Affective Empathic Interaction in Museum Narrative: Interactive Response Between History and Tourists’ Culture

Cultural Narrative of History

Culture is the mark and symbol of human survival and development, as well as the source and power of social generation and evolution (Fanea-Ivanovici & Pana, 2020), As a space carries profound history and culture, museums also provide the soil for narrative to grow. Cultural sociologists and other social scientists increasingly use “narrative” as a theoretical tool to understand the relationship between the past, present and future of individuals (Harding et al., 2017). Culture needs a corresponding narrative form, which is not presented in science or facts, but expressed through stories (Tinworth, 2011). As the space carries culture, the relationship between museum and narrative has also attracted the attention of the academic circles. As Kidd (2012) said that museums should become the narrative space of collective memory and emotion, and narrative is the historical narrative of a group based on emotion and identity. Therefore, museums create a social space embodies the long-standing historical culture, emotion and memory for narrative, while narrative provides effective strategies for empathic interaction between cultural relics and tourists.

The American Museum Alliance suggested that there has been a structural change in museum cultural experience, which represented by the mode of cultural consumption driven by situational and narrative stories. The diversified narrative mechanism can help tourists gain concrete experience and free interpretation with cultural information (Marshall et al., 2016). The user-generated narrative can give tourists a stronger engaging experience (Lim et al., 2021). The interaction of rich narrative and tourists’ free choice can create rich personal experience (Not & Petrelli, 2018). Cultural narrative transmits the cultural information contained in cultural relics, landscapes and other entities to tourists through “storytelling,” and evokes tourists’ feelings and memories, by receiving and decoding information. Cultural heritage is always dynamic, never would be a single dimension or bound by time (Selim et al., 2022). Through the narrative framework, museums build a bridge connecting the specific historical events symbolized by cultural relics and tourists’ cultural experience, which ensures the culture can be inherited and innovated in this process. It is obvious that “telling stories” is important in exploring the mechanism of museum narrative to resonate with tourists.

Cultural Communication of Tourists

The cultural core of a museum is composed of the traditional culture and esthetic culture, which is contained in the cultural relics or landscapes in a specific historical period and local regional culture. Tourists from different regions gather into a same social space, would evoke differences between the tourists’ own culture and the local culture, even evoke the differences between the culture of specific historical periods. According to the environmental foam theory, tourists could avoid cultural shock with a series of strategies. Environmental foam is composed of social contracts and activated by tourists themselves (Cortini & Converso, 2018). Berry (2003) distinguished four cultural adaptation strategies including separation, marginalization, assimilation, and integration, according to the tendency of one culture to communicate with other cultures and maintaining their own differently. With the accelerated cultural communication, integration has become the best strategy for individuals to face cultural differences. Cultural communication has also become a way to resolve differences, while cultural mediation creates a bunch of tools to connect tourists’ culture and historical culture for museum narrative (Capuano et al., 2016). In addition, higher tourist satisfaction can effectively promote cultural integration and assimilation, and prevent cultural separation and marginalization (Zhang et al., 2018). Since the worldwide spread of the Internet, digital media have been used by museums to enhance their communication and interaction with tourists, to promote understanding, analysis and interpretation of cultural content (Caggianese et al., 2018), and to enhance the emotional resonance of the audience (Chen et al., 2021). It can be seen that cultural communication can ease the differences between the historical culture of museum and the tourists’ own culture, with communication and interaction. Understanding the dialog between museums and tourists enables museums to survive and transform to cultural places with social value (Murriello, 2015), which is also an important reason to incorporate tourists’ cognition into the research.

The research on tourists’ cultural communication demonstrated its consistency in promoting travel experience. Gomez-Oliva et al. (2019) established a communication channel to better integrate tourists with Spanish villages of high cultural value, and enhanced the dissemination of local culture. The research results of Zhang et al. (2020) indicated that although there is a clear boundary for communication between local people and immigrants in daily interaction, increasing objective opportunities for communication is still a key to promote interaction and integration between groups. Sinitò et al. (2020) implemented a new communication system based on tourists’ personal experience, which weakened the cultural barrier between tourists and museums, and brought a better tourism experience. From this point of view, we suggested that the cultural integration between tourists and travel destinations could be eased, by establishing and expanding communication channels.

Emotional Expression in Museum Narrative

Each cultural relic in the museum is a witness of history (Hogervorst, 2020) and the most reliable guide for tourists to understand history (Carnegie & Kociatkiewicz, 2019). However, the separation between exhibits and the original space-time coordinates could cause audiences’ difficulties to know the information behind the isolated cultural relics (Gazi, 2019). Therefore, the space atmosphere creation needs the translatable narrative language, according to the historical environment and cultural characteristics of the cultural relics (Sumartojo & Graves, 2018), and make sure it could be expressed in the space through a series of narrative designs (Dasu et al., 2020), which could provide conditions for the audiences to read and understand the historical culture. In the emerging field of literary research, scholars have proposed that emotional experience can create more lasting verbal verbatim memory than neutral experience (Kim et al., 2021). Therefore, for museum narrative, it is also necessary to build a similar emotional interaction channel to enhance the communicative effect of the storytelling (Augello, 2022; Cipresso & Riva, 2016). Nowadays, the development of new media technology has given the museum more possibilities (Fenu & Pittarello, 2018). Creating a series of digital three-dimensional scenes (Jiang et al., 2022) is a new way to communicate with the public (Shaby et al., 2019), and to enhance the interaction between tourists’ senses and experiences, such as vision, hearing, smelling, tasting, and proprioception (Laukkanen et al., 2022), thereby activating the emotional memory and resonance of tourists (Chen et al., 2021).

In brief, this study built a theoretical framework for empathic interaction based on the comprehensive analysis of previous literature and in combination with our own understanding (as shown in Figure 1).

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Figure 1.

Theoretical framework for empathic interaction.

Methodology

Using “museum + culture” as the keyword, Study 1 combined open-ended interviews and netnography, aiming to explore in-depth the emotional expression of historical culture in the museum, as well as related elements of cultural lyricism. The specific process is as follows. First, in the open-ended interviews, Study 1 referred to the principle of sample saturation proposed by Robinson (2014), which indicated that interview studies aiming at uniqueness usually seek a relatively small sample size, and the number of participants in a single study is usually 3 to 16. Therefore, Study 1 ensured that all participants were fully aware of the purpose of the study, the process, and its possible implications, and volunteered to participate. We randomly selected 16 managers of a museum as the study participants, focusing mainly on topics related to the emotional expression of historical culture. The length of each interview was set between 30 and 60 min. However, the interviews of 15th and 16th participant showed no new content, thus further verified the validity of sample saturation. Study 1 subsequently focused on analyzing the interview content of the first 14 participants, whose basic information have been shown in Table 1. To protect the privacy of the participants, the content of the interviews has been anonymized.

