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Abstract

Consistent with global trends in cultural tourism, museum tourism has emerged as a popular form of cultural tourism that has increasingly drawn the significant attention of scholars as the target of academic research. The tourists’ cultural experience can affect their evaluation of the specific visit and subsequent behavior. While previous researchers have paid more attention to the mechanism of visitors’ post-visit behaviors, cultural transmission as a dependent variable has received scarce attention. This study examines factors influencing college students’ behavior in communicating specific museum cultural content after a visit. It also identifies the mediating mechanism underlying the relationships between cultural transmission and its antecedents. The purposive questionnaire in a highly structured survey was distributed online among college students. A total of 195 usable responses were drawn. A quantitative survey methodology was employed, including Chi-square analysis, Confirmatory Factor Analysis, and Structural Equation Modeling. The results show that: (1) the determinants of college students’ cultural transmission behavior are cultural experience, cultural identity, and satisfaction, which explains 59% of the variance of cultural transmission; (2) the impact of cultural experience on cultural transmission was mediated by cultural identity and satisfaction (it includes a serial mediation effect as the effect of cultural experience on satisfaction flowed through cultural identity, where student satisfaction mediated the impact of cultural identity on cultural transmission); and (3) college students pursuing the liberal arts present statistically different preferences in visiting museums when compared with science and engineering students. The discussion and implications present theoretical advancements in elucidating the mechanism of visitors’ cultural communication processes and recommend the use of technology-driven innovations for improvements in post-visit activities for cultural transmission.

Keywords

cultural experience cultural transmission cultural identity satisfaction mediation analysis

Introduction

Culture and tourism are intimately linked, and cultural tourism continues to increase in popularity as a particular subset of mass tourism (Richards, 2018). Cultural attractions provide extensive learning environments to strengthen visitors’ cultural understanding and consolidate cultural identity (S.-N. Zhang et al., 2021). Cultural tourism is related to trips to attractions like museums, art galleries, and architectural and heritage sites (H. L. Hughes, 1996; Stebbins, 1996; Verma & Rajendran, 2017). Museums have significantly shifted from their primary and exclusive emphasis on preserving and consolidating the local culture and memory (Fu et al., 2015) to the current focus on providing comprehensive visitor-oriented experiences. Brida et al. (2012, p. 167) stated, “Museums play a relevant role as repositories of cultural diversity, education, social cohesion, and the preservation of community identity.”

Although studies have focused on different factors affecting visitors’ experiences, such as information and communication technologies (Kang et al., 2018; Nava & Cruz, 2022; Trunfio et al., 2019), brainwave technology (Qi et al., 2023), staff services and facilities (Harrison & Shaw, 2004), and the moderating role of visiting frequency (Kofi Preko & Gyepi-Garbrah, 2021), little research has focused on the influences of cultural information or knowledge obtained by visitors during their tours, and the effects of cultural identity (S.-N. Zhang et al., 2021), defined as the extent to which a person can recognize and respect the cultural value inherent in a museum. Moreover, from the perspective of independent variables, the most widely used antecedents include service quality (Alhawamdeh et al., 2023; Çiftçi & Çizel, 2024), perceived value (Palau-Saumell et al., 2016), and satisfaction level (Seung-Wan et al., 2022; R. Zhang & Abd Rahman, 2022). Meanwhile, from the perspective of dependent variables, two dependents are predominantly investigated: “visitors’revisit intention” (Brida et al., 2012; Volkan Genç et al., 2023; Q. Zhou & Pu, 2022) and “willingness to pay (WTP)” (Baldin & Bille, 2023; Bedate et al., 2009; Choi & Nam, 2018; Plaza, 2010), whereas studies concerning cultural transmission as a dependent variable are insufficient and have not been systematically expounded in theory. Therefore, this study intends to fill this gap by proposing and answering the following research questions:

Besides the most widely analyzed factors, are there other variables, such as cultural experience and identity, that affect the post-visit behavior of museum visitors?

Does cultural experience, directly and indirectly, affect cultural transmission through cultural identity and satisfaction in the museum tourism context?

Do demographic characteristics cause differences in visitors’ satisfaction vis-a-vis choosing a museum?

The specific objectives of this study are as follows: from college students’ perspectives and in the museum tourism context, firstly, it intends to expand the existing research models regarding the causal mechanisms of cultural experiences and transmission. Secondly, it further explores the relationships between different variables, including cultural experience, cultural identity, satisfaction, and cultural transmission, with empirical evidence. Thirdly, it also strives to analyze the mediating effects of cultural identity, which is rarely investigated in the existing literature, and satisfaction in this proposed structural relationship. Fourthly, it sheds light on the preferences of visitors with different demographics, especially majors in liberal arts and science and technology. Therefore, this empirical analysis focuses on the college students’ experience and perception of the Tao Xingzhi Memorial Museum in Nanjing, China, an important memorial museum in memory of the great educator Mr. Tao Xingzhi and his educational philosophy, introducing his all-around achievements. This study enables a better understanding of the cultural transmission model and identifies new museum visitor profiles.

The rest of this study is structured as follows. First, the literature review focuses on cultural and museum tourism, cultural experience and identity, and satisfaction. Next, the model is presented with nine hypotheses and an explanation of the instrument design and sampling process. The following sections focus on the data quality, reliability, and validity of the model, as well as the goodness-of-fit indices of measurement and structural models, and highlight the results of the model and hypotheses testing. The next section illustrates the results of the mediation process. The last four sections discuss the results and present this study’s theoretical and practical contributions, conclusion, limitations, and recommendations.

