Smart Experience and Green Health Tourism: The Moderating Role of Content Marketing

Abstract

The purpose of this research is to evaluate smart experience in green health tourism with the mediating role of content marketing by using the two models of technology acceptance and hedonism. This study utilizes quantitative and causal research methods. A total of 332 respondents completed a survey conducted at two Iranian tourism hubs. Also, purposeful sampling was used for data collection. Respondents rated their perceptions of each item on a five-point Likert scale. Using the partial least squares path modeling technique, the results reveal the direct effects of smart experience on green health tourism. The findings suggest that content marketing interacts with smart experience to influence green health tourism, such that the use of smart experience in health tourism can reduce the annual costs of developing environmental protection methods. This paper thus contributes to the hospitality management theory, green tourism, and wellness literature.

1. Introduction

Evolving consumer preferences [1,2], coupled with the enhancement in living standards [3], have played an important role in driving the growth of the hospitality sector, thereby contributing to health tourism. As competition is steadily growing within health tourism sectors, there has been increased emphasis on service innovation as a potent customer experience strategy. While the initial literature focused sporadically on how the emergence of the Internet has advanced the tourism industry [4,5], this has now become an emerging topic in smart hospitality [6], starting with an extension to sustainable health tourism. This, in turn, sheds light on the importance of consumer experience, and how the technology ecosystem can co-create smart experiences for consumers, ultimately driving medical tourism growth. Within this evolving ecosystem, the concept of “green health tourism” has gained prominence, thus becoming a trendsetter. Green health tourism refers to trust and satisfaction [7], cost–green quality inference, and green procurement [8]. And health tourism generally means choosing travel destinations based on health orientations and improving the standard of living [9].

With the promotion of environmental protection, an increasing number of tourists are interested in experiencing green tourism products. According to the 2018 Global Sustainable Travel Report, 87% of visitors prefer to use green and sustainable tourism products. Furthermore, 67% of tourists are willing to pay a 5% surcharge on green tourism products to minimize the impact on scenic areas [10]. Likewise, a survey conducted by MMGY Global (MMGY Global is an integrated marketing firm focused on the needs of the travel, hospitality, and entertainment industries) found that 32% of visitors are willing to pay 10% more for green tourism products to demonstrate their environmental responsibility [11,12].

Green health tourism, as implied by the term, encompasses aspects of sustainability and consumer experience within the servicescape [13]. While the former emphasizes the sustainable dimension of tourism practices, the latter advocates for the utilization of emerging technologies [14], illustrating the intersection of technology and tourism to deliver improved encounters, increased efficiency, and enjoyable experiences for consumers. This, in turn, speaks to the concept of smart experience, referring to the extent of the integration of technology for co-creating authentic experiences, facilitated by the exchange of resources [15]. Smart experience and its conceptualizations in the tourism domain point to dimensions such as psychological, socio-cultural, and educational elements, in addition to strategic management [16]. Smart tourism at its core combines infrastructure, consumer service encounters, information systems, and more importantly, the commercial environment. This is consistent with the literature on the intersection of the technology acceptance model, within which are functional factors, e.g., perceived ease of use and perceived value [17], and hedonic theory, within which are essential factors, e.g., emotional ones such as enjoyment and emotional involvement [18,19,20], which together influence one’s subjective experiences. The reason is that when tourists plan to choose green health tourism services, they care about not only the smartness of the technology itself but also how the experience itself involves smartness and hedonism, which may be driven by attitude, emotion, and intention factors.

While there has been a surge in smart tourism research in recent years, the elements that contribute to smart tourism experiences have not been thoroughly explored. The literature has examined a multitude of factors that intervene in such ecosystems, but the importance of technology and smart experience in green health tourism is still in its infant phase. Therefore, the first contribution investigates the relationship between the dimensions of smart experience and green health tourism. Additionally, the commercial environment aspect of smart tourism underscores the notion of consumer involvement [21], thereby speaking to the importance of marketing strategies, e.g., content marketing. Content marketing refers to fundamental attributes of digital content, including information recombination, accessibility, navigation interaction, speed, and essentially zero marginal cost [22], as well as “value is contextual”, interactivity, delivery and technology, inseparability and tangibility [23]. Yet, it remains unclear how content marketing strategies interact with smart experience to influence green health tourism. What is clear is that content marketing plays an important role in both creating and distributing consistent, personalized, relevant, and valuable content. In line with this logic, the nuanced literature suggests that green health tourism has evolved, taking on a different persona compared with what was initially envisaged. As such, it can be argued that content marketing intervenes in the relationship between smart experience and green health tourism. Thus, the second contribution in this article examines the relationship between the dimensions of smart experience and green health tourism with the moderating role of content marketing, which can affect the attraction of tourists in developing countries such as Iran, by using partial least squares structural equation modeling. We have chosen Iran as the context for our study due to its ranking as the lowest in the Medical Tourism Index. This highlights the crucial need to introduce a model of green health tourism to harness its uncovered potential. In particular, the purposes of this study are the following: (1) examine the relationship between smart experience (in terms of perceived ease of use, perceived value, enjoyment, and emotional involvement) and green health tourism; (2) examine the mediating role of content marketing (in terms of “value is contextual”, delivery and technology, inseparability, tangibility, accessibility, navigation, speed, marginal cost, interactivity, and information) between smart experience and green health tourism.

The study proceeds as follows: Section 2 provides an overview of the theoretical background and hypothesis development. Section 3 presents the research methodology. Section 4 presents the analysis and the results from the empirical data. Finally, Section 5, Section 6 and Section 7 bring together the discussion, implications, limitations, and recommendations for future research.

2. Theoretical Background and Hypothesis Development

Tourism development can enhance the quality of life and make traveling a source of well-being [24,25]. Pursuing novelty and quality tourism has turned into a new kind of life experience [26].

