Asymmetric dual-process mechanisms under symbolic exposure: music-induced destination perception.

Asymmetric dual-process mechanisms under symbolic exposure: music-induced destination perception

Abstract

Background

Music connects listeners with places through imagery, cultural meanings, and personal associations. How cognitive and emotional responses relate to place attachment and behavioral intentions in destination-song contexts remains unclear.

Objective

This study examines cognitive–affective pathway differences and the relational role of place attachment.

Methods

A mixed-methods design combined Latent Dirichlet Allocation analysis of 57,228 NetEase Cloud Music comments on 15 destination-related songs with a survey of 472 respondents. Expert interpretation and psychological theory informed construct development. PLS-SEM assessed direct and indirect associations, with 5,000 paired bootstrap resamples used for exploratory pathway comparisons.

Results

Place imagery, local cultural meaning, and associative experience were positively associated with cognitive evaluation and emotional experience. Pathway comparisons showed stronger associations between place imagery and cognitive evaluation, and between associative experience and emotional experience. Cognitive–affective differences in paths to attachment, visit intention, and sharing intention were not significant. Place attachment partially mediated the associations of cognitive evaluation (β = 0.040, 95% CI [0.016, 0.072]) and emotional experience (β = 0.050, 95% CI [0.021, 0.086]) with visit intention.

Conclusion

The findings refine the SOR framework by locating asymmetry in selected antecedent pathways and identifying place attachment as a shared relational link to visit intention. The cross-sectional design and predominance of previous visitors limit conclusions about causal ordering and new attachment formation.

Keywords: behavioral intentions, cognitive evaluation, destination songs, music-evoked emotion, place attachment, symbolic exposure

1.Introduction

Digital media provide access to destination information and place narratives through images, sound, and text. Streaming platforms, social media, and user-generated content (UGC) offer material through which people understand and imagine destinations (Guo and Pesonen, 2022; Pop et al., 2022; Abbasi et al., 2023). Destination perception can therefore draw on mediated cues alongside direct experience.

Destination songs connect musical experiences with places through melodies, lyrics, emotional tone, and cultural narratives (Bassano et al., 2019; Bennett and Janssen, 2016; Zhuang et al., 2023). Music psychology has examined how listening evokes emotions, autobiographical memories, and imagination (Juslin et al., 2014; Koelsch, 2014; Eskine et al., 2020; Margulis and Jakubowski, 2024), while destination-song research has documented associations with destination image and visit intention (Yin et al., 2020; Lv et al., 2022; Wei et al., 2023). These studies provide a basis for examining how emotional engagement with a song relates to evaluations of, and psychological bonds with, the represented place. Such mediated encounters may involve both imagined experiences and meanings grounded in previous visits.

Clarifying these relationships requires distinguishing emotional experience, cognitive evaluation, and place attachment. Tourism research has linked emotion, image, and nostalgia with tourist responses (Prayag et al., 2017; Ramkissoon, 2023; Lu et al., 2022; Wang, 2023; Bhogal et al., 2024), and examined how electronic word of mouth, mediated information, and prior experience relate to evaluations and intentions (Jalilvand and Samiei, 2012; Guo and Pesonen, 2022; Abbasi et al., 2023; Hu and Xu, 2021). Musical emotions also vary with personal experience and listening context (López et al., 2024; Juslin, 2025). Feeling moved by a song, evaluating a destination favorably, and feeling attached to it are therefore conceptually distinct. Further examination is needed of their connections: whether attachment links cognitive and emotional responses with visit intention, how these responses relate to sharing intention, and where corresponding cognitive–affective pathways differ in strength. This approach distinguishes intended travel from communication about songs and destinations without presuming cognitive or emotional dominance.

Although analytically distinct, emotional responses, personal memories, and place-related meanings may intertwine in listeners’ accounts of musical experiences (Margulis and Jakubowski, 2024). UGC captures these expressions in context, providing material for connecting psychological concepts with the language listeners use (Wang et al., 2024). Latent Dirichlet Allocation (LDA) can identify recurring semantic themes across large comment corpora (Blei et al., 2003), while theory-guided interpretation helps assess their relevance to psychological constructs (Maier et al., 2018). Combining this semantic exploration with survey measurement allows listeners’ expressions to inform construct contextualization and supports the examination of individual-level psychological associations.

Accordingly, this study combines LDA and partial least squares structural equation modeling (PLS-SEM), drawing on music psychology, tourism psychology, and the Stimulus–Organism–Response (SOR) framework. It examines how place imagery, local cultural meaning, and associative experience relate to cognitive evaluation and emotional experience, and how these responses connect with place attachment, visit intention, and sharing intention. Additional exploratory comparisons assess differences between corresponding cognitive and affective pathways. The study seeks to clarify where these pathways differ, how attachment connects them with visit intention, and how travel-oriented intentions relate to communicative engagement.

2.Literature review and hypothesis development

2.1.Destination songs as symbolic environmental stimuli

Destination songs serve as symbolic environmental stimuli by representing places through melodies, lyrics, emotional tone, and culturally embedded narratives (Bassano et al., 2019; Bennett and Janssen, 2016; Moreno-Lobato et al., 2023). Here, symbolic exposure refers to encountering a destination through its mediated representation, regardless of prior visitation. Although photographs and written narratives also convey place meanings, destination songs combine musical expression with place-related references, inviting listeners to interpret these references through imagination and personal associations (McAuley et al., 2021; Margulis and Jakubowski, 2024; Taruffi et al., 2017). This combination helps explain the relevance of music to destination promotion and mediated tourism communication (Coronel and Irimiás, 2023).

Music listening can involve emotional contagion, autobiographical memory, imagery, and self-related interpretation (Juslin et al., 2014; Koelsch, 2014; Schäfer et al., 2013). These experiences provide a basis for considering how listeners mentally engage with represented places beyond immediate physical presence (Eskine et al., 2020; Herff et al., 2021). Tourism studies have linked music and destination-song perceptions to destination image and behavioral intentions (Yin et al., 2020; Lv et al., 2022; Wei et al., 2023; Min et al., 2019). Research on UGC further highlights the role of mediated content in destination imagery and audience responses (Guo and Pesonen, 2022; Abbasi et al., 2023; Aboalganam et al., 2025). Together, these perspectives suggest that destination songs connect musical engagement with place-related interpretation through meanings that listeners bring to the listening experience.

