Progress and Prospects of Destination Image Research in the Last Decade

Abstract

Destination image influences tourists’ perceptions and opinions of destinations and plays a crucial role in tourist behavior and travel-purchase-related decisions. This study summarizes and reviews 151 pieces of literature on destination image published in six major international hospitality and tourism academic journals in the last decade (January 2012–February 2022). By combing through the literature, we found that research on destination image in the previous decade has focused on the following four major areas: (1) the structure of destination image; (2) the measurement and branding of destination image, (3) the influencing factors of destination image, and (4) the influence of destination image on tourists’ behavioral intentions. These results revealed and clarified the latest international research dynamics. The findings provide an all-encompassing understanding of destination image, illustrate the academic evolution of the topic, and point to crucial directions for future research.

1. Introduction

1.1. Destination Image

The concept of image has been used in social and environmental psychology, consumer behavior research, and marketing since the 1960s [1], to represent people’s perceptions of objects, events, and behaviors driven by impressions, feelings, and beliefs [2]. Image is given a different meaning in the marketing of tourism destinations and is often referred to as “brand image” or “destination image”. Most researchers consider destination image to be an individual’s expectations, impressions, and emotions about a place [3,4,5,6], which is the overall assessment of the tourist’s psychological and emotional perception of a destination [7]. The above definition of destination image can be understood as the overall perception of the destination by tourists, which is the concept of the one-dimensional structure of destination image.

At least two schools of thought support the structuring of destination image [8], and the understanding of the concept of the destination image is continuously deepened by revealing its structure, i.e., by conceptualizing destination image as a multidimensional structure. The concept of multidimensional attributes of the destination image is used and more popular among most destination image researchers. Embacher and Buttle recognize the cognitive and affective two-dimensional structure of the destination image [9]. Dann argues that destination images are composed of intentional components in addition to cognitive and affective components [10]. In terms of cognition, Pike views it as the sum of what visitors know about a destination and the relevant knowledge they have or have not been able to acquire from previous trips [11]. He and Deng consider cognitive components as knowledge about the attributes of a place, such as climate, inhabitants, scenery, food, etc. [8]. The affective component represents the visitor’s feelings about the destination and is a personal emotional response or evaluation [12,13,14]. The intentional component indicates the visitor’s positive perception of a place as a potential tourist destination [15], or a desire [16]. It is also defined as a behavioral disposition [17]. The definition of the intentional image had different voices and views in the early days, with some researchers arguing that intentional image is synonymous with the intention [18,19,20,21]. However, there is evidence that intentional motion and intent have different meanings [16,22,23]. An intentional movement is not the same as an intention, but rather a pre-intention [24]. Bagozzi argues that “a person who finds an action attractive may not have the will to perform it, or may intend not to do so, or may have no intention one way or the other”, and that it considers the intentional process as an antecedent of intention [17]. This perspective contributes to a deeper understanding of the definition of intentional image as merely a favorable consideration of potential destinations by tourists. In early studies, investigations focused on cognitive images, followed by holistic and affective images [25]. In recent years, an increasing number of studies have changed this trend by realizing the importance of affective image [26,27,28]. Some researchers believe that studying the affective component of images has no practical value [29]. However, more researchers have demonstrated that combining cognitive and affective evaluations is necessary to study destination images. For example, Lai, Wang, and Khoo-Lattimore used the example of Australia to predict the behavioral intentions of potential Chinese tourists by combining the cognitive and affective components of food images, and the results demonstrated that cognitive food images were better predictors of tourists’ behavioral intentions than affective images [30]. Stylidis, Shani, and Belhassen also highlight the greater applicability of the integrated destination image model to residents of tourist destinations [31]. Later Baloglu and McCleary proposed a cognitive-affective-whole model of destination images [3]. The overall image is the tourist’s overall perception of the tourist destination [32].

The definition of destination image as a multidimensional or one-dimensional structure depends on the purpose of the study [33]. When exploring the relationship between destination image and visitor satisfaction, place attachment, and visitor behavioral intentions, researchers often use destination image or overall image as the object of study [34,35,36,37]. In some studies, destination image has also been conceptualized as a cognitive or affective component of a one-dimensional structure. For example, Chang and Mak considered the image of food as a unique competitive advantage of the destination [38]; that is, they considered one of the most representative elements of the cognitive image—food—as the best representative of the destination image, and they used a catalog grid approach to explore the attributes and dimensions of Taiwan’s food image, identifying seven categories of attributes such as attractiveness, flavor characteristics, and familiarity of the food image.

1.2. Status of the Reviewed Literature

New research results better reflect the trends and features in the destination image field, especially the work published in authoritative professional journals during the last decade. Therefore, the literatures reviewed in this paper are relevant articles published in English academic tourism research journals from 1 January 2012 to 1 February 2022. Tourism Management (hereinafter referred to as TM), Annals of Tourism Research (hereinafter referred to as ATR), and Journal of Travel Journal of Travel Research (hereinafter referred to as JTR) are the three most authoritative tourism research journals in the field of tourism scholarship at the national level. In addition, in order to make the reviewed literature as complete as possible, this literature review is supplemented by the International Journal of Hospitality Management (hereinafter referred to as IJHM), Journal of Sustainable Tourism (hereinafter referred to as JST), and Journal of Hospitality Marketing & Management (hereinafter referred to as JHMM), which are three top-ranked tourism journals in the field of international tourism research. These six journals are Social Science Citation Index (SSCI) journals in tourism. All the reviewed literatures are selected from the above six journals, in order to ensure that the reviewed literatures are authoritative, cutting-edge, and representative.