Today, smart technologies, as a key component of experience, play an outstanding role in tourism [27]. Acknowledging the potential of smart technologies, researchers predict that smart technologies for tourists will become more diverse [28]. Health tourism is a rapidly growing arena of tourism marketing, and it includes trips for individuals’ access to treatment services or medical interventions alongside ordinary tourism services [29]. A tourist destination is chosen according to its advantages. Smart marketing can create a mental image of the destination in the tourist’s mind via electronic tools and deal with the attraction of tourists [30]. The continuous development of information technology, together with the smart content of computing environments, has revolutionized the way we access and share information in our daily activities without any temporal or spatial constraints [31]. Accordingly, considering the importance that the tourism industry has in the development of every country and the necessity of sustainable development by paying attention to green tourism, the present study investigates the effects of the independent variables “perceived ease of use, enjoyment, perceived value, and emotional involvement” on the dependent variable “green health tourism”.

According to the literature review, the present study examines the relationship between smart experience and green health tourism, with an emphasis on the moderating role of content marketing. Smart experience is defined by variables such as “perceived ease of use”, “perceived value”, “enjoyment”, and “emotional involvement”. For this purpose, the theories of hedonism and technology acceptance are utilized in this research.

2.1. Smart Experience and Tourism

Design solutions to enhance consumer experience have long been used by famous brands, e.g., Airbnb, Booking, and Trip Advisor. Such brands often take into consideration the relevant theories dominating the field. Most notably, leading brands leverage the technology acceptance model and hedonic theory. By using the latest smart technologies in service contexts like hospitality and tourism [32] and retail [33], businesses can create an unforgettable customer experience. This means that customers, especially when buying goods, are not in direct physical contact with the provider [34]. It is also essential to protect customer information [35]. The term “smart” refers to the capability of increasing speed, flexibility, precise perception, and resolving problems. In English, it is synonymous to wisdom (knowledge and cognizance), meaning the quality of experience, knowledge, and possession of the ability of judging and sagacity [36]. “Smart” characterizes technological and socio-economic improvement due to the rapid development of information, communication, and related technologies [37].

Ref. [30] states that virtual experience is the experience in the virtual environment using a computer-mediated environment and is based upon the concept of telepresence or the extent to which consumers feel their existence in the virtual space [38]. Herewith, it is worth noting that the terms virtual experience and telepresence are now used interchangeably in the literature. For example, ref. [39] defines telepresence as the experience of presence in an environment by means of a communication medium or an illusion of being there in a mediated environment [40]. In the same way, ref. [41] contends that presence is often understood as a type of experience of being there, one loosely involving some technological mediation and often depending on virtual environments. Consequently, virtual experiences created by environmental simulations such as sketches, photographs, and videos are considered important in the successful creation and communication of an image of a destination [42]. In fact, information technology development has made it possible to provide consumers with more real-life experiences through environmental simulations [43]. With the advent of the Internet and virtual reality systems, tourists can actively become virtual participants and truly choose what they want to “experience” in order to better evaluate their destination.

Virtual tourism experience can influence destination choice in tourism. According to [44], 65% of the tourists search for their destination in the virtual space before taking the trip and 69% set out a definite plan for their destination through online and virtual investigation of the trip [45]. Virtual tourism can become an entertaining activity to provide people with an immersive experience without being them physically at the destination. Based on a survey conducted by [46,47], about 90% of the participants preferred to continue using virtual tourism even after the pandemic is over. Their main reasons are getting familiar with the destination in advance, planning trips earlier, visiting places they cannot visit due to certain restrictions (such as time, financial constraints, distance, accessibility, etc.), experiencing new technologies, and being entertained by using virtual tourism as a recreational activity.

Virtual tourism, as a promising tourism product, can offer an immersive experience to potential visitors. It can also provide them with a “try-before-you-buy” experience and a destination sneak preview [46]. Some studies have investigated the factors affecting the experience of smart tourism [27,45]. For example, ref. [48] focused on how travelers perceive smart tourism experiences, highlighting trust, security, independence, and commitment as key subjective factors. They also emphasized the importance of considering the emotional state in studies of smart tourism experiences. Ref. [49] examined the hedonic motivation adoption frameworks of virtual reality (VR) tourism, discovering that enjoyment significantly influences subjective wellbeing. Consistent with the review of the literature and based on the technology acceptance model and hedonic theory, the variables used in this study include perceived ease of use [50,51,52], perceived value (PV) [53], enjoyment [51], and emotional involvement [51,52]. The model and its components are depicted below (Figure 1).

2.2. The Effect of Smart Experience on Green Health Tourism

Tourists mostly make decisions about whether to visit a particular destination and weigh its advantages under uncertain conditions. One of these uncertainties in tourists’ decision making is the absence of objective scales by which a certain destination can be evaluated. To bridge this gap, tourists find themselves in the position of having to experimentally gain knowledge about a destination’s features and attributes. Marketers, traditionally, have used mass media channels to design and convey a mental image of a destination to tourists. However, with the advent of the Internet and the proliferation of smart technologies, the most effective method for creating this mental image now involves tourists virtually exploring the destination themselves [54]. New smart surfaces are able to transform this industry from static and passive to dynamic, active, and almost alive [55]. Also, this can help to provide information to tourists [56]. Previous research indicates that smart tourist destinations foster an environment conducive to the socio-economic sustainability of smart tourism experiences [48]. Additionally, the application of 3D visualization has been found beneficial in the planning of sustainable tourism [57]. Building on this, formally, we predict the following:

H1: 

Smart experience is positively related to green health tourism.

