Investigating the Impact of Social Marketing on Tourists’ Behavior for Attaining Sustainable Development Goals (SDGs)

Abstract

Social marketing modifies individual behavior to achieve specific outcomes, mitigating environmental pressures. While proven effective in influencing consumer behavior, empirical studies on its impact on the tourism sector remain limited. This study examines how various social marketing channels influence tourists’ consumption decisions and contributes to achieving SDGs 11 and 12 by reviewing the existing methods of disseminating social marketing content. A conceptual model grounded in theory was developed and empirically tested. In particular, it focuses on the establishment of direct and indirect multi-route effects between social marketing and consumer behavior and introduces different influencing factors. Given the scarcity of research on collective culture, quantitative methods were employed, with data collected through questionnaires in mainland China. Results indicate that social marketing media significantly influence tourist behavior, with three mediators—subjective norms, personal values, and communication channels—playing varying roles across media types (events, public relations, and traditional media). Subjective norms, values, and communication channels act as mediators. This study bridges social marketing, tourist behavior, and SDG attainment, offering novel insights and practical implications for tourism practitioners.

1. Introduction

Global tourism is facing mounting environmental challenges, with transport emissions projected to reach 1.998 billion metric tons by 2030, amid anticipated 86.7 billion domestic and 9.0 billion international tourist arrivals [1,2]. This unprecedented travel volume accelerates energy consumption, exacerbates climate challenges, and poses public health risks [3,4], underscoring the need for a more sustainable approach. “Experts and scholars widely recommend transforming consumption patterns and lifestyles to become more sustainable and environmentally responsible. Particularly through “shifting consumption behaviors toward sustainability”—a transformation requiring private-sector and public participation [5]

Social marketing (SM) has demonstrated efficacy in addressing environmental issues [6,7,8]. Tourism applications span heritage preservation and pro-environmental behavior [9,10]. Relevant research has demonstrated that we can learn from the successful implementation of SM in consumption behavior [11]. While its potential is recognized, further research is needed to clarify its role in driving behavioral shifts that align with the SDGs. From a practical point of view, there are few practical applications of SM in China, and the scope of application is relatively narrow. Western society is characterized by individualism, which emphasizes personal goals, autonomy, and self-realization. East Asian societies, such as China, take collectivism as their core and value group harmony, interdependence, and social responsibility. Chinese tourists are more susceptible to “social recognition” and “collective interests,” and their willingness to adopt sustainable behaviors is significantly enhanced when they are shaped as a social norm or group obligation. The government typically leads China’s public utilities, and more emphasis is placed on institutional and normative aspects, which makes the process of social marketing less innovative. Such insights inform policy and grassroots initiatives aimed at advancing sustainable consumption.

The 2030 Agenda (SDGs) provides a vital framework for tourism research [12], with empirical evidence demonstrating a reciprocal relationship between tourism and sustainable development [13]. Meanwhile, progress toward sustainable development enhances tourism production and consumption [14], aligning with the requirements of SDG 12. This study specifically examines sustainable consumption within this symbiotic relationship, addressing the persistent gap between environmental preferences and actual tourist behavior [15]. By investigating how SM influences tourist consumption patterns, this research enhances our understanding of the SDGs, particularly SDG 11 (sustainable cities) and SDG 12 (responsible consumption and production). It addresses a critical literature gap regarding behavioral mechanisms for achieving the SDGs, building on established evidence of SM’s behavioral influence. The study specifically examines how different SM media affect key behavioral determinants.

The extant literature identifies subjective norms, personal values, and communication channels as key determinants of consumer behavior [5,16]. However, their mediating role in SM contexts remains poorly understood. Hence, this study responds to the following question: “How do influencing and mediating factors influence the relationship between SM and consumer behavior in the context of SDGs 11 and 12?” This study aims to generate insights with both theoretical and practical implications for academia and industry by employing an SM.

The research offers dual contributions. First, from a theoretical perspective, they provide a solid foundation for research examining the interrelationship between sustainable development and consumer behavior. Second, this study makes a practical contribution by providing useful insights and formulating suggestions for tourism destinations and marketers on designing and implementing action plans and marketing activities that promote sustainable consumer behavior.

2. Literature Review

2.1. Consumer Behavior in Tourism for Attaining SDG11&12

As already pointed out, tourist behavior can exert a positive impact on the SDGs, especially SDG 12, which is closely and directly related to tourism activities on both sides (supply and demand). More specifically, our research focused on demand (tourists’ consumption) and sustainable consumption behavior. One important dimension of this consumption is the patterns of consumption by tourists.

The sustainable practices emphasized in SDG 12 exhibit strong synergies with SDG 11, as demonstrated by recent studies [17]. Sustainable urban development requires low-carbon travel and the protection of scenic areas, while sustainable consumption patterns necessitate energy conservation and efficient use of resources. Luxury hotels have implemented environmental measures to address energy efficiency issues, reducing water consumption, waste, and carbon emissions [18]. Effective waste classification at the source reduces management expenditures and promotes circular economy principles, with consumer behavior modification proving to have a particularly significant impact on enhancing resource recovery [19]. Parallel to these objectives, SDG11 emphasizes the adoption of sustainable mobility through public transportation systems. Achieving this transition demands dual governmental and consumer commitments: developing eco-friendly transport infrastructure while encouraging sustainable travel choices among users [20]. Responsible tourism contributes to and enhances the quality of life for communities, cultures, the environment, and local economies, in line with Sustainable Development Goal 11 (SDG11) [21].