Literature Review and Research Hypotheses

Culture, Cultural Tourism, and Museum Tourism

Culture refers to a complex collection of specific information that is better communicated, absorbed, transmitted, and spread among people, communities, and regions with similar lifestyles, value systems, beliefs, and traditions. As highlighted in the Cultural Dimensions Theory introduced by Hofstede (1980), people with geographical proximity, similar historical backgrounds, and a common language are more likely to understand and appreciate each other’s cultures. Meanwhile, cultural sights or attractions provide an essential motivation for traveling (Richards, 2018). In other words, travel helps to increase cultural understanding, and culture, in turn, improves tourism. In the pioneering study by Richards (1996), the research emphasized that the availability of museums, exhibitions, and other cultural manifestations for public consumption helped boost tourism.

Cultural tourism is based on cultural identity and provides visitors with distinguished, informative, and entertaining experiences (Nhan, 2021). Stylianou-Lambert (2011) highlighted that cultural tourism is related to visiting museums, galleries, and historic sites in destinations. According to Richards (2018), the emergence of cultural tourism can be traced back to the increase in leisure travel in Europe during the 1950s. During that period, individuals sought to recover mentally and physically from World War II through traveling, increasing cultural understanding, and rebuilding shattered economies. Cultural familiarity and activation are core elements in the sustainability of cultural tourism (Pratt, 2005).

Museum tourism belongs to a subfield of cultural tourism (Richards, 2018). It plays a vital role in the development of cultural tourism. From an economic perspective, several papers discussed related topics, such as studies by Artal-Tur et al. (2018), Ponferrada (2015), and Guccio et al. (2018). All of the research studies indicated increased museum tourism in the past decade. Attention also has been paid to analyzing museums’ learning and educative functions (Andre et al., 2017; L. Zhou et al., 2019). A visit to a museum can expose visitors to detailed information on a topic and the museum’s cultural features, which allows them to have unique experiences and absorb information that interests them most. The International Council of Museums (ICOM, 2022) defines a museum as “a not-for-profit institution providing service that collects, protects, interprets, and spreads cultural heritage.”Herreman (1998) noted that museums are a part of a cultural complex for the spread of knowledge and experience. As Kirshenblatt-Gimblett (2009) mentioned, museums can be considered premier attractions for cultural tourists.

Furthermore, museum tourism can be considered an essential cultural tourism component, providing visitors with memorable experiences that improve their emotional, physical, and spiritual well-being (Pine & Gilmore, 1999). Museum visits are a journey of experiencing service and culture involving visitors’“value imaginative, affective, and emotional perspectives” (Chan, 2009, p. 176). Additionally, studies have examined the domains of cultural tourist typologies (H. Hughes, 2001) and motivations behind visiting an art museum (Stylianou-Lambert, 2011). In Stylianou-Lambert (2011), a classification criterion referred to as the Museum Perceptual Filters (MPFs) was proposed to categorize visitors based on their different museum perceptions.

Cultural Experience

Cultural experience in heritage sites and museums has received continuous attention from researchers in recent years (Trunfio et al., 2022; Z. Wang et al., 2021). Visitors’ experiences can be personal and exhibited varying degrees of attachment and feelings to the site or destination, especially for cultural heritage visitors (Timothy, 1997). Meanwhile, people’s emotional and cultural bonds to the specific heritage site can influence their willingness to travel and perceptions of the place (Y. Zhang & Liu, 2021). H. Hughes (2001) noted that visitors who focus on specific types of culture or historical dimensions capture the spirit of the attraction. Cultural attractions, such as heritage and museums, provide essential motivation for travel, and travel, in turn, generates culture (Richards, 2018), and the more meaningful experience the visitors obtain, the more likely they will understand and appreciate the nature of a place deeply. When tourists engage in cultural elements and experiences while traveling, they can retain both surface-level impressions and profound understandings (Lehto et al., 2004). This process generates a cultural identity consistent with their self-association (X. Zhang, 2021).

Cultural Identity

The core of cultural identity is related to recognition and a sense of value, which is considered a reflection of unique cultural information presented by specific cultural attractions (Vidal González, 2008). Therefore, the term cultural identity, in this study, refers to visitors’ understanding and recognition of the cultural value displayed by the museum. Tajfel and Turner (2004) defined cultural identity as an aspect of social identity and of an individual’s self-concept, which derives from the knowledge of a social group and the value and emotional significance attached. Pratt (2005) suggested that cultural identity contributes to an individual’s association with and strengthening national identity. He and Ai (2021) applied correlation analysis and stepwise regression to identify how tourists’ experiences influenced cultural identity at Daming Palace National Heritage Park in Xi’an, China. They found that cultural identity focuses on belonging to a particular cultural value, essentially recognizing and affirming the value connotation under a specific cultural system.

For the relationship between cultural experience and cultural identity, Domínguez-Quintero et al. (2019) analyzed the relationships among authenticity, experience quality, emotions, and satisfaction in a cultural heritage context and stated that authenticity as a dual objective-and-existential variable can make a tourist feel relaxed and contribute toward achieving a higher quality experience. Also, Trunfio et al. (2021) noted that museum visitors had multiple experiences that could enhance their degree of cognition, including meeting their identity-related needs. In museum tourism, the relationship between cultural experience and identity was significant in He and Ai (2021). Thus, the following hypothesis is proposed:

H1: Cultural experience affects museum visitors’ cultural identity positively.