2.2.1. Perceived Ease of Use (PEU)

Digital technologies are fundamentally reshaping the landscape of marketing strategies and, in particular, creating global tourism [11]. In this context, the concept of perceived ease of use plays a pivotal role. The perceived ease of use refers to the degree to which the individuals think they can use technology easily and without a lot of struggles, along with an increase in their performance and efficiency [58]. The behavioral patterns exhibited by passengers and travelers are instrumental in shaping their engagement with the tourism industry. The personality characteristics influence the behavioral patterns and preferences of passengers and travelers by transferring a sense of continuity in the individuals [31]. Prior studies have shown that the perceived ease of use exerts a positive effect on the users’ attitudes and their perception of the usefulness of system use [50,59]. Perceived ease of use implies that an individual considers a VR device more valuable when the operational complexity is low [60]. According to [60], tourists may adopt VR as an alternative to travel. The prevalent application of VR in the tourism industry aims to enrich the experiences related to tourist sites and attractions. Additionally, VR contributes to the improved accessibility of tourist destinations. Building on this, formally, we predict the following:

H1a: 

Perceived ease of use is positively related to green health tourism.

2.2.2. Perceived Value (PV)

Perceived value stands out as a pivotal factor in understanding customer behaviors within technology and tourism contexts. The perceived priority of customers for the evaluation of properties, performances, and results is the result of the consumption and applications of the intended goods [61]. The perceived value of a tourist destination refers to the process by which the tourist engages in comprehending, selecting, organizing, and interpreting the information based on various experiences for the creation of a meaningful image of the value of a destination’s experience [62].

Perceived value, which currently enjoys a significant position in marketing research, stems from the importance given by today’s business entities to the creation of value for the customers. The creation and transfer of value to the tourist have become a first-degree competitive advantage in regions that enjoy a larger deal of competition following globalization [53]. The perceived value of experience has also been mentioned and examined in different tourism contexts, such as hospitality [63], heritage tourism [64], timeshare [65], cruise experiences [66], dining experiences [67], golf tourism [68], and adventure tourism [69].

Researchers have studied and examined the value structure in the marketing context [70] and in the tourism context [65,69]. Ref. [70] emphasizes the relevance of “personal perception of benefits derived from a customer’s association with an organization’s offering”. Virtual experience in the tourism context can have an impact on the customers’ image of the destination, perceived value, destination attachment, and various elements of attitudinal loyalty [52]. In sum, we argue that perceived value plays a positive role in shaping the adoption of green health tourism practices, highlighting the importance of perceived value in promoting sustainable and environmentally conscious tourism behaviors. According to the empirical evidence and the discussion above, the following hypothesis is proposed:

H1b: 

Perceived value (PV) is positively related to green health tourism.

2.2.3. Enjoyment (En)

Enjoyment, as an element of hedonic theory, plays a crucial role in shaping consumer behaviors and preferences within the context of tourism. It has been made clear in research that users’ experiences in the virtual world, as well as their perception of the outside environment regarding the system application, significantly influence their enjoyment of such environments. According to hedonic theory, consumers are driven by their desire to seek pleasurable experiences, thus reducing discomfort. Within the framework of tourism and in line with our conceptual model, enjoyment is a fundamental aspect that gives rise to travelers’ overall satisfaction and engagement significantly. Virtual environments and learning in this type of environment generate increased motivation for attending this world in users [51]. In their examination of competition in the health tourism market, ref. [71] dealt with the investigation of passengers’ experience. In the above research, they also assessed the intermediary variable “satisfaction” and concluded that the relationship of the quality of satisfaction is stronger than the other alternatives in this framework. Based on the empirical evidence and the discussion above, the following hypothesis is proposed:

H1c: 

Enjoyment (En) is positively related to green health tourism.

2.2.4. Emotional Involvement (EI)

Emotional engagement, as described by [72], plays an important role in the development of consumers’ positive valence emotional engagement capacity and behavioral activity during or related to focal consumer/brand interactions. Recalling emotional responses is one of the important advertisement strategies for getting customers engaged. This stimulation emphasizes personal properties in its influencing of emotions and arouses tourists’ feelings and emotions to attract them towards the intended destination [36]. This indicator is cognitive, psychological, and motivational, as well as a propelling engine and an emotional experience [73]. In their investigation of the customers’ experience and its effect on their loyalty to the use of spa hotels, ref. [74] concluded that individuals’ internal conditions and customers’ experience exert a positive effect on customers’ loyalty, disregarding their stay duration. In an investigation on tourists’ emotional and cognitive response to the servicescape and credibility, ref. [75] expressed that services and credibility are among the effective backgrounds in customers’ mental images and feeling of pleasure.

The primary results of virtual tourism experience are connected to the tourist’s emotional reactions, attitudes, and behavioral intentions. Laboratory experiments conducted by [76] on groups of tourists exposed to virtual scenarios, using traditional screens and head-mounted displays, showed different electrodermal activity and heart rate responses conventionally associated with emotional arousal. In a similar heart rate experiment [77], it was demonstrated that the properties of virtual reality can induce strong memories. Others pointed to emotional involvement as an outcome [51,78] or revealed specific emotions, such as enjoyment [79]. We argue that the emotional involvement of individuals in virtual tourism experiences positively influences the adoption of green health tourism practices. Emotional involvement mirrors the strong emotional connections shaped during these experiences, which in turn drive individuals to engage in sustainable and eco-friendly tourism behaviors. Building on this, formally, we predict the following:

H1d: 

Emotional involvement (EI) is positively related to green health tourism.