Sustainable consumption behavior refers to the behavioral actions that contribute to environmental preservation and protection [22]. The consumer behavior literature often describes environmental sustainability as green consumption patterns. Green consumption behavior is considered a voluntary form of consumption that aims to protect the natural environment [23]. Consumers frequently engage in pro-environmental behaviors, with prevalent practices including eco-conscious transportation choices, sustainable product acquisition, waste recycling, and conservation of natural resources [24]. Such actions predominantly involve acquiring and utilizing goods and services designed to minimize their environmental impact.

Chinese tourists are also concerned about the importance of sustainable consumption, and various corporate entities are involved in promoting this cause. For example, Ctrip Group reduces the supply of disposable items in hotel standards, and Huangshan Scenic Area encourages tourists to recycle mineral water bottles in exchange for small gifts. Tourists tend to choose public transport or new energy vehicles to reduce pollution and practice the ‘disc plan’ to reduce food waste. Chinese tourists are also actively involved in tree-planting projects when visiting remote areas such as Yunnan and Qinghai.

Many studies on consumer behavior focused on pre-purchase/consumption behavior for choosing/selecting environmentally friendly products, savings of energy and water, protection of natural resources, recycling, reduction in food and other solid waste, preference/purchase of organic/green services and productions, and also the use of public transport [25].

In summary, tourists’ consumption behavior can contribute to achieving SDGs 11 and 12.

2.2. The Applications of Social Marketing in Tourism

Social marketing (SM) has been conceptualized through two seminal definitions. Lee and Kotler describe SM as “the systematic design, implementation, and evaluation of programs that advance social objectives through comprehensive marketing mix strategies encompassing product development, pricing, distribution, and market analysis” [26]. Kotler and Lee subsequently refined the definition to emphasize “the application of marketing principles and techniques to modify target audience behaviors for societal and individual benefit” [27]. The fundamental objective of SM initiatives involves transforming specific behavioral patterns within designated population segments. When effectively implemented, SM campaigns can produce several behavioral outcomes: adoption of novel beneficial practices, rejection of potentially harmful actions, modification of existing behaviors, or complete cessation of undesirable activities [26]

SM also aims to foster sustainable development and eco-conscious behaviors, establishing a vital linkage with tourism for enduring behavioral transformations [28]. Such sustainable behavioral modifications represent the core outcomes of SM interventions. This approach enhances the social standing of tourism enterprises while facilitating more responsible tourism practices. Despite limited explicit recognition, SMs are commonly utilized to drive societal change [29]. SM plays a significant role in promoting positive behavior change and social change, including improving the quality of public life and environmental conditions. Studies have shown that incorporating the concept of environmental protection into marketing strategies can help maintain the long-term balance of the ecological environment while meeting consumer demand [30].

Existing research demonstrates that both public and private sector SM can effectively shape sustainable tourist conduct [31]. Supporting evidence suggests that sustainability-oriented branding approaches have a significant influence on consumer decisions [8]. Social marketers believe that providing a wealth of marketing information to help create a good product presents a good opportunity for development, which, in turn, enables sustainable consumption [11]. A key goal of SM is to promote sustainable development and encourage people to adopt environmentally friendly behaviors. Sustainable behavior change has been proven to be related to SM. Kaczynski et al. pointed out that SM can be employed to understand tourists’ behavioral patterns and to implement targeted measures to promote environmentally friendly behavioral changes [10]. Linking SM to tourism is one of the keys to driving long-term sustainable behavior change [32].

As an effective strategy to promote social change and sustainable development, SM has received extensive attention from overseas academic circles. However, there are still few studies on SM based on China’s national conditions. From the perspective of the basic connotations and influencing factors of social marketing, existing research still requires expansion, and in-depth theoretical exploration is necessary to guide practical applications. Therefore, our study adopts this marketing approach to explore both the factors influencing tourist behavior and the methods through which they exert their impact. The ultimate aim is to influence consumers to become responsible co-actors in attaining SDGs 11 and 12.

3. Theoretical Framework, Hypotheses Development, and Conceptual Model

It is believed that SM is a suitable theoretical framework for exploring the impact on consumer behavior in achieving SDGs 11 and 12. Organizations implement SM through three primary channels: social media, events, and public relations, supplemented by additional media, as depicted in

Table 1. An example of various social marketing channels.

