You exist in my song! How a destination-related popular song enhances destination image and visit intentions

Abstract

Research on media-induced tourism has been growing in recent years. The existing research has shown that films, television programs, and radio commercials can induce tourism behavior. The present research aimed to introduce a new form of music-induced tourism to the literature by examining the impact of a destination-related popular song on prospective tourists’ intentions to visit the destination. A theoretical model that included music-evoked mental imagery, affective image, overall image, and visit intentions was developed; 381 respondents participated in a web-based experiment to test the hypotheses, and the model was validated using structural equation modeling. The results revealed that music-evoked mental imagery led tourists to generate positive affective images and overall images of the destination, which in turn influenced their intentions to visit the destination. The implications of the findings for tourism marketers and future research directions are also discussed.

Keywords

Affective image destination image destination-related song mental imagery overall image visit intentions

Introduction

In that damp and rainy small town, I’ve never forgotten you. Chengdu, what I can’t take away is you! So, come and have a walk with me on the streets of Chengdu. We’ll walk on till the lights are out and walk through it. I will hold you close, every step we’ll take it slow. And, then, we will take a break in a little pub down by Yulin Road.

Above, we present lyrics from one of the most popular Chinese songs in recent years, named Chengdu, after a city located in southwestern China. According to the Sina Weibo (the Chinese counterpart of Twitter) Index, hashtag mentions of the city of “Chengdu” tripled in the month following the release of the song (National Business Daily, 2017). We cannot simply say that the recent great increase in the number of tourists in Chengdu was the result of the contribution of this song, but clearly, the possibility exists. Therefore, the following questions arise: Can a destination-related song (that is not intended to promote the destination) influence prospective tourists’ perceptions of the destination’s image and their visit intentions? If so, how does this occur?

Music tourism has been discussed in numerous studies. In particular, Connell and Gibson examined the relationship between music and place from the perspective of human geography during the last two decades, which represented an important contribution to this field. However, previous music tourism studies have mainly focused on a destination’s local music (Connell and Gibson, 2003, 2004a), music for place promotion (Connell and Gibson, 2004b), and music festivals as a promotional tool for places (Gibson and Connell, 2007, 2011), while the influence of songs with titles or lyrics that are related to, but not created for, a destination on consumers’ intentions to visit the destination has been neglected. Most importantly, all of these previous music tourism studies involved qualitative research. Therefore, the mechanism of the influence of destination-related music remains largely unknown and should be further explored and empirically examined.

On the other hand, as a key element in the travel decision-making process, tourists’ destination choice has always been a fundamental issue for both academics and practitioners (Karl et al., 2015). Abundant studies from various academic disciplines have concentrated on the influencing factors of the destination choice process (see the review by Wu et al., 2011). Among these factors, destination image plays a major role in the destination choice process because prospective visitors heavily rely on images of alternative destinations when choosing their tourism destinations (Chen et al., 2016; Tasci and Gartner, 2007). Thus, over the last four decades, extensive research has been conducted on destination image, particularly image formation (Rodríguez-Molina et al., 2015). A wide array of sources has been identified, mostly from direct marketing elements, such as ad pictures (Babin and Burns, 1997), radio commercials (Miller and Marks, 1992), destination websites (Lee and Gretzel, 2012), and travel brochures (Jenkins, 2003). However, recent studies have found that destination images are more affected by the use of nonpromotional communication (e.g. Connell, 2005), such as films (Lee and Bai, 2016), TV series (Skinner, 2016), reality shows (Fu et al., 2016), and postcards (Yüksel and Akgül, 2007). As another form of nonpromotional communication, the influence of popular music on destination image should be further discussed.

Music, as a symbolic element in the communication of meaning, has been identified as an effective inducer of emotions (Hung, 2001). In a related field, marketing and advertising scholars, beginning with Gorn (1982), have discussed the effect of music in advertisements, but contradictory findings have been reported (Oakes, 2007).

Unlike music in commercials, which combine promotional information and music in one advertisement and are designed to enhance the advertising effect by making people more involved in advertising (Allan, 2006), a destination-related popular song is just ordinary popular music that is connected to a place through its title and content, without any commercial purposes, and the place is mostly where the narrative story in the song occurs. However, mental images can be evoked while listening to music, and listeners’ emotions can consequently be induced by such visual imagery (Egermann et al., 2013). Additionally, consumers’ mental images of a product have been demonstrated to have a substantial influence on consumer interest and information search behavior (MacInnis and Price, 1987), consumer attitudinal judgments (McGill and Anand, 1989), and consumer affective responses (Miller and Marks, 1997). We expect that potential tourists experience the same mental image process when listening to a destination-related hit song and that this mental image process influences their destination image formation and, ultimately, their intentions to visit the destination.