These listener-dependent meanings help explain why the same song may evoke different responses. Musical interpretation varies with mood, personality, autobiographical relevance, prior experience, and listening context (Vuoskoski and Eerola, 2011; López et al., 2024), producing diverse emotional experiences across listeners (Warrenburg, 2020; McCrae, 2021). A song’s emotional tone therefore cannot be equated with the listener’s feelings or evaluation of the destination, nor should these responses be assumed to be uniformly positive. This distinction motivates examining cognitive evaluation and emotional experience separately and assessing their associations with attachment and behavioral intentions.

2.2.Music-induced psychological processing under symbolic exposure

Building on the variability outlined above, understanding destination-song responses requires distinguishing how listeners interpret a represented place from how they feel during listening. Tourism research has examined relationships among emotional experience, destination evaluations, and relational or behavioral outcomes (Prayag et al., 2017; Ramkissoon, 2023). Under symbolic exposure, listeners may draw on imagined scenes, autobiographical associations, and narrative engagement to make sense of the destination (McAuley et al., 2021; Margulis and Jakubowski, 2024; Taruffi et al., 2017; Green and Brock, 2000). These sources of meaning may inform both destination judgments and emotional involvement, providing a basis for examining cognitive and affective responses as related but distinct.

Cognitive evaluation concerns judgments of a destination’s attractiveness and desirability, informed by the interpretation of mediated information and place meanings (Jalilvand and Samiei, 2012; Guo and Pesonen, 2022; Abbasi et al., 2023; Aboalganam et al., 2025). Emotional experience concerns emotional intensity and involvement during listening, drawing on the music-evoked processes discussed above (Juslin et al., 2014; Koelsch, 2014; Schäfer et al., 2013). Research on music-related imagination provides a basis for examining how these listening experiences connect listeners with represented destinations (Hashim et al., 2023; Herff et al., 2021). These responses may overlap, but they differ in focus: cognitive evaluation addresses the destination, whereas emotional experience captures feelings during engagement with the song.

Cognitive evaluation and emotional experience may both relate to place attachment, but these associations do not establish when attachment emerged or how long it persists. Musical emotions vary with personal relevance, mood, and listening context (Vuoskoski and Eerola, 2011; López et al., 2024; Juslin, 2025), and emotional intensity alone does not specify the meaning of the experience (Warrenburg, 2020; McCrae, 2021). These distinctions provide a basis for examining whether cognitive and affective responses differ in their antecedents and associations with attachment and behavioral intentions, without assuming temporal precedence or a fixed hierarchy.

2.3.SOR and asymmetric dual-process mechanisms

The Stimulus–Organism–Response (SOR) framework links environmental stimuli to behavioral responses through internal psychological states (Mehrabian and Russell, 1974), organizing relationships among evaluations, emotions, and relational outcomes in tourism (Prayag et al., 2017; Ramkissoon, 2023). Here, place imagery, local cultural meaning, and associative experience represent perceived symbolic cues; cognitive evaluation, emotional experience, and place attachment represent internal responses; and visit and sharing intentions represent behavioral intentions. Attachment provides a potential relational link between cognitive and emotional responses and visit intention.

Dual-process perspectives distinguish interacting rational and experiential processing (Epstein, 1994) and emphasize specifying their interaction (De Neys, 2023). Affective preferences need not depend on deliberate inference (Zajonc, 1980), while appraisal theory emphasizes evaluations of personal significance (Lazarus, 1991). Distinctions between adaptive processes and conscious feelings (LeDoux, 2012), alongside cognitive–affective interdependence (Pessoa, 2023), caution against treating destination judgments and listening-related feelings as independent processing systems. These perspectives guide conceptual distinctions; the questionnaire does not test processing speed, automaticity, or temporal precedence.

Mediated information and prior experience can inform destination evaluations and behavioral intentions (Jalilvand and Samiei, 2012; Guo and Pesonen, 2022; Abbasi et al., 2023; Hu and Xu, 2021), while musical engagement varies with personal relevance and listening conditions (Vuoskoski and Eerola, 2011; López et al., 2024; Warrenburg, 2020; Juslin, 2025). Place imagery provides representations for evaluation, associative experience connects listening with personal memories and imagined experiences, and local cultural meaning may inform both interpretation and emotional engagement. These functions motivate comparing each cue’s associations with cognitive evaluation and emotional experience.

Such comparisons also extend to cognitive and emotional associations with attachment, visit intention, and sharing intention. The Framework for Adaptable Musical Emotions highlights the situational, cultural, personal, and psychophysical conditions of musical responses (Susino et al., 2025), offering context for interpreting potential differences without predicting their direction. The study therefore examines asymmetry as differences in the strength of corresponding cognitive and affective associations across antecedent and outcome pathways, without presuming a general hierarchy. Direct comparisons of path coefficients assess these differences; significance within individual pathways alone is insufficient.

2.4.Symbolic interpretation and psychological processing

2.4.1.Place imagery, local cultural meaning, and associative experience

Destination songs provide spatial, cultural, and personal references through which listeners interpret represented places (Bassano et al., 2019; Bennett and Janssen, 2016; Zhuang et al., 2023). Place imagery concerns the mental visualization of a destination’s scenes, environment, and atmosphere, drawing on music-related imagination and spatial simulation (Herff et al., 2021; Hashim et al., 2023). Local cultural meaning concerns listeners’ perceptions of a destination’s cultural characteristics and identity, conveyed through dialects, narratives, musical styles, and local references (Bassano et al., 2019; Moreno-Lobato et al., 2023). Associative experience concerns connections between the song, personal memories, life experiences, and imagined involvement with the destination (Juslin et al., 2014; Eskine et al., 2020). These constructs distinguish what listeners imagine about a place, what cultural meanings they perceive, and how they relate the song to themselves. They represent perceived aspects of the listening experience rather than objective musical properties.

2.4.2.Cognitive evaluation

Cognitive evaluation refers to judgments of a destination’s attractiveness and desirability based on the song and its associated meanings (Jalilvand and Samiei, 2012; Guo and Pesonen, 2022). Research on mediated information and prior experience provides a basis for examining how listeners form evaluations relevant to behavioral intentions (Abbasi et al., 2023; Hu and Xu, 2021). Place imagery supplies representations to evaluate, local cultural meaning provides information about destination distinctiveness, and associative experience introduces personal relevance (Yin et al., 2020; Wei et al., 2023; Bassano et al., 2019; Moreno-Lobato et al., 2023; Juslin et al., 2014; Eskine et al., 2020). Cognitive evaluation thus captures an appraisal of the destination, distinct from the vividness of its imagery, emotional involvement during listening, or a personal bond with the place.