Social Marketing Channels	Example
Social media	“Curators of Sweden”: The Swedish government assigns the management of the official Twitter account, @Sweden, to different citizens every week, allowing them to share their real-life experiences. This “rotation–curation” model has successfully shaped Sweden’s image as an open and inclusive country. Liberal arts public relations research shows that this “citizen diplomacy” strategy is more likely to gain the trust of international audiences than traditional state advocacy.
Events	The Coca-Cola “Share a Coke” event in Kenya involved replacing the logo on Coca-Cola bottles with names to create personalized souvenirs, encouraging everyone to stay in touch with friends and family, create lasting memories, and foster offline social interaction. The event emphasizes “authentic social experiences” to combat social distancing in the digital age.
Public Relations	“H&M Garment Recycling System”: H&M translates its environmental commitment into a tangible consumer experience by visualizing the recycling process of used clothes through a transparent window. This PR strategy not only enhances brand reputation but also drives the industry’s focus on the circular economy, demonstrating how “social marketing” can transform consumer behavior through transparent communication.
Other Medias	The Michigan Fitness Foundation piloted a new social marketing tagline (i.e., promoting healthy choices) and professionally designed messages and images. The campaign promotes healthy eating and increases public awareness through billboards, bus signs, and ground materials such as banners used by local enforcement agencies, A-frame signs, pop-up tables, and tablecloths.

. As mentioned, consumer behavior is a multidimensional concept that is influenced by numerous factors. This study focused on three factors that influence this: subjective norms (SN), values (VA), and communication channels (CC). Hereafter, all concepts and constructs are accurately and precisely defined, forming the basis for advancing and postulating the hypothesized relationships.

3.1. The Means/Media of Social Marketing and Their Effect

3.1.1. The Influence of Social Media on Subjective Norms, Values, and Communication Channels

The term “Social Media” denotes internet-based platforms that facilitate content creation and dissemination through networked user interactions. These digital environments serve as vital spaces for individuals to share opinions, perspectives, and lived experiences through participatory engagement. The Chinese Social Media Platforms (SMP) are WeChat, Weibo, and TikTok. Organizations utilize these channels for various purposes, including promotional campaigns, talent acquisition, academic research, and fundraising initiatives [33]. Their effectiveness in promotional strategies has pioneered innovative digital marketing methodologies.

Social media harnesses the potential of digital platforms to advance a wide range of social initiatives. A representative case is “Meal Train”, an event coordination system built on social media platforms to facilitate activities associated with SMP [34]. This mechanism primarily seeks to enhance civic engagement by motivating voluntary participation, thereby encouraging behavioral changes among community members to address social needs and collectively maximize public welfare.

Subjective Norms (SN) refer to the social pressure felt by individuals to either implement or refrain from implementing a certain behavior, which is based on the individual’s perception of the expectations of others within a social 35 context [35]. Increasingly, companies and organizations are recognizing the power of SMP. Studies have found a specific relationship between social media and SN, which can influence the relationship between SN and intentional behavior, and the SMP can also impact the subjective norms of individuals [36].

Value (VA) refers to “values are used to characterize cultural groups, societies, and individuals, to trace change over time, and to explain the motivational basis of attitudes and behavior” [37]. Value creation is a crucial prerequisite for motivating consumers to engage in prosocial behavior change. Value shows consumers’ goals and desires when using these social platforms. Consumers take action when they believe that SM platforms align with their values and help them achieve specific goals [38].

Andreasen states that information is one of the primary factors influencing consumer behavior [39]. A Communication Channel (CC) is the medium of information dissemination selected and established by information sources, that is, the method by which information disseminators disseminate information [40]. The CC in this study refers to the means of communication that tourists choose to use for their interactions with others. With the advent of Web 2.0, consumer behavior varies regarding CC and information quality. The information from CC and the channels in which it is disseminated impacts consumer decisions [41].

Therefore, based on the above discussion, SMP can influence individual SN [36] and adjust the relationship between SN and intentional behavior. The effect of SN on behavior has been documented by Suk et al. [42]. Likewise, SMP affects the tourists’ values and the channels used to disseminate information and communicate with tourists. Hence, this study postulated the following hypotheses:

H1a: 

Social media significantly and positively impact the subjective norms of tourists.

H1b: 

Social media significantly and positively impact the values of tourists.

H1c: 

Social media significantly and positively impact the communication channels with tourists.

3.1.2. The Influence of Events on Subjective Norms, Values, and Communication Channels

Morgeson pointed out that an event is an external dynamic experience that breaks organizational conventions and requires entities (such as individuals and teams) to perform controlled information processing [43]. Marketing and tourism activities often incorporate food festivals, cultural performances, and experiential projects, thereby enhancing the appeal of destinations and increasing visitor numbers [44]. Music concerts and cultural shows are examples of event marketing. Public agencies and Destination Management Organizations (DMOs) utilize them to raise environmental awareness, encourage resource conservation, and promote responsible consumption [45]. Such initiatives align with SM by promoting societal well-being.

Our study focuses on activities that promote SM to influence individuals’ behavior. Prior research has examined SM events across different contexts. Yan and Liu emphasize the role of social relationships in shaping subjective norms, particularly in health-related events such as cancer screenings, which influence experiential value and prosocial outcomes [46]. He et al. propose a value-driven framework to predict behavioral change, emphasizing the importance of effective communication strategies [15]. Research on smoking cessation and fire incident management further demonstrates the role of communication channels, such as public gatherings, in driving behavioral change [47]. Based on the above information, we advanced the following hypotheses:

H2a: 

Social marketing events significantly and positively impact the tourists’ subjective norms.