2.3. Moderating Roles of Content Marketing

The term “content” originally has its roots in publishing, where words, images, and motion graphics must be sufficiently captivating to compel the target audience to engage with the publishing platform, be it a newspaper, magazine, TV, or radio channel [80]. While these definitions provide a general understanding of content, either in a traditional or digital context, the concept of “content marketing” is still evolving as a viable online marketing strategy. Therefore, various definitions of this term need exploration. The authors of [81] were among the first to propose a definition for content marketing, defining it as “the creation and distribution of educational and/or compelling content in multiple formats to attract and/or retain customers”. Subsequently, ref. [82] suggested that content marketing is a strategy focused on creating a valuable experience. Content marketing has been an integral part of the digital marketing strategies employed by companies operating online for many years [83]. Key characteristics of digital content in content marketing include information recombination, accessibility, navigation interaction, speed, and essentially zero marginal cost [22]. Additionally, value in content marketing is contextual and influenced by factors such as interactivity, delivery and technology, inseparability, and tangibility [23]. Digital content conceptualization is carried out through electronic distribution channels [22]. Considering the influence of digital technologies on today’s life, studies emphasize the connection between technology and tourism [84]. Additionally, this method can help tourists select their destinations [85]. Digital content marketing involves creating and disseminating content in digital and intelligent formats. Smart content marketing represents a fusion of conventional and digital channels. It revolves around understanding the needs of customers, a comprehension achievable through active involvement in the supply chain and, ultimately, through institutions that engage with customers [23].

In an investigation of the properties of gastro-tourists’ memorable experiences, ref. [86] mentioned seven relevant attributes that influence the booming of the tourism sector and stimulation of tourists’ emotions for the selection of the destination. These seven features are tourist, intentional and random destination tourism, trip stages, foodstuff risk during the travels, touristic relations and common and interdependent host, originality, sociability, and emotions. In their investigation of online communication with prospective medical tourists, ref. [87] concluded that communication through online instruments in hospitals differs according to their managers’ needs. In a research study called “Searching for the Experiences”, ref. [30] engaged in the investigation of web-based virtual tours for tourism marketing and finally stated that tourism organizations can use web-based virtual tours to better offer their tourist destinations on the market. This forms the basis for the following hypothesis:

H2: 

Content marketing influences the relationship between smart experience and green health tourism.

3. Method

This study utilizes quantitative and causal research methods. It involves hypotheses and theories that examine the causal relationship between predictors and criterion variables. To investigate the relationship between smart experience and green health tourism with the mediating role of content marketing, the positivist perspective is used. In the view of positivism, it is assumed that there is a kind of intelligible reality that can be understood through the understanding and identification of mechanisms and immutable natural laws. The chosen approach for this purpose is deduction. In this context, data collection and validation are conducted based on a predefined model. The study adopts a cross-sectional approach, gathering data over a single period of time.

3.1. Sampling and Data Collection

Data were collected from health tourism, and tourism and green marketing area activists from Iran, most of which were members of the Iran Health Tourism Cluster. We selected two Iranian tourism hubs, defined as the places that receive the most treatment tourist and have treatment areas for health tourists. Tehran, with the most equipped medical-tourist centers, and Sistan-Baluchestan, with hot springs, sand therapy, and an ophthalmology hub, in the southeast of Iran were selected. These destinations were chosen because there have been recognized in Iran strategic documents as cities with significant potentials for the development of all health tourism segments. Since the number of health tourism, and tourism and green marketing area activists and entrepreneurs was clear beforehand, purposeful sampling was used for data collection. Thirty different treatment and health visitor attraction centers in two places were involved in the study. In this research, we tried to question all members of the sample. An online survey was designed to collect information about the role of smart experience in green health tourism. The data provided relevant information about this relationship and how content marketing moderates this relationship.

When developing the questionnaire, we ensured that no items were industry-sensitive. Following [88], to assess the quality of responses and minimize measurement errors, an item asking how confident the respondent felt regarding their responses was included in the questionnaire. Six respondents who indicated a very low level of confidence (<6) were excluded. The average level of confidence was 5.82 (sd = 0.805). Following [89,90], we tested nonresponse bias by comparing early and late responses across all variables. We also compared online and mail responses. There were no significant variances. Data collection lasted an entire month. Out of the 440 questionnaires distributed, 322 completed questionnaires were approved and analyzed. This number is approximately 73.2 percent (

Table 1. Demographic profile of respondents.

	Gender		Age			Job Experience			Job
	Frequency	Percent		Frequency	Percent		Frequency	Percent		Frequency	Percent
Men	258	80.1	20–30	92	28.6	5–15	38	11.8	Tourism	106	32.9
Women	64	19.9	30–40	105	32.6	15–25	164	51	Health	77	23.9
Total	322	100.0	40–50	101	31.4	25–35	97	30.1	Marketing	100	31.1
			upper 50	24	7.5	35-more	23	7.1	Teacher	39	12.1
			Total	322	100.0	Total	322	100	Total	322	100

).

3.2. Construct Measures

This research adopted multi-measurement items for each construct to overcome measurement errors associated with single items [91,92]. Drawing on previous research, the reliability and validity of the scales were established. The smart experience variable was operationalized with four constructs suggested by previous research [23,60,64,78,79]. These constructs include “perceived ease of use”, “perceived value”, “enjoyment” and “emotional involvement”. The green health tourism variable was operationalized with four constructs from previous research [7,8]. These constructs include “trust”, “satisfaction”, “inference”, and “procurement”. The content marketing variable was operationalized with ten constructs based on past research [22,23]. These constructs include “value is contextual”, “delivery and technology”, “inseparability”, “tangibility”, “accessibility”, “navigation”, “speed”, “marginal cost”, “interactivity”, and “information”. Respondents rated their perceptions of each item on a 5-point Likert scale ranging from “strongly disagree” to “strongly agree” (1 to 5) [93].

3.3. Analysis Procedure

To assess the relationship between the dependent and independent variables, as well as the extent of the moderating variables’ effect, we used structural equation modeling (SEM) with the partial least squares approach. To assess the causal relations, partial least squares is a very appropriate approach. PLS-SEM using SmartPLS 3.5 provides effective and better results in explanation- and estimation-oriented models and effective data analysis of ordinal and interval scales. On the other hand, the main goal of the partial least squares (PLS) method is to predict indicators by expanding components”.