2.4.3.Emotional experience and place attachment

Emotional experience refers to emotional intensity and involvement during destination-song listening, which may involve contagion, autobiographical associations, and immersion (Juslin et al., 2014; Koelsch, 2014; Vuoskoski and Eerola, 2011). Place imagery, cultural meaning, and associative experience may support such engagement through nostalgia and personal recollections (Wang, 2023; Bhogal et al., 2024). The construct captures emotional involvement rather than a specific emotion or positive–negative valence (López et al., 2024; Juslin, 2025).

Place attachment concerns emotional connection, personal meaning, and psychological closeness to the represented destination. Tourism research provides grounds for examining its relationship with emotional experience (Prayag et al., 2017; Ramkissoon, 2023; Lu et al., 2022). Given the diversity of musical responses (Warrenburg, 2020; McCrae, 2021), feelings during listening should be distinguished from bonds with the place. These responses may be positively associated, without implying that attachment first emerged during listening.

2.5.Hypotheses development

Destination songs provide cues for evaluating represented places. Place imagery makes destination scenes and attributes mentally accessible, while local cultural meaning supports appreciation of their distinctiveness (Yin et al., 2020; Wei et al., 2023; Bassano et al., 2019; Moreno-Lobato et al., 2023). Associative experience may support favorable evaluation by connecting place meanings with personal experiences and imagined involvement (Juslin et al., 2014; Eskine et al., 2020). Accordingly:

H1a. Place imagery is positively associated with cognitive evaluation.

H1b. Local cultural meaning is positively associated with cognitive evaluation.

H1c. Associative experience is positively associated with cognitive evaluation.

These cues may also support emotional engagement. Imagined scenes can be emotionally evocative, while cultural references may acquire affective significance through identity and shared meanings (Bassano et al., 2019; Herff et al., 2021). Personal memories and imagined experiences may similarly connect the song with emotionally meaningful aspects of the listener’s life (Juslin et al., 2014; Eskine et al., 2020). Thus:

H2a. Place imagery is positively associated with emotional experience.

H2b. Local cultural meaning is positively associated with emotional experience.

H2c. Associative experience is positively associated with emotional experience.

Research on mediated information and destination evaluation provides grounds for examining relational and behavioral associations (Jalilvand and Samiei, 2012; Guo and Pesonen, 2022). Favorable judgments may support willingness to visit and provide reasons to recommend or share destination-related content. Evaluations carrying personal significance may also relate to attachment. Accordingly:

H3a. Cognitive evaluation is positively associated with place attachment.

H3b. Cognitive evaluation is positively associated with visit intention.

H3c. Cognitive evaluation is positively associated with sharing intention.

Emotional involvement may connect the listening experience with psychological closeness to the represented place, consistent with research on tourism emotions and attachment (Prayag et al., 2017; Ramkissoon, 2023). Although musical responses vary across listeners and contexts (Vuoskoski and Eerola, 2011), emotional engagement may accompany place-related bonds, including those grounded in prior experience. Therefore:

H4. Emotional experience is positively associated with place attachment.

Place attachment gives a destination personal significance and may support willingness to seek or renew contact through travel (Prayag et al., 2017; Ramkissoon, 2023). Emotional involvement may also relate to visit intention through destination-related emotional salience and to sharing intention through personally meaningful expression. These proposed associations concern emotional involvement, acknowledging variation in the feelings elicited during listening (Vuoskoski and Eerola, 2011). Accordingly:

H5. Place attachment is positively associated with visit intention.

H6a. Emotional experience is positively associated with visit intention.

H6b. Emotional experience is positively associated with sharing intention.

Together, these arguments suggest that cognitive evaluation and emotional experience may relate to visit intention indirectly through place attachment. Favorable judgments and emotional involvement may each accompany personal bonds with the destination, which are associated with willingness to visit. Thus:

H7a. Cognitive evaluation has a positive indirect association with visit intention through place attachment.

H7b. Emotional experience has a positive indirect association with visit intention through place attachment.

Beyond these hypothesized associations, corresponding cognitive and affective pathways may differ in strength. As the theoretical arguments do not establish a consistent direction for these differences, asymmetry is examined through two exploratory research questions:

RQ1. For each symbolic cue—place imagery, local cultural meaning, and associative experience—does its association with cognitive evaluation differ in strength from its association with emotional experience?

RQ2. For each outcome—place attachment, visit intention, and sharing intention—do its associations with cognitive evaluation and emotional experience differ in strength?

Figure 1 presents the hypothesized relationships. The exploratory questions are assessed through direct comparisons of corresponding path coefficients.

3.Methodology

3.1.Data source and text preprocessing

This study used a sequential mixed-methods design combining user-generated content (UGC) analysis with survey-based structural modeling. Comments were collected from NetEase Cloud Music between January 2024 and August 2025. Fifteen destination-related songs were selected based on geographic diversity, cultural representativeness, and comment volume (Table 1). The initial corpus contained 60,601 comments, totaling approximately 1.85 million Chinese characters. Comments were obtained from publicly accessible pages without login restrictions; no personally identifiable information was retained in the analytical dataset.

Table 1Characteristics and contextual relevance of the selected destination songs.

Song title Release year Destination Artist Genre/musical style Emotional tone Destination-related content

Mohe Ballroom 2020 Mohe Liu Shuang Folk-pop Nostalgic and melancholic Place-based storytelling associated with Mohe.

Lanzhou Lanzhou 2011 Lanzhou Low Wormwood Folk rock Reflective and wistful Local everyday life and cultural associations.

Beijing Beijing 2007 Beijing Wang Feng Rock ballad Reflective and yearning Urban experience and meanings associated with Beijing.

South of Colorful Clouds 2005 Yunnan Xu Qianya Pop with regional folk influences Uplifting and yearning Regional landscapes and cultural imagery.

Pearl of the Orient 1991 Hong Kong Lo Ta-you Pop ballad Affectionate and solemn Symbolic representations of Hong Kong and its urban identity.

Xiangjiang River 2021 Hunan Lay Zhang feat. Kung Fu-Pen Hip-hop/Changsha-dialect rap Excitement and hometown pride Changsha-dialect rap expressing local identity and hometown pride.

Changsha 2017 Changsha C-BLOCK Hip-hop/regional rap Spirited and playful Local urban life and place-specific references.

Guangdong Love Story 2017 Guangdong Guangdong Yushen Cantopop ballad Melancholic and nostalgic Personal relationships and everyday experiences situated in Guangdong.

Chengdu 2016 Chengdu Zhao Lei Folk-pop Tender and wistful Named streets and everyday urban settings.