1.2.1. Literature Sources

In the Elsevier Science Direct database, we included “Destination Image” in the title, keyword, and abstract, the article source was TM, ATR, or IJHM, and the time of publication was “1 January 2012–1 February 2022”. A total of 144 articles were retrieved, and 97 articles were obtained after eliminating the irrelevant ones; among them, 68 were published in TM, 24 in ATR, and 5 in IJHM. In the EBSCO database, we searched for articles published in JTR between 1 January 2012 and 1 February 2022 by topic, title, and keyword “Destination Image”, and then eliminated the same articles in the three searches, and found a total of 34 relevant articles. In the Taylor & Francis database, we searched for articles published in JST or JHMM between 1 January 2012 and 1 February 2022 with the title, keywords, and abstract containing “Destination Image”, and found a total of 30 articles. A total of 20 papers were obtained after excluding irrelevant papers, with 9 papers published in JST and 11 papers published in JHMM. A total of 151 papers were retrieved from the three databases. The year and distribution of the literature are shown in Figure 1. In general, more literatures were published in TM because most of the destination image studies are based on marketing perspective. At the same time, TM is focused on the management, planning, and policy studies of travel and tourism.

1.2.2. Literature Characteristics

Among the 151 literatures reviewed, this paper summarizes four major research themes based on the research focus and major research themes of the selected literature, which are (1) structure of destination image, (2) measurement and branding of destination image, (3) influencing factors of destination image, (4) destination image and tourists’ behavioral intention. Studies related to the structure and measurement of destination image, influencing factors of destination image, and destination image and tourists’ behavioral intentions are traditional research themes and long-standing popular topics, with 128 publications related to them. The literature on branding and destination image structure research is the latest research perspective that destination image research has focused on, with 13 literatures related to this topic and 10 other types of research.

A review of the relevant literature revealed that in recent years, destination image research has persisted in traditional research, but the expansion of measurement methods and the deepening of related theories have also been explored. Moreover, from the themes of the research literature, there is a crossover in the themes of each literature. of them involve multiple themes at the same time, which indicates that the themes are more closely related to each other and can learn from each other, and the deepening of one theme can promote another or more themes to move forward together. In the following, we will further organize and summarize the reviewed literature, practically analyze the shortcomings of the existing studies, and provide an outlook on the future research directions.

From the reviewed literature, the countries and regions listed in the studies related to destination image have two meanings: one is the destination, and the other is the place of origin of tourists (hereinafter referred to as the place of origin). The destinations and places of origin involved in the 151 papers compiled in this paper include 69 countries and regions, and 54 countries and regions appear as destinations. The top five countries and regions, in descending order of frequency as destinations, are China (including Hong Kong, Macau, and Taiwan) (34), the United States (17), Spain (17), Greece (11), Italy (9), France (8), and Korea (8) (see Figure 2). There are 60 countries and regions that appear as places of origin, and the top five, in descending order of their frequency of appearance as places of origin, are China (including Hong Kong, Macau, and Taiwan) (40), the United States (32), the United Kingdom (25), Germany (21), and Spain (19) (see Figure 3).

2. Structure of the Destination Image

The word “structure” is defined in the Oxford English Dictionary as “the interrelationship of the components, parts or elements of a whole that determine its particular nature”. Looking at the historical evolution of the concept of destination image, we can conclude that the deepening of the definition of destination image has been achieved by researchers through the continuous revelation of its structure. There are at least two schools of thought that support the destination image structure. The first conceptualizes the destination image as a three-dimensional causal network structure, dividing the destination image into three dimensions: cognitive image, affective image, and overall image, and validated the “cognitive image–affective image”, “affective image and cognitive image–affective image”, and “cognitive image–affective image–overall image” [3,5]. Another is devoted to studying the distribution pattern of destination image information [39,40], which refers to the core–edge structure pattern. Deutsch and Merritt argue that mental imagery tends to have a core–edge structure, where people focus on a tiny number of elements. In contrast, the vast majority of elements at the edges are ignored or receive little attention. Furthermore, “over time, more and more peripheral details are forgotten, and fewer and fewer simple features are remembered” [41]. Lai and Li extend this theorization to the field of tourism destination image by defining the core–periphery structure of a tourism destination as “a mental structure of a destination co-constructed by actual and potential tourists, in which the destination can be intentionally deconstructed into smaller units that can be reconstructed into core–periphery patterns, in which these units of the destination image (or its sub-dimensions) can be reliably ordered according to certain differentiation criteria anchored by logical binary pairs ” [42].

Recent researchers have explored the distribution of destination images using a social network approach and concluded that the distribution has a “core–edge” pattern. Wang, Li, and Lai used a social network approach to demonstrate that destination images have single and multiple core–edge structures, with respondents making image associations from the core to the edge or closest to the center level [43]. This research also provides lessons for tourism marketing, where marketers can “move” the image elements that interest consumers from the edge to the core [42].

In summary, it is clear that destination images have both single and multiple core–edge structures. It confirms that the study of core–edge structures in destinations has positive implications for promoting consumer engagement and tourism marketing. In the future, efforts should be made to examine the core–edge structure of destination images in different contexts, in particular the need to assess the core–edge structure of emerging destinations whose core image is unclear or needs to be strategically changed, to clarify the “core image” of these destinations or how to strengthen the core image of a destination. In terms of research methodology, in addition to the recently used social network analysis methods, the broader use of machine learning methods should also be promoted. For specific destinations or destination-specific features (e.g., canyons), there are some limitations of machine learning methods, which need to be addressed in the future by tourism researchers working together to create context-specific ground truth labels. In terms of the type of data studied, due to the limited access to metadata, there should be more combinations of online and offline data in the future, which may require the introduction of qualitative methods to obtain image data, which makes possible comparative studies of destination image structure before and after the emergence of the destination.