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Table 1.

Basic Information of 14 Museum Management Personnel.

Basic information about interviewees	Options	Frequency	Percentage	Average value	Standard deviation
Gender	Male	8	57.10%	1.43	0.514
	Female	6	42.90%
Age	<30	3	21.40%	1.93 (40.900)	0.616
	30–50	9	64.30%
	>50	2	14.30%
Education level	Junior college	2	14.30%	2.14	0.663
	Undergraduate	8	57.1%
	Postgraduate and above	4	28.6%

Second, to make full use of the netnography, Study 1 crawled online text data related to “museum” and “culture” from August 2021 to June 2022, using the Opinion Pass tool. In the data processing, we strictly screened the collected data, eliminated duplicated, irrelevant and meaningless texts, and extracted a total of 39,504 valid and relevant text data. Researchers ensured that the collected data were stored in a secure environment to prevent unauthorized access and data leakage, and would be used followed relevant laws and regulations.

Last, Study 1 employed ROST Content Mining 6 for high-frequency word analysis, semantic network analysis, and sentiment analysis of the collected texts. For high-frequency word analysis, the high-frequency words in the text data were counted and categorized. In order to obtain the most concerned high-frequency words of “cultural lyricism in museum narrative,” in addition to the establishment of the scenic sub-word corpus, we filtered the deactivated words. We chose the authoritative stop list from Harbin Institute of Technology for filtering, and removed high-frequency but meaningless words. Then we analyzed the features of cultural lyricism in the museum narrative. For the network semantic analysis, we constructed the co-occurrence matrix according to the number of co-occurrences of high-frequency words between each other in the same text, and revealed the relationship between words graphically based on the co-occurrence matrix. The semantic network diagram presented the natural semantic structure of “cultural lyricism in museum narratives.” We analyzed the relationship between the features through visual mapping, to better extract the features of cultural lyricism in museum narratives from natural language. Sentiment analysis is a quantitative scoring of the emotional expressions in the text, which can obtain the emotional image of “historical and cultural lyricism in museum narratives.” We prepared an emotional lexicon, which contains words labeled with positive, negative, and neutral emotions, and then the software analyzed the proportion of each type of emotion, dug out the reasons for each type of emotion, to find out and improve the aspects that dissatisfy tourists in a timely manner.

Findings

First, we collected a total of 40 high-frequency words through word frequency analysis of the text data in the corpus (as shown in Table 2). Among them, “museum” and “culture” have been taken as the main body of cultural lyricism, connecting other words, such as “tourism,”“history,”“spirit” and “immersive.” It demonstrated that in the Internet era, museums create an immersive experience through interactive participation and optical effects to enable the tourists to deeply appreciate the spiritual connotation behind historical culture. As one of the participants said, “We create not only an immersive experience for tourists, but also a ‘travelling museum’… anyone visits is not only tourist but actor (interviewee M5).” Second, we conducted the semantic network analysis to form a double-layer structure (as shown in Figure 2), which consist of the core circle composed of “museum,”“culture” and “service,” and the external circle composed of words, such as “public.” It indicated that the museum, as a public cultural institution, could mobilize its available resources and expand its social service function to the fields of national education, economic growth and cultural exchange. There was another participant said, “Every year, schools organize academic visits to public cultural facilities such as museums and memorials, which is a special form of education and cultural immersion (interviewee M12).” Last, the emotional tendency of cultural lyricism in the text has been analyzed through sentiment analysis. As shown in Table 3, the public sentiments about historical culture in the museum narrative are mainly positive, which affirms the emotional expression in the cultural lyricism. Moreover, it is necessary to improve the insufficient elements to guide tourists to have a positive change, and make the emotional transmission of cultural lyricism more vivid and distinct.

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Table 2.

Word Frequency of History and Culture Lyricism of Museum Narrative.

Ranking	Word	Frequency	Ranking	Word	Frequency
1	Museum	1,052	21	College	229
2	Culture	983	22	Tourist area	219
3	Tourism bureau	686	23	Highest	213
4	Tourism	639	24	Host	206
5	Team	633	25	Visitor	204
6	Sponsor	607	26	Education	195
7	Center	484	27	Opening ceremony	191
8	Railway	417	28	Tourism industry	182
9	Urban area	403	29	City wall	180
10	Precious	356	30	Ministry of Tourism	157
11	Entity	352	31	Science and technology	144
12	Unity	330	32	Concept	142
13	Silk Road	325	33	Treasure	139
14	Urban and rural	323	34	Spirit	139
15	Dean	312	35	Service	138
16	Latest	296	36	Public	136
17	Library	272	37	Fortune	129
18	Art gallery	257	38	Immersive	129
19	Active	245	39	Exhibition	126
20	History	232	40	Tian’anmen Square	121

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Figure 2.

Network semantic diagram of “Museum and Culture.”

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Table 3.

Sentiment Analysis of “Museum + Culture.”

Key words	Positive emotions	Neutral emotions	Negative emotions
“Museum” + “Culture”	89.48%	3.20%	7.32%

Based on the above analysis, Museums undertake the important mission of spreading historical culture and providing public services. History and culture can be passed on through museums, which is also a kind of cultural consumption for public services. Public services through the construction of museum and their historical culture, to attract tourists to visit, and also to thrive the local tourism industry. That is how a closed loop field of cultural lyricism has been formed, with public service, museum and its historical culture as the main body. Based on it, the explanatory framework for cultural lyricism has been constructed (as shown in Figure 3). With the help of non-material factors such as stories, spirits and management, as well as material factors such as cultural relics, buildings, science and technology, the cultural narrative entered the cultural lyric field of “museum, historical culture, and public service” for its rich story connotation, and achieved the cultural lyricism through the innovative media in the field.

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Figure 3.

Interpretation framework for historical and cultural lyricism.