Magical Jiuzhaigou 1999 Jiuzhaigou Rongzhong Erjia Pop with Tibetan musical influences Reverent and uplifting Scenic imagery associated with Jiuzhaigou.

Shanghai Bund 1980 Shanghai Frances Yip Cantopop Dramatic and impassioned Representations of Shanghai associated with a television narrative.

Crescent Bay 2007 Dunhuang F.I.R. Pop with Chinese musical influences Romantic and yearning Desert landscapes and cultural imagery associated with Dunhuang.

Return to Lhasa 2007 Lhasa Zheng Jun Rock with Tibetan musical influences Exuberant and yearning Place references and cultural imagery associated with Lhasa.

Summer in Xiamen 2011 Xiamen LifeJourney Band Indie pop Lighthearted and relaxed Coastal scenery and local urban settings.

West Lake 2008 Hangzhou Miserable Faith Folk rock Contemplative and wistful Scenic and cultural imagery associated with West Lake.

English titles are provided for identification. Genre and emotional tone are descriptive characterizations, not measures of listeners’ responses.

Preprocessing used Python-based tools, including Jieba and SnowNLP, to remove duplicate, excessively short, and irrelevant comments, followed by segmentation, stop-word and symbol removal, synonym standardization, and place-name normalization (Guo et al., 2017; Maier et al., 2018). The resulting corpus comprised 57,228 comments for LDA, whose themes informed survey construct contextualization.

3.2.Exploratory text analysis

Before topic modeling, exploratory diagnostics were conducted to characterize the corpus’s semantic structure. Keyword frequencies were computed using Python, with representative high-frequency terms reported in Table 2. Frequent words were dominated by destination-related expressions (e.g., Yunnan, Beijing, Chengdu, West Lake, Lhasa), affective vocabulary (e.g., like, hope, remembering), and identity-related references (e.g., motherland, friends, university), indicating that destination-song discourse centers on destination imagery, emotion, and shared symbolic meanings. The word cloud (Figure 2) further shows clustering around spatial imagery, emotional expression, and autobiographical association, suggesting that destination songs function as symbolic media through which listeners construct place meanings under mediated exposure (Guo et al., 2017; Maier et al., 2018). Overall, the exploratory analysis identifies recurring semantic domains associated with cognition, affect, and behavioral orientation, providing an empirical basis for subsequent LDA modeling and SEM construct development.

Table 2High-frequency words extracted from destination-song reviews.

Keyword Freq. Keyword Freq. Keyword Freq.

This song 5,225 Hope 1,058 Anniversary 655

Yunnan 4,400 Place 1,049 Friends 630

Like 3,385 Xiamen 949 Lijiang 602

Beijing 2,285 Return 919 Music 599

Chengdu 1,559 First time 807 Return to 584

West Lake 1,533 Thinking of 687 Remember 576

Lhasa 1,488 City 681 Snow Mountain 566

Pleasant to listen to 1,303 Hong Kong 676 Childhood 565

Changsha 1,223 Shanghai 667 Every time 560

Lanzhou 1,203 Crying hard 667 Shanghai Beach 554

Frequencies are based on 57,228 UGC comments retrieved from NetEase Cloud Music.

3.3.Topic number selection and model estimation

LDA models with K ranging from 2 to 10 were compared using coherence and log-perplexity (Blei et al., 2003; Guo et al., 2017; Maier et al., 2018). Coherence was highest at K = 8 and remained close to this level at K = 9 (Figure 3). The nine-topic solution was retained for its semantic differentiation and interpretability. Topic prevalence, intertopic distances, and salient terms were visualized using pyLDAvis (Sievert and Shirley, 2014; Figure 4). The topic keywords subsequently informed theory-guided construct contextualization (Section 3.4).

3.4.Construct development and measurement design

LDA themes contextualized the survey constructs, while psychological theory guided their definitions and measurement (Guo and Pesonen, 2022; Pop et al., 2022). Three tourism experts established nine topic labels and their interpretive links to the constructs through three rounds of discussion. Two additional tourism experts independently assigned each topic to its most relevant construct using construct definitions, topic keywords, and linked comments, without seeing the proposed mappings or each other’s judgments. Their initial classifications agreed on all nine topics (100% agreement; Cohen’s κ = 1.00). Table 3 presents the interpretive links and illustrative comments. The original LDA topics remained unchanged, and these links were not treated as measurement equivalence.

Table 3Theory-guided topic–construct links and illustrative comments.

Panel A. Topic–construct links

LDA topic Selected topic keywords SEM construct Interpretive link and theoretical basis

T5 West Lake; snow mountains; intro; guitar; soul Place Imagery (PI) Place and landscape references contextualize destination imagery; musical terms describe the listening context (Yin et al., 2020).

T4 rock; band; melody; Shanghai; Shenzhen; working Local Cultural Meaning (LC) Musical and urban references provide contextual cues for interpreting place-related cultural meanings (Bassano et al., 2019).

T1 Xiamen; college entrance examination; future; longing; postgraduate entrance examination Associative Experience (AE) Place references and life aspirations suggest personal associations relevant to musical imagination and autobiographical interpretation (Eskine et al., 2020; Margulis and Jakubowski, 2024).

T8 recommendation; friends; city; love; youth Cognitive Evaluation (CE) Recommendation-related keywords and a topic-linked comment expressing destination liking provide context for cognitive evaluation, which remains theoretically defined (Jalilvand and Samiei, 2012; Abubakar et al., 2017).

T2, T3, T9 T2: missing; hope; dislike. T3: recalling; high school; school. T9: sadness; memories; reminiscing. Emotional Experience (EE) Emotional expressions and autobiographical references jointly contextualize listening-related feelings; measurement addresses intensity and involvement (Juslin et al., 2014; Koelsch, 2014; López et al., 2024).

— — Place Attachment (PA) Introduced from theory to represent psychological bonds with the destination, rather than derived from a distinct LDA topic (Chen et al., 2019; Ramkissoon, 2023).

T6 travel; returning home; companionship; dreams; yearning Visit Intention (VI) Travel and aspiration-related terms contextualize possible visitation interests; intention is operationalized through theory-guided measurement (Yin et al., 2020).

T7 music festival; concert; stranger; good night; graduation Sharing Intention (SI) Social references provide indirect context for interpersonal engagement; sharing intention is specified through communication research (Zhou et al., 2020).