The present article therefore aims to clearly explain the effect of a destination-related hit song on destination image and consumers’ visit intentions. Drawing on a theoretical model addressing the proposed link between music-evoked mental imagery processing, affective destination image, overall destination image, and visit intentions, we first extend the current destination image literature by proposing a new source of image formation, that is, the destination-related song; by testing the proposed model, our results also provide empirical evidence for the mechanism of such destination image formation. The findings also broaden the music-evoked mental image literature by examining the effect of the destination-related song on tourists’ destination choice, thereby contributing to this field of literature as well. Meanwhile, our findings may benefit practitioners by helping them take a new approach to making decisions regarding destination image development and destination marketing.

Theoretical background

Music tourism

Music tourism is an underestimated component of the cultural economy (Gibson and Connell, 2003) that occurs when “people travel, at least in some part, because of music, whether to festivals or raves, concerts, museums, graveyards or opera houses” (Gibson and Connell, 2007). Thus, tourists travel to a destination because of the link between the destination and music-related factors, such as a place of performance (e.g. opera house), places of musical composition, places in lyrics (e.g. the song “Mull of Kintyre”), and places of births and deaths (e.g. Vienna and Salzburg) (Gibson and Connell, 2007). Although many song lyrics mention places, only a few song lyrics have been used by tourism organizations, and they are rarely used as a trigger for tourism behavior (Gibson and Connell, 2007). Additionally, almost all of the existing research on music tourism has involved qualitative research. Thus, the mechanism for the effect of music on consumers’ tourism behavior remains unknown.

Destination-related popular songs

Destination-related music usually refers to music that represents one place (Forman, 2000) because local music can be viewed as a sensuous production of a place (Cohen, 1995). Thus, from the perspective of place marketing, music can constitute an identity and a promotional image of a place, such as Tamworth, a small town in Australia, which has successfully positioned itself as a “country music capital” based on its January festival (Gibson and Davidson, 2004). In addition, when people travel to a place to attend festivals, concerts, or other music-related events, this synergy between the arts and the tourism constitutes music tourism (Gibson and Connell, 2007; Nurse, 2004).

In contrast to the types of music associated with tourism describe above, the destination-related music discussed in the present study refers to popular songs that are connected to a destination only through the lyrics, particularly the name of the song, and that tell a story that takes place in this destination. In addition, the genre, form, or other characteristics of the song are not connected to the destination, and the purpose of the songwriting is also unrelated to marketing or promoting the destination. There are many destination-related popular songs, such as Bertie Higgins’s “Casablanca,” The Eagles’ “Hotel California,” and Savage Garden’s “Santa Monica.” Surprisingly, it is difficult to find any literature regarding the effect of such popular songs on listeners’ reactions to the places in these songs. In the tourism field, studies on the influence of mass media on destination image and destination choice have been on the rise in recent years (e.g. Fu et al., 2016; Lee and Bai, 2016). As an important part of mass media, popular music and its role in tourist decisions need to be addressed.

Music-evoked mental imagery

Mental imagery refers to the perceptual experience of sensory information without direct sensory input (Pearson et al., 2015; Renner et al., 2019). As mental imagery enables us to “pre-experience” future activities (Holmes et al., 2016) and anticipates the emotional consequences of such activities, it is an essential part of decision-making (Schacter et al., 2012) and a guide for future behavior (Sandberg and Conner, 2008).

Mental imagery can be triggered by multiple stimuli, including auditory, visual, haptic, and gustatory stimuli (MacInnis and Price, 1987); among these types of stimuli, visual stimuli are dominant (White et al., 1977). As a major form of auditory stimuli, music is effective in stimulating listeners’ visual imagery (Eerola and Vuoskoski, 2015; Vuoskoski and Eerola, 2012). Thus, music-evoked visual imagery is a process whereby a listener conjures visual images while listening to music, whether intentionally or unintentionally (Eerola and Vuoskoski, 2015).