Satisfaction

Satisfaction is a subjective assessment of the extent and level of one’s positive experience (Tarrant et al., 1994), which is widely considered an essential variable in imposing high effects on customers’ future attitudes and behaviors around specific services, products, or experiences (Che et al., 2021). Satisfaction is related to the tourists’ psychological reaction to their experience (Suhartanto et al., 2020). The tourist experience is frequently considered a prerequisite for satisfaction (Sheng & Chen, 2012), visitor loyalty (S. Lee et al., 2020), and behavioral intention (Zeithaml et al., 1996). In the museum tourism context, it refers to visitors’ attitudes after a visit based on an integrative appraisal of emotion (Tang et al., 2021). Kofi Preko and Gyepi-Garbrah (2021) investigated tourist behavior in the museum setting in Ghana and found that museum experiences were influential in improving visitor satisfaction. Similarly, Brida et al. (2012) and Harrison and Shaw (2004) revealed that many museum visitors consider satisfaction a critical assessment indicator when evaluating their museum experience. Other scholars have focused on research on using technology (virtual and augmented reality) to improve visitors’ experience and satisfaction in a museum by enhancing their immersive experiences (Jung & tom Dieck, 2017; Yung & Khoo-Lattimore, 2019). Thus, the following hypothesis is proposed:

H2: Cultural experience affects museum visitors’ satisfaction positively.

Cultural Transmission

Cultural transmission is a manifestation of post-tour perception behavior. It is also known as cultural diffusion, relevant to communicating specific cultural traits from one social group to another (Cui, 2016). In the museum tourism context, recommending a museum to others and promoting cultural knowledge can extend satisfaction with the previous travel experience and recognition of its culture. Several factors affect the intention to communicate and transmit valuable cultural information, such as service quality (Caruana & Ewing, 2010), experience (Radder & Han, 2015), and perceived cultural value (Suhartanto et al., 2020), which have been examined in this study as the result and extension of emotional and cultural understanding.

Cui (2016) proposed two models based on relevant theories of transmission dynamics for promoting cultural transmission and found that cultural experience positively influences visitors’ personal quality and cultural transmission behavior. J. Xu (2020) examined cuisine in cultural tourism and found that cultural experience relates to post-consumption behaviors positively, particularly recommending specialties to others and communicating local food culture. Thus, the following hypothesis is proposed:

H3: Cultural experience positively affects museum visitors’ cultural transmission.

The significant positive relationship between cultural identity, satisfaction, and destination loyalty, including cultural transmission, was empirically verified by Tian et al. (2020). The display of various exhibits in a museum offers visitors immersive experiences and helps improve the psychological processes of distinction, cognition, and judgment, as well as belonging to and forming an identity with a given culture. Tian et al. (2020) treated cultural identity as an antecedent of satisfaction in their research on intangible cultural heritage and found that it affected satisfaction positively through authenticity perception. Thus, the following hypotheses are proposed:

H4: Cultural identity affects museum visitors’ cultural transmission positively.

H5: Cultural identity affects museum visitors’ satisfaction positively.

The relationship between satisfaction and cultural transmission has been studied empirically by researchers. For example, Yang (2021) found that a museum’s communication methods and content impact the tourists’ experience and affect post-visit behavior. The more satisfied the visitors are, the more likely they are to share the experience with others and promote the place to their friends (Izzo, 2017). A visitor is more likely to establish a long-lasting relationship with the museum by continuing beyond the visit, recommending its display, and presenting the cultural connotations they appreciate most (Stylianou-Lambert, 2011). Therefore, the following hypothesis is proposed:

H6: Visitors’ satisfaction affects cultural transmission positively.

Mediating Effects Between Cultural Experience and Transmission

Park et al. (2019) explored the tourists’ behavior at a historic winery in Spain and found that the experience positively affected the satisfaction of tourists, which, in turn, affected their revisit and recommendation intentions. A positive experience can influence satisfaction (Csikszentmihalyi, 2014) and arouse feelings like joy, happiness, and delight (J. Lee & Kyle, 2013). As S. Lee et al. (2020) noted, visitors’ experience positively related to satisfaction, and satisfaction furthermore positively influenced visitors’ intention. Positive emotions acquired during a visit, such as satisfaction or pleasure, can affect visitors’ subsequent attitudes and behavior (Han & Jeong, 2013). Thus, the following hypotheses are proposed:

H7a: Cultural identity mediates the relationship between cultural experience and transmission.

H7b: Satisfaction mediates the relationship between cultural experience and transmission.

H7c: A sequential mediating effect between cultural identity and satisfaction mediates the relationship between cultural experience and transmission.

Research Model

Figure 1 presents the proposed research model from the literature review and hypotheses. Cultural experience positively influences three constructs: cultural identity, satisfaction, and cultural transmission (CE→CI, CE→SAT, CE→CT). Cultural identity positively influences cultural transmission and satisfaction (CI→CT, CI→SAT). Satisfaction positively influences cultural transmission (SAT→CT). Cultural identity and satisfaction also mediate the effects of cultural experience on cultural transmission, including parallel (CE→CI→CT, CE→SAT→CT) and sequential mediation effects (CE→CI→SAT→CT).