Panel B. Illustrative topic-linked comments

LDA topic Comment excerpt (Chinese) English translation Interpretive relevance

T8 因为一首歌而喜欢上一座城市有生之年一定要来成都看一看 “A song made me like a city. I must visit Chengdu someday.” Connects favorable destination evaluation with visit intention; illustrates related responses without establishing their equivalence.

T2 读书的时候听现在要当妈妈了这周就要和宝贝见面了希望一切顺利 “I listened to this while studying; now I am about to become a mother. I will meet my baby this week and hope everything goes smoothly.” Connects listening with personal transitions and hope, providing autobiographical and emotional context.

T3 高中时第一次听到这首歌从此种下一颗种子现在坐在电子科大再听这首歌感慨万千 “I first heard this song in high school, and it planted a seed. Now, listening again at the University of Electronic Science and Technology of China, I feel deeply moved.” Links school-related memories with present emotional involvement.

T9 每听一首当年喜欢的歌都会有一些回忆听这首回忆是年年末的内时候刚认识 “Every song I liked back then brings back memories. This one reminds me of the end of that year, when we had just met.” Illustrates autobiographical recollection associated with listening; recollection alone does not establish emotional intensity or place attachment.

Excerpts are drawn from preprocessed comments and translated into English. Comments illustrate contextual meanings rather than establish topic–construct equivalence.

Keywords are selected translations from the LDA output. Topic–construct links reflect theory-guided interpretation, not measurement equivalence. PA was introduced from theory.

T5, T4, and T1 contextualized place imagery, local cultural meaning, and associative experience through place references, musical and urban narratives, and personal associations, respectively (Yin et al., 2020; Bassano et al., 2019; Eskine et al., 2020; Margulis and Jakubowski, 2024). T2, T3, and T9 remained separate topics but jointly informed the contextualization of emotional experience: their keywords concerned longing and hope, school-related recollections, and sadness and memories, respectively. These themes provided emotional and autobiographical context, while theory defined emotional experience as listening-related intensity and involvement (Juslin et al., 2014; Koelsch, 2014; López et al., 2024).

T8 provided indirect recommendation-related context for cognitive evaluation, which was theoretically defined as destination-focused judgment (Jalilvand and Samiei, 2012; Abubakar et al., 2017). Place attachment was introduced from theory to capture psychological bonds with the destination, including existing bonds from prior visits (Chen et al., 2019; Ramkissoon, 2023). T6 and T7 contextualized travel aspirations and social engagement, while theory guided the measurement of visit and sharing intentions (Zhou et al., 2020; Yin et al., 2020). Table 3 summarizes these interpretive links (Ali et al., 2022).

3.5.Measurement design

Measurement items were developed from theoretical definitions and contextualized using LDA themes. Place imagery, local cultural meaning, and associative experience drew on destination image, cultural meaning, and music-related association research (Yin et al., 2020; Bassano et al., 2019; Eskine et al., 2020). Cognitive evaluation and emotional experience addressed destination judgments and listening-related emotional involvement (Jalilvand and Samiei, 2012; Abubakar et al., 2017; Juslin et al., 2014; Koelsch, 2014). Place attachment, visit intention, and sharing intention addressed place-related bonds and behavioral intentions (Chen et al., 2019; Ramkissoon, 2023; Zhou et al., 2020; Yin et al., 2020). Table 4 reports the administered items and their theoretical foundations.

Table 4Measurement constructs, items, and theoretical sources.

Construct Code Measurement item Theoretical basis

Place Imagery (PI) PI1 This song allows me to imagine the destination’s appearance even without visiting it. Yin et al. (2020); Wei et al. (2023)

PI2 This song helps me form a clear and vivid mental picture of the destination. Yin et al. (2020)

PI3 The scenes described in this song stimulate concrete imagination about the destination. Wei et al. (2023)

PI4 This song enhances my psychological imagination of the destination environment and atmosphere. Herff et al. (2021)

Local Cultural Meaning (LC) LC1 This song conveys the destination’s unique cultural atmosphere. Bassano et al. (2019); Lee and Bai (2016)

LC2 This song allows me to perceive the destination’s local identity and cultural characteristics. Lee and Bai (2016)

LC3 The cultural elements in this song enhance my understanding of the destination culture. Bassano et al. (2019)

LC4 This song strengthens my perception of the destination’s cultural uniqueness. Moreno-Lobato et al. (2023)

Associative Experience (AE) AE1 This song reminds me of my own life experiences or personal stories. Eskine et al. (2020); Margulis and Jakubowski (2024)

AE2 This song reminds me of certain people or past experiences. Eskine et al. (2020)

AE3 This song connects the destination with my own emotions. Margulis and Jakubowski (2024)

AE4 This song creates a feeling of imagining myself being in the destination. McAuley et al. (2021)

Cognitive Evaluation (CE) CE1 Based on this song, I consider the destination attractive. Jalilvand and Samiei (2012); Abubakar et al. (2017)

CE2 This song improves my overall evaluation of the destination. Jalilvand and Samiei (2012)

CE3 This song makes the destination worth considering for a future trip. Abubakar et al. (2017)

CE4 The symbolic meanings in this song increase my positive impression of the destination. Guo and Pesonen (2022)

Emotional Experience (EE) EE1 I experience clear emotional reactions while listening to this song. Juslin et al. (2014); Koelsch (2014)

EE2 This song creates emotional involvement for me. Koelsch (2014)

EE3 This song immerses me in its emotional atmosphere. Juslin et al. (2014)

EE4 This song evokes short-term but intense emotions. Juslin et al. (2014)

Place Attachment (PA) PA1 I feel emotionally connected to the destination described in this song. Chen et al. (2019); Ramkissoon (2023)

PA2 This destination holds personal meaning for me. Ramkissoon (2023)

PA3 I feel psychologically close to this destination. Chen et al. (2019)

PA4 I can imagine forming an emotional relationship with this destination. Lu et al. (2022)

Visit Intention (VI) VI1 After listening to this song, I would like to visit the destination in the future. Yin et al. (2020); Zhou et al. (2020)

VI2 This song increases my intention to visit the destination. Yin et al. (2020)

VI3 Compared with other destinations, I would be more willing to consider visiting this place. Zhou et al. (2020)

VI4 I would include this destination in my future travel plans. Yin et al. (2020)

Sharing Intention (SI) SI1 I would share this song or destination-related content on social media. Zhou et al. (2020); Abubakar et al. (2017)

SI2 I would recommend this song or destination to friends or family. Abubakar et al. (2017)

SI3 I would discuss topics related to this destination online. Zhou et al. (2020)

SI4 I would repost, comment on, or interact with destination-related content associated with this song. Dogaru et al. (2024)

Items were developed with reference to the cited literature. English wording translates the administered Chinese items.