Nearly all the music in people’s everyday lives, particularly popular songs, has lyrics with explicit narrative content. The construction of narratives is a fundamental way for a person to express his/her experiences or to make sense of the world (Polkinghorne, 1988). When the narrative (in the form of lyrics) appears to be an emergent property of the listening process (Lavy, 2001), music conveys semantic meaning (Koelsch et al., 2004). According to the transportation-imagery model (Green and Brock, 2002), listeners experience a state of transportation while listening to a narrative and are transported to the narrative world by undertaking a mental journey (Appel and Richter, 2010). In addition, music can enhance listeners’ emotional experiences of a narrative (Brown and Volgsten, 2005); thus, visual imagery may be evoked in most music-listening episodes, particularly when listening to music is the primary activity (Vuoskoski and Eerola, 2015).

Regarding the consequences of music-evoked mental imagery, a change in a listener’s emotions is the most commonly reported result in the existing studies (see the review by Eerola and Vuoskoski, 2013) because music-evoked imagery can produce deep relaxation; thus, health benefits, such as a reduction in cortisol levels, may be produced (McKinney et al., 1997). The influence of music-evoked mental imagery on emotions or mood has also been found based on other forms of mental imagery, such as mental images from visual cues, for example, print ads and photographs (MacInnis and Price, 1987) and sound-evoked mental imagery in radio commercials (Miller and Marks, 1992). In the tourism field, Walters et al. (2007) revealed that in a destination advertisement, picture-evoked mental imagery could enhance expectations of the destination and facilitate consumption decisions. However, the effect of popular music-evoked mental imagery on the decisions of prospective tourists remains unknown.

Affective destination image

Destination image generally refers to the sum of knowledge, ideas, feelings, or impressions that an individual has with regard to a destination (Crompton, 1979; Fakeye and Crompton, 1991; Kotler et al., 1993; MacKay and Fesenmaier, 1997; Stylidis et al., 2017). Previous studies have confirmed that destination image is a multidimensional construct that includes both the cognitive and affective components (Baloglu and Brinberg, 1997; Stylidis et al., 2017). Cognitive destination image consists of the beliefs and knowledge regarding the destination’s physical attributes that are based on factual information (Papadimitriou et al., 2015; Whang et al., 2016), whereas affective destination image emphasizes the subjective feelings and emotions that an individual attaches to a destination (Baloglu and Brinberg, 1997; Papadimitriou et al., 2015). The current study focuses only on affective destination image because in the context of popular music-evoked mental imagery, no visual elements exist, as they do in, for example, ad pictures, videos, and postcards. Additionally, it is difficult to visualize the specific information about a destination, such as the landscape, infrastructure, or accommodations, that are described in the narrative part of a song (lyrics); thus, cognitive destination image is not suitable for the present study.

Because affective destination image emphasizes a person’s emotional responses to a destination (Shani and Wang, 2011), it influences the destination selection stage of destination evaluation (Gartner, 1993). Furthermore, a number of studies have revealed that compared to cognitive destination image, affective destination image has a greater impact on the development of an overall image of the destination (Baloglu and McCleary, 1999; Kim and Yoon, 2003). This finding indicates that affective destination image, which is consistently highlighted in the existing literature, is a powerful influencer in the evaluation of a destination.

Overall image

Overall image refers to a consumer’s overall perceptions of a product derived from the processing of information from different sources (Han et al., 2009). In the tourism context, overall image can be summarized as a holistic impression of a destination ( Echtner and Ritchie, 1993) that is formed as a result of both the cognitive and affective evaluations of the destination (Baloglu and McCleary, 1999). Many past studies have examined the interrelationship between cognitive destination image and affective image in forming an overall image of a destination (e.g. Gartner, 1994; Sidali, 2014; Stern and Krakover, 1993). Some studies have also shown evidence that the cognitive image is an important source of affective image formation (Baloglu and McCleary, 1999; Kim and Richardson, 2003). Furthermore, several studies have suggested that the overall image is greater than the sum of its parts (Calantone et al., 1989; Fakeye and Crompton, 1991; Phelps, 1986). An overall image can be real or projected, and it may determine tourists’ attitudes toward a destination and be connected to overall favorable or unfavorable feelings (Ahmed, 1991; Whang et al., 2016). Thus, overall image plays an important role in tourists’ decision-making processes (Papadimitriou et al., 2015).