3. Destination Image Measurement and Branding

The measurement of destination image has been a topic of great interest to researchers and has certain theoretical and practical significance. Theoretically, it can enrich the connotation of destination image, and at the same time, provide a reference for destination image positioning and destination marketing. After continuous exploration and reflection by researchers, certain breakthroughs in destination image measurement methods have been achieved in recent years.

3.1. Destination Image Measurement Methods

There are two approaches to measuring destination images: structural and unstructured approaches [44,45]. Structured methods use semantic differences and Likert scales to measure the cognitive or affective attributes of destination images. Unstructured methods use mainly open-ended questions and tests, focus group interviews, content analysis, and various ranking and classification techniques. This paper also summarizes the research methods involved in destination image studies between 1 January 2012 and 1 February 2022 accordingly, as well as several previous studies (see

Table 1. Destination image measurement methods and the corresponding literature.

Method	Authors
Structural method	Lai et al., 2020; Stylidis et al., 2017; Echtner and Ritchie, 1991; Stylidis, 2018; Chen and Peng, 2018; Echtner and Ritchie, 1993; Wang et al., 2016; Stepchenkova et al., 2015; Bender, 2013; Karamustafa et al., 2013; Smith et al., 2015; Line and Hanks, 2016; Yang et al., 2012;
Structural method + non-structural method	Becken et al., 2017; Stylidis et al., 2016; Martín–Santana et al., 2017; Choe and Kim, 2019; Huang and Wang, 2018; Stone and Nyaupane, 2019; Stylidis et al., 2015; Llodrà–Riera et al., 2015; Hao and Ryan, 2013; Hunter, 2013; Ryu et al., 2013; Toral et al., 2018;
Non-structural method	He et al., 2021; Bastiaansen et al., 2022; Liang, 2011; Borgatti and Martin, 2000; Cardoso et al., 2019; Stepchenkova and Li, 2014; Govers et al., 2007; Sun et al., 2015; Mak, 2017; Paivio et al., 1968; Blain et al., 2005; Boo et al., 2009; Hunter, 2016; Deng and Li, 2018; Arefieva et al., 2021;

Source: Compiled from relevant literature.

).

Structured methods have the advantages of flexibility, suitability for coding, and ease of analysis. Dolnicar and Grün’s review of papers on destination image research published in top international academic tourism journals between 2002 and 2012 shows that 75% of the papers used a structured approach [46]. The structured approach also has limitations because its list of intended attributes may be influenced by researcher stereotypes. In addition, because consumers were not involved in developing the list, the actual factors that attract them to choose a destination may be excluded [44,47,48]. Structural approach measures of the destination image are primarily investigated in questionnaires, which are multidimensional lists of attributes that make up the destination image. According to the reviewed literature, most questionnaires include infrastructure, service quality, tourism resources, tourism environment, comfort, destination accessibility, tourism activities, social environment, affective image, overall image, loyalty, and revisit intention as destination image attribute scales [49,50,51]. The method used to determine destination images in most studies is structural equation modeling (SEM) [3,50,52], followed by factor analysis [52,53].

Probably the most commonly used unstructured methods when measuring destination images are the three open-ended questions [54,55,56]. Echtner and Ritchie point out that the role of open-ended questions is to capture the overall impression, character, and atmosphere [55]. It is more challenging to collect data using these three questions when a relatively large sample size is required. Therefore, researchers usually ask respondents to list only the first three words, phrases, or three pictures that come to their mind [57,58]. To date, there are still many technical and practical challenges in using unstructured methods, which not only have to demonstrate analytical rigor and minimize interpretation bias [59], but qualitative research and analysis of qualitative data also face the practical challenge of costing a lot of time and money [60]. Some researchers have provided new directions on how to analyze qualitative image data; Stepchenkova and Li proposed image diversity based on the concept of species diversity in biology and applied biodiversity indicators such as dominance, richness, and evenness to describe the diversity and relative richness of destination images [54,58]. Traditional questionnaire and interview methods were used to collect homogeneous and structured information, but not for fragmented and unstructured UGC data, such as travel blogs, online travel reviews on travel websites, images, videos, etc. While most early researchers used photos taken by tourists alone to analyze projected and perceived destination images [61], more recent studies used text and photo data, combining textual and visual analytics to measure projected and perceived destination images [62,63]. The “picture dominance effect” suggests that pictures are usually easier to remember than words [64]. In addition, findings indicate that the affective attributes of destination images may have a more significant impact on the construction of destination images than cognitive attributes [65], so it is more important to emphasize the emotional attributes of the positive destination images projected through pictures and videos [66,67].

The measurement methods of destination images have become more sophisticated in recent years, and many studies have used mixed methods. One trend is the increasing number of studies that combine structural and non-structural techniques. Wang, Qu, and Hsu, for example, used mixed methods, first developing scales through focus group interviews and in-depth interviews. Quantitative analysis was then performed using EFA (exploratory factor analysis) and CFA (constraint factor analysis) methods [68]. Another trend is that in addition to the three open-ended question methods, more studies have begun to use qualitative methods, such as focus group interviewing, telephone interviewing, picture, audio, video and word association methods, and box analysis. For example, Huang and Wang further used a mixed approach of quasi-experimental design, using fieldwork and focus group discussion scale items in the first phase and compiling them into a questionnaire; in the second phase, they used a quasi-experimental design method in which respondents viewed pictures, videos, and listened to audio to collect the questionnaire and analyzed the destination image based on the results [69].

3.2. Destination Image Branding

For tourism destinations, early researchers argued that visitor experience should be understood in the context of the branding process [70], because a quality brand experience has a positive impact on the acquisition of a value experience [71]. Good destination branding creates a halo effect, helping the destination to build a positive affective image and overall image [72]. Destination brand image, as part of brand equity [73], has the same direct or indirect impact on brand loyalty as brand quality and brand value [74,75].