Figure 1.

Research model and hypotheses.

Research Methodology

Instrument Development

This study conducted a quantitative survey using an anonymous, structured questionnaire and also emphasized that there are no wrong or correct responses to minimize social desirability bias (Jamshidi et al., 2023). A pilot test was conducted before the formal survey to validate the instrument. First, a scale containing 21 items was drawn up based on the literature. It used a 7-point Likert scale anchored on “1 = totally disagree” and “7 = totally agree.” Second, the questionnaire was distributed online and pilot-tested on 30 respondents through purposive sampling since it focused on college students at Jinling Institute of Technology (JIT) who recently visited the Tao Xingzhi Memorial Museum to participate in extra-curriculum activities. The introductory part explained the academic objective of this study. Participants were given a questionnaire using a purposive sample method (Ali et al., 2015), with the first question asking if they had visited the museum before. Respondents who had visited the museum before were examined. Third, the data obtained from the pilot were examined for scale reliability and validity. All constructs had acceptable alpha values exceeding the threshold of .700 (J. Hair et al., 2009). Two indicators from the cultural experience and identity constructs were removed as their shared variances of loading value had crossed the other constructs.

The final questionnaire had 19 items (Appendix A). It was divided into two sections, where the first focused on the measurement items of four latent constructs, and the second on the socio-demographic information of the respondents, such as gender, education, academic major, frequency of visiting the museum, and preference in terms of museum type. The indicators for the cultural experience were drawn from Han and Hyun (2017) and Li et al. (2021). The items for cultural identity were adapted from Oh (2017) and C. Xu et al. (2019). The items for satisfaction were drawn from S. Lee et al. (2015) and Chen and Ryan (2020). The items for cultural transmission were drawn from Han and Hyun (2017) and Suhartanto et al. (2020).

Data Collection

Research site

Located in Nanjing, Jiangsu Province (in the east of China), the Tao Xingzhi Memorial Museum is an iconic and refurbished complex dedicated to the storage, display, and research center of Mr. Tao Xingzhi, who was an influential educator and philosopher in China, whose teaching philosophy have deeply influenced generations of educators in China. His philosophy of education shares similarities with prestigious educator Dewey (1900), who emphasizes the belief that people learn and grow due to their experiences and interactions with the world. In other words, people continually develop new concepts, practices, and understandings, which, in turn, are refined and continue affecting the learners’ life experiences and social interactions (Dewey & Archambault, 1974).

The museum has rich treasures of exhibits through traditional and innovative multimedia presentations, including photos, videos, and personal handwritten letters. After the renovation and reopening in 2021, it continues to attract the increased attention of visitors with richer experiences and a greater cognition of the museum. In addition, this museum is located adjacent to the JIT campus, which particularly facilitates the convenience of students choosing to visit this museum as the most popular extracurricular activity. Also, the university administration selected this place as a preferred cultural education site.

Respondents

The JIT encourages college students to visit museums to broaden their horizons, expand their knowledge, and enhance their cultural identity. Students formed campus societies by volunteering at the Tao Xingzhi Memorial Museum in their spare time. The formal survey was administered to the students online through purposive sampling between July and August 2022. According to J. Hair et al. (2009), a sample size is based on the number of constructs. The minimum sample size for models containing 5 or fewer constructs (each with more than 3 items) is 100. A total of 198 completed questionnaires were received. After eliminating the outliers, 195 valid questionnaires were retained (response rate = 98.5%). Thus, the sample size was not an issue.

Demographic Information

The sample demographics are as follows: 41% were male, 59% were female. Regarding education, 35.4% were undergraduate students in their third year of study, 24.1% were in their first year, and 20.5% and 20.0% were in their second and final years of study, respectively. For academic majors, 39.5% were in Science and Engineering and 60.5% in Liberal arts (Table 1).

Table 1.

Demographic Statistics of the Respondents.

Response variable	Options	Frequency (n)	Percentage
Gender	Male	80	41
Gender	Female	115	59
Education	1st-year undergraduate	47	24.1
	2nd-year undergraduate	40	20.5
	3rd-year undergraduate	69	35.4
	Final year undergraduate	39	20.0
Academic majors	Science and Engineering	77	39.5
Academic majors	Liberal arts	118	60.5

Procedure and Statistical Methods

SPSS 24.0 and AMOS 23.0 software were used to encode and analyze the responses. The study drew on demographic data, frequency analyses, and Confirmatory Factor Analysis (CFA). As the data met the multivariate requirements, Covariance-based Structural Equation Modeling (SEM) was applied to test the structural models and hypotheses (Ketkaew et al., 2019). As recommended by Preacher and Hayes (2008), the bias-corrected bootstrap method was performed to analyze parallel and sequential mediation effects through PROCESS procedure 4.0 (Model 6).

Results

Descriptive Statistics

For “Frequency of visiting the museum per year,” 40.5% visited the museum 1 or 2 times in a year, 37.4% visited 3 or 4 times a year, 14.9% visited 5 or 6 times a year, and 7.2% visited the museum more than 7 times a year. Regarding the multiple-response question of “Preference of the museum type,” 26.1% preferred historical museums, 23.9% preferred natural science museums, and 21.3% preferred national museums. The remaining 18.6% and 10.1% preferred art and science and technology museums, respectively (As shown in Table 2).