Research framework and hypothesis development

Although individuals form their beliefs regarding a destination based on the attributes of the destination that external stimuli reveal, these beliefs vary among individuals depending on their internal factors (Um and Crompton, 1992), such as their personal needs, motivations, prior knowledge, and preferences (Beerli and Martín, 2004). Thus, prospective tourists build their own mental pictures of a tourist destination based on their personal perceived images (Bramwell and Rawding, 1996; Gartner, 1993). Currently, listening to music has become the most prevalent leisure activity, overtaking other traditional forms of leisure, including watching TV/movies and reading books (Rentfrow and Gosling, 2003). Thus, music might be an external stimulus that affects a prospective tourist when he/she makes a decision; hit songs might particularly act as such a stimulus owing to their high exposure rates and great popularity. A destination-related song can at least introduce the name of a destination into the consideration set. More importantly, music has been found to change a person’s internal state, such as his/her emotions, moods, or feelings (Eerola and Vuoskoski, 2013). While imagery processing can be influenced by the emotions that an individual experiences as he/she pictures the imagery (Robinson and Swanson, 1993), whether individuals have positive or negative moods, they will be likely to have vivid imagery (Bywaters et al., 2004). From a holistic perspective, mental imagery has been found to be an important source of psychological impressions of a place, which are an important component of destination image (Echtner and Ritchie, 1993). Meanwhile, imagery also has a particularly powerful effect on emotions (Holmes et al., 2009). The emotions or feelings an individual has about a destination constitute his/her affective destination image (Papadimitriou et al., 2015). Thus, it appears that listening to a destination-related song can influence the formation of tourists’ affective destination images.

On the other hand, similar to the effect of mental imagery in advertising, which prompts consumers to imagine themselves in the circumstances of the advertisement setting, visual imagery may serve as a favorable accompanying stimulus and may thus be able to improve consumers’ attitudes toward a product in an advertisement (Rossiter and Percy, 1980). Following this logic, we assume that when prospective tourists listen to a destination-related hit song, the music-evoked mental imagery will lead them to imagine the situation, moment, and destination in which the story in the song happened. Similar to attitudes toward a product in an advertisement, their attitudes toward the destination will be influenced by the feelings or emotions generated by the mental imagery. Therefore, according to the definition of affective destination image, we propose the following hypothesis:

H1: Music-evoked mental imagery directly influences affective destination image.

A large amount of existing evidence has shown that affective destination image is the affective component of overall destination image (Baloglu and McCleary, 1999; Gartner, 1994; Sidali, 2014; Stern and Krakover, 1993) and that affective destination image has a direct influence on overall destination image (Papadimitriou et al., 2015; Whang et al., 2016). Thus, considering that music-evoked mental imagery can influence the affective image of a destination, we infer that such mental imagery could influence overall destination image as well. Therefore, we hypothesize the following:

H2: Music-evoked mental imagery directly influences overall destination image.

Mental imagery involves the creation of stories through the mental simulation of future events (Green and Brock, 2000), which entails the cognitive construction of fantasies about hypothetical scenarios (Escalas, 2004). In the context of tourism decision-making, the mental imagery evoked by a destination-related hit song may lead tourists into the hypothetical scenario of the song’s story. Such mental imagery not only improves tourists’ perceptions of the tourism product but also can potentially facilitate the satisfaction of tourists’ original travel motives (Um, 1993). Before making a final destination choice, tourists usually imagine their future activities when they travel to the destination, and the actual behavior (travel to the destination) may become the goal that tourists wish to achieve (Walters et al., 2007). Therefore, mental imagery can influence an individual’s subsequent behavior (Libby et al., 2007). Because visit intentions can be explained as a tourist’s “perceived likelihood of visiting a certain place within a specific period” (Whang et al., 2016), we propose the following:

H3: Music-evoked mental imagery directly influences visit intentions.

Regarding the relationship between affective destination image and overall destination image, prior research has provided strong support for the direct impact of affective image on overall image (Baloglu and McCleary, 1999; Beerli and Martín, 2004; Lin et al., 2007). Furthermore, the contribution of affective destination image to overall image is greater than that of the cognitive image component (Baloglu and McCleary, 1999). Thus, based on the conceptual and empirical results from the literature, we propose the following:

H4: Affective destination image directly influences overall destination image.