All items used five-point Likert scales (1 = strongly disagree; 5 = strongly agree). Expert review provided qualitative support for content validity, followed by a pilot survey with 150 participants. Item analysis and participant feedback guided revisions before the main survey; pilot responses were excluded from the main analysis. The questionnaire was developed in Chinese, and its English translation was checked through back-translation by two bilingual researchers.

3.6.Survey procedure and analytical strategy

Data were collected through Wenjuanxing from late October to December 2025. Invited members participated voluntarily and were randomly assigned one of 15 destination-related songs via a link. They were instructed to listen in full and immediately complete the questionnaire; repeat listening was permitted, but listening environments were neither controlled nor recorded. Eligibility required prior exposure to the assigned song, without a minimum familiarity level. Responses with missing values, incomplete listening, questionnaire completion times below 60 s, straight-line responses, or inconsistent screening answers were excluded. Of 575 questionnaires, 472 were retained (82.09%); 87.3% of respondents were moderately or very familiar with the song, and 91.7% had previously visited the destination (Table 5).

Table 5Respondent characteristics and prior exposure (N = 472).

Characteristic and category n %

Gender

Male 244 51.7

Female 228 48.3

Age

18–25 years 79 16.7

26–35 years 169 35.8

36–45 years 119 25.2

46–55 years 59 12.5

≥56 years 46 9.7

Education

High school or below 108 22.9

Junior college 107 22.7

Bachelor’s degree 173 36.7

Master’s degree 58 12.3

Doctoral degree or above 26 5.5

Occupation

Student 79 16.7

Corporate employee 195 41.3

Public-sector employeeb 115 24.4

Freelancer 37 7.8

Retired 46 9.7

Annual travel frequency

0–1 trips 123 26.1

2–3 trips 213 45.1

4–5 trips 83 17.6

≥6 trips 53 11.2

Destination media exposurea

Never 33 7.0

Occasionally 37 7.8

Sometimes 135 28.6

Often 166 35.2

Very often 101 21.4

Music-listening frequency

Rarely 42 8.9

Occasionally 46 9.7

Sometimes 126 26.7

Often 169 35.8

Daily 89 18.9

Main music platform

NetEase Cloud Music 145 30.7

QQ Music 162 34.3

Spotify 65 13.8

Apple Music 100 21.2

Song familiarity

Heard but not familiar 60 12.7

Moderately familiar 240 50.8

Very familiar 172 36.4

Prior destination visits

Never 39 8.3

Once 314 66.5

Twice or more 119 25.2

Percentages may not sum to 100% because of rounding.

aFrequency of exposure to destination information through music, short videos, or social media.

bCivil servants and public institution employees.

Anonymity and separate construct sections were used to reduce common method bias. Harman’s first factor explained 32.4% of the variance, although this does not rule out such bias. Structural paths and indirect effects were assessed in SmartPLS 4 using 5,000 bootstrap resamples. Exploratory pathway comparisons used 5,000 paired bootstrap resamples in Python (seed = 20,260,913), with full model re-estimation and two-sided 95% percentile confidence intervals for coefficient differences.

4.Results

4.1.Measurement model assessment

The measurement model showed satisfactory reliability and convergent validity (Hair et al., 2022). Outer loadings ranged from 0.764 to 0.867, Cronbach’s α from 0.818 to 0.872, composite reliability from 0.880 to 0.912, and AVE from 0.648 to 0.722 (Table 6). HTMT values ranged from 0.359 to 0.558, and the square roots of AVE exceeded the corresponding inter-construct correlations, supporting discriminant validity (Tables 7, 8; Henseler et al., 2015). Indicator-level VIF values ranged from 1.569 to 2.257.

Table 6Reliability and convergent validity.

Construct Item Loading Cronbach’s α CR AVE VIF

PI PI1 0.833 0.818 0.880 0.648 1.834

PI2 0.794 1.624

PI3 0.764 1.569

PI4 0.826 1.868

LC LC1 0.851 0.857 0.903 0.700 2.156

LC2 0.855 2.148

LC3 0.836 1.941

LC4 0.804 1.771

AE AE1 0.850 0.847 0.897 0.686 2.091

AE2 0.801 1.740

AE3 0.848 2.014

AE4 0.814 1.793

CE CE1 0.840 0.852 0.900 0.694 1.996

CE2 0.783 1.696

CE3 0.851 2.150

CE4 0.855 2.052

EE EE1 0.807 0.834 0.889 0.666 1.683

EE2 0.814 1.749

EE3 0.806 1.848

EE4 0.838 1.941

PA PA1 0.828 0.872 0.912 0.722 1.965

PA2 0.867 2.257

PA3 0.846 2.126

PA4 0.858 2.160

VI VI1 0.838 0.846 0.897 0.684 1.976

VI2 0.812 1.858

VI3 0.829 1.881

VI4 0.831 1.848

SI SI1 0.772 0.825 0.884 0.657 1.582

SI2 0.827 1.843

SI3 0.801 1.702

SI4 0.840 1.981

Loadings are standardized outer loadings. CR = composite reliability (ρ_c); AVE, average variance extracted; VIF, indicator-level variance inflation factor. PI, place imagery; LC, local cultural meaning; AE, associative experience; CE, cognitive evaluation; EE, emotional experience; PA, place attachment; VI, visit intention; SI, sharing intention.

Table 7Discriminant validity (HTMT).

Construct PI LC AE CE EE PA VI SI

PI -

LC 0.482 -

AE 0.400 0.415 -

CE 0.558 0.460 0.359 -

EE 0.420 0.424 0.479 0.426 -

PA 0.459 0.383 0.388 0.401 0.449 -

VI 0.485 0.519 0.423 0.453 0.485 0.406 -

SI 0.510 0.501 0.428 0.434 0.555 0.463 0.485

All HTMT values are below the recommended threshold of 0.85. Construct abbreviations are defined in Table 6.

Table 8Discriminant validity (Fornell–Larcker criterion).

Construct PI LC AE CE EE PA VI SI

PI 0.805

LC 0.404 0.837

AE 0.334 0.354 0.828

CE 0.468 0.393 0.305 0.833

EE 0.352 0.361 0.405 0.363 0.816

PA 0.387 0.333 0.333 0.348 0.386 0.850

VI 0.403 0.440 0.357 0.387 0.413 0.349 0.827

SI 0.417 0.423 0.359 0.366 0.463 0.395 0.405 0.810

Diagonal values represent the square roots of AVE. Construct abbreviations are defined in Table 6.