H2b: 

Social marketing events significantly and positively impact the tourists’ values.

H2c: 

Social marketing events significantly and positively impact tourist communication channels.

3.1.3. The Influence of Public Relations on Subjective Norms, Values, and Communication Channels

Public relations (PR) encompasses strategic communication efforts undertaken by organizations to cultivate positive relationships with key stakeholders and enhance their institutional reputation [48]. These efforts foster public engagement, organizational transparency, and a positive audience perception. PR is at the core of the interaction between an entity (such as a firm or organization) and the public, as well as the relationships with society as a whole. The discipline emphasizes achieving social good through ethical communication practices [49], aligning with the objectives of SM. PR’s inherent focus on advocacy and network influence makes it a natural conduit for SM initiatives. This synergy suggests that PR methods should form the foundation for relationship-building in SM implementation.

Research shows that social relations, as a form of public relations, can impact tourists’ satisfaction [50]. Heath and Waymer pointed out that PR can be carried out by telling coherent and truthful stories to help shape values [51]. As for the CC, it is the focus of PR management. CC refers to the carrier or path of information transmission, and PR needs to achieve effective interaction between the organization and the public through these channels. Effective PR requires the strategic selection of channels and the optimization of communication content based on feedback from each channel, ultimately achieving the goal of building a strong organizational image and managing public relations effectively. PR attaches importance to information spreading. Organizations attempt to communicate through PR to influence a particular individual’s or group’s knowledge, attitudes, and behaviors to promote ethical behavior [52]. Content on various digital communication channels is significant in PR practice and impacts communication channels [53]. Therefore, we postulated the following hypotheses:

H3a: 

PR significantly and positively impact the subjective norms of tourists.

H3b: 

PR significantly and positively impacts the tourists’ values.

H3c: 

PR significantly and positively impact the communication channels with tourists.

3.1.4. Other Media

SM is not only SMP, PR, and events, but it also uses other media. For instance, the Michigan Fitness Foundation launched and conducted an SM campaign using billboards, bus signs, banners, A-frame signs, and floor materials such as pop-up tables and tablecloths for communication and promotion [54]. Regarding tourism, some hotels utilize smartphones to send text messages or emails in advance to promote environmental protection, and others provide feedback cards placed in their rooms to gauge visitors’ efforts to conserve water and participate in other environmental activities [31]. Organizations also conduct SM by publishing statements that highlight their charity donations [6]. However, Truong and Hall pointed out that many projects, while employing SM principles in their design and implementation, do not label themselves as such because the terms are difficult to discern [28]. We classify such terms/media as other media (OM). SM itself is a potentially useful consumer-oriented approach that can promote behavior change [29]. Reviewing the above information, we postulated the following hypotheses:

H4a: 

Other media significantly and positively impact the tourists’ subjective norms.

H4b: 

Other media significantly and positively impact the tourists’ values.

H4c: 

Other media significantly and positively impact the communication channels with tourists.

3.2. The Effect of Influencing/Mediating Factors on Consumer Behavior

Scholars have indicated that responsible consumption behavior is primarily related to one’s level of knowledge and environmental context [55]. Socioeconomic characteristics are also related to behavior, and education level, age, and gender are related to pro-environmental behavior [56]. Numerous studies have also demonstrated that certain core variables in social and environmental psychology theories are crucial, including subjective norms, values, and communication channels.

3.2.1. Subjective Norms

Being incorporated into the traditional architecture of the Theory of Planned Behavior (TPB), SN emerges as a fundamental psychological construct, constituting one of the three principal factors that directly influence the formation of behavioral intentions. As indicated, this conceptual framework establishes behavioral intention as the most proximate predictor of observable actions, wherein attitudinal dispositions, normative influences, and control perceptions jointly determine an individual’s intentional state [57]. Scholars such as Lam T and Sparks have studied the tourism intention of tourists in mainland China by using TPB and verified the effectiveness of this theory in explaining and predicting tourist behavior [58,59].

SN involves the social pressures individuals feel when engaging in or refraining from a certain behavior [35]. They are personal suggestions in a social context. Differences in individuals’ SN can influence green consumption [23]. Consumers rarely make purchasing decisions independently; they typically consult with reliable social circles for guidance [36]. The willingness to consider others’ opinions demonstrates how individual actions are fundamentally connected to group dynamics, making SN a crucial factor in shaping behavioral intentions [57]. If consumers make purchasing decisions regardless of signals from others, they will perceive themselves as violating or rejecting SN. It seems plausible to presume that SN may positively influence consumer behavior by being more responsible and sustainable. Thus, it is postulated as follows:

H5: 

Subjective norms significantly and positively influence the behaviors of tourist consumers.