Most tourists usually have limited knowledge about a destination before they visit it. Under these circumstances, destination image plays a critical role in tourists’ decision-making processes, and a destination with strong, positive, recognizable, and distinctive images is more likely to be chosen (Beerli and Martín, 2004; Woodside and Lysonski, 1989). All the characteristics of destination image noted above are tightly related to tourists’ feelings about and emotions regarding a place, which is precisely the meaning of affective destination image. In other words, tourists’ behavior is influenced by their images of a destination, particularly at the destination choice stage (Beerli and Martín, 2004), and the influence of the affective component of destination image is much stronger than the influence of the cognitive component, that is, the objective properties of the destination (Russell and Snodgrass, 1987). The more positive the affective image of a destination is, the greater the likelihood that tourists will choose the destination as their actual travel destination. Therefore, we hypothesize the following:

H5: Affective destination image directly influences visit intentions.

Overall image can be viewed as tourists’ general impressions of a specific destination (Echtner and Ritchie, 1993). Overall image integrates the cognitive and affective components of destination image (Sidali, 2014) but can be greater than the sum of these two components (Fakeye and Crompton, 1991). Prior studies have provided strong support for the significant influence of overall image on consumers’ or tourists’ decision-making processes (e.g. Lin et al., 2007; Prendergast and Man, 2002; Ryu et al., 2008). A destination with a strong positive image is more likely to be included in a tourist’s selection set and has a high possibility of being chosen (Alhemoud and Armstrong, 1996; Echtner and Ritchie, 1993). Therefore, we propose the following hypothesis:

H6: Overall destination image directly influences visit intentions.

The theoretical framework and hypotheses of the present study are presented in Figure 1.

Figure 1.

Research framework.

Methodology

Pretest

The objective of the pretest was to choose a popular song that was suitable for our study. Ten popular songs with names related to a Chinese city, including Beijing, Nanjing, Chengdu, Chongqing, Hangzhou, Dali, Alashan, Lanzhou, Xian, and Guiyang, were selected by the authors by searching various music websites. All songs were popular songs, and we researched in-depth the background of all the songs, including their writers, singers, and background stories and any information about the connection between the songs and the destinations, to ensure that none of them were written with the purpose of promoting the destination. Furthermore, to avoid bias due to prior impressions, we deleted two songs that had been at the top of the Billboard chart of Chinese songs in the last 10 years. The remaining eight songs were played one by one in a focus group that included three PhD students, three master’s students, and two professors. The basic selection criteria for the song that would be used as the stimulus in our research were the possibility that the song would trigger mental imagery when someone listened to it and its potential to easily motivate strong emotions, whether positive or negative. After two rounds of discussion, the song “Go to Dali” was chosen as the stimulus. The song expresses a common person’s depressive emotions and hope. The lyrics of the chorus are as follows:

You aren’t satisfied with your life, and you haven’t laughed for a while, but you don’t know the reason why. Since you’re not happy and don’t like it here, why don’t we go all the way to Dali toward the west? The trip is a bit bumpy, and the air is a bit thin. The wider the scenery, the lonelier you feel. I don’t know who will be waiting there later. Who doesn’t have a head covered with dust? Whose shoulder hasn’t been bitten? Maybe love is by Erhai Lake, waiting. Stories may be happening….

The city in the song, Dali, is located in the northwestern area of Yunnan Province and is an ancient city west of Erhai Lake and east of Cangshan Mountain. Dali is famous because of its unique cultural heritage and picturesque surroundings (Dai et al., 2012).

Sample

An online experiment was developed to achieve the research objectives. A total of 400 participants (381 valid samples) were recruited by a well-known professional online survey company in China. The participants came from 25 provinces (of 29 total provinces) and 4 municipalities (among all municipalities) of China. The participants from Guangdong represented the largest portion (13.91%), followed by those from Shanghai (9.45%) and Beijing (8.14%). We used the following two screening questions to ensure that none of the respondents had been to the city of Dali and that they had not heard the stimulus song before: “Have you even heard this song named ‘Go to Dali’ before?” and “Have you been to Dali city before?” Among the participants, 45.31% were male, and 54.69% were female. Approximately three-fourths of the respondents (76.4%) were 20–40 years old, and 69.3% had earned a bachelor’s degree. A large portion of the respondents (77.4%) reported a monthly income of less than 10,000 RMB (see Table 1 for details).

Table 1.

Demographic characteristics of the respondents.