4. Results

In order to investigate the measurement model’s fit, three scales, namely, content validity, convergent validity, and divergent validity, were employed. Content validity was investigated by several university professors and subsequently confirmed.

Outer loadings (λ) demonstrate the correlation between the latent and observed variables of the model (

Table 2. Measurement model (outer loadings (λ)).

Items		λ
	Green Health Tourism
GHT1	With smart experience, I can trust the healing process through green health tourism at that destination.	0.721
GHT2	This destination has managed to gain my trust.	0.769
GHT3	I am satisfied with my decision to undergo treatment through green health tourism in Iran.	0.705
GHT4	My feelings about the treatment methods and tourism in Iran are positive.	0.714
GHT5	I am content with the management of programs in health tourism in Iran.	0.639
GHT6	The conclusion I draw from the green cost affects my choice.	0.641
GHT7	The conclusion I draw from the green quality significantly impacts my destination choice.	0.735
GHT8	The green sourcing of raw materials has a meaningful effect on the choice of a destination labeled as health tourism.	0.751
GHT9	Green provisioning can influence the smart experience of tourism.	0.748
PEU	Perceived Ease of Use in Smart Experience
EA1	Smart experience significantly affects my perceived ease of use.	0.965
EA2	Smart experience can enhance my understanding of ease of use.	0.962
PV	Perceived Value in Smart Experience
U1	Using smart experience increases my perceived value of the destination.	0.951
U2	My understanding of the value of health tourism is enhanced through smart experience and observation.	0.937
En	Enjoyment in Smart Experience
En2	Smart experience increases my enjoyment of health tourism, making it a more fulfilling experience.	0.945
Po	Smart experience enhances long-term enjoyment and the inclination for repeated pleasure.	0.945
EI	Emotional Involvement in Smart Experience
EM1	I feel like a part of the virtual environment during the smart experience.	0.928
Em2	I feel influenced by the virtual environment.	0.896
	Value is Contextual in Content Marketing
C1	For me, the content of smart experience advertising tailored to a specific field is more important.	0.976
M1	Providing value in advertising content is very important to me.	0.977
	Interactivity in Content Marketing
C2	The interaction of information in smart tourism affects me significantly.	0.963
M2	The interaction of information drives me to learn and be more interested.	0.963
	Delivery and Technology in Content Marketing
C3	Fast and high-quality delivery of information in the smart experience encourages me to choose tourism services.	0.963
M3	Utilizing new technologies in the smart experience motivates me to opt for tourism services.	0.962
	Inseparability in Content Marketing
C4	The inseparability of content in the smart experience significantly influences my choice of health tourism.	0.939
M4	The integration of content in the smart experience significantly influences my choice of health tourism.	0.945
	Tangibility in Content Marketing
C5	The tangibility of health tourism reality in the smart experience affects my choice.	0.952
M5	Touching a part of the smart experience tools in health tourism affects my choice.	0.928
	Accessibility in Content Marketing
C6	Access to smart experience considering the presented content significantly influences my choice.	0.971
M6		0.971
	Navigation in Content Marketing
C7	The level of guidance in the content presented in smart experience advertising affects my choice of green health tourism.	0.975
M7	The accessibility of smart content about health tourism affects my choice.	0.972
	Speed in Content Marketing
C8	The speed of service delivery from presented smart experience advertising significantly affects me.	0.955
M8	The timely awareness from presented smart experience advertising significantly affects me.	0.951
	Marginal Cost in Content Marketing
C9	Marginal costs have a significant impact on my choice to use smart experience for tourism.	0.934
M9	Cost and time to access relevant content have a significant impact on my choice to use smart experience for tourism.	0.908
	Information in Content Marketing
C10	Adequate information in the introduction of health tourism through smart experience significantly influences my choice.	0.956
M10	The simplicity and comprehensibility of the content of the smart experience of health tourism significantly influence my choice.	0.933

). These outer loadings determine the extent to which the latent variable elaborates the variance in the observed variables. Since external loadings represent correlations, outer loadings have to be significant statistically. If the factor load is below 0.3, the relationship is deemed weak and hence ignored. Factor loads between 0.3 and 0.6 are acceptable. Factor loads above 0.6 are indicative of very favorable differences.

4.1. Assessing the Quality of the Structural (Internal) Model

The quality of an internal or structural model refers to the independent variables’ ability to predict the dependent variable. In this regard, use was made of construct cross-validated redundancy or the Stone–Geiser Scale, based on which the model should be able to predict the endogenous latent variables’ indicators. In this method, a part of the data are eliminated from a given block of indicators during the estimation of the parameters, and efforts are subsequently made to use the estimated parameters for estimating the eliminated part. This process is continued until the elimination of all the data points and the re-estimation of the parameters. This coefficient’s positive value confirms the good reconstruction of the observed values and the proper quality of the structural model. The sum of squares of observation for block (SSO) and the sum of squared prediction errors for block (SSE) were also two of the applied methods. Q² was also used to specify the model’s power of the dependent variables’ prediction. Models with acceptable goodness-of-fit in the structural part should have the ability to predict the related indices to the model’s endogenous constructs. That is because the constructs would have the ability to sufficiently influence one another’s indices in case the relations are correctly defined in a model following which the hypotheses can be correctly approved. Low, intermediate, and strong values for this index are 0.2, 0.15, and 0.35, all of which are based on

Table 3. Model’s internal quality.

