), and Schofield et al. (2020). The intention to revisit and to recommend were measure using four-item scales adapted from Lam et al. (2022) and Maghrifani et al. (2022).

The English-language instrument was pilot-tested with a sample of 30 international travellers, which aligned with the recommended sample size for normal data distribution (Dolnicar et al., 2014; Tuncer, 2021). The pilot testing respondents were excluded from the main data collection. The questionnaire was modified to clarify misunderstood questions. A purposive sampling strategy (Berndt, 2020) was used to screen respondents using the criteria as follows: (1) ages ≥ 18 years old, (2) non-resident of Thailand and (3) must have visited Thailand within the past three years. Only individuals who met all aforementioned criteria were eligible to proceed with the questionnaire survey. This study was approved by the Institute Ethics Committee of Research Ethics (Social Sciences). Written informed consent was obtained from all participants before date collection began.

3.2. Data Collection

Data were obtained from 392 respondents via face-to-face surveys. A nonprobability sampling technique (purposive sampling) was used to contact only international tourists who were likely to have relevant experiences and opinions about the destination image of Thailand. The survey targeted international tourists at popular destinations (Phuket, Krabi and Phang-Nag), which had been ranked among the top 10 destinations for international tourists in 2022 (Ministry of Tourism and Sports [2023], 2023). The SEM guidelines recommend sample sizes of 150-400 (Dash & Paul, 2021), with 200 typically required for large-sample methods (Nunkoo et al., 2013). However, ethical issues surrounding personal details needed to be considered. Prior to participation, all subjects were informed about the study objectives, procedures, potential risks, and benefits. Written informed consent was obtained from all participants before data collection began.

3.3. Data Analysis

The PLS-SEM is a modern multivariate analysis technique that was used for internal consistency assessment of the latent variable and supports alternative data groups through MGA (F. Hair Jr et al., 2014; Manley et al., 2021). A minimum sample size of 100 is indicated for PLS-SEM (Cheah et al., 2018). This study involved 185 first-time and 207 repeat travellers, which exceeded the recommended thresholds, hence ensuring sufficient data for analysis. The data were analysed usning SmartPLS 4.1.0.9 (Deng & Yu, 2023; Qureshi et al., 2023)

4. Results

4.1. Descriptive Statistics

Table 1 depicts the participants’ demographic profile. First-time travellers had higher mean values for affective image, intent to revisit, and intent to recommend than repeat travellers (Table 2). Nonetheless, both groups had similar mean values for cognitive image. These results highlighted the appeal of Thailand as a tourist destination through its cognitive and affective components. The first-time travellers’ higher affective image and behvioural intent underscored the ability of the country to create strong emotional impressions, particularly for first-time experiences. The consistent cognitive image across both groups reflected the reliable strengths of Thailand, such as its good climate, rich culture, and historical attractions.

4.2. The PLS-SEM Model Assessment

4.2.1. Measurement Model Assessment and Measurement of Invariance

The model of measurement included the constructs cognitive image (CO), affective image (AF), intent to revisit (IV), and intent to recommend (IR). The main evaluation metrics were internal consistency (Cronbach’s alpha and composite reliability [CR]), indicator reliability, construct validity (average variance extracted [AVE]), loadings, and the heterotrait-monotrait [HTMT] radio), and discriminant validity. Indicator reliability was established using factor loading, which exceeded the 0.70 threshold for most indicators (Aburumman et al., 2023). Internal consistency was confirmed based on Cronbach’s alpha of 0.769-0.937, which exceeded the recommended 0.70 threshold (Cham et al., 2022). The CR values were 0.900-0.975, which were supportive of the measurement model reliability. Convergent validity was used to determine the AVE, where the values recorded exceeded the 0.50 threshold for all constructs (Hulland, 1999). Discriminant validity was ascertained through the criterion of HTMT, where all values were below the 0.90 threshold (Hair et al., 2017; Henseler et al., 2015). The full collinearity variance inflation factors (VIFs) were 1000-1.367, which were below the threshold of 3.33 and indicated no significant common method bias (Kock & Lynn, 2012) (Tables 3–6).

Table 3. Full collinearity results.

Relationship between constructs	VIF
Cognitive image -> Affective image	1.000
Cognitive image -> Intention to revisit	1.367
Cognitive image -> Intention to recommend	1.367
Affective image -> Intention to revisit	1.367
Affective image -> Intention to recommend	1.367

Table 3. Full collinearity results.