Demographic characteristics	Frequency	Percentage (%)
Gender
Male	174	45.31
Female	207	54.69
Age
20 and under	54	14.2
21–30	163	42.8
31–40	128	33.6
41–50	28	7.3
51 and over	8	2.1
Educational level
Without a bachelor’s degree	78	20.5
Bachelor’s degree	264	69.3
Graduate	39	10.2
Monthly income (RMB)
5000 and under	146	38.3
5000–10,000	149	39.1
10,000–15,000	62	16.3
15,000 and over	24	6.3

Measurement

A self-report questionnaire consisting of five sections was used to examine (i) music-evoked mental imagery, (ii) affective image, (iii) overall image, (iv) visit intentions, and (v) demographic measures. All scales used in our study were adopted from prior research. Specifically, an eight-item scale with a seven-point response scale from Miller and Marks (1997) was used to measure music-evoked mental imagery processing. This scale consisted of two dimensions: quantity (three items with a Likert-type scale ranging from 1 “strongly disagree” to 7 “strongly agree”) and vividness (five items, i.e. clear, vivid, intense, lifelike, and sharp with a seven-point Likert-type scale anchored by “does not describe at all” and “describes perfectly”). The affective image scale included four items (e.g. unpleasant/pleasant) and also used a seven-point bipolar scale; it was adapted from the instruments used by Papadimitriou et al. (2015) (two items) and Alvarez and Campo (2014) (two items). An overall image scale from Papadimitriou et al. (2015) was used; it included a single item that asked participants to indicate their overall feelings toward the destination on a seven-point scale. This one-item measurement has been widely used by prior studies (e.g. Baloglu and McCleary, 1999; Bigne et al., 2001; Kneesel et al., 2010; Lin et al., 2007; Qu et al., 2011). The three-item visit intentions scale, which used a seven-point Likert-type scale (ranging from 1 “strongly disagree” to 7 “strongly agree”), was adopted from Alvarez and Campo (2014). Finally, the demographic information of the sample, including gender, age, educational level, and income, was collected (see Appendix 1 for details).

Because the survey was conducted in China and all our participants were Chinese consumers, to ensure that all scales were clearly consistent with the original meaning and were well understood by the participants, we first translated the original English versions of the scales into Chinese and then carried out back-translation (Soriano and Foxall, 2002). A professional translator was invited to compare the two versions of the scales.

Process

All subjects were required to log on to the experimental website; they were informed that they would be participating in a psychological test that would involve listening to a popular song. After they passed the two screening questions, the stimulus song was automatically played, which lasted approximately 3 min. Then, the subjects were asked to complete the self-report questionnaire, including all measures and demographic items, in 5 min based on their feelings triggered by the song. All subjects who completed the entire experiment were paid by the online survey company.

Results

Reliability and validity of the measurement

Confirmatory factor analysis (CFA) was conducted with SPSS AMOS (24.0) to examine the reliability and validity of each construct. According to the fit statistic guidelines provided by Hu and Bentler (1995, 1998, 1999), a comparative fit index (CFI) score ≥ 0.95, an normed fit index (NFI) score ≥ 0.9, an root mean square error of approximation (RMSEA) score ≤ 0.6, and an standardized root mean square residual (SRMR) score ≤ 0.08 indicate a good fit. The CFA results showed a good overall fit between the measurement and the respective data sets. As presented in Table 2, χ²/df = 2.18, CFI = 0.975, goodness of fit index (GFI) = 0.942, NFI = 0.955, RMSEA = 0.056, and SRMR = 0.035. The convergent validity and discriminant validity of the constructs were also tested, as presented in Table 3. All average variance extracted (AVE) scores were higher than the threshold value of 0.5, indicating adequate convergence (Hair et al., 2006). For discriminant validity, as presented in Table 3, the square roots of the AVE value of each construct were greater than the correlations between the construct and all other constructs, indicating good discriminant validity as well. All the results of the CFA confirmed the causal relationships between observed variables and their underlying latent factors and verified the underlying factor structure for each scale.

Table 2.

Model fit indices for the measurement model.

Model fit statistics	χ ²	df	χ²/df	CFI	GFI	NFI	RMSEA	SRMR
	170.013	78	2.18	0.975	0.942	0.955	0.056	0.035

CFI: comparative fit index; GFI: goodness of fit index; NFI: normed fit index; RMSEA: root mean square error of approximation; SRMR: standardized root mean square residual.

Table 3.

Validity and reliability of the constructs (diagonal scores are the square roots of the AVE values).

Constructs	MIP	AFI	VI	AVE	CR	α-Value
MIP	0.79			0.63	0.93	0.93
AFI	0.79	0.89		0.51	0.80	0.80
VI	0.72	0.71	0.81	0.65	0.85	0.85

AVE: average variance extracted; MIP: mental imagery processing; AFI: affective image; VI: visit intention; CR: composite reliability.