Methodology

Study 2 took “museum + memory” as the keyword, and combined open-ended interviews and netnography, to explore the expression of tourists’ emotional feedback, and relevant elements of cultural communication. The specific process is as follows. First, the open-ended interviews still referred to the sample saturation principle proposed by Robinson (2014), which indicated that interview studies aiming at uniqueness usually seek a relatively small sample size, and the number of participants in a single study is usually 3 to 16. However, Study 2 required a relative larger sample of participants to the sample of managers in Study 1, and increased the sample size by a certain amount. We ensured that all participants were fully aware of the purpose, process, and its possible impacts of this study, and were voluntarily participated. By adopting a random sampling method, we chose 27 tourists went on a particular museum tour as the research participants, and questioned their responses to the museum narrative and other related contents, such as emotional feedback. The interview time was designed to be 30 to 60 min. However, the results of the 27th participant showed no new interview content, thus further verifying the validity of sample saturation. Study 2 subsequently focused on analyzing the interview content of the first 26 participants, whose basic information has been shown in Table 4. In order to protect the privacy of the participants, the content of the participants has been anonymized.

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Table 4.

Basic Information of 26 Tourists.

Basic information about interviewees	Options	Frequency	Percentage	Average value	Standard deviation
Gender	Male	14	53.85%	1.46	0.508
	Female	12	46.15%
Age	<18	3	11.53%	2.35 (35.077)	0.905
	18–35	10	38.46%
	35–50	9	34.62%
	>50	4	15.39%
Education level	High school and below	5	19.23%	2.54	0.838
	Junior college	9	34.62%
	Undergraduate	11	42.31%
	Postgraduate and above	1	3.84%
Career	Student	8	30.76%	2.42	1.137
	Project units	4	15.38%
	Private industry	9	34.62%
	Individual operation	5	19.24%

Second, in terms of netnography, Study 2 systematically crawled the travelog data related to “Museum + Memory” from August 2021 to June 2022, using the Opinion Pass tool. We screened the collected data strictly, eliminated duplicated, irrelevant and meaningless texts, and harvested 65,203 relevant text data. The researchers ensured that the collected data were stored in a secure environment to prevent unauthorized access and data leakage, and would be used according to relevant laws and regulations.

Last, Study 2 employed ROST Content Mining 6 for high-frequency word analysis, semantic network analysis and sentiment analysis. From the high-frequency word analysis, we obtained the most concerned high-frequency words of “tourists’ emotional feedback in museum narratives,” and analyzed the characteristics of tourists’ emotional feedback in museum narrative. From network semantic analysis, we constructed a co-occurrence matrix, based on the number of co-occurrences of high-frequency words in the same text. With the co-occurrence matrix, we drew a semantic network diagram to show the natural semantic structure of “tourists’ emotional feedback in museum narrative,” and extracted the features of tourists’ emotional feedback in museum narrative from natural language. For sentiment analysis, we prepared a semantic network map to express the natural semantic structure of “tourists’ emotional feedback in museum narratives.” For sentiment analysis, we first prepared an emotional lexicon, which contains words with positive, negative and neutral labels, and then analyzed the proportion of each type of sentiment, so as to obtain the sentiment image of “tourists’ emotional feedback in museum narrative.”

Findings

We collected 40 high-frequency words through word frequency analysis of the text data in the corpus. The analysis results have been shown in Table 5. In particular, “museum” and “memory” have been used as and the main body of tourists’ emotional feedback. Words such as “red,”“memory,” and “blood” have been combined to indicate that the museum bridged the emotional interaction between tourists and revolutionary martyrs through narrative, to enable the tourists to experience red culture in tourism, visit revolutionary sites, and sustain the revolutionary legacy. As stated by another participant, “I can have a ‘one-stop’ understanding of the city’s red stories and memories of the War of resistance against Japanese aggression, leading me back to the revolutionary years, just like a red tour (interviewee T16).” Second, we conducted network semantic analysis to form a three-layer structure (as shown in Figure 4), the core circle composed of “museum” and “memory”; the sub-core circle composed of words such as “culture,”“experience,” and “education,” reflecting the original power of narrative and forming an integrated process of empathy between tourists and museums; and the external circle composed of words such as “protection,” reflecting tourists’ wishes for the continuation and promotion of historical culture, “…I still hope that our generation can carry on this culture and spirit, so that future generations can also feel the learning (interviewee T3).” Last, we analyzed the emotional tendency of tourists’ experience feedback in the text data through sentiment analysis. As shown in Table 6, among the emotional feedback attitudes of tourists, participants held a positive attitude toward museum narrative, accounting for 87.04%. But there is still a certain proportion held negative emotions and neutral emotions. It is necessary for the museum managers to further improve the narrative level and emotional experience, as well as stimulate the tourists’ visiting intention.

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Table 5.

Word Frequency Analysis of Tourists’ Emotional Feedback.

Ranking	Word	Frequency	Ranking	Word	Frequency
1	Museum	19,824	21	Entity	224
2	Memory	10,530	22	Cherish	213
3	Precious	820	23	Fortune	212
4	Red	819	24	Deposit	208
5	Culture	806	25	Visit	203
6	Team	753	26	Blood vessel	201
7	Railway	603	27	Urban and rural	199
8	Host	483	28	Trend	195
9	Chair	466	29	Spirit	195
10	Treasure	390	30	Latest	188
11	Creative ideas	389	31	Highest	179
12	Director	363	32	Host	178
13	Urban area	328	33	Fresh and alive	178
14	Best	317	34	Experience	156
15	Unity	316	35	Development	143
16	Education	288	36	Optimal	136
17	City wall	279	37	Celebrate the spring festival	116
18	Tourism bureau	260	38	Treasure	115
19	Ultimately	259	39	Remote	112
20	Revolution	239	40	Story	110

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Figure 4.

Network semantic diagram of “Museum and Memory.”

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Table 6.

Tourists’ Emotional Feedback Tendency.

Key words	Positive emotions	Neutral emotions	Negative emotions
“museum + culture”	87.04%	3.59%	9.37%

Based on the above analysis, museum narrative showed tourists the specific cultural values and essence of the museum, promoted resonance in the tourists’ own cultural cognition and their communication, and influenced the tourists’ memories of their visit through its educational function. There are tourists perceives the museum narrative through interactions with historical artifacts, to establish an emotional connection with the museum and activating the memories of their visit. Culture itself does not have cognitive abilities, but could manifests itself through interactions between people and people, and between people and objects (Fanea-Ivanovici & Pana, 2020). Thus, the cultural narrative that tourists experienced in museums involves not only an understanding of the exhibits and historical stories, but also reflects the perceptions and empathy of their own cultural backgrounds. Through this interaction, tourists are able to feel more deeply the emotions conveyed by history and culture. A closed-loop field of emotional feedback based on museum narrative, tourists’ own culture and tour memory has been formed. Based on it, we constructed the explanatory framework of tourists’ emotional feedback (as shown in Figure 5). With the help of non-material factors such as cultural attributes and stories, as well as material factors such as exhibition, buildings and design, cultural communication can promote the operation of the emotional feedback field of “museum narrative, tourists’ own culture, and tourism memories,” which enables tourists to evolve from their initial sensory experience to spiritual perception, and promote emotional feedback.