3.2.2. Values

Researchers emphasize the significance and importance of values and behaviors [60]. Value creation constitutes a crucial premise for social good, motivating consumers to engage in prosocial behavior change [61]. These studies support the investigations into values in this study and provide a deeper understanding of their relevance in consumer behavior. Values constitute pivotal elements that enhance theoretical explanatory capacity [62]. Specifically, green values, which are intrinsically linked to sustainability principles, are frequently incorporated into conceptual models that analyze the decision-making mechanisms of environmentally conscious consumers [22]. Empirical evidence confirms their moderating influence on purchase decisions [63]. Previous research has systematically examined the behavioral impacts of value systems, particularly highlighting how biospheric values—a subset of environmental values—serve as robust predictors of pro-environmental actions [64]. Therefore, we could reasonably postulate the following:

H6: 

Values significantly and positively influence the behaviors of tourist consumers.

3.2.3. Communication Channels

Van Dijk investigated electronic data interchange from a communication channels perspective, highlighting its role in shaping consumption patterns [65]. Subsequent research has identified information technology as a key enabler of efficient channel management and commercial activities. Conrad and Lotz investigated how communication channels influence deceptive practices, revealing differences in consumer reactions across various media [66]. During the COVID-19 crisis, the rapid shift toward digitalization created new opportunities for technological media exchange within communication systems [67]; behavioral responses to CC show differing degrees of intensity. While face-to-face interactions maintain their persuasive power, with clearer channels producing superior results, consumers frequently distrust information from multiple channel sources [68]. Traditional brick-and-mortar stores, which emphasize direct personal contact, continue to play a crucial role in influencing purchasing decisions. With digital CC becoming increasingly prevalent, understanding the interplay between businesses and consumers has gained critical importance [69]. Thus, communication channel formats exert significant influence. Thus, we may reasonably postulate the following:

H7: 

Communication channels have a significant and positive influence on the behaviors of tourist consumers.

Drawing upon the preceding examination, environmentally sustainable tourist practices manifest through multiple concrete actions. These include, but are not limited to, water conservation measures, towel reuse initiatives, energy efficiency efforts, the procurement of ecologically sustainable merchandise, a preference for locally sourced products, the repeated use of plastic containers and packaging materials, and the reduction in food waste at hospitality venues and tourist locations. Of particular significance is the conscious selection of green-certified and environmentally responsible products during the consumption process. Additionally, we further classified the related behaviors of SDG11 and SDG12 as follows. SDG11 pays more attention to transport modes, waste disposal, streamlined product packaging, and sustainable material packaging. SDG 12 emphasizes responsible production and consumption patterns, particularly in terms of energy savings, reducing food waste, and strengthening the conservation of water and electricity resources. These behaviors are reasonably related to and correlate with consumer behavior. Thus, we could logically advance the following hypothesized relationships between consumer behavior and the attainment of SDGs:

H8: 

Consumer behavior of tourists significantly and positively contributes to the achievement of SDG11.

H9: 

Consumer behavior of tourists significantly and positively contributes to the achievement of SDG12.

All the above-discussed hypotheses form the foundation for the research model to analyze and understand the influence of SM activities on the responsible consumption behavior of tourists aiming to attain SDGs (see Figure 1). As discussed in the previous section, SMP, PR, events, and OM are indispensable elements in the SM approach to shaping consumer behavior, that is, the media often used by social marketing to obtain targeted results. They can influence tourists’ SN, values, and CC and thus influence tourist behavior. SN, values, and CC are the mediating factors between social marketing and sustainable consumption behavior. The ultimate goal is to contribute to the realization of SDG 11 and SDG 12, which are the focus of our research.

4. Method

4.1. Questionnaire Design

Our study aims to examine tourists’ consumption behavior by analyzing four dependent variables—SM, events/activities, PR, and OM—along with the following three influencing variables: SN, VA, and CC. Each variable was measured by adapting the measurement items suggested by previous studies (

Table 2. Measurement items.