Recent studies have basically tested consumers’ attitudes and intentions towards destinations based on the construction of a consumer brand equity (CBBE) model. Bianchi, Pike, and Ling tested the gap in perceptions of the same destination image in Argentina, Chile, and Brazil by constructing a consumer-based brand equity (CBBE) model [76]. Molina et al. tested how brand images from online and offline information sources influence brand preferences through brand equity and how they differ in this process by using a brand equity model [77]. Sang further reconstructed the place branding model from a Peircean (Peirce semiotics) perspective, where destination planners, villagers’ destination identity, and tourists’ constructed destination image interacts to constitute destination branding [78].

4. Influencing Factors of Destination Image

Baloglu and McCleary divided the influencing factors of tourism destination image into personal factors and stimulus factors, where individual factors include both psychological and social factors [3], and Beerli and Martin extended their study on this basis and summarized the influencing factors of destination image into individual factors (personal factors) and information sources [79]. The latter is a more common way of classifying the factors influencing destination image. This paper also summarizes the factors involved in the formation of destination image between 1 January 2012 and 1 February 2022 accordingly (see

Table 2. Types of influencing factors and their corresponding literature.

Influencing Factors			Authors
Individuals factors	Travel motivation		Pan et al., 2014; Wang et al., 2016; Prayag and Hosany, 2014;
	Cultural background		Sun et al., 2015; Prayag and Hosany, 2014; Stepchenkova et al., 2015; Bender et al., 2013; Stone and Nyaupane, 2019; Chen et al., 2016; Assaker and O’Connor, 2021; Tse and Tung, 2022; Chen et al., 2013; Moura, 2015;
	Demographic variables		Wang et al., 2016; Stylidis et al., 2015; Pan et al., 2021;
	Destination familiarity		Sun et al., 2013; Horng et al., 2012;
	Personal experience		Kim, 2018; Stylidis et al., 2021; Stylidis, 2022; Tse and Tung, 2022;
	Trust		Sannassee and Seetanah, 2015;
Information source factors	Second-hand	Destination promotional materials	Sun et al., 2015; Llodrà–Riera et al., 2015; Lee and Lockshin, 2012; Millar et al., 2017; Voltes–Dorta et al., 2017; Jeuring, 2017; Bilynets et al., 2021; Lin and Kuo, 2018;
		Social media	Martín–Santana et al., 2017; Stepchenkova and Zhan, 2013; Kim and Stepchenkova, 2015; Camprubí and Coromina, 2016; Tang and Jang, 2014; Rodríguez–Molina et al., 2015;
		TV and movies	Zhang et al., 2014; Tessitore et al., 2014; Hao and Ryan, 2013;
		Public figures	Hunter, 2013; Lee and Bai, 2016; Nicolau et al., 2020;
		News	Potwarka and Banyai, 2016;
	First-hand	Experiences	Cardoso et al., 2019; Kim et al., 2012; Karamustafa et al., 2013; Smith et al., 2015; Lee et al., 2014;
		Perception	Lu et al., 2015; Zenker et al., 2019; Guizzardi et al., 2021; Zhang et al., 2018;

Source: Compiled from relevant literature.

).

4.1. The Influential Role of Individual Factors

Individual factors generally contain demographic variables, travel motivation, personal experience, cultural background, destination familiarity, and trust (also known as expectations).

Tourism motivation factors include push and pull factors. Prayag and Hosany identified tourism motivation as different impressions of the same destination among three groups based on a push–pull framework. Different motivations make their overall perceptions of the destination image different [80]. Wang et al. investigated the image of Macau in the eyes of foreign tourists through a questionnaire survey. They found a significant positive correlation between travel motivation and cognitive image, but no significant correlation with affective image [68]. Pan et al. further explored the relationship between motivation, image dimension, and affective quality of place through a content analysis of 145 travel photographs in the New York Times, which showed that the natural image dimension tended to be associated with “pleasant” motivation, while historical and artistic cultural images were associated with “pleasant” motivation. The study showed that the natural image dimension tends to be associated with “pleasant” motivation, while the historical and artistic–cultural image dimension tends to be associated with “intellectual” motivation [66]. In general, a summary of the recent literature shows that travel motivation is more likely to be associated with the cognitive image dimension of the destination. In contrast, earlier studies found that it is relevant to the affective image of the destination only if the motivation is at a moderate level [5,79]. Because of the mixed findings, numerous empirical studies are needed to explore the relationship between the two further.

Studies on cultural contextual factors of destination image have basically investigated the disparity in perceptions of destinations among people of different origins and nationalities [80,81,82,83,84,85,86]. There are also studies on the influence of cultural values on the formation of destination images [62,87,88].

Demographic variables factors include gender, educational status, marital status, occupation, etc. Wang et al. verified that gender moderated the effect of travel motivation on the cognitive image, which was more remarkable for men than for women, while gender did not affect affective image [68]. Stylidis et al. investigated the differences in the perceptions of tourists, residents, and the tourism sector regarding the image of the same city destination, with the result that tourists had the best perceptions [89]. Pan et al. also revealed differences in perceptions of destination images between those with higher education and those with primary/secondary education, those who are married or have a partner, and those who are unmarried. Demographic variables are generally present as moderating variables in the study and need to be combined with other variables for comprehensive research and further tourism planning based on the findings.