Relationship between constructs	VIF
Cognitive image -> Affective image	1.000
Cognitive image -> Intention to revisit	1.367
Cognitive image -> Intention to recommend	1.367
Affective image -> Intention to revisit	1.367
Affective image -> Intention to recommend	1.367

Group-specific parameter estimates (path coefficients and outer loading and weight) were compared using MGA. Using PLS-SEM, MGA differences were assessed through bootstrapping and permutation tests. The measurement invariance of composite models (MICOM) was evaluated through configural invariance, compositional invariance, and composite equality. The results demonstrated partial measurement invariance between the repeat and first-time travellers.

Table 4. Measurement model assessment results.

Constructs or associated items	Loadings		Cronbach’s alpha		CR		AVE
	First-time	Repeat	First-time	Repeat	First-time	Repeat	First-time	Repeat
CO			0.767	0.81	0.769	0812	0.683	0.725
CO 2	0.858	0.851
CO 1	0.844	0.855
CO 3	0.774	0.848
AF			0.827	0.846	0.832	0.853	0.594	0.618
AF2	0.836	0.819
AF5	0.824	0.771
AF1	0.748	0.814
AF3	0.751	0.776
AF4	0.684	0.749
IV			0.9	0.857	0.937	0.861	0.772	0.703
IV1	0.873	0.747
IV2	0.945	0.902
IV3	0.938	0.882
IV4	0.743	0.814
IR			0.922	0.926	0.922	0.928	0.812	0.82
IR1	0.892	0.865
IR2	0.939	0.931
IR3	0.925	0.935
IR4	0.846	0.889

Notes: AVE: average variance extracted; CO: cognitive image; CR: composite reliability; AF affective image; IV: intention to revisit; IR: intention to recommend.

Table 4. Measurement model assessment results.

Constructs or associated items	Loadings		Cronbach’s alpha		CR		AVE
	First-time	Repeat	First-time	Repeat	First-time	Repeat	First-time	Repeat
CO			0.767	0.81	0.769	0812	0.683	0.725
CO 2	0.858	0.851
CO 1	0.844	0.855
CO 3	0.774	0.848
AF			0.827	0.846	0.832	0.853	0.594	0.618
AF2	0.836	0.819
AF5	0.824	0.771
AF1	0.748	0.814
AF3	0.751	0.776
AF4	0.684	0.749
IV			0.9	0.857	0.937	0.861	0.772	0.703
IV1	0.873	0.747
IV2	0.945	0.902
IV3	0.938	0.882
IV4	0.743	0.814
IR			0.922	0.926	0.922	0.928	0.812	0.82
IR1	0.892	0.865
IR2	0.939	0.931
IR3	0.925	0.935
IR4	0.846	0.889

Notes: AVE: average variance extracted; CO: cognitive image; CR: composite reliability; AF affective image; IV: intention to revisit; IR: intention to recommend.

4.2.2. Structural Model and MGA Assessment

The structural model evaluation involved bootstrapping (5000 resamples) and permutation testing (1000 permutation) to compare repeat and first-time travellers’ path coefficients. The path coefficients indicated stronger cognitive-to-affective image influence among repeat travellers (β = 0.557, p < 0.001, t = 10.097) compared to first-time travellers (β = 0.520, p < 0.001, t = 8.726) (Table 7). Similarly, cognitive image influenced the intention to recommend more strongly for repeat travellers (β = 0.230, p < 0.001, t = 3.593) as compared to first-time travellers (β = 0.165, p < 0.05, t = 2.578). Affective image significantly influenced the intention to revisit for both groups but was slightly stronger for repeat travellers (β = 0.569, p < 0.001, t = 7.845) as compare to first-time travellers (β = 0.523, p < 0.001, t = 7.727). Contrastingly, the influence of affective image on the intention to recommend was stronger for first-time travllers (β = 0.548, p < 0.001, t = 7.925) as compared to repeat travellers (β = 0.424, p < 0.001, t = 5.539) as compare to first-time travellers (β = 0.001, p < 0.05, t = 0.009), but no significant difference was observed.

The MGA revealed no statistically significant differences between repeat and first-time travellers observations of the destination image of Thailand, cognitive and affective images, or intents to revisit and to recommend. These results confirmed that the appeal of Thailand was consistent across visitor types, which reinforced the strong cognitive and affective characteristics of the destination.

5.1. Discussion

The motivation for first-time and repeat visits to a destination can differ, particularly when viewed through the lens of the CAB model. This study investigated the relationship between cognitive, affective, and behavioural processes in determining the destination image of Thailand from international repeat and first-time travellers’ perspectives.