Variables	SSO	SSE	Q2
Accessibility	644.000	251.864	0.609
CM	6440.000	3721.866	0.422
Value is contextual	644.000	238.660	0.629
Delivery and technology	644.000	270.746	0.580
EI	644.000	383.198	0.405
En	644.000	311.625	0.516
GHT	2898.000	1813.982	0.374
Information	644.000	312.909	0.514
Inseparability	644.000	317.183	0.507
Interactivity	644.000	269.776	0.581
MCM	322.000		1.000
Navigation	644.000	246.770	0.617
PEU	644.000	268.660	0.583
PV	644.000	313.374	0.513
SE	2576.000	1614.669	0.373
Speed	644.000	292.526	0.546
Tangibility	644.000	321.054	0.501
Marginal cost	644.000	364.100	0.435

Note. CM: content marketing; EI: emotional involvement; En: enjoyment; GHT: green health tourism; MCM: moderating role of content marketing; PEU: perceived ease of use; PV: perceived value; SE: smart experience.

below.

4.2. Evaluation of the Hypotheses’ External Model

For the evaluation of the external model, use was made of two scales, namely, composite reliability and extracted variance mean. The superiority of composite reliability (CR), or Dillon–Goldstein coefficient, to Cronbach’s alpha coefficient lies in the fact that the constructs’ reliability is calculated not in an absolute form but according to their correlation. Moreover, to calculate CR, the indices with larger factor loads are more important. The amount confirmed for this index, furthermore, should be larger than/equal to 0.7. Cronbach’s alpha coefficient indicates the reliability or internal consistency of the items and the model. This value, which is obtained based on the items’ internal correlation, should be larger than or equal to 0.7 for confirmation. The other scale is the extracted variance mean, or convergent validity (AVE), which indicates the extent to which every construct is correlated with its indices. Ref. [94] believe that convergent validity exists when AVE is larger than 0.5; the CR scale, furthermore, is confirmed when being larger than 0.7. As is observed in the following table, convergent validity was confirmed for all of the variables (

Table 4. Convergent validity.

Variables	Alpha	rho_A	CR	AVE
Accessibility	0.939	0.939	0.97	0.942
Content marketing	0.946	0.95	0.952	0.501
Value is contextual	0.952	0.952	0.976	0.954
Delivery and technology	0.92	0.92	0.962	0.926
EI	0.8	0.816	0.908	0.832
En	0.879	0.879	0.943	0.892
Green health tourism	0.881	0.888	0.904	0.511
Information	0.88	0.908	0.943	0.892
Inseparability	0.873	0.874	0.94	0.887
Interactivity	0.922	0.922	0.962	0.927
Moderating role of content marketing	1.000	1.000	1.000	1.000
Navigation	0.944	0.946	0.973	0.947
PEU	0.923	0.924	0.963	0.929
PV	0.878	0.887	0.942	0.891
SE	0.867	0.874	0.896	0.519
Speed	0.898	0.899	0.952	0.908
Tangibility	0.87	0.894	0.939	0.884
Marginal cost	0.822	0.837	0.918	0.848

).

4.3. Reliability and Validity

The heterotrait–monotrait ratio, or HTMT index, was proposed by [95] for the evaluation of divergent validity. The HTMT scale replaced with the older method presented by Fornell and Larker. Ref. [95] showed that neither the Fornell–Larcker criterion nor the assessment of the cross-loadings allows users of variance-based SEM to determine the discriminant validity of their measures. Further, as a solution to this critical issue, they proposed the heterotrait–monotrait ratio of correlations (HTMT) as a new approach to assessing discriminant validity in variance-based SEM (

Table 5. Discriminant validity.

	Access.	CM	VC	Deli.	EI	En	GHT	Info.	Insep.	Inter.	MCM	Navi.	PEU	PV	SE	Speed	Tang.
Access.
CM	0.867
VC	0.546	0.789
Deli.	0.524	0.799	0.719
EI	0.065	0.25	0.034	0.167
En	0.255	0.438	0.128	0.313	0.533
GHT	0.431	0.545	0.371	0.476	0.238	0.532
Info.	0.638	0.752	0.484	0.424	0.199	0.369	0.418
Insep.	0.426	0.655	0.322	0.453	0.442	0.817	0.554	0.445
Inter.	0.676	0.846	0.681	0.709	0.116	0.268	0.497	0.452	0.473
MCM	0.396	0.437	0.355	0.22	0.232	0.16	0.142	0.354	0.185	0.286
Navi.	0.830	0.862	0.489	0.514	0.096	0.319	0.383	0.578	0.453	0.632	0.392
PEU	0.242	0.37	0.084	0.258	0.466	0.496	0.400	0.332	0.431	0.284	0.372	0.285
PV	0.335	0.325	0.148	0.156	0.477	0.528	0.325	0.397	0.361	0.092	0.239	0.327	0.565
SE	0.299	0.457	0.131	0.295	0.876	0.885	0.494	0.429	0.673	0.253	0.331	0.341	0.867	0.892
Speed	0.440	0.73	0.413	0.529	0.537	0.399	0.281	0.471	0.489	0.456	0.293	0.522	0.384	0.319	0.534
Tang.	0.797	0.837	0.577	0.475	0.198	0.173	0.328	0.514	0.309	0.64	0.481	0.744	0.346	0.208	0.306	0.557
MC	0.566	0.82	0.639	0.56	0.05	0.285	0.365	0.538	0.441	0.539	0.326	0.658	0.15	0.105	0.196	0.525	0.538

Note. Access.: accessibility; CM: content marketing; VC: value is contextual; Deli.: delivery; EI: emotional involvement; En: enjoyment; GHT: green health tourism; Info.: information; inseparability; Inter.: interactivity; MCM: moderating role of content marketing; Navi.: navigation; PEU: perceived ease of use; PV: perceived value; SE: smart experience; Tang.: tangibility; MC: marginal cost.

).

If the values of this scale are lower than 0.9, divergent validity would be acceptable. All of the values were below 0.9, as shown in

Table 6. Divergent validity.