Constructs	Measurement Items	Supporting Library Source
Social media	SM1: During my trips/holidays, the use of social media (WeChat, Weibo, Red Book, and TikTok) affects my purchase of green products.	Armutcu et al. [70]
	SM2: The content on social media (WeChat, Weibo, Xiaohongshu, and TikTok) about green products and other sustainable consumption is trustworthy.
	SM3: The content on social media (WeChat, Weibo, Xiaohongshu, and TikTok) regarding green products and sustainable consumption is generally reliable.
Events (EV)	EV1: During my trips/holidays, participating in or understanding various events and festivals affects my purchase of green products.
	EV2: The communication and content of sustainable consumption at various events and festivals are trustworthy.
	EV3: The communication and content of sustainable consumption at various events and festivals are reliable.
Public Relations (PR)	PR1: During my trips and holidays, PR messages (statements, notices, presentations, and events) affect my purchase of green products.
	PR2: The communications and content about sustainable consumption through PR activities are trustworthy.
	PR3: The communications and content about sustainable consumption through PR activities are reliable.
Other Medias (OM)	OM1: During my trips/holidays, the messages by other media (magazines, journals) affect my purchase of green products.
	OM2: The communications and content about sustainable consumption from other media (magazines, newspapers) are trustworthy.
	OM3: The communications and content about sustainable consumption from other media (magazines and newspapers) are reliable.
Subjective Norms (SN)	SN1: Most people who are important to me support me in adopting green consumption behavior.	Wan et al. [71]
	SN2: My friends think I should have green consumption behavior.
	SN3: My family thinks that I should adopt green consumption behavior.
	SN4: Colleagues and peers who work with me think that I should adopt sustainable consumption behavior.
Values (VA)	VA1: The value of “unite nature” has an impact on my consumption behavior.	Han et al. [62]
	VA2: The value of “respect for the earth” has an impact on my consumption behavior.
	VA3: The value of “pollution prevention” has an impact on my consumption behavior.
	VA4: The value of “protecting and preserving the environment” has an impact on my consumption behavior.
Communication Channels (CC)	CC1: The mass media (TV, radio, magazines, and billboards) affect my consumption choices.	Dzidzornu et al. [72]
	CC2: Communications with other people (peers, social groups, relatives, and friends) influence my consumption choices.
	CC3: Communications by other entities (tourism companies, national tourism organizations, local tourism offices, and other bodies) affect my consumption choices.
Consumer Behavior (CB)	CB1: My consumption habits have become more environmentally friendly during my trips.	Ali et al. [73]; Su et al. [74]
	CB2: When on holiday, I buy more environmentally friendly and green products.
	CB3: During my trips, I have reduced waste production through prevention, reuse, and recycling.
	CB4: I attempt to convince my travel companions to protect the natural environment of the visited place.
	CB5: I like to participate in environmentally friendly activities
SDG11	SDG11-1: I always opt for public transport.	Cheng & Wu [75]
	SDG11-2: When visiting, I give priority to low-emission and sustainable modes of transport, such as bicycles.
	SDG11-3: I handle waste properly, sorting and recycling.
	SDG11-4: I avoid packaging and reduce the use of plastics.
SDG12	SDG12-1: During my trips, I prefer reusable and recyclable products to minimize waste.	Borden et al. [31]
	SDG12-2: During my trips, I order moderately and pack the remaining food to reduce food waste.
	SDG12-3: During my trips, I save water (in the shower and kitchen).
	SDG12-4: I save energy by properly using electric devices and equipment (e.g., air conditioning) during my trips.

). Tourist consumption behavior was evaluated using five items, and SDG11 and SDG12 were each measured with four items.

The questionnaire has two sections. The first section is designed to inform participants of the purpose of this study and to collect demographic information, including age, gender, education, and occupation. Respecting respondents’ privacy does not require the registration of real names and contact information. At the same time, this part involves determining whether participants are suitable for the study. In the next section, the interviewees were asked to answer the main questions of this survey based on their real-life situations, using a seven-level Likert scale (1 = strongly disagree to 7 = strongly agree). The necessary concepts or some essential examples were provided to ensure the interviewees understood the questions.

The population in this study is an unlimited number of Chinese consumers who have had recent travel experiences. The sample size was determined using a 10-time rule [76], resulting in a study sample of 360 respondents. The sampling strategy is a well-planned method that employs a purposeful sampling approach, focusing on predetermined criteria. This study employs simple random sampling because it is considered a more representative method.

4.2. The Sample and Data Collection

This study employed a quantitative research design, with a questionnaire survey as the primary method of data collection. A pre-test was conducted on 58 respondents who had travel experience in the past year. After deleting two blank questionnaires, this tool was enhanced by eliminating vague or irrelevant items to ensure the readability of the questionnaire and the pertinence of the questions. The reliability and validity were then strictly tested. At the same time, due to different understandings of green products among the respondents, examples were added after pointing out relevant concepts. This preliminary stage improves the validity of the questionnaire and ensures the quality of the data. Pre-test samples from different regions of China were used to assess problem clarity, scale accuracy, and respondents’ understanding of key constructs; fuzzy items were subsequently deleted.

Data is collected online and offline. Respondents are encouraged to complete the questionnaire honestly and accurately. All information is collected anonymously, and no personal information or preferences will be disclosed. From January to March 2025, 572 valid questionnaires were collected through the Questionnaire Star online data platform and field data collection. SPSS 27.0 and SmartPLS 4.0 were used, including testing reliability and validity, testing model measurement hypotheses, and analyzing interacting effects. The descriptive information is summarized in

Table 3. The Profile of Participants.

	Demographic Variable	N	%
Gender	Male	258	45.10%
	Female	314	54.90%
Age	18–25	153	26.70%
	26–35	128	22.40%
	36–45	113	19.80%
	46–55	75	13.10%
	55–65	72	12.60%
	>65	31	5.4%
Education	Junior high school	38	6.60%
	Senior high school	162	28.30%
	Vocational/College	162	28.30%
	Undergraduate	185	32.30%
	Postgraduate	25	4.40%
Job	Professionals	89	15.60%
	Civil servants	86	15.00%
	Managers of enterprises	78	13.60%
	General staff of enterprises	71	12.40%
	Service/sales staff	55	9.60%
	Primary sector staff	31	5.40%
	Production, transport operators, and related personnel	44	7.70%
	Unemployed	2	0.30%
	Self-employed	28	4.90%
	Retired/pensioner	41	7.20%
	Students	22	3.80%
	Other	25	4.40%

.