Table 2.

Frequency of Visiting the Museum per Year and Preference for Museum Type.

Response variable	Options	Responses		Percentage of cases
Response variable	Options	N	Percentage	Percentage of cases
Frequency of visiting the museum per year	1–2 times	79	40.5
	3–4 times	73	37.4
	5–6 times	29	14.9
	More than 7 times	14	7.2
	Total	195	100.0
Preference for museum type	Historical museums	153	26.1	78.5
	Science and technology museums	59	10.1	30.3
	Art museums	109	18.6	55.9
	Natural science museums	140	23.9	71.8
	National museums	125	21.3	64.1
	Total	586	100.0	300.5

Preliminary Data Analysis

Normality and multicollinearity analyses were conducted to reduce systematic errors. Univariate skewness and kurtosis of each item ranged within the acceptable interval (−2 to +2), supporting normality in the data distribution (J. F. Hair et al., 2019). The value of the multivariate coefficient should be less than the Mardia coefficient (Bollen, 1989). In this study, the multivariate coefficient was 264.712 < 399(19 × 21), thus confirming multivariate normality distribution. The variance inflation factor (VIF) was used to evaluate multicollinearity among variables. All VIF values must be less than 3 (J. Hair et al., 2009). The VIFs ranged from 1.648 to 1.736 in this study. Thus, there were no multicollinearity concerns.

Chi-Square Analysis

A Chi-square analysis was conducted to understand the difference in the students’ preferences for museum type (Hosmane, 1986). Table 3 presents the results. The results of the Chi-square analysis show that the preferences of science and engineering students vis-a-vis historical museums differ significantly from those of liberal arts students (p = .008 < .01). The latter are more interested in historical and art museums than the former, with statistical significance (p = .008 < .01). There were no significant differences in the interest levels in science and technology, natural science, and national museums.

Table 3.

Chi-Square Analysis.

Variable	Options	Responses (%)		Total	χ²	p
Variable	Options	Science and engineering	Liberal arts	Total	χ²	p
Historical museum	Not interested	24 (57.14)	18 (42.86)	42	6.983	.008**
Historical museum	Interested	53 (34.64)	100 (65.36)	153	6.983	.008**
Science and technology museum	Not interested	59 (43.38)	77 (56.62)	136	2.854	.091
Science and technology museum	Interested	18 (30.51)	41 (69.49)	59	2.854	.091
Art museum	Not interested	43 (50.00)	43 (50.00)	86	7.116	.008**
Art museum	Interested	34 (31.19)	75 (68.81)	109	7.116	.008**
Natural science museum	Not interested	21 (38.18)	34 (61.82)	55	0.055	.815
Natural science museum	Interested	56 (40.00)	84 (60.00)	140	0.055	.815
National museum	Not interested	33 (47.14)	37 (52.86)	70	2.678	.102
National museum	Interested	44 (35.20)	81 (64.80)	125	2.678	.102

p < .01.

Measurement Model

Reliability and Convergent Validity

The measurement model was analyzed by testing internal reliability, convergent validity, and discriminant validity. The results are shown in Appendix B. First, the internal reliability was measured using Cronbach’s Alpha, factor loading, and Composite Reliability (CR). The Cronbach’s Alpha values ranged between .925 and .956, exceeding the cut-off value .70 (Cronbach, 1951). All factor loading values were ≥0.7, indicating acceptable indicator reliability (J. Hair et al., 2009). All values met the minimum requirements with CR ≥0.7 (Urbach & Ahlemann, 2010). Second, Kaiser-Meyer-Olkin (KMO) was 0.941 (>0.80), and Bartlett’s test was statistically significant, which validates the appropriateness of factor analysis (Cerny & Kaiser, 1977; Kaiser, 1970). Third, Principal Component Analysis was applied to choose the attributes, with Parameter Eigenvalues ≥1 in the analytical model. Four factors that provided the best summary of information were extracted, accounting for 81.90% of the variance. Fourth, Average Variance Extracted (AVE) was applied to examine the convergent validity, and the value of every construct must be above 0.50 for acceptable validity (Fornell & Larcker, 1981).

Discriminant Validity

Discriminant validity was assessed using the following criteria: (1) Cross-loading (Urbach & Ahlemann, 2010), where each indicator loads highest on the construct it is associated with, and (2) Fornell-Larcker criterion (Fornell & Larcker, 1981). The retrieved cross-loading values of each indicator show that each indicator loaded highest on the construct associated with Appendix C. As Fornell and Larcker (1981) recommended, the correlations between any two shared items within a construct should be lower than the square root of the average variance construct. As Table 4 shows, all diagonal values ( illustrated in bold ) exceeded the inter-construct correlations. Thus, the instrument had satisfactory construct validity.

Table 4.

Discriminant Validity.

Construct	CE	CI	SAT	CT
CE	0.888
CI	0.574	0.890
SAT	0.618	0.597	0.849
CT	0.641	0.626	0.649	0.887

Notes. CE = cultural experience; CI = cultural identity; SAT = satisfaction; CT = cultural transmission; The square root of AVE are shown in bold on the diagonal.

Common Method Variance (CMV) Testing

Two rigorous techniques were applied to test CMV: (1) Model comparison of CFA: single- and multi-factor model (Mossholder et al., 1998; L. Wang & Huang, 2022); and (2) Unmeasured latent method construct (ULMC; Podsakoff et al., 2003; Y. Wang & Li, 2019).