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Figure 5.

Interpretation framework of tourists’ emotional feedback.

Methodology

Study 3 combined qualitative and quantitative methods to reveal the internal logic of empathic interaction between cultural lyricism and emotional feedback in museum narratives. It is mainly divided into the following three steps. First, we employed a random sampling method, referring to the Affective and Cognitive Measure of Empathy (ACME) scale (Vachon & Lynam, 2016; Yi et al., 2021), and used measurements based on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree, higher scores indicating higher levels of relevance). The questionnaires were distributed to the tourists through a web link (we ensured that all participants were fully aware of the study’s purpose, process, and its possible implications, and participate in the study voluntarily). To protect the privacy of the participants, the researcher ensured that no information that could identify the participants would be disclosed. The questionnaire was designed with reverse scoring items to ensure the quality of the questionnaire recovery, which was also judged by factors such as the time of filling in the questionnaire. The items of the scale have been shown in Table 7. In terms of sample capacity, this survey in accordance with the statistical standard sample measurement method, set a confidence interval Z of 90% and a sample sampling error of 5%, with the estimated sample demand about 270. In the actual survey, Study 3 collected 302 questionnaires. In order to ensure that the quality of data could meet the needs of the study, after the questionnaire collection, the second author of this paper organized 3 to 4 trained graduate students to screen out those with insufficient filling time, missing content, similar answer, and inconsistency. Ultimately, we obtained 288 valid data. Subsequently, Statistical Product and Service Solutions (SPSS) 25.0 software was utilized to verify the reliability and validity of the research data, together with the rotation matrix suggestions to adjust the division of the questions. The overall reliability of the pre-research data was 0.934 (>0.9) and the structural validity was 0.955 (>0.9), which was basically in line with the projected objectives. Accordingly, we conducted K-means cluster analysis on the 288 valid data, and then combined with the empathy scale to classify the tourists into different empathy attribute types. The basic information of the tourists has been shown in Table 8. The clustering algorithm has been used to locate the best-fit centroid position (I. C. Chang et al., 2022; Swart et al., 2022; Tabianan et al., 2022). We analyzed the similarity of tourists within the same empathy category and the differences between different empathy categories of tourists, so that after identifying the characteristics of tourists in different empathy categories, the tourists can be classified and randomly selected for the interview, which ensured that the selection of interview participants is scientific, and further to construct the empathic interaction model between the historical culture in museum narrative and the tourists’ own culture.

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Table 7.

Basic Information of 288 Tourists.

Basic information about interviewees	Options	Frequency	Percentage	Average value	Standard deviation
Gender	Male	146	50.69%	1.49	0.501
	Female	142	49.31%
Age	<18	51	17.71%	2.37 (40.550)	0.924
	18–35	113	39.24%
	35–50	90	31.25%
	>50	34	11.80%
Education level	High school and below	117	51.32%	1.97	0.966
	Junior college	86	29.86%
	Undergraduate	62	21.53%
	Postgraduate and above	23	7.90%
Career	Student	75	26.04%	2.58	1.126
	Project units	37	12.84%
	Private industry	101	35.07%
	Individual operation	71	24.65%
	Else	4	1.39%

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Table 8.

Scale Items of ACME.

Study scale	Symbol	Measurement question items
Cognitive empathy	CE1	I find it difficult to understand the emotions that museums want to express when telling stories
	CE2	Through museum storytelling, exhibitions, or performances, I can tell when characters in a story feel scared
	CE3	I usually understand why some museums tell stories in this way
	CE4	I find it difficult to understand the feelings of some historical figures
	CE5	Through the storytelling, exhibitions, or performances in museums, I know when the characters in the story will get angry
	CE6	In the process of telling stories in museums, I can usually distinguish the feelings of characters in history
	CE7	In the process of telling stories in museums, I am not good at understanding the emotions of the characters in the story
	CE8	In the process of telling a story in a museum, I can usually guess what makes the people in the story angry
	CE9	In the process of telling stories in museums, narrators or performers don’t have to tell me that when they are sad, I can see it on their faces
	CE10	In the process of telling history in museums, I find it difficult to distinguish when the characters in the story will be sad
Affective empathy	AE1	If I could help those in need in the historical stories told by museums, it would make me feel great
	AE2	I am very excited if I could give a gift that I believe would be appreciated by a character in a historical story told by a museum
	AE3	I’m not too worried about hurting the emotions of the characters in the historical stories told by the museum
	AE4	When telling historical stories in museums, I don’t care if historical figures feel happy or not
	AE5	When telling historical stories in museums, I don’t care if historical figures feel discouraged
	AE6	When telling historical stories in museums, the feelings of historical figures do not interfere with my emotions at all
	AE7	If I hurt the emotions of characters in the historical stories told by museums, I feel very sad
	AE8	The misfortunes of characters in historical stories told by museums do not bother me much
	AE9	If my actions harm the characters in the story, I will stop quickly
	AE10	If my actions can make the characters in the story feel happy, I will do it
	AE11	I am unable to detect the emotions of the characters in the story in a timely manner through storytelling, exhibitions, or performances in museums
Affective bias	AB1	In museum storytelling, I enjoy watching historical figures get angry
	AB2	In telling stories in museums, I like to see historical figures scared
	AB3	If museums tell stories about characters in history that make them happy, it makes me very disgusted
	AB4	I like to let museums tell stories about characters in history that are uncomfortable
	AB5	I don’t want others to think I’m stupid while telling stories in museums
	AB6	When characters in historical stories told by museums get angry, I often feel like laughing
	AB7	Sometimes I like to see people crying in museums telling historical stories
	AB8	Sometimes it’s interesting to see people in museums telling historical stories being humiliated
	AB9	If I could get rid of something by harming the characters in the story, I would choose to do it

Second, on the basis of cluster analysis, tourists were randomly selected from each category of empathic attribute samples for interviews. It was found that when the number of interviews reached 20, we could collect no new insights or themes, so the number of sampled interviewees was set at 20. In order to protect the privacy of the participants, the content of the interviews will be anonymized to ensure that no information that might identify the participants would be revealed. Last, based on the above two analyses, we constructed an empathic interaction explanatory framework for museum narrative.