Although Hair et al. [76] published a study on vinegar in 2022, PLS-SEM employs bootstrapping techniques. Since there is no problem with normal distribution, it is also necessary to assess the normality of the data when using PLS-SEM [77]. The data normality assessment uses skewness and excess kurtosis values, with a value limit of −2 to +2. The summary of the data normality test is shown in

Table 4. Validity and reliability.

Constructs	CA	OL	CR	AVE
SM	0.781	0.827–0.842	0.782	0.695
EV	0.784	0.816–0.862	0.788	0.698
PR	0.771	0.812–0.848	0.772	0.686
OM	0.790	0.816–0.870	0.794	0.705
SN	0.834	0.804–0.831	0.834	0.667
VA	0.834	0.788–0.838	0.837	0.667
CC	0.761	0.803–0.843	0.763	0.676
CB	0.862	0.788–0.822	0.863	0.644
SDG11	0.850	0.818–0.853	0.854	0.689
SDG12	0.844	0.816–0.841	0.846	0.681

.

5. Results

5.1. Reliability and Validity Test of the Questionnaire

The assessment of reliability utilized both Cronbach’s alpha (CA) and composite reliability (CR), with all variables required to surpass the threshold of 0.70. The CA coefficient indicates scale reliability, specifically assessing the internal consistency of measurement instruments. CR evaluates the dependability of combined variables, where elevated values correspond to greater internal consistency levels.

Convergent validity was assessed using outer loading (OL) values, which should exceed 0.70. The average variance extracted (AVE) must exceed 0.50. The latter specifically evaluates convergent validity, with values above 0.50 demonstrating adequate convergent validity. The scholars use the Heterotrait–Monotrait ratio (HTMT) for testing the discriminant validity, which calculates the ratio between inter-trait and intra-trait correlations. An HTMT threshold below 0.85 confirms discriminant validity between factors, whereas lower values indicate stronger discriminant validity. As presented in Table 4, all constructs satisfy this criterion (HTMT < 0.85), thereby establishing discriminant validity.

Since the scale of this study is based on the establishment of multiple mature scales, it is necessary to consider whether the items are targeted at the variables and conduct an exploratory factor analysis (EFA). Prior to conducting EFA, an assessment of data adequacy must be performed. The established criteria specify that the Kaiser–Meyer–Olkin (KMO) measure should be more than 0.7, while Bartlett’s test must achieve statistical significance (p < 0.05). The current analysis yielded particularly robust indicators for factor extraction, evidenced by a KMO coefficient of 0.944 and a highly significant Bartlett’s value (p < 0.001). For the factor extraction process, the eigenvalue threshold was maintained at values exceeding unity.

The measurement model effectively operationalizes ten first-order constructs, with all dimensions meeting the criteria for unidimensionality. Factor analysis of 36 value indicators yielded ten distinct components explaining 68.5% of total variance. All items exhibited commonalities above 0.4, confirming strong factor loadings and adequate information extraction. Our study employed Harman’s single-factor test to evaluate potential common method variance. Results showed that the initial unrotated component explained 33.42% of the total variance, which falls substantially below the critical 50% cutoff value established by Podsakoff et al. (2003) [78]. This suggests that method bias, if present, remains at sufficiently low levels to ensure the integrity of our findings.

5.2. Structural Model Evaluation

The structural equation model (SEM) can simultaneously analyze the complex relationships between multiple variables. Examining the variable covariance matrix can reveal the direct effect between variables and identify the indirect influence path, which overcomes the limitations of traditional regression analysis in dealing with complex relationships. SEM contains a variety of parameter estimation techniques, among which the PLS method has no strict requirements for data distribution. When the sample data presents non-normal distribution characteristics and there is no multicollinearity problem, it is more appropriate to use the PLS method for model estimation.

Following Hair et al.’s (2021) [76] suggestions, our study adopted the following three-stage analytical approach: (1) assessing structural model collinearity, (2) examining variable relationship significance, and (3) evaluating model fit (R² and SRMR). The collinearity detection was based on the variance inflation factor (VIF) value < 3.3. According to

Table 5. Discriminant Validity-HTMT.

	CB	CC	EV	OM	PR	SDG11	SDG12	SM	SN	VA
CB
CC	0.550
EV	0.556	0.547
OM	0.535	0.535	0.526
PR	0.553	0.547	0.575	0.588
SDG11	0.537	0.499	0.540	0.494	0.575
SDG12	0.572	0.515	0.541	0.478	0.527	0.440
SM	0.521	0.463	0.529	0.478	0.624	0.549	0.426
SN	0.560	0.553	0.488	0.532	0.602	0.516	0.494	0.521
VA	0.547	0.572	0.521	0.488	0.567	0.526	0.494	0.550	0.568

, the relationship between all variables indicates that the VIF value is within the range of 1–2.020, suggesting that there is no collinearity problem in the model. This confirms acceptable levels of multicollinearity and appropriateness for PLS.

The model analysis demonstrates statistically significant relationships for most hypothesized variable paths. The standardized path coefficient in the structural equation model effectively reflects the strength of the correlation between variables. When the coefficient reaches a statistically significant level, it indicates a substantial impact between the variables.