First, as shown in Table 5, the results indicated that the single-factor model exhibited worse goodness-of-fit indices than the multi-factor model (Δχ² = 1222.756, Δdf = 8, p < .05). The CMV problem in this study was not a concern. Second, the ULMC approach has been applied frequently in academia (Lindell & Whitney, 2001; Y. Wang & Li, 2019). Adding a single unmeasured latent method factor to the four-factor model, the results demonstrated that the goodness-of-fit indices of the CMV model did not improve significantly (Δχ² = 2.33, Δdf = 6, p = .887 > .05, ΔGFI = 0.001, ΔCFI = 0.001, ΔRMSEA = 0.001, ΔSRMR = 0.0026, ΔTLI = 0.002). Thus, CMB was not a serious problem.

Table 5.

Goodness-of-Fit Indices of the Single- and Multi-factor Model.

Model	χ²/df	GFI	RMSEA	CFI	AGFI	TLI	Δχ²	Δdf	p
Fit criteria	<3	>0.9	<0.08	>0.9	>0.8	>0.9	1,222.75	8	.000
Single-factor model	9.385	0.477	0.208	0.652	0.346	0.609
Multi-factor model	1.396	0.905	0.045	0.984	0.876	0.981

Note.χ²/df = Chi-square divided by degree of freedom; GFI = goodness-of-fit index; RMSEA = root mean square error of approximation; CFI = comparative fit index; AGFI = adjusted goodness-of-fit index; TLI = Tucker-Lewis Index.

Structural Model

Goodness-of-Fit Analysis

As seen in Table 6, the goodness-of-fit indices for both measurement and structural models meet the minimum requirements.

Table 6.

Goodness-of-Fit Criteria for the Measurement and Structural Models.

Items	Criteria	Measurement model	Structural model	Result	References
χ²/df	<3	1.396	1.397	Good	Schumacker and Lomax (2004)
GFI	>0.9	0.905	0.905	Good	Hu and Bentler (1999)
RMSEA	<0.08	0.044	0.045	Good	Hu and Bentler (1999)
CFI	>0.9	0.983	0.984	Good	Fan et al. (1999)
AGFI	>0.8	0.876	0.877	Good	Marsh et al. (1988)
TLI	>0.9	0.981	0.982	Good	Bentler and Bonett (1980)

Note. χ²/df = chi-squared divided by degree of freedom; GFI = goodness-of-fit index; RMSEA = root mean square error of approximation; CFI = comparative fit index; AGFI = adjusted goodness-of-fit index; TLI = Tucker-Lewis Index.

Structural Model Analysis and Hypotheses Testing

The path significance of each hypothesized association and R² value were calculated. Figure 2 and Table 7 show that CE, CI, and SAT jointly predicted the CT. These variables moderately explained 59% of the variation in cultural transmission and weakly explained the variance in SAT and CI with 47% and 33%, respectively.

Figure 2.

Structural model and path coefficient.

Table 7.

Hypotheses Testing.

Hypotheses	β	T-value	Results
H1 CE→CI	.574***	8.368	Support
H2 CE→SAT	.410***	5.439	Support
H3 CE→CT	.262***	3.639	Support
H4 CI→CT	.246***	3.489	Support
H5 CI→SAT	.362***	4.797	Support
H6 SAT→CT	.386***	5.052	Support

***

p < .001.

Hypotheses 1 to 6 gained empirical support. The strongest relationship emerged in support of H1. Cultural experience significantly affected cultural identity (β = .574; T = 8.368; p < .001). It also positively influenced students’ satisfaction (β = .410; T = 5.439; p < .001), thus confirming H2. Students’ satisfaction significantly affected cultural transmission (β = .386; T = 5.052; p < .001), thus confirming H6. Cultural identity significantly affected cultural transmission (β = .246; T = 3.489; p < .001) and satisfaction (β = .362; T = 4.797; p < .001), thus confirming H4 and H5. The cultural experience was a significant predictor of cultural transmission (β = .262; T = 3.639; p < .001), thus supporting H3.

Mediation Analysis

Mediation analysis examines the direct and indirect pathways through which an independent variable X affects a dependent variable Y through one or more mediator variables (Castro-González et al., 2019). Hayes’ (2018) PROCESS 4.0 -Model 6 is suitable for testing. Table 8 presents the direct, indirect, and total effects of CE on CT. First, the total effect of CE on CT was 0.611 (0.257 + 0.354 = 0.611). Second, the direct effect of CE on CT was 0.257. Third, the total indirect effect was 0.354. The 95% confidence intervals of the bootstrap method did not include 0 points for all the values, indicating the robustness of the results.

Table 8.

The Total, Direct, and Indirect Effects.

	Effects	SE	[LLCI, ULCI]	Hypotheses	Results
Total	0.611***	0.055	[0.479, 0.694]
Direct	0.257***	0.061	[0.126, 0.367]
Indirect	0.354***	0.065	[0.234, 0.491]
Ind1
CE→CI→CT	0.142	0.049	[0.040, 0. 240]	H7a	Support
Ind2
CE→SAT→CT	0.143	0.047	[0.063, 0.247]	H7b	Support
Ind3
CE→CI→SAT→CT	0.068	0.034	[0.020, 0.150]	H7c	Support

Notes. SE = standard errors; LLCI = lower level confidence interval; ULCI = upper level confidence interval.