4.2.Structural model and hypothesis testing

Inner VIF values ranged from 1.152 to 1.278, indicating no substantial collinearity among the predictors. The model yielded SRMR = 0.081 and NFI = 0.851. R2 values were 0.280 for cognitive evaluation, 0.245 for emotional experience, 0.199 for place attachment, 0.258 for visit intention, and 0.259 for sharing intention. All hypothesized direct paths were positive and significant (p < 0.001, except AE → CE: p = 0.012), with f2 values ranging from 0.015 to 0.170 (Figure 5; Table 9).

Table 9Structural model results and hypothesis testing.

Hypothesis Structural path β t-value p-value f2 Result

H1a PI → CE 0.344 7.469 <0.001 0.131 Supported

H1b LC → CE 0.213 4.466 <0.001 0.049 Supported

H1c AE → CE 0.115 2.526 0.012 0.015 Supported

H2a PI → EE 0.183 3.841 <0.001 0.035 Supported

H2b LC → EE 0.189 3.575 <0.001 0.037 Supported

H2c AE → EE 0.277 5.952 <0.001 0.085 Supported

H3a CE → PA 0.239 5.179 <0.001 0.062 Supported

H3b CE → VI 0.233 4.993 <0.001 0.060 Supported

H3c CE → SI 0.228 4.616 <0.001 0.061 Supported

H4 EE → PA 0.300 6.262 <0.001 0.097 Supported

H5 PA → VI 0.166 3.548 <0.001 0.030 Supported

H6a EE → VI 0.264 5.554 <0.001 0.075 Supported

H6b EE → SI 0.380 8.121 <0.001 0.170 Supported

β denotes the standardized path coefficient from the original sample; statistical significance was assessed using 5,000 bootstrap resamples. f2 denotes the effect size. Construct abbreviations are defined in Table 6.

Place imagery had the largest estimated association with cognitive evaluation (β = 0.344), whereas associative experience had the largest with emotional experience (β = 0.277). Cognitive evaluation and emotional experience were positively associated with place attachment (β = 0.239 and 0.300), visit intention (β = 0.233 and 0.264), and sharing intention (β = 0.228 and 0.380), respectively. Place attachment was also positively associated with visit intention (β = 0.166).

4.3.Exploratory tests of pathway asymmetry

Exploratory paired-bootstrap comparisons showed that place imagery was more strongly associated with cognitive evaluation than with emotional experience (Δβ = 0.161, 95% CI [0.050, 0.273]), whereas associative experience was more strongly associated with emotional experience than with cognitive evaluation (Δβ = 0.163, 95% CI [0.051, 0.273]). The corresponding difference for local cultural meaning was not significant. Differences between cognitive and emotional paths to place attachment, visit intention, and sharing intention were also not significant (Table 10). These results support asymmetry in selected antecedent pathways.

Table 10Exploratory comparisons of cognitive and affective pathways.

Path comparison Δβ Bootstrap SE 95% percentile CI

PI → CE − PI → EE 0.161 0.057 [0.050, 0.273]

LC → CE − LC → EE 0.025 0.064 [−0.099, 0.150]

AE → EE − AE → CE 0.163 0.056 [0.051, 0.273]

EE → PA − CE → PA 0.061 0.082 [−0.098, 0.224]

EE → VI − CE → VI 0.031 0.077 [−0.118, 0.182]

EE → SI − CE → SI 0.153 0.085 [−0.014, 0.321]

Δβ is the first coefficient minus the second, using unrounded estimates. Two-sided 95% percentile CIs were obtained from 5,000 paired bootstrap resamples with full model re-estimation.

4.4.Indirect effects

Cognitive evaluation and emotional experience were indirectly associated with visit intention through place attachment (β = 0.040, 95% CI [0.016, 0.072]; β = 0.050, 95% CI [0.021, 0.086]), supporting H7a and H7b, respectively. Their direct associations remained significant, consistent with partial mediation. Exploratory analyses identified positive indirect associations for AE → EE → PA → VI (β = 0.014), AE → EE → SI (β = 0.106), and PI → CE → PA (β = 0.082), with all confidence intervals excluding zero (Table 11). These findings do not establish temporal or causal ordering.

Table 11Hypothesized and selected exploratory indirect effects

Hypothesis Indirect path β Bootstrap SE t-value p-value 95% bootstrap CI

H7a CE → PA → VI 0.040 0.014 2.770 0.006 [0.016, 0.072]

H7b EE → PA → VI 0.050 0.017 2.909 0.004 [0.021, 0.086]

— AE → EE → PA → VI 0.014 0.006 2.452 0.014 [0.005, 0.027]

— AE → EE → SI 0.106 0.023 4.546 <0.001 [0.066, 0.155]

— PI → CE → PA 0.082 0.020 4.016 <0.001 [0.046, 0.126]

β = specific indirect effect; SE = bootstrap standard error; CI = confidence interval; — = exploratory analysis. Construct abbreviations are defined in Table 6.

4.5.Predictive relevance

PLSpredict yielded positive Q2predict values for all constructs and indicators (Shmueli et al., 2019). PLS-SEM produced lower RMSE than the linear-model benchmark for all CE and EE indicators, two PA indicators, and three SI indicators, but none of the VI indicators. CVPAT showed lower prediction loss than the indicator-average benchmark across constructs and overall (all p < 0.001). Compared with the linear model, loss was significantly lower only for CE (p = 0.001) and EE (p = 0.036), with no significant overall difference (p = 0.465; Table 12).

Table 12Predictive performance assessed using PLSpredict and CVPAT.

Construct Q2predict (LV) Q2predict (MV range) Lower RMSE (n/4) ΔLoss vs IA p(IA) ΔLoss vs LM p(LM)

CE 0.265 0.145–0.206 4/4 −0.260 <0.001 −0.031 0.001

EE 0.232 0.098–0.177 4/4 −0.204 <0.001 −0.023 0.036

PA 0.175 0.117–0.134 2/4 −0.182 <0.001 0.005 0.816

VI 0.219 0.136–0.159 0/4 −0.217 <0.001 0.013 0.544

SI 0.222 0.126–0.158 3/4 −0.207 <0.001 0.002 0.920

Overall — — — −0.214 <0.001 −0.007 0.465

LV = construct level; MV = indicator level; LM = linear model; IA = indicator average. RMSE counts compare PLS-SEM with LM; negative ΔLoss favors PLS-SEM.