Destination familiarity is a visitor’s visual or psychological impression of a destination. It is an information assessment process where perceptions of destination service quality, personality, or satisfaction influence the destination familiarity assessment process, which determines customers’ attitudes and travel intentions. Sun et al. demonstrate that destination familiarity significantly and positively affects destination image [90]. Horng et al. confirmed that destination familiarity positively moderates the relationship between brand image and travel intentions, and that a good brand image increases tourists’ travel intentions attributed to destination familiarity [91].

Personal experience factors include both memorable tourism experiences and the quality of host–guest (resident–tourist) interactions. Kim defined tourism experiences as those actively remembered and recalled after the event and demonstrated a positive relationship between memorable tourism experiences (MTEs) and destination image [92]. The host–guest interaction theory suggests that tourists interact with locals, develop relationships, gain knowledge, increase awareness, and gradually develop an attachment to the destination [93]. Stylidis extends the research on the quality of host–guest interactions to demonstrate that the quality of host–guest interactions positively affects the affective and cognitive image of a destination [94,95]. Tse and Tung further show that positive host–guest interactions can increase visitors’ emotional attachment and overall satisfaction with residents, and vice versa [96]. Overall, there is limited research on the impact of host–guest interactions on tourists’ destination image. Current research focuses on tourist–resident interactions without considering interactions with other tourists; future research is needed to fill this gap. Finally, since host–guest interactions are influenced by destination familiarity/cultural factors, future research should do comparative studies on resident interactions with different visitors (e.g., first-time vs. repeat visitors, or visitors of different nationalities).

4.2. The Influential Role of Information Sources

The information source factor is generally subdivided into primary and secondary information sources.

Secondary sources of information contain sources from different channels such as destination promotional materials, social media, TV and movies, and news. Researchers have examined the impact of information sources from different channels, both online and offline, on the image of the destination in a comprehensive manner, with the results generally being that social media (the Internet), official tourism websites, and tourism brochures play a greater role, followed by television and movies [97,98]. The data used by researchers in the collected literature often come from destination promotional materials containing national tourism official websites [63], destination accommodation [97], tourism brochures [82], destination products [99], destination safety and security [100], destination transportation facilities [97,101], destination weather [102], etc. According to the literature, social media and destination communication materials have their own merits. Therefore, many studies have used them in combination to enable tourists to perceive destination images better. For example, Mak examined the perceived and projected online destination images displayed in tourist-generated content (TGC) and content generated by national tourism offices (NTOs). The results showed that TGC and NTOs each have advantages for the formation of destination images [63]. In addition, destination promotional materials have overt environmental initiatives, and Bilynets et al. confirmed that overt environmental initiatives of destinations are positively associated with environmentally sustainable organic destination images [103].

The above studies show that, in general, information sources on the Internet and official channels such as official websites and tourism brochures have a more significant impact on destination image. However, in some specific cases, television programs and information sources controlled by the non-governmental and tourism sectors, such as national leaders and pop stars, have a more substantial influence on specific destinations than traditional and Internet sources. Researchers have used social media in combination with information sources such as TV shows [26,104], movies [105], and public figures [106,107,108]. Tessitore et al. showed through experiments that reality TV could change the image of destinations set by the program, with positive effects on cognitive, affective, and behavioral outcomes [104]. Therefore, for particular destination types, such as the hometown places of national leaders, pop culture developed regions, and reality show filming locations, different information sources should be used as much as possible, combining online and offline sources as much as possible and using a multidimensional approach to study destination images.

The first-hand information sources mainly refer to tourists’ personal experiences in the destination and factors related to perceptions. Experience refers primarily to the times of visiting the same destination, the number of experiences in visiting similar destinations, the strength of travel experiences at different time points before, during, and after visiting the same destination, or the change of experience intensity at different periods in the same destination; perceptions refer to perceived authenticity, perceived fluency, perceived openness, or perceived value.

Regarding experiential factors, Karamustafa et al. confirmed that travel experiences reinforce individuals’ overall impressions of the destination and positively influence revisit intentions [109]. Karamustafa et al. later re-validated that first-time and repeat visitors differ significantly in their perceptions of mixed destination images [110]. Smith et al. built on this by examining multiple critical moments in which dynamic destination images perceived by tourists at several key moments, and the results showed that there is a great gap between the cognitive and affective images of tourists before and after the trip [111]. A review of the literature reveals that most researchers have only examined the impact of tourist experiences on images of the same destination at different moments, and there is a lack of research on the effects of tourist experiences on images of various destinations. Cardoso and Dias fill this gap by using an online multilingual questionnaire containing 36 languages to evoke, through free recall, the images associated with dream destinations and favorite destinations perceptions and analyzed the data using content analysis methods. The results showed significant structural differences between tourists’ dream destination images and favorite destination images [57].

In terms of perceptual factors, Lu et al. verified that perceived authenticity influences the formation of a good heritage tourism destination image [112]. Openness is about the friendliness and politeness people feel and their tolerance for cultural and religious diversity [113]. Zenker et al. demonstrated that perceived openness indirectly influences tourists’ intentions by affecting destination image [114]. Guizzard et al. clarified the relationship between tourism and sustainability and verified that perceived value mediates between perceived sustainability and destination image [115].

From the compilation of literature, it is concluded that the formation of destination image is intricate and complex, and its formation process is affected by various factors with different degrees and aspects. Therefore, to gain a comprehensive and in-depth understanding of the formation process of different types of destination images, it is necessary to examine the influence of both personal factors and information sources on destination images in a comprehensive manner in practical research.

5. The Influence of Destination Image on Consumer Behavior

Tourist behavior associated with destination image can be divided into three stages: pre-tourism, during tourism, and post-tourism [116]. Tourist behavior before tourism includes travel intention/visit intention and decision; tourist behavior during tourism mainly refers to place attachment/brand attachment; and tourist behavior after tourism has satisfaction, loyalty, revisit intention, recommendation intention, purchase intention, and word of mouth (WOM). By compiling the literature from January 2012 to February 2022, it is found that studies on destination image on consumer behavior in the last decade have focused on three major aspects of post-tour behavior, travel intention/visit intention, travel decision, and place attachment.