***

p < .001.

The results show that cultural identity and student satisfaction partially mediated between cultural experience and transmission, and highlight the chain mediating effect between cultural identity and student satisfaction with the effect coefficient of 0.068, BC bootstrap 95% CI = [0.020, 0.150]. Thus, H7a, H7b, and H7c were supported.

Discussion

According to the results, nine advanced hypotheses were supported. Causative relationships and mediation effects have been confirmed between cultural experiences and cultural transmission. First, cultural experience, identity, and satisfaction explained 59% of cultural transmission. The finding implies that the more satisfied the visitor is with cultural experience, the higher identity and greater cultural impact on college students will be obtained and achieved. In other words, the cultural experience gained during the visit positively improved the recognition of cultural value, affected visitors’ emotions, and had an optimistic impact on promoting the cultural spirit of the museum. In this context, for students who visited the Tao Xingzhi Memorial Museum, the more unforgettable experiences they obtained, the higher the possibility that they improved their understanding of Tao’s philosophy of education and scientific research, contributing to cultural transmission.

Second, the parallel and sequential mediating effects were approved. An in-depth study of the relationships raised in the model considered the indirect effects. Cultural identity mediates the relationships between cultural experience and satisfaction and between cultural experience and transmission. Therefore, when visitors generate cultural experiences, they will be reflected in their understanding of specific cultural content in museums. This positive post-visit cognition can enhance student satisfaction and affect their willingness for recommendation. The findings align with those of Leri and Theodoridis (2019) and Meng (2022), who reported that participants were satisfied with their experience at the Henan Museum and through winery tourism. Third, the Chi-square analysis showed that liberal arts students were more interested in the historical and art museums than were science and engineering students. The results reflect the personalities and characteristics of students pursuing different majors. Liberal arts students consciously chose leisure activities more closely related to history and art.

Third, in the previous literature, researchers revealed that visitors’ cognitive, affective, and behavioral performances might vary based on their educational experience (Stylianou-Lambert, 2011); thus, for better systematic and comprehensive results, respondents should focus on museum visitors with various educational backgrounds (Etikan et al., 2016). This study mainly focused on college students’ demographics, unlike most other studies on museum tourism (Q. Zhou & Pu, 2022; Volkan Genç et al., 2023). The Chi-square analysis showed that liberal arts students were more interested in the historical and art museums than were science and engineering students. The results align with Li et al. (2020), whose research selected respondents pursuing different majors with different students’ personalities and characteristics. Liberal arts students consciously choose leisure activities more closely related to history and art.

Implications

Academic Contributions

The first contribution is a multi-dimensional, comprehensive model that can help evaluate the mechanism influencing college students’ cultural experiences and post-visit behaviors in the context of museum tourism. Although several studies have analyzed essential variables such as satisfaction and revisit intention in different subsets of tourism, cultural transmission has not been examined thus far. The closest concept is “perceived value” (Kim & Thapa, 2018, p. 374). It is essential for museum tourism researchers to focus on cultural experience, identity, and satisfaction as critical factors while developing a robust theoretical framework to understand museum visitors’ post-visit behaviors, especially college students. The second contribution centers on the performance of different variables. Consistent with previous studies (S.-N. Zhang et al., 2021), this study confirmed the positive relationships among cultural experience, identity, and transmission, and satisfaction. However, the findings show that not all variables improve visitors’ subsequent behavior equally after visiting the museum. The third contribution revolves around the analysis of mediating effects. The current study investigated new sequential relationships that were not empirically tested. Studies have referred to the relationship with satisfaction alone (Domínguez-Quintero et al., 2020).

Practical Implications

From a practical standpoint, this study provides significant managerial implications for cultural museum operators. Cultural experience plays a vital role in shaping the whole process of cultural transmission, including correlating and mediating relationships among cultural identity, satisfaction, revisit intention, and cultural transmission. Considerations should focus on how to display exhibits in cultural museums and positively promote museum visitors’ affective and emotional responses (Q. Zhou & Pu, 2022). Y. Zhang and Liu (2021) highlighted that museum visitors’ affective and emotional responses illustrate visitors’ agency in making and remaking cultural values and meaning.

Moreover, as the targeted respondents in this study are mostly university students born in a digitally rich world tagged as digital natives (Prensky, 2001), their immersion in digitally rich environments can enhance their experience at the museum. The digitization and use of immersive technologies in cultural attractions can render museums’ cultural offerings more accessible to wider audiences. Since visitors’ perceived experiences, directly and indirectly, influence behavioral intentions (recommendations, commitment, and revisit intentions) (Žabkar et al., 2010), museum operators should seek to meet visitors’ expectations by exploiting diverse forms of technology-driven innovations to enhance the understanding of their cultural content and visitors’ satisfaction level (Little et al., 2020). Combined with AR and VR, a well-designed mode of presenting cultural products or exhibits, including internal distribution or lighting, can stimulate and enhance tourists’ perceptions. Integrating AR and VR into a cultural exhibition can create additional value, enhance multifaceted museum visits, and attract new visitors (Trunfio et al., 2020).