Findings

In this study, we employed SPSS 25.0 to conduct K-means cluster analysis, with the measured data of 288 tourists, and obtained three cluster central points, as shown in Table 9. In combination with ACME scale, empathic attributes have been classified into three types. Specifically, 98 tourists have prominent cognitive empathy, who tend to rationalize from other individuals’ perspective, could predict and understand the emotional changes of the characters in the story; 146 tourists have prominent affective empathy, accounting for the largest proportion, who could be easily affected by external emotions, and can empathize with the situation of the characters in historical stories; 44 tourists have prominent emotional bias, who cannot clearly perceive the emotions conveyed in the historical stories, and even remain indifferent. Therefore, among the three types, tourists with affective empathy were the target group in the museum narrative, while the other two types belong to the potential target group.

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Table 9.

Cluster Analysis and Division of Empathy Attributes.

Cluster central point	Empathy attribute type	Number
1	Prominent cognitive empathy	98
2	Prominent affective empathy	146
3	Prominent emotional bias	44

The interview results were transformed into texts for the following analysis. First, the word frequency analysis has been carried out to the interview texts, and we obtained 30 high-frequency words, as shown in Table 10. Among them, “museum,” as a symbol of cultural lyricism and emotional feedback, together with words such as “protection,”“deposit,” and “innovation,” demonstrated that how the museum should strengthen the protection of cultural relics by means of digital means, and enhance the interactivity and experience of the exhibition to promote the service upgrading, so as to meet diversified needs of tourists. As one of the participants said, “There are many innovations in the process of visiting, which expand the original traditional cultural space through digital and mobile presentation forms, such as video (interviewee S9).” Second, network semantic analysis has been carried out to the text data to form a three-layer structure (as shown in Figure 6). Specifically, the core circle composed of “museum,”“culture,” and “memory” representing the main body of historical and cultural lyricism expression and tourists’ emotional feedback in empathic interaction; the sub-core circle composed of words such as “inheritance,”“cultural relics,”“development,” and “China,” implying that museums play a very important role in cultural inheritance and development; and the external circle composed of words such as “feeling,” indicating that the museum narrative can promote the emotional integration of tourists and historical culture. As one of the participants said, “The relationship between me and the museum is connected through culture, and it also gives us a way to connect with the past, which awaken my emotional memory of that history.” Last, the emotional tendency in empathic interaction is explored through sentiment analysis. As shown in Table 11, positive emotions account for 88.06% and negative emotions account for 10.04% in tourists’ empathic interaction. It indicated that tourists themselves mostly have positive attitudes toward museum narrative, but museum managerial personnel should pay attention to and relieve negative emotions.

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Table 10.

Word Frequency Analysis of Empathic Interaction.

Ranking	Word	Frequency	Ranking	Word	Frequency
1	Museum	253	16	Cultural relics	63
2	Culture	218	17	Team	60
3	National	216	18	Spirit	59
4	Tourist	205	19	Friend	59
5	History	165	20	Tour	58
6	Revolution	164	21	Deposit	57
7	Nature	163	22	Create	56
8	Mask	123	23	Experience	54
9	Innovation	122	24	Highlight	54
10	Advance	106	25	Build	53
11	Memory	101	26	Develop	53
12	Practice	92	27	Carry forward	52
13	Creative ideas	91	28	Fully	52
14	Promotion	79	29	Develop	52
15	Protection	77	30	Service	51

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Figure 6.

Network semantic diagram of empathic interaction.

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Table 11.

Sentiment Analysis of Empathic Interaction.

Key words	Positive emotions	Neutral emotions	Negative emotions
Empathic interaction	88.06%	1.90%	10.04%

Based on the above cluster analysis and network text analysis, we constructed the explanatory framework of the empathic interaction in museum narrative, as shown in Figure 7. The museum’s historical culture and tourists’ own culture are two subjects in museum narrative. The former mainly carries out cultural narrative through connotation exploration and technological innovation, together with different story themes and media to express cultural feelings, passing the emotions contained in the stories to tourists to meet their emotional needs; The latter mainly carries out cultural communication through learning and education, and carries out emotional feedback in combination with the psychological changes of “visit, experience, and spirit” to decode historical and cultural information. Their interactive response forms the empathic interaction in museum narrative, inherits and spreads the historical culture of the museums, as well as activates and awakens the tourists’ own culture.

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Figure 7.

Interpretation framework for empathic interaction in museum narrative.

Hypotheses

Cultural identity is the basic form of national identity, which originates from the same historical cognition and is shaped by culture. The formation of tourists’ cultural identity, on the one hand, depends on long-term cognition, and stable emotion; on the other hand, can be formed through short-term cultural learning process (Yang et al., 2022). Cultural identity is formed based on the perception, understanding and experience of culture (Kranz & Goedderz, 2020). For example, participants who has been required to engage in complex conversations, are able to resist oppressive colonial narratives, to reconnect and strengthen their indigenous identity, and to work toward the realization of their ancestors’ vision of health and well-being (Fernandez & Beltrán, 2022). Museums provide a platform for tourists to communicate, allowing visitors to strengthen cultural and social ties, and are an important channel for tourists to perceive cultural identity (Kozinets et al., 2017). Cultural communication can reduce tourists’ sense of cultural distance, so as to improve their cultural heritage experience (Lee et al., 2018), so as to achieve the psychological state of cultural identity. Dialog and interaction among tourists and cultural learning in museum narrative, can effectively promote tourists’ understanding of culture and activate their own cultural memory, thus forming cultural identity of specific history. Based on this, Study 4 proposed the following hypothesis:

From the individual level, the interaction between personal narrative and cultural narrative can promote the development of comprehensive narrative identity and carry out the reconstruction of self-identity (Y. Guo et al., 2022). And cultural narrative that resonates with people’s personal narratives may contribute to the formation and identification of meaning (Moss & Sandbakken, 2021). From the perspective of museums, as an important material and symbolic place for ethnic history and heritage, museums are valuable contributors to ethnic cultural identity. By enhancing narration, the interaction and emotional exchange between cultural heritage and tourists have been enhanced, which contribute to the shift of tourists’ attitude toward cultural heritage from concern to emotional participation to emotional identity (Y. Guo et al., 2022). In addition, by presenting a culture-specific narrative perspective that strengthens and presents the image of the site in a cohesive way, museums could also enhance tourists’ understanding of the information and promote the “place identity” for the value of the specific cultural heritage. It can be seen that museum cultural narrative have a significant impact on cultural identity. Based on this, Study 2 proposed the following research hypothesis:

Empathy is the ability to understand and share the emotions of others (Zhao et al., 2019), which is presented in the form of multiple experiences by receiving, encoding and decoding information (Zaslavsky et al., 2019). In communication, we often share our feelings with others to arouse the resonance of listeners, and show empathy by showing sincere concern for listeners’ experiences, feelings and emotions (Y. W. Chang et al., 2021). And cultural identity plays an important role in “empathy” between listeners and speakers (Mauchand & Pell, 2022). Empathic interaction in museum narrative is a process from cultural communication and cultural narrative to cultural identity, and then to psychological empathy. It can be seen that cultural identity has a significant impact on psychological empathy. Based on this, Study 4 proposed the following hypotheses:

Methodology

Based on the above research hypotheses, Study 4 constructed a structural equation model with cultural communication and cultural narrative as independent variables, psychological empathy as dependent variable, and cultural empathy as mediating variable. Among them, we borrowed five question items from Cultural Communication Identity Scale of Rodríguez-Rivero et al. (2020) for cultural communication; we combined three question items from Asian Self-Identity Cultural Adaptation Scale of Suinn et al. (1987) and Racial Identity Measurement Scale of Phinney and Ong (2007) for cultural narrative; we borrowed six question items from Psychological Empathy Scale of Vachon and Lynam (2016) for psychological empathy; and we designed five question items referenced to Cultural Identity Scale of Tu et al. (2019) for Cultural Empathy, all measured in a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree, higher scores indicate higher levels of the relevance) to obtain a preliminary questionnaire. Subsequently, in order to ensure the quality of the questionnaires filled out by the participants, and the authenticity and validity of the data, we distributed a certain number of questionnaires (a total of 43) for pre-survey before the formal survey. The survey team first analyzed the possible problems in the questionnaire with the results of the collected questionnaires. At the same time, we communicated with the participants, listen to their questions and suggestions, to find out flaws in the questionnaire, and referred it for structural adjustment and revision. Furthermore, the results of the pre-survey questionnaire were summarized and preliminarily analyzed using SPSS 25.0 software, and the division of the questions was adjusted according to the reliability and validity of the pre-survey data, as well as the rotated matrix suggestions. The overall reliability of the pre-survey data was 0.873 (>0.8) and the structural validity was 0.802 (>0.8), which basically meets the projected objectives. The questions were combined, with careful deliberation and repeated modification, in order to form the final questionnaire, as shown in Table 12.

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Table 12.

Scale Items of Museum Narrative.

Study scale	Items’ tags	Measurement question items
Cultural communication	CC1	In the narrative process of museums, I feel that museums use scene reproduction or videos to make cultural relics more closely related to themselves
	CC2	In the narrative process of museums, I feel involved and gradually become a disseminator of museum culture
	CC3	During the narrative process in the museum, I felt the interaction with museum artifacts
	CC4	I believe that using the commentator’s Q&A during the narrative process can enhance my understanding of history and culture
	CC5	I believe that in the narrative process, the cultural background of tourists will interact with the specific context of the museum
Cultural empathy	CE1	Through the narrative experience of museums, I can feel the brilliance of historical culture
	CE2	Through the narrative experience of museums, I feel that a certain period of history or cultural relic has a certain special cultural significance
	CE3	Through the narrative experience of the museum, I have felt the special customs or habits in the historical background presented by the museum
	CE4	During the storytelling process at the museum, I felt that cultural relics can be presented as stories
	CE5	In the narrative process of museums, I can feel the significance of the cultural value continuation of this period of history or cultural relics
Cultural narrative	CN1	During the process of telling stories in museums, I have a strong sense of belonging and pride in my own ethnic development history
	CN2	In museum storytelling, I am very willing to help me better understand my ethnic and cultural background through reading historical introductions, explanations, and other means
	CN3	After telling stories in museums, I usually have a better understanding of local customs and related history
Psychological empathy	PE1	If I could help those in need in the historical stories told by the museum, it would make me feel great
	PE2	I would be excited if I could give a gift that I think would be liked by a character in a historical story told by a museum
	PE3	If I hurt the emotions of characters in the historical stories told by museums, I feel very sad
	PE4	If my actions harm the characters in the story, I will stop quickly
	PE5	If my behavior can make the characters in the story feel happy, I will do it
	PE6	When telling historical stories in museums, the feelings of historical figures do not interfere with my emotions at all

In addition, we reviewed the past modeling methods of empirical research, especially the Covariance Base Structural Equation Model (CB-SEM). The algorithmic logic of CB-SEM is to construct relationships, by observing the covariance matrices of latent variables, and then connecting paths between each facet to reveal the interactions between the variables. However, the CB-SEM modeling technique is extremely demanding in terms of model fit, and is suitable for modeling large samples with normal distributions. CB-SEM has been developed to test the interactive strength of the structural relationships inherent in theoretical conceptual models, and is mostly used in path-testing studies to derive and validate such models. Hair et al. (2012) confirmed that when the data acquired for modeling are small-sampled, the CB-SEM modeling technique often fails to accurately predict the interrelationships among the variables because the data can only converge to a normal distribution, so it is difficult to complete the construction of structural equation models. In order to properly solve the limits of CB-SEM modeling technique in constructing non-theoretical models with small samples, we employed the Partial Lease Square Structural Equation Model (PLS-SEM) modeling technique, which is based on the method of least squares estimation and focuses on the verification of model paths rather than the overall goodness-of-fit. This method mainly verifies and predicts the strength of the relationship between observed variables and latent variables through linear equations, which is essentially general linear model. It has been widely used by positivist scholars in recent years, because it can effectively fix the problem of covariance between observed variables and the influence of regression unhelpful noise, and could greatly validate path hypothesis of general research. Compared to the huge amount of data in the macro database, the number of samples that can be obtained in Study 4 is generally small. The hypothetical model to be verified in Study 4 is mainly its hypothesis of the influence relationship between variables, which is not a purely theoretical modeling. Therefore, Study 4 chose Smart-PLS software to establish the PLS structural equation model of the tourists’ empathic interactions in the museum narrative, as shown in Figure 8.

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Figure 8.

Model for interactive empathy of museum narrative.