Cronbach’s α coefficients and composite reliability (CR) values were used to test the reliability of the measurement, as presented in Table 3. All the CR values of the variables were larger than 0.7, and the Cronbach’s α coefficients were also greater than 0.7, suggesting that our scales have good reliability according to the recommendations by Fornell and Larcker (1981).

Structural equation modeling and hypothesis testing

Structural equation modeling (SEM) with SPSS AMOS 24.0 was used to test the overall model fit and the hypotheses of the conceptual model. The structural model included three latent variables (i.e. music-evoked mental imagery, affective image, and visit intentions) and one observed variable (i.e. overall image). Observed variables have been used in SEM in prior studies and have shown good fit with the models (e.g. Baloglu and McCleary, 1999; Qu et al., 2011; Tsiros and Mittal, 2000). As presented in Table 4, the structural model fit was good. All fit indices were acceptable according to the thresholds suggested by Hu et al. (1995) and Hu and Bentler (1998, 1999), that is, χ²/df = 2.23, CFI = 0.97, GFI = 0.94, NFI = 0.95, RMSEA = 0.057, and SRMR = 0.039.

Table 4.

Model fit indices for the structural model.

Model fit statistics	χ ²	df	χ²/df	CFI	GFI	NFI	RMSEA	SRMR
	204.838	92	2.226	0.971	0.935	0.949	0.057	0.039

CFI: comparative fit index; GFI: goodness of fit index; NFI: normed fit index; RMSEA: root mean square error of approximation; SRMR: standardized root mean square residual.

The model effectively explained all indicator variables. The squared multiple correlation coefficient (R²) for affective image was 0.473, the R² for overall image was 0.479, and the R² for visit intentions was 0.61. The final model and the estimates of the standardized path coefficients are shown in Figure 2. The results revealed that music-evoked mental imagery had a significant and positive influence on the participants’ affective images of the destination (β = 0.69, t = 9.51, p < 0.001) and visit intentions (β = 0.42, t = 6.08, p < 0.001). However, the influence on the overall image was not found to be statistically significant at the 0.05 level (β = 0.11, t = 1.68, p = 0.09), but the p-value was still less than 0.1; thus, it appeared to be marginally significant. The influences of affective image on overall image (β = 0.61, t = 7.54, p < 0.001) and visit intentions (β = 0.32, t = 3.66, p < 0.001) were also positive and significant, and the influence of overall image on visit intentions (β = 0.15, t = 2.48, p < 0.05) was significant and positive as well. This result indicates that hypotheses 1, 3, 4, 5, and 6 were well supported, while hypothesis 2 was marginally supported. All the path coefficients of the structural model are presented in Table 5.

Figure 2.

Final structural model. The values in parentheses are t values. *p < 0.05; **p < 0.01; ***p < 0.001.

Table 5.

Path coefficients in the structural model.

Hypotheses	Standardized loadings	t-Value	Results of hypothesis testing
H1: Affective image ← Mental imagery	0.69	9.51***	Supported
H2: Overall image ← Mental imagery	0.11	1.68	Marginally supported
H3: Visit intentions ← Mental imagery	0.42	6.08***	Supported
H4: Overall image ← Affective image	0.61	7.54***	Supported
H5: Visit intentions ← Affective image	0.32	3.66***	Supported
H6: Visit intentions ← Overall image	0.15	2.48*	Supported

*p < 0.05; **p < 0.01; ***p < 0.001.

General discussion

The present research aims to explore how a popular destination-related song can trigger listeners’ intentions to visit the destination in the song. As presented in Figure 2, the results show that through music-evoked mental imagery processing, listeners may generate destination visit intentions through four paths, including a direct path from mental imagery to visit intensions (β = 0.42) and three indirect paths, that is, (i) the path from mental imagery to affective image (β = 0.69), which in turn influences visit intentions (β = 0.32); (ii) the path from mental imagery to affective image (β = 0.69), which in turn influences overall image (β = 0.61) and ultimately influences visit intentions (β = 0.15); and (iii) the weak path from mental imagery to overall image (β = 0.11), which in turn influences visit intentions (β = 0.15).