Table 3. Overview of studies on the influence of destination image on tourists’ consumption behavior.

Author (Year)	Independent Variable	Dependent Variable		Path Relations Containing Image Variables
		Name of Variable	Measurement Indicators
1. Josiassen and Assaf (2013)	A, B, C	Travel decision	①, ②	A + B + C→① + ②
2. Fu et al. (2016)	A1, A2, D	Travel intention	②	D→A1→③; D→A2→③; D→A1→A2→③; D→③
3. Lai et al. (2020)	A1, A2	Intention to visit	④	A1→④; A1 a→A2→④
4. Jiang et al. (2017)	A, E	Place attachment	⑤, ⑥, ⑦, ⑧	A→E→⑤ + ⑥ + ⑦ + ⑧
5. Liu et al. (2020)	A2, F, G, H2	Place attachment	⑨, ⑩	F→A2; F + G→A2; G + H2→b A2; F→A2→⑨ + ⑩
6. Kim et al. (2012)	A, I	Intention to revisit	⑪	I→A→⑪
7. Prayag and Ryan (2012)	A, D, J, K	Loyalty	⑪, ⑫	D→A→J→K→⑪ + ⑫; D→A→K→⑪ + ⑫
8. Veasna et al. (2013)	A, J, L	Satisfaction	⑬	L→A→J→⑬
9. Sun et al. (2013)	A, K, M, N	Loyalty	⑪, ⑫	M→A→N→K→⑪ + ⑫; M→A→K→⑪ + ⑫
10. Chen and Phou (2013)	A, J, K, O, P	Loyalty	⑪, ⑫	A→K→⑪ + ⑫; A→K→P→J→⑪ + ⑫; A→P→J→⑪ + ⑫; A→O→P→J→⑪ + ⑫
11. Assaker and Hallak (2013)	A, K, Q	Intention to revisit	⑪	Q→A→K→⑪
12. Chew and Jahari (2014)	A1, A2, R2, R3	Intention to revisit	⑪	R2→A1→⑪; R2→A2→⑪; R3→A1→⑪; R3→A2→⑪
13. Hallmann et al. (2015)	A1, A2, A4	Intention to revisit	⑪	A1 + A2→A4→⑪
14. Stylos et al. (2016)	A2, A3, A4, S	Intention to revisit	⑪	A2→A4→⑪; A3→⑪; S→A3→A4→⑪
15. Stylos et al. (2017)	A1, A2, A3, A4	Intention to revisit	⑪	A1→A4→⑪; A2→A4→⑪; A3→A4→⑪; A3→⑪
16. Stylidis et al. (2017)	A1, A2, A4	Willingness to recommend	⑫	A1→A2; A1→A4→⑫; A2→A4→⑫; A1→⑫; A2→⑫
17. Kim (2018)	A, K, T	Loyalty	⑪, ⑭	A→⑪ + ⑭; T→A→⑪ + ⑭; T→A→K→⑪ + ⑭
18. Lv and McCabe (2020)	A, K, N, U, V	Loyalty	⑪, ⑫	A→⑪ + ⑫; A→K→⑪ + ⑫; A→N→⑪ + ⑫; A→V→⑪ + ⑫; U→⑪ + ⑫; U→K→⑪ + ⑫; U→N→⑪ + ⑫; U→V→⑪ + ⑫
19. Marques et al. (2021)	A1, A2, A5, K	Loyalty	⑫, ⑮	A1→⑫→⑮; A2→K; K→⑫→⑮; A2→⑫→⑮; A5→⑮
20. Tasci et al. (2022)	A1, A2, J1, J2, H2, W3	Loyalty	⑪, ⑫	A1 + A2→J1 + J2; J1 + J2→⑪ + ⑫; A1 + A2→J1 + J2→⑪ + ⑫; H2→c W3; W3→⑪ + ⑫; H2→c W3→⑪ + ⑫

Source: compiled from relevant literature. Note: 1. The meaning of independent variable symbols: A, destination image (A1, cognitive image; A2, affective image; A3, intentional image; A4, overall image; A5, unique image); B, social awareness; C, normative sensitivity; D, personal involvement; E, perceived authenticity; F, affective component of brand loyalty; G, brand authenticity; H, perceived distance (H1, social distance; H2, cultural distance); I, experience; J, place attachment (J1, place identity; J2, place dependence); K, satisfaction; L, destination source credibility; M, familiarity; N, perceived value; O, destination personality; P, destination trust; Q, novelty-seeking motivation; R, perceived risk (R1, physical risk; R2, psychosocial risk; R3, financial risk); S, personal normative beliefs; T, memorable travel experience; U, sensory impressions; V, perceived quality; W, emotional solidarity (W1, hospitality; W2, emotional closeness; W3, compassionate understanding). 2. The meaning of measurement indicator symbols: ① willingness to travel in the next 12 months; ② likelihood of traveling in the next 12 months; ③ intended future choice; ④ choice in the near future; ⑤ my experience at this destination is irreplaceable; ⑥ it means a lot to me to visit this destination; ⑦ I feel a strong sense of belonging to this destination; ⑧ this destination promotes my relationship with others; ⑨ I have a strong sense of attachment to this destination; ⑩ I have a strong emotional connection to this destination; ⑪ intention to revisit; ⑫ willingness to recommend; ⑬ satisfaction; ⑭ word of mouth; ⑮ purchase intention. ^a Three of the six cognitive image factors. 3. Path relationship symbolic meanings: ^b and ^c denote “→” represent significant negative correlations, and the rest “→” all represent significant positive correlations.

broadly reflects the overview of research on this topic in the last decade with 20 empirical studies, including 1–3 studies on travel intention and decision making, 4–5 studies on place attachment, and 6–20 studies on post-trip behavior.