Furthermore, to exert better social and educational functions, the practitioners and managers of museums should cooperate with educational institutions, such as colleges and universities, to create cultural products, as a museum can convey cultural and historical value to tourists by creating and selling cultural products. Inviting college students to get involved in everyday volunteer activities, such as museum docents, can enhance their connection with the museum’s cultural content and improve their comprehensive capabilities, such as communication skills.

Conclusion

This study defined the essential concepts, including cultural experience, identity, satisfaction, and cultural transmission in a museum tourism context by collating and summarizing the theory and reviewing the literature to create a solid conceptual background. In addition, this study explored the determinants and relationships of college students’ cultural experience and post-visit behaviors, particularly in revisit intention, recommending intention, and cultural transmission in the museum tourism background.

Generally, this research successfully achieved all study objectives. H1 was tested, and the results showed that cultural experience positively affects cultural identity. The better the cultural experience, the more fulfilled the cultural identity of the visitors. H2 was tested, and the results revealed that cultural experience positively affects visitors’ satisfaction. Consistent with findings from previous research (Jung & tom Dieck, 2017; Sheng & Chen, 2012), the tourists’ satisfaction level often depends on their previous experience. H3 was tested, and the results indicated that cultural experience positively affects museum visitors’ cultural transmission. This testing emphasized that when visitors return from a tourist destination to their usual residences, they spread the cultural knowledge gained from the travel experience via social networking to friends. After receiving this information, friends will relay the tourist’s word-of-mouth to others. This method allows the widespread dissemination of culture. H4 and H5 were tested, and the results illustrated that, as an antecedent variable, cultural identity positively affects satisfaction and cultural transmission. In other words, if tourists improve their understanding of and recognition of the museum’s cultural value, their affection level and cultural transmission behaviors will increase. Testing H6 revealed that satisfaction positively affects cultural transmission. Satisfaction is a vital antecedent variable for predicting cultural transmission. Testing H7 revealed that cultural identity and satisfaction mediated the effect of cultural experience on cultural transmission. The whole mechanism of cultural transmission and its antecedents go through cognitive, affective, and behavioral processes.

The predictive power has an R² value of 59% for cultural experience toward cultural transmission, followed by an R² value of 47% for cultural experience and identity toward satisfaction, and an R² value of 33% for cultural identity. Cultural identity and satisfaction are critical variables with partial mediating effects between cultural experience and transmission, and an indirect effect coefficient of 0.354. The sequential mediation effect was verified. A Chi-square analysis was applied, and the results showed that college students pursuing different majors preferred different types of museums. Statistically, liberal arts students were more interested in visiting historical and art museums than were science and engineering students. It offers an empirical investigation of a holistic model to evaluate the mechanism underlying the cultural transmission process. The paper proposes theoretical advances, has managerial implications for future improvements in museum management, and opens academic debate.

The continuous need for improvement is becoming imperative for cultural attractions and heritage sites, such as museums, to satisfy specific needs as museums possess rich cultural information. Thus, emotional and embodied experiences during the tours improve visitors’ cultural commitment and national pride.

Limitations and Future Research

First, as this study investigated participants in a college setting, the results cannot be easily generalized across other categories of museum visitors. Other visitors with different demographic backgrounds should be investigated to improve the generalizability of the findings of this study. Second, although the valid number of samples reached 100 for the minimum requirement suggested by J. Hair et al. (2009), there was still room for a survey with a larger number of participants, thus providing more convincing results. Finally, the model analyzing the relationships among four latent variables explained 59%, 47%, and 33% of cultural transmission, satisfaction, and cultural identity, respectively. This model did not fully capture the determinants of individual factors. Thus, there is still room to investigate more qualified factors. Further analysis can extend more determinants to obtain complete results.

Footnotes

Appendix

Appendix C.

Cross Loadings.

Construct items	CE	CI	SAT	CT
CE01	0.845
CE02	0.822
CE03	0.830
CE04	0.778
CI01		0.839
CI02		0.865
CI03		0.813
CI04		0.792
SAT01			0.776
SAT02			0.804
SAT03			0.761
SAT04			0.803
SAT05			0.770
CT01				0.797
CT02				0.793
CT03				0.794
CT04				0.839
CT05				0.795
CT06				0.786

Notes. CE = cultural experience; CI = cultural identity; SAT = satisfaction; CT = cultural transmission.

Declaration of Conflicting Interests

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

Funding

The author received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Jiyun Chen

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon request due to privacy restrictions.

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Factors Affecting Cultural Transmission in Museum Tourism: An Empirical Study with Mediation Analysis

Abstract

Keywords

Introduction

Literature Review and Research Hypotheses

Culture, Cultural Tourism, and Museum Tourism

Cultural Experience

Cultural Identity

Satisfaction

Cultural Transmission

Mediating Effects Between Cultural Experience and Transmission

Research Model

Research Methodology

Instrument Development

Data Collection

Research site

Respondents

Demographic Information

Procedure and Statistical Methods

Results

Descriptive Statistics

Preliminary Data Analysis

Chi-Square Analysis

Measurement Model

Reliability and Convergent Validity

Discriminant Validity

Common Method Variance (CMV) Testing

Structural Model

Goodness-of-Fit Analysis

Structural Model Analysis and Hypotheses Testing

Mediation Analysis

Discussion

Implications

Academic Contributions

Practical Implications

Conclusion

Limitations and Future Research

Footnotes

Appendix

Declaration of Conflicting Interests

Funding

ORCID iD

Data Availability Statement

References