Theoretical contributions

Our results provide three contributions to the existing literature. First, to the best of our knowledge, this study is the first empirical study to examine whether and how a popular song can effectively trigger consumers’ intentions to visit the destination related to the song. As prior research has identified various external stimuli that can motivate tourism behavior, including print advertisements (Babin and Burns, 1997; Walters et al., 2007), radio advertisements (Miller and Marks, 1997), television (Connell, 2005), postcards (Yüksel and Akgül, 2007), destination website design (Lee and Gretzel, 2012), and reality TV shows (Fu et al., 2016), the current study broadens the scope of tourism behavior stimuli by introducing a new form, that is, popular music, and it provides strong empirical support for the mechanism of its influence.

Second, the current study extends the literature on music tourism. Although previous studies, particularly those presented in the series of papers and books written by Connell and Gibson, have shown that music can be a useful trigger of tourism behavior, these previous works adopted the perspective of human geography and lacked empirical research support. Thus, our results could be a useful complement to Connell and Gibson’s achievements.

Third, our results extend the mental imagery literature, particularly concerning music-evoked mental imagery. Most existing research has focused on individual differences in mental imagery (Aleman et al., 2000; Halpern, 2015), mental imagery stimuli (MacInnis and Price, 1987), and the impact of mental imagery on emotions (Eerola and Vuoskoski, 2013; Schubert et al., 2018). Only a few recent studies have attempted to connect mental imagery to future tourism behaviors using picture stimuli (Walters et al., 2007), destination websites (Lee and Gretzel, 2012), and virtual reality presence (Bogicevic et al., 2019). Our results provide new evidence by demonstrating the influence of music-evoked mental imagery on consumers’ future intentions to visit a destination related to a song.

Finally, the current study also contributes to a better understanding of the psychological mechanism of the influence of music-evoked mental imagery on consumers’ destination visit intentions. No existing study has reported the specific paths for how music-evoked mental imagery influences consumer visit intention. Using SEM, we obtained results that provide a clear map for such a mechanism.

Practical implications

This study provides important implications for tourism marketers. First, the study suggests a completely new way to encourage prospective tourists to decide to visit a destination, that is, a destination-related popular song, which is a popular song created by one singer that is not intended to be a promotional tool for the destination. The key point of a destination-related popular song is the narrative related to the destination, such as a love story that took place in the destination or romantic memories connected to the destination. The results showed that such a song could trigger consumers’ mental imagery, generate a positive affective destination image, and ultimately influence consumers’ intentions to visit the destination. Thus, the question of how to motivate singers to create popular songs related to a destination is important for destination marketing managers. Destination managers could choose singers based on their own judgments and sponsor them to create popular songs related to the destination, or they could invite singers to come to the destination, immerse them in the context, and then ask them to write a song. Furthermore, even after a destination-related song has been created, it still needs to become popular; thus, the quality of destination-related songs and their promotion remain major challenges for destination marketers. Nevertheless, a popular destination-related song is undoubtedly a new and useful opportunity for destination marketers to promote a destination.

Second, based on our results, the most important facet of the mechanism of the influence of destination-related popular songs on visit intentions is music-evoked mental imagery. Thus, when creating songs, the kind of lyrics, the melody, the rhythm, and the type of music that can easily trigger consumers’ mental imagery are also crucial considerations for destination marketers. Therefore, professionals are needed to help marketing managers identify the different musical elements before they choose singers to create a song.

Third, we identified another important variable in the mechanism of the influence of mental imagery on visit intentions, that is, affective image. Affective destination image is also a necessary consideration for destination marketers to determine whether the song created can induce consumers to have positive affective destination images. Positive affective image refers to the emotions or moods that the song may generate in listeners. When choosing a song or collaborating with singers before a song is created, destination managers need to ensure that the song can make listeners have positive emotions or moods.

Limitations and future research

The present study has some limitations that should be addressed in future research. First, the choice of the stimulus song was critical for our experiment, and the average score of consumer attitudes toward the song was high (on a seven-point scale, M = 5.55, SD = 1.17). If we had used another song as our stimulus, the results might have been different. Thus, future research can extend our results by examining moderators, such as the attitude toward the song. In addition, the song that we chose represented only one type of music, that is, popular music; thus, we do not know whether our results can be generalized to other types of music (e.g. classical music). Thus, future research may examine our theoretical framework using blues, jazz, classical, or even rock and roll music. Finally, we focused only on prospective tourists; thus, none of the participants had had any experience of the destination. What happens when people hear a popular song related to a destination that they have already been to? Can such music trigger their intentions to revisit the destination? Such questions warrant future research.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by the National Social Science Fund of China (no. 15BGL092).

ORCID iD

Cheng-Yue Yin

Appendix 1

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