5.1. The Influence of Destination Image on Pre-Travel Behavior

Regarding the influence of destination image on pre-travel behavior, researchers in the last decade have focused on the impact of destination image on tourists’ intention to travel or visit and travel decisions. Josiassen and Assaf used Denmark as an example to demonstrate the relationship between destination image and tourism decision-making in terms of social awareness and normal sensitivity, and the relationship between destination image and travel decision-making was stronger for travel with higher social awareness; in addition, the relationship between destination image and tourism decision-making is stronger when the tourists who are more easily influenced by the regulations are more socially well-known [117]. Using China as an example, Fu et al. confirm that there is a correlation between audience engagement and tourist travel intention, but that cognitive and affective images do not mediate the relationship [26]. Lai et al. investigated the effects of perceived and affective images of Australian food on Chinese tourists’ intention to visit and found that cognitive food images were better predictors of intention to visit than affective images. Three of the six cognitive food image factors were associated with “choosing in the near future”, and five other measures were significantly positively correlated [30].

The results show that to have a comprehensive understanding of the influence of destination image on pre-travel behavior, in addition to distinguishing the influence of destination image dimensions on tourists’ travel intention/visit intention and travel decision, the antecedents of destination image, such as personal involvement (tourist/audience involvement), should be continuously explored and further explored how the antecedents of destination image affect different dimensions of destination image by influencing tourists’ intention to visit. In addition, the moderating role of different attributes and characteristic factors of destinations and tourists in the process of destination image influencing tourists’ travel intentions and tourism decisions should also be continuously explored. Finally, it is also essential to consider the specific types of destinations and to develop appropriate and effective destination marketing strategies for destinations based on different attributes and characteristics of tourists.

5.2. The Influence of Destination Image on Tourist Behavior during Tourism

Jiang et al. surveyed the destination image of Australia in the minds of international tourists and explored the relationship between the different dimensions of destination image, perceived authenticity, and place attachment, and it turns out that there was a remarkable positive relationship between destination image and all four dimensions of place attachment through the mediation of perceived authenticity [37]. Liu et al. used wine brands as a context to explore how brand loyalty affects place attachment; the results showed that the affective component of brand loyalty was related to the “I have a strong sense of attachment to this destination”, “I have a strong emotional connection to this destination”, and “I have no emotional connection to this destination” dimensions of place attachment. “I have no emotional connection to this destination” were significantly and positively correlated, and affective images positively mediated this process [118]. Although loyalty includes both cognitive and affective aspects, in the past, few tourism studies have studied the affective component. This study innovatively investigates the strong influence of the affective component of loyalty on place attachment.

By compiling the literature, the research on the impact of destination image on place attachment in the last decade is underdeveloped and in-depth. Exploration of the factors that shape place attachment is not comprehensive, and other factors need to be included in this research framework in the future, such as gender as a moderating variable for destination image influencing place attachment. In addition, previous studies often did not distinguish different dimensions of destination image. Future research should expand the influence of various dimensions of destination image on different dimensions of place attachment.

5.3. The Influence of Destination Image on Post-Travel Behavior

The impact of destination image on post-travel behavior is affected by a range of factors. Compared with the studies on tourists’ behavior before and during the trip, researchers have studied more deeply the effects of destination image on post-trip behavior in the last decade. Post-trip behavior mainly refers to the intention to revisit, willingness to recommend, satisfaction, and loyalty. Loyalty generally includes revisit intention and recommendation intention, and sometimes word-of-mouth and purchase intention. Kim et al. surveyed American college students’ perceptions of Korean tourist destinations and confirmed that experiences indirectly impact tourists’ revisit intention by positively influencing destination image [109]. Veasna et al. surveyed international tourists in two destinations, Angkor Wat, Cambodia, and Taipei 101. They verified that destination source credibility positively influenced tourist satisfaction with the destination through the mediation of place attachment and destination image [119]. Many researchers have proved that there is also a correlation between tourist satisfaction and loyalty; for example, Prayag and Ryan surveyed international tourists on the island of Mauritius and found that personal involvement, destination image, and place attachment indirectly affect loyalty, and overall tourist satisfaction directly affects loyalty [74]; Sun et al. used Hainan as a context to develop an integrated model to examine the antecedents of destination loyalty among Chinese domestic tourists, with satisfaction directly and positively influencing loyalty, perceived value indirectly and positively influencing loyalty through the mediation of satisfaction, and destination familiarity indirectly and positively influencing satisfaction through the mediation of destination image, ultimately having an indirect positive effect on loyalty [90]; Chen and Phou conducted a survey of foreign tourists visiting Angkor Wat, Cambodia, continued to explore the antecedents of loyalty, and in addition to destination image, destination personality, as an antecedent of satisfaction, had an indirect positive effect on loyalty [120]. Kim argued that loyalty encompasses revisit intention and word of mouth, verifying that memorable tourism experiences indirectly and positively influence loyalty mediated by destination image [92]. Lv and McCabe first integrated sensory impressions into existing destination loyalty models, and the results showed that sensory impressions are highly correlated with perceived quality, perceived value, satisfaction, and loyalty, especially after the trip, and sensory impressions had a greater impact on loyalty than destination image [121].