In conjunction with the above methodology, this part of Study 4 used random sampling to collect data through online questionnaire distribution. According to Kock and Hadaya (2018), the minimum sample size for PLS-SEM modeling should be greater than or equal to the greater one of the following requirements: (1) 5 to 10 times the maximum number of formative indicators used to measure a construct; and (2) 10 times the maximum number of structural paths in the structural model for a particular latent construct. The number of formative indicators in Study 4 was 19, and according to the minimum requirement of at least 5 times, the sample quota should be no less than 95. The maximum number of structural paths in the structural model for a particular latent construct is 6, and according to the requirement of at least 10 times, the sample quota should be no less than 60. In accordance with the principle of the greater of the two, the sample quota required for completing the statistical analysis for Study 4 should be at least equal to or higher than 95. We collected a total of 184 questionnaires. Questionnaires should be filled with more than 3 min and have sufficient key information, and there should be no obvious human errors before and after options matched, some of the missing data and outliers have been replaced by the mean value of the variables. We harvest 169 valid questionnaires, with a validity rate of 91.8%, and the basic information of the samples has been shown in Table 15. In order to protect the privacy, this study was conducted with the consent of the participants themselves. In terms of demographic indicators, we found that the male to female ratio of participants was 1.06, which is quite reasonable. In terms of educational composition, the main body of participants had a high-school education or less (65), followed by a bachelor’s degree (54). The age of the participants is aggregated between 15 and 35 years old and 35 to 50 years old, which is relatively in line with the characteristics of the contemporary museum tourism population, featured a certain learning and cognitive ability. The basic information of the sample has been shown in Table 13. In addition, because PLS-SEM analysis method can effectively prevent the occurrence of covariance between the observed variables, PLS-SEM analysis method can meet the main requirements of this study.

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Table 13.

Basic Information of 169 Tourists.

Basic information about interviewees	Options	Frequency	Percentage	Average value	Standard deviation
Gender	Male	87	51.50%	1.49	0.501
	Female	82	48.50%
Age	<18	34	20.10%	2.35 (40.550)	0.908
	18–35	58	34.30%
	35–50	61	36.10%
	>50	16	9.50%
Education level	High school and below	65	38.50%	2.51	1.086
	Junior college	54	32.00%
	Undergraduate	37	21.90%
	Postgraduate and above	13	7.70%
Career	Student	44	26.00%	1.99	0.957
	Project units	29	17.20%
	Private industry	62	36.70%
	Individual operation	34	20.10%

Findings

In the PLS-SEM test, the Cronbach α of cultural communication, cultural narrative, cultural empathy, and cultural identity were .886, .772, .863 and .870, respectively, all greater than 0.7, indicating that each latent variable had good reliability. CR of each latent variable was 0.917, 0.868, 0.901, and 0.903, respectively, which were all greater than 0.7, further indicating that the model has high reliability. The AVE of each potential variable was 0.687, 0.687, 0.647 and 0.607, and the rho_A was 0.889, 0.774, 0.863 and 0.871, which were all greater than 0.7. Therefore, the various facets of the proposed model passed reliability and validity test. By the predictive power test, the R² values for cultural empathy and psychological empathy were .626 and .609 respectively. According to the PLS-SEM modeling evaluation criteria proposed by Hair et al. (2019), the R² values were all between .5 and .75, indicating that each exogenous latent variable has a strong explanatory power for endogenous latent variables; The Q² values of cultural empathy and psychological empathy were .4 and .363 respectively, both greater than 0.35, indicating that the exogenous variables of this model have strong correlation with the prediction of empathy interaction in museum narrative as the endogenous variables. It is obvious that the PLS model has strong overall prediction ability for the occurrence path of empathy interaction in museum narrative.

Based on a large number of social empirical studies, Voorhees et al. (2016) believed that researchers can check the upper limit of 95% confidence interval of HTMT to conduct discriminating validity test for the facet connection in the measurement model, which could check whether the upper limit of HTMT is lower than 0.9, or 0.85. We performed the discrimination-validity test to the relevant facet connection of the four measurement variables proposed in this study, their HTMT were all less than 0.9 (as shown in Table 14), indicating that the proposed measurement model has a high degree of differentiation.

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Table 14.

Discrimination Validity Detection.

Variable	Cultural communication	Cultural empathy	Cultural narrative	Psychological empathy
Cultural communication
Cultural empathy	0.857***
Cultural narrative	0.886***	0.886***
Psychological empathy	0.832***	0.899***	0.887***

Note. ***p < .001.

As shown in Figure 8, the research hypothesis has been verified. The results showed that: The path coefficient of cultural communication and cultural empathy was 0.479, the path coefficient of cultural narrative and cultural empathy was 0.373, and the path coefficient of cultural empathy and psychological empathy was 0.782. In general, the path coefficient of each path is basically greater than or close to 0.3. The influence path structure model of cultural communication, cultural empathy, cultural narrative and cultural identity has been proved to be reasonable and effective, and the significance level p value of all paths is less than .05 (As shown in Table 15). Therefore, hypothesis 1, 2 and 3 have been all validated.

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Table 15.

Model Path Coefficients.

Model path	Original sample (O)	Mean(M)	Standard deviation(STDEV)	T statistic(|O/STDEV|)	p Value
Cultural empathy → Psychological empathy	0.782	0.785	0.04	19.402	.000
Cultural narrative → Cultural empathy	0.373	0.379	0.091	4.091	.000
Cultural communication → Cultural empathy	0.479	0.474	0.088	5.457	.000

In addition, Bootstrapping has been used in Study 4 to calculate the T-statistic for each path coefficient to test the significance level of the path coefficient (As shown in Table 16). There are two mediating effect paths in the empathic-interaction model of museum narrative, namely “cultural communication → cultural empathy → cultural identity” and “cultural narrative → cultural empathy → cultural identity.” The T-values in the two mediating effect paths were 4.981 and 3.911 respectively, indicating that each path coefficient has passed the significance test. It is further indicated that the model structure has high stability and significant indirect effect after repeated sampling.

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Table 16.

Specific Indirect Effects Test Results.