	Access.	CM	VC	Deli.	EI	En	GHT	Info.	Insep.	Inter.	MCM	Navi.	PEU	PV	SE	Speed	Tang.	MC
Access.	0.971
CM	0.827	0.708
VC	0.517	0.754	0.977
Deli.	0.487	0.749	0.673	0.962
EI	0.057	0.204	0.028	0.144	0.912
En	0.232	0.388	0.117	0.281	0.455	0.945
GHT	0.402	0.513	0.350	0.439	0.195	0.495	0.715
Info.	0.585	0.685	0.448	0.386	0.17	0.327	0.383	0.944
Insep.	0.386	0.583	0.293	0.406	0.376	0.715	0.508	0.395	0.942
Inter.	0.629	0.801	0.638	0.653	0.103	0.242	0.454	0.415	0.425	0.963
MCM	−0.383	−0.424	−0.346	−0.211	−0.207	−0.15	−0.141	−0.333	−0.172	−0.275	1.000
Navi.	0.782	0.822	0.464	0.480	0.085	0.291	0.364	0.533	0.412	0.59	−0.381	0.973
PEU	0.224	0.338	0.078	0.239	0.401	0.447	0.363	0.301	0.386	0.261	−0.357	0.266	0.964
PV	0.305	0.257	−0.132	0.145	0.405	0.467	0.293	0.349	0.322	0.087	−0.226	0.300	0.512	0.944
SE	0.277	0.397	0.035	0.272	0.699	0.791	0.455	0.382	0.599	0.235	−0.308	0.319	0.786	0.78	0.721
Speed	0.404	0.657	0.382	0.481	0.459	0.355	0.268	0.426	0.433	0.415	−0.278	0.481	0.35	0.286	0.465	0.953
Tang.	0.726	0.769	0.533	0.432	0.167	0.154	0.303	0.458	0.275	0.581	−0.450	0.679	0.309	0.184	0.268	0.495	0.94
MC	0.500	0.720	0.570	0.491	0.022	0.245	0.323	0.466	0.378	0.471	−0.300	0.584	0.132	0.094	0.173	0.454	0.462	0.921

below.

Based on an evaluation of the theoretical model, the result of path coefficient estimation (

Table 7. Path coefficients and significance.

Path	Path Coefficient	Standard Deviation	T-Statistic	p-Value	Results
Accessibility → content marketing	0.154	0.006	25.54	0.000	Supported
Content marketing → green health tourism	0.449	0.058	7.45	0.000	Supported
Value is contextual → content marketing	0.141	0.006	23.35	0.000	Supported
Delivery and technology → content marketing	0.143	0.006	24.36	0.000	Supported
Emotional involvement → smart experience	0.260	0.018	15.21	0.000	Supported
Enjoyment → smart experience	0.364	0.017	21.11	0.000	Supported
Information → content marketing	0.124	0.007	17.56	0.000	Supported
Inseparability → content marketing	0.119	0.006	18.82	0.000	Supported
Interactivity → content marketing	0.152	0.007	21.54	0.000	Supported
Content marketing → green health tourism	0.111	0.042	7.45	0.009	Supported
Navigation → content marketing	0.151	0.006	25.67	0.000	Supported
Perceived ease of use → smart experience	0.353	0.015	24.42	0.000	Supported
Perceived value → smart experience	0.324	0.012	26.51	0.000	Supported
Smart experience → green health tourism	0.322	0.051	6.41	0.000	Supported
Speed → content marketing	0.114	0.006	18.66	0.000	Supported
Tangibility → content marketing	0.129	0.005	23.73	0.000	Supported
Marginal cost → content marketing	0.118	0.006	18.41	0.000	Supported

) was determined. The path coefficient (β), moreover, shows the intensity and type of relationship between two latent variables. It is a number between −1 and +1, and values equal to zero are reflective of the absence of linear relationships between the two latent variables. This coefficient indicates the correlation between two latent variables. In order to investigate the study’s hypotheses, use was made of the t-statistic. At the 95% confidence level, if the value of the t-statistic is larger than 1.96 and the significance level is below 0.05, the hypothesis is confirmed. At the 95% confidence level, considering the results in Table 5, since the t-statistic was larger than 1.96, the significance level of the factor load was assessed according to the p-value and t-value. The p-value indicates the value of the allowed error for the acceptance of the results’ credibility. This value should be smaller than/equal to 0.05 at the 0.95 level for all the variables to be confirmed. In addition, all of hypotheses were supported. Also, the column chart of path coefficient distribution for content marketing to the green health tourism and for moderating role of content marketing to green health tourism is presented in Figure 2. The structural model and hypotheses were assessed (Figure 3).

4.4. Explained Variance Scale

Explained variance indicates the percentage to which the dependent variables’ changes are elaborated by the independent variables. R² coefficients pertain to the endogenous latent (dependent) variables of the model and indicate the effect of an exogenous variable on an endogenous variable; the three values of 0.19, 0.33, and 0.67 are considered as the standard values designating weak, intermediate, and strong values, respectively. The larger the amount of R² about the endogenous constructs of a model, the more it is indicative of the model’s better goodness-of-fit. The obtained value expressive of the dependent variable’s explanation is 0.336 for green health tourism, which is an upper-intermediate value (

Table 8. Explained variance.

	R-Squared
Green health tourism	0.336

).

5. Discussion

The present study investigated the relationship of smart experience and green health tourism with the presence and effectiveness of the content marketing variable with the role of moderator. In the previous sections, the reasons for the importance of health tourism were stated, and by examining the smart experience factor, an attempt was made to examine the relationship between them. This research presented a model based on which content marketing can be used to create an effective smart experience, since content marketing can improve the impact of perceived value, perceived ease of use, enjoyment, and emotional involvement on health tourism. In this section, the results obtained are discussed.