In addition to the above studies, which only examine destination image as a whole to study its influence on post-travel behavior, many studies comprehensively address cognitive image, affective image, intentional image, overall image, and unique image. Chew and Jahari divided destination image into two dimensions, cognitive image and affective image, and surveyed Malaysian tourists who visited Japan to verify that psychosocial risk and financial risk were significantly and positively related to revisiting intention through the mediation of cognitive and affective images [122]. Hallmann et al. verified that cognitive and affective images positively influenced tourists’ revisit intention with the mediation of overall image, using winter sports destinations as an example [14]. Stylos et al. examined the complex relationship between destination image components and behavioral intentions, and affective images in the mediation of overall image. Stylos et al. surveyed the intricate connection between destination image components and behavioral intentions and found that affective images mediated by holistic images significantly and positively influenced revisit intentions, and that personal normative beliefs moderated the relationship between affective images and holistic images; intentional images directly and indirectly positively influenced revisit intentions [123]. Revisit intention, which is generally consistent with the previous findings. The last study examined the moderating effect of individual normative beliefs about the dimensions of destination image on revisit intention, but the results were that there was no moderating effect. The current study verified that place attachment moderates the positive impact of intentional image on revisit intention and introduced nationality (UK and Russia) as a moderating variable. The results showed that there is a different ranking of the indirect effects of cognitive, affective, and intentional images on revisit intention for tourists from the two countries [27]. Marques et al. surveyed foreign tourists in Sofia, the capital of Bulgaria, based on cognitive and affective images. Based on cognitive and affective images, a unique image of the destination was introduced for the first time to test the impact on the intention to revisit the destination. Affective image was found to indirectly influence loyalty (willingness to recommend and purchase intention) mediated by satisfaction, while cognitive and unique image did not influence satisfaction and directly influenced loyalty. In addition, the study found that willingness to recommend affects purchase intention [124].

The above studies introduce different concepts about destinations and tourists and combine them with destination images to explain destination loyalty. However, few existing studies integrate place-oriented and people-oriented concepts to investigate their relative effects on loyalty. Tasci et al. filled this gap by investigating domestic and international tourists in Antalya, Turkey, and showed that cognitive and affective images indirectly and positively influence, mediated by place attachment and place identity loyalty; the shorter the cultural distance, the higher the sympathetic understanding of tourists and the greater the positive effect on loyalty [125]. From the results, it is clear that perceived distance and affective solidarity are less predictive of destination loyalty than the cognitive image, affective image, and place attachment.

It has been generally verified that destination image influences tourist behavior. When researching specific types of destinations, it is essential to base the research on the distinctive properties of the destination, try to understand the characteristics of tourists’ needs, reasonably select relevant concepts of destination orientation and people-orientation, and combine different dimensions of destination image to study their complex effects on tourists’ behavior and their processes.

6. Conclusions

The study of destination image has been a hot issue in the field of international tourism for approximately fifty years, and the research on destination image has been constantly updated, and the research methods have become more and more diverse. By analyzing the research content of this field in the last decade, the current research on destination image still needs to be improved and enhanced. It is also the direction that researchers should strive towards in the future.

6.1. Research Perspectives

Focus on researching the effects of the COVID-19 epidemic on destination image: As a significant global public health emergency, COVID-19 objectively curtails the possibility of offline field tourism, while at the same time potentially allowing virtual tourism to reach an unprecedented growth peak. Researchers, therefore, need to conduct future studies on the impact of COVID-19 on the image of virtual tourism destinations and the influence of COVID-19 on virtual tourism behavioral intentions by affecting the image of virtual tourism destinations; traditional tourism destination development will also continue to face significant challenges. The differences in tourists’ perceptions of destination images before and after tourism are influenced not only by tourists’ factors, but also by the risk of COVID-19 infection at the destination, the degree of protection against COVID-19 at the destination, the problem of tourists’ dining, and the possible crowding problems and ticket price increases caused by the restriction of tourist flow at the destination in the post-epidemic era.

Focus on comparative studies among destinations to enhance the generalizability of the study: When measuring destination image, most researchers select only a single destination as a sample place. However, because of the different types of destinations and their various attributes and characteristics, applying the research framework of one destination to other destination image studies may be “unconventional” and the research findings are largely inconsistent. In order to improve the generalizability of research results and to discover common patterns among different types of destination images, future researchers should conduct comparative studies of different kinds of destinations as much as possible.

Focus on research on the differences in destination images of the same destination at different stages: By reviewing the literature, we can figure out that most scholars focus more on measuring different dimensions of destination image or the causes and results of its formation, while relatively little research has been conducted on the dynamic formation process of the destination image. Smith et al. documented the dynamic destination image perceived by Canadian travelers to Peru at several critical moments of their trip [111], and this study suggests that experiences and personal experiences influence destination image, but it was not possible to measure the extent of the respective influences, and future research should strive to break through this limitation.

Focus on the differences in destination image across time or climate conditions for specific types of destinations: This can help destination managers better understand the accurate perceptions and needs of tourists, and, thus, improve their image. Future research should expand to other types of destinations, such as heritage tourism destinations, rural tourism destinations, and various types of nature tourism destinations, so as to guide destinations to gain a deeper understanding of their own image, and to improve their image in a targeted manner based on an understanding of the current situation, thus establishing a unique destination image.

6.2. Limitations

First, the literature reviewed in this paper is in English and may not represent the views of literature written in other languages. Second, English is not the author’s native language, and there may be some fallacies in reading and understanding the English literature due to their level of proficiency. Finally, this paper only compares the relevant literature published in the top six journals in the international tourism academic field and does not consider other journals; therefore, the literature reviewed may not be comprehensive. At the same time, it should be pointed out that, considering that some of the literatures appearing in the tables were not analyzed in depth in the context, our study mentioned the relevant references here to ensure the completeness of the review information [126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141].