Specific indirect effect	Original sample (O)	Mean(M)	Standard deviation(STDEV)	T statistic(|O/STDEV|)	p Value
Cultural narrative → Cultural empathy → Psychological empathy	0.291	0.297	0.074	3.911	.000
Cultural communication → Cultural empathy → Psychological empathy	0.375	0.373	0.075	4.981	.000

Conclusions

Focusing on “empathic interaction in museum narrative,” this study collected and analyzed the text data of cultural lyricism, tourists’ emotional feedback, and empathy interaction response between historical culture and tourists’ own culture, to explore the construction logic of the empathic interaction, and drew the following three conclusions. First, as public cultural institutions, museums mobilize their material and non-material resources, to promote the upsurge of cultural consumption to form a cultural lyric field of the “museum, history and culture, and public service.” Moreover, cultural lyricism in museum narrative is based on the rich storyline, and makes the emotional expression more vivid with the support of innovative technology. The intergenerational inheritance of culture featured with distinct connectivity and interaction, which can effectively enhance the cultural and emotional value of tourists. Second, the museum narrative can interact with tourists’ own culture, wake up tourists’ visit memory, and form an emotional feedback field of “museum narrative, tourists’ own culture, and visit memory.” In addition, the emotional feedback of tourists in museum narrative promotes the field operation by means of cultural communication, so that tourists can evolve from the initial sensory experience to spiritual perception and to form positive emotional feedback. Third, the empathic interaction in museum narrative is based on the history and culture of museum and the tourists’ own culture. The former carries out cultural lyricism by combining different story themes and media, in the form of cultural narrative, and transmits the emotional information contained in the stories to the tourists. The latter carries out emotional feedback in the form of cultural communication and combines with the psychological changes of “visit, experience, and spirit,” to understand the information conveyed by history and culture. And among the three types of empathy, tourists with prominent affective empathy are the target group in museum narrative, while tourists with prominent cognitive empathy and emotional bias belong to the potential target group.

Theoretical Implications

This study made the following three theoretical contributions to research related to museum narrative.

First, the study revealed a new structure of cultural lyricism in museum narrative. Unlike previous museum studies that highlighted historical and cultural connotations (L. Jin et al., 2020; Johnson & Owens, 2023), embodied artistic and cultural qualities (Raimo et al., 2022; Trunfio et al., 2020), or addressed scientific and techno-cultural discoveries (Mihelj et al., 2019; Pesce et al., 2019), but only reached the surface of cultural features or patterns of influence, and rarely explored the emotional factors involved. It is clear that museum narrative can only evoke emotions to shape positive experiences. In this regard, this study took historical museums as an example and proposed an explanatory framework of cultural lyricism. Based on non-material elements such as story, spirit and management, as well as material elements such as cultural relics, architecture and science and technology, the cultural narrative enters the cultural lyricism field of “museums-history, culture and public service” with its rich story connotation, and uses the innovative media for field dissemination. This study proposed the cultural lyricism of material landscape, which integrated immaterial and material elements to reach media communication in the cultural public service field, not only emphasizing the significance of non-material elements, but also the significance of material elements in the tourists’ experience. It can be observed that material elements just like human beings, providing tourists with the contents and effects of “storytelling.” This fusion of non-material and material elements in the communication mechanism, standardizes the subsequent development and application of museum resources.

Second, the research has revived the communicative features of tourists’ emotional feedback (Akgün et al., 2020; Toral et al., 2018; Yan et al., 2018), and constructed an explanatory framework for tourists’ emotional feedback in museum narrative. Based on immaterial elements such as cultural attributes and stories, as well as material elements such as exhibitions, architecture, and design, this explanatory framework can facilitate the field operation of the “museum narrative-tourists’ own culture-visit memory,” so that tourists can evolve from the initial sensory experience to spiritual enlightenment, which promote their emotional feedback at the same time. This study proposed a push-back mechanism, emphasizing that tourists’ emotional feedback does not exist in isolation, but a positive response to the narrative, which in turn enhances the sensory effects, from experience to spirit and then to the cycle of positive feedback.

Third, this study proposed a logic of interactive response between historical culture and tourists in museum narratives. This study verified the interactive response relationship between history and tourists through the cultural lyricism in museum narrative and tourists’ emotional feedback, and constructed an empathetic interactive explanatory framework of museum narrative. The historical culture of the museum and the tourists’ own culture are the two main subjects of the museum narrative, and the former mainly carries out the cultural narratives through connotation excavation and technological innovation, then combines the themes of the stories with the different media for cultural lyricism, and passes the emotions embedded in the stories to the tourists to satisfy their emotional needs; the latter mainly carries out cultural communication through learning and education, then combines the emotional feedback with the psychological changes of “visiting-experiencing-spirituality,” and decodes the historical and cultural information. The two responses to each other to form the empathic interaction of museum narrative, thus passing on and spreading the history and culture of museum, and activating tourists’ own culture. This study emphasized the difference between material and non-material elements under the framework of empathy theory, and the findings of the study can help to understand what behind the material elements of museums. The material elements are influenced by designers, managers and other related subjects, in the form of historical “spokespersons,” they achieve the interactive response between the history, and the tourists. This study promotes the exploration of the “human-object” relationship of empathy theory, and further explains the meaning behind it.

Practical Implications

This study provided the following three practical inspirations for the development of museum narrative. First, for the long-term development of museums, as tourists pay more attention to the plot performance of the narrative and their emotional needs during the visit, museums can make more detailed plans for the design and construction of the museum exhibitions, combining with the empathic interaction framework constructed in this study. Second, as for the tourists’ experience and demand, museums need to take culture as a breakthrough point, make full use of the educational functions, improve the cultural heritage of tourists, and create immersive narrative scenes through digital technology. These measures mentioned above can give tourists a higher level of emotional experience and meet their cultural needs. Last, concerning social and cultural heritage, museums and tourists have established communication channels through culture. The interactive relationship between the museum and tourists, completes the dissemination and inheritance of cultural undertakings, indirectly facilitate cultural consumption, and drive the development of tourism economy.

Deficiency and Prospect

This study has certain limitations and needs to be improved in future research. First, it focused on the empathic interaction in narrative, and preliminarily discussed the elements of empathic interaction. Future research should better enrich the specific influence paths of each element in empathic interaction. Second, this study has been limited to a single perspective of emotions, to explore the experience of tourists in museum narrative. In future research, multiple factors (such as the type of tourists) should be considered to improve the empathic interaction in museum narrative. Third, although this study classified tourists into groups of cognitive empathy, affective empathy and emotional bias, the difference of their role in the museum narrative has not been discussed. In the future, we can explore this aspect to support the empathy interaction path of museum narrative. Last, it is worth to be further discussed whether the theoretical model of empathic interaction in museum narrative proposed in this study can be applied to cultural carriers, such as libraries and art galleries that have similar social attributes to museums.