5.Discussion

5.1.Cognitive, affective, and relational pathways

The findings address how feelings during destination-song listening relate to evaluations of, bonds with, and intended responses toward the represented place. Pathway comparisons showed that place imagery was more strongly associated with cognitive evaluation, whereas associative experience was more strongly associated with emotional experience. However, cognitive–affective differences in the paths to attachment, visit intention, and sharing intention were not statistically supported. Asymmetry therefore concerns selected antecedent pathways. The PI → CE → PA indirect association further links place imagery with attachment through evaluation, consistent with accounts of narrative imagination and meaning construction in music (McAuley et al., 2021; Margulis and Jakubowski, 2024; Hashim et al., 2023).

Both cognitive evaluation and emotional experience were indirectly associated with visit intention through place attachment, identifying a shared relational pathway. The additional AE → EE → PA → VI association connects personal associations with this pathway, consistent with music psychology accounts of memory, imagery, and emotional engagement (Juslin et al., 2014; Koelsch, 2014; Warrenburg, 2020). Because 91.7% of respondents had previously visited the destination, this small indirect effect may reflect engagement with existing place-related experiences rather than newly formed attachment. Such an interpretation remains tentative and recognizes the contextual dependence of musical responses (Vuoskoski and Eerola, 2011).

The AE → EE → SI association also links personal associations with willingness to share songs or destination-related content through emotional experience (Zhou et al., 2020; Dogaru et al., 2024). This extends the analysis beyond visit intention to communicative engagement, without equating sharing with destination promotion or actual behavior. Together, the findings specify how listening-related emotion and destination evaluation connect with place attachment and distinct behavioral intentions.

5.2.Theoretical contributions and explanatory boundaries

This study elaborates the Stimulus–Organism–Response (SOR) framework by distinguishing the antecedents of cognitive and emotional responses from their relational connections with behavioral intentions. Building on tourism research on emotions, evaluations, attachment, and intentions (Prayag et al., 2017; Ramkissoon, 2023; Yeh et al., 2012), it shows that differentiated cognitive–affective associations can coexist with a shared attachment pathway. The contribution lies in locating where asymmetry occurs within the model, without assuming that either cognition or emotion consistently dominates destination-related responses.

The study also clarifies symbolic exposure as a mediated encounter that can draw on prior firsthand experience. Embodied tourism research emphasizes environmental interaction (Fan et al., 2023; Chan et al., 2025), while music research highlights imagination, memory, and narrative interpretation (McAuley et al., 2021; Margulis and Jakubowski, 2024; Herff et al., 2021). Together, these perspectives suggest that destination songs may engage meanings grounded in previous visits alongside imagined experiences, consistent with the personal and contextual nature of musical responses (Vuoskoski and Eerola, 2011; López et al., 2024; Klempe, 2017). The distinction between exposure mode and experiential history provides an explanatory boundary; whether prior experience moderates these pathways remains untested.

Methodologically, the study connects UGC analysis with survey measurement (Guo and Pesonen, 2022; Pop et al., 2022; Ali et al., 2022). Expert interpretation of LDA themes contextualizes theoretically defined constructs, while the survey assesses their measurement properties and associations. This approach links semantic exploration with psychological measurement without treating topic labels as validated constructs.

5.3.Managerial implications

The three indirect pathways suggest practical options for destination management organizations (DMOs). PI → CE → PA suggests pairing songs with identifiable landscapes, local stories, and brief explanations of cultural references to help listeners interpret the destination’s appeal (Jalilvand and Samiei, 2012; Yin et al., 2020; Abbasi et al., 2023). AE → EE → SI suggests inviting personal memories and stories as material for voluntary sharing (Dogaru et al., 2024; Zhou et al., 2020). AE → EE → PA → VI further suggests connecting these recollections with opportunities to revisit meaningful places, particularly for previous visitors (Chen et al., 2019; Ramkissoon, 2023; Chan et al., 2025).

For example, a DMO could pair a destination song with an image of the place and a brief explanation of a culturally specific lyric. A prompt such as “What memory does this song bring back?” could invite personal stories, while a linked page provides walking routes, transport information, and local events. This approach connects destination interpretation and emotional engagement with practical travel information. Because the observed associations do not establish that such campaigns strengthen attachment or increase visitation, these proposals require field testing. Comments and shares should be tracked separately from itinerary clicks and verified visits.

5.4.Limitations and future research

The cross-sectional, self-report design limits causal and temporal inference and remains susceptible to common method bias. Most respondents had previously visited the destination, so attachment may reflect existing bonds. Longitudinal and experimental studies could distinguish immediate listening responses from changes in attachment. Musical genre and emotional tone were described but not statistically controlled, and emotional experience captured intensity and involvement rather than valence. Future studies could control or manipulate these characteristics and compare listeners with different visitation histories. Comparisons across media formats, incorporating construal level and psychological distance, could clarify the boundaries of cognitive–affective associations. Research should also distinguish song sharing from destination-content sharing and assess observed behavior alongside intentions. The Chinese destination-song context, single-platform UGC source, and uneven predictive performance, particularly for visit intention, warrant validation across samples and settings.

6.Conclusion

This study identifies differentiated cognitive and affective associations in music-mediated destination perception. Place imagery was more strongly associated with cognitive evaluation, whereas associative experience was more strongly associated with emotional experience. Both responses were indirectly associated with visit intention through place attachment, but their corresponding paths to attachment and behavioral intentions did not differ significantly. These findings refine the SOR framework by locating asymmetry in selected antecedent pathways and identifying attachment as a shared relational link. Symbolic exposure may engage both imagined and previously experienced place meanings, without establishing causal or temporal ordering.

Acknowledgments

The authors thank all participants for their time and contributions to this research.

Funding Statement

The author(s) declared that financial support was not received for this work and/or its publication.

Footnotes

Edited by: Kartal Doğukan Çiki, Gelisim University, Türkiye

Reviewed by: Erhan Nuh Öztürk, Karamanoğlu Mehmetbey University, Türkiye

Abdullah Köseoğlu, Bitlis Eren University, Türkiye

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent from the participants was not required to participate in this study in accordance with the national legislation and the institutional requirements.

Author contributions

XP: Conceptualization, Data curation, Methodology, Writing – original draft, Writing – review & editing. BH-H: Conceptualization, Data curation, Investigation, Methodology, Software, Writing – original draft. CR-W: Conceptualization, Data curation, Investigation, Methodology, Software, Writing – review & editing. QS: Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Software, Writing – review & editing.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that Generative AI was not used in the creation of this manuscript.

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Associated Data

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.