The results from PLS–SEM reveal that smart experience is positively linked to green health tourism, which supports H1. Smart experience can have an impact on the development of green health tourism by influencing the experience of tourists. Ref. [30] confirmed the effect of virtual tours on the selection of a tourist destination. Although numerous studies have been conducted on health tourism [96,97] and green tourism [12], studies on green health tourism have not reached maturity. On the other hand, the destruction caused by health tourists resulted in considering green health tourism in this research.

The findings of this research show that firstly, regarding smart experience in green health tourism, the perceived ease of use can influence the conscious choice of tourist destinations, which supports H1a. The findings of [53,54] are consistent with this result. Therefore, in smart experience, individuals’ mentality can be guided towards a positive direction through the use of the designed virtual space so as to influence the selection of their destinations to a large extent. The perceived ease of use of smart experience and virtual world within the framework of trips and tourism is a result that is consistent with what [51] found.

The perceived value of smart experience is one of the concepts that can greatly reduce costs, time, and energy and can create the experience of recognizing the destination for the tourist, which supports H1b. The study of [53] confirms this finding. Moreover, with regard to smart experience, we can refer to research by [33] on customer experience and the impact of smart technology, whose results lead to understanding the factors of customer dynamics and customer experience when using smart technologies.

Enjoyment can influence the conscious choice of tourist destinations, which supports H1c. The study of [71] confirms this finding. The experience that the tourist gains in the smart experience can influence the tourist to choose the destination, repeat its use, and recommendation it to others. Enjoyment is a psychological factor that plays a pivotal role in shaping smart experiences.

Emotional involvement is positively linked with green health tourism, which supports H1d. Although studies confirmed the direct effect of emotional involvement on digital marketing content [98], in this study, it is one of the components of smart experience that can affect the growth of green health tourism, especially through the mediation of content marketing.

In the end, smart experience can affect the customer’s experience when choosing a tourist destination, especially in the health sector concerning the environment, which supports H2. On this basis, ref. [99] confirmed the effect of content on the reviewing of relevant materials and contents. Smart experience can not only contribute to the recognition of the intended destination and its relatively exact properties by the health tourists, as well as to the development of the health tourism industry, but it can also help tourists and others better treat nature via the codification of content marketing strategies. It can be said that the review of the content that is in the smart experience section is performed by content marketing. Content marketing, by providing the right content at the right time and right place of smart experience, can lead to customer experience and repeat experience.

6. Implications

6.1. Theoretical Implications

Content marketing is a crucial strategy in the realm of marketing. In this study, an analytical framework has been developed through the lens of hedonic theory. The analysis delves into various dimensions of content marketing while incorporating the concept of smart experience. The research posits that content marketing plays a moderating role and explores the potential of smart experience in facilitating the diffusion of green health tourism. The structural equation modeling analysis reveals that smart experience contributes to the promotion of green health tourism, primarily through positive content marketing. The application of hedonic theory serves to comprehend how smart experience influences green health tourism, offering a fresh perspective on the role of content marketing in this context. The study not only extends marketing theory but also introduces a new theoretical model elucidating the impact of smart experience on green health tourism through content marketing. This research proposes a model wherein content marketing serves as a tool for crafting an effective smart experience. This is attributed to the ability of content marketing to enhance perceived value, perceived ease of use, enjoyment, and emotional involvement in health tourism. Additionally, this study establishes the suitability of hedonic theory in examining smart experience. Consequently, a comprehensive understanding of the mechanisms through which content marketing influences smart experience in the context of green health tourism is provided, laying the groundwork for the development of strategic content marketing implementations.

6.2. Managerial Implications

In the age of information and communication technology, all industries are undergoing radical changes; therefore, it is natural for the health tourism industry to change its tourist attraction methods based on the current changes. One of the fields that can attract health tourists to certain destinations is a smart experience that can lead to cost reduction for tourists. Furthermore, recognizing the intended destination by utilizing smart experience encourages tourists to focus on that destination and especially those destinations that have been underrated despite their great potential, such as tourism enterprises located in developing countries. Considering the potential in the field of medical treatment as well as natural therapy in Iran, developing health tourism can bring in more foreign exchange to the country. Managers are suggested to pay more attention to this context.

Based on this research, tourists’ perceived value of a destination can be changed by using content marketing for creating a planned smart experience. Even the destinations that have long been used with the view of not being able to attract foreign visitors can now use perceived value, perceived ease of use, enjoyment, and emotional involvement to pave the way for the presence of tourists. This is because not only the medical sector and the private sector can have such an advantage, but even nature therapy centers and medical centers created by the public sector can benefit from such an opportunity in order to influence the sustainable growth and development of the country. Moreover, since in most societies governments play the main role in protecting the environment, the use of smart experience in health tourism, which leads to green (sustainable) tourism, can reduce the annual costs of developing environmental protection methods. On the other hand, it is suggested that considering the potential capacities of nature therapy, such as hydrotherapy, sand therapy, flower therapy, sun therapy, etc., the public sector or even the private sector, such as tourism enterprises, invest in these areas and start health tourism centers based on smart experience.

7. Limitations and Recommendations for Future Research

Due to time constraints and limited resources, this study has focused on health tourism in Iran. Therefore, all or part of its results may not be generalizable to some other regions in the world. Consequently, it is suggested that for other regions, researchers use population selected from those regions. Since this study discusses the concept of smart experience, it is suggested that the Metaverse in smart experience and its impact on tourism also be considered in future studies. Since the weather is also considered in some research, such as [100], the results of this research may not be applicable in some parts of Iran. This should particularly be taken into consideration at the international level. It is, therefore, suggested that the components of digital communication with appropriate bandwidth, the weather, public services, etc., in the field of green health tourism and smart experience be investigated in future studies.