Regarding H1, the MGA results revealed significantly differing effects of cognitive destination image on affective destination image between repeat and first-time travellers. A stronger positive relationship was detected in repeat travellers, which aligned previous demonstrations of how cognitive evaluation create emotional responses to destinations (Lam et al., 2022; Rather et al., 2022; Woosnam et al., 2020). First-time travellers frequently depend on external sources (marketing tools, recommendations, and social media) to form cognitive assessments. Marketing tools, which include social networks, digital media, and mobile applications (Facebook, WhatApp, and TikTok), are vital for forming perceptions, which affect emotions (affective image) regarding Thailand. Contrastingly, repeat travellers depend on experiences and emotional connections, such as nostalgia or unforgettable events, which creates a stronger link between cognitive and affective images.

Regarding H2, the effects of cognitive destination image on intent to revisit did not differ significantly between repeat and first-time travellers. This results aligned with reports that cognitive assessments of attractions, infrastructure, and safety form primary impressions but may not be the main factors in the intention to revisit (Carvalho, 2022; Rather et al., 2022; Ren et al., 2022). First-time travellers’ revisit intention is frequently fostered by emotional stimuli, such as satisfaction in relations to the trip. Conversely, loyalty, nostalgia, or other motivational factors, affect repeat travellers and extend beyond cognitive qualities.

Regarding H3, the cognitive destination image effects on the endorsement intention differed significantly, where repeat travellers demonstrated a stronger association. Nonetheless, both groups had a positive relationship, which agreed with previous studies (N. (Chris) Chen et al., 2018; Cubillas-Para et al., 2023; Prayag et al., 2017). First-time travellers’ endorsements are based on tangible qualities (outdoor activities, cultural sites, and infrastructure) and how their expectations are matched. Nevertheless, the endorsements of repeat travellers involve broader factors, such as experiences and general satisfaction.

Regarding H4, the MGA determined that the effects of affective destination image on the revisit intention was significantly different where repeat travellers demonstrated a slightly stronger association. Similar results have been reported for the positive link between affective image and tourists’ revisit intent (Liang & and Xue, 2021; Rather et al., 2022). First-time travellers’ excitement or satisfaction during the visit affect their decision to revisit. Nonetheless, these emotional responses are frequently limited to the direct trip experience. Contrastingly, repeat travellers’ decisions are motivated by deeper emotional links, such as nostalgia, attachment, and familiarity established over several visits. These emotional factors are stronger revisit motivators.

Regarding H5, the affective destination image significantly influenced the recommend intention of both groups, where first-time travellers recorded slightly higher results. This result aligned with prior studies demonstrating the role of emotions in driving recommendations (Manthiou et al., 2017; Prayag et al., 2017; Rather et al., 2022). For first-time travellers, pleasure, stimulation, interest, comfort, and excitement are central to creating meaningful experiences and contribute positively to the affective destination image.

5.2. Implications

The literature review emphasized the importance of destination image in enhancing destination loyalty among first-time and repeat travellers. Nevertheless, the role of affective and cognitive images in shaping destination loyalty within the context of the destination image of Thailand remains underexplored. This study used the CAB model to investigate differences between repeat and first-time travellers in terms of the effects of cognitive and affective images in relation to destination loyalty. The results contributed to the understanding of the CAB model and the affective and cognitive elements of destination image.

This study compared the perceptions of repeat and first-time travellers and provided unique theorical insights into international tourists’ views. In the context of the destination image of Thailand, particularly concerning the interplay between cognitive, affective, and behavioural processes, the CAB model yielded significant theoretical contributions. Measurement invariance and group-specific differences were assessed through advanced methodologies, such as MGA through PLS-SEM and MICOM. These results reinforced the theoretical importance of integrating cognitive and affective dimensions in destination image research.

This study also presented the following practical implications for stakeholders (destination marketing organisations) managing the destination image of Thailand:

• Tailored marketing strategies should be developed to address first-time and repeat travellers’ unique perceptions and inspirations;
• Plans to endorse new attractions and inspire repeat visits should be created;
• Undated information should be provided to improve first-time travellers’ experiences and encourage their revisit intention;
• Loyalty programs or incentives should be developed to enhance repeat travellers’ emotional links to the destination.

5.3. Limitations of Study

The data were obtained from 392 international travellers visiting the Andaman Sea coastal region of southern Thailand. Thus, the result generalizability to other destinations may have been limited. Second, the focus on the cognitive and affective factors influencing destination loyalty and potential may have neglected other significant variables, such as visitor inspirations or satisfaction. Lastly, broader influences, such as information sources and personal motivations, in forming the destination image were not extensively investigated. These gaps should be addressed by studying diverse regions and additional features that influence destination loyalty.