This study explores the consumption behavior of tourists, which is influenced by SM and the following three influencing factors: SN, Value, and CC. The standardized coefficients of all significant paths are greater than 0, indicating that all effects are positive. As a means of SM, SMP has a positive and significant effect on SN, VA, and CC; therefore, H1a, H1b, and H1c are accepted. As for the relation between EV and SN, VA, and CC, all the sub-hypotheses of H2 are accepted, and the p-value is <0.05. PR positively and significantly affects SN, VA, and CC, with all p-values of the paths <0.05; H3a, H3b, and H3c are accepted. OM positively and significantly affects SN, VA, and CC, with a p-value < 0.05. So H4a, H4b, and H4c are accepted. SN, VA, and CC have a positive and significant effect on consumer behavior, with all p-values < 0.05, supporting the fifth, sixth, and seventh hypotheses. Consumer behavior has a positive and significant impact on SDG11, as confirmed by H8. Consumer behavior also positively and significantly affects SDG12, and H9 is accepted.

The standardized residual root mean square (SRMR) is a key metric for assessing the structural equation model fit and quantifying the discrepancy between model predictions and observed values through standardized residual analysis. The range of SRMR is typically 0 to 1, with a critical value of approximately 0.08. The smaller the SRMR value, the better the model’s fitting degree. The SRMR value of this study is 0.043, indicating a good model-fitting degree within the critical value range. Normed fit index (NFI), whose value is required to be between 0 and 1, and the closer to 1, the higher the degree of fitting. The NFI value of this study is 0.838, which is greater than 0.8, indicating ideal model fitting. About the coefficient of determination (R²), which evaluates model explanatory ability by quantifying accounted variance, all values demonstrated statistical significance (p < 0.001).

5.3. Mediating Effect Analysis

This research employed the bootstrap method to analyze the indirect path of SN, VA, and CC in the path from SM to consumer behavior. As presented in

Table 6. The result of factor analysis and collinear survey.

Item	Excess Kurtosis	Skewness	VIF	Q2	Factor Loading	Explained Variance
Construct 1: Social Marketing						22.924%
Factor 1: Social media						5.803%
SM1	−0.917	−0.214	1.629	/	0.743
SM2	−0.656	−0.218	1.583	/	0.732
SM3	−0.869	−0.157	1.649	/	0.754
Factor 2: Events						5.744%
EV1	−0.882	−0.117	1.645	/	0.734
EV2	−0.951	−0.134	1.723	/	0.720
EV3	−0.785	−0.258	1.559	/	0.768
Factor 3: Public Relations						5.518%
PR1	−0.761	−0.261	1.548	/	0.696
PR2	−0.687	−0.283	1.703	/	0.753
PR3	−0.749	−0.204	1.524	/	0.709
Factor 4: Other Media						5.859%
OM1	−0.860	−0.103		/	0.746
OM2	−0.696	−0.215		/	0.763
OM3	−0.897	−0.145		/	0.749
Construct 2: The Influencing Factors						20.847%
Factor 5: Subjective Norms						7.566%
SN1	−0.671	−0.324	1.856	0.224	0.741
SN2	−0.829	−0.238	1.788	0.201	0.774
SN3	−0.815	−0.185	1.827	0.209	0.735
SN4	−0.775	−0.200	1.701	0.218	0,705
Factor 6: Value						7.616%
VA1	−0.642	−0.286	1.662	0.180	0.715
VA2	−0.582	−0.302	1.865	0.235	0.709
VA3	−0.722	−0.271	1.811	0.211	0.746
VA4	−0.702	−0.258	1.842	0.206	0.758
Factor 7: Communication Channel						5.665%
CC1	−0.706	−0.223	1.467	0.177	0.706
CC2	−0.846	−0.103	1.586	0.221	0.716
CC3	−0.714	−0.232	1.580	0.163	0.784
Construct 3						9.082%
Factor 8: Consumer Behavior						9.082%
CB1	−0.745	−0.239	1.778	0.233	0.692
CB2	−0.694	−0.182	1.800	0.213	0.705
CB3	−0.887	−0.236	1.843	0.200	0.746
CB4	−0.812	−0.217	1.955	0.253	0.705
CB5	−0.949	−0.184	1.997	0.174	0.775
Construct 4						15.677%
Factor 9: SDG11						7.848%
11-1	−0.871	−0.167	1.936	0.145	0.795
11-2	−0.718	−0.221	1.848	0.170	0.732
11-3	−0.738	−0.325	1.850	0.168	0.743
11-4	−0.823	−0.205	2.020	0.174	0.757
Factor 10: SDG12						7.829%
12-1	−0.806	−0.212	1.856	0.145	0.766
12-2	−0.885	−0.144	1.907	0.162	0.754
12-3	−0.835	−0.298	1.823	0.137	0.751
12-4	−0.678	−0.203	1.849	0.158	0.745

, all mediation analyses yielded statistically significant results, as evidenced by 95% confidence intervals that excluded zero, thereby confirming the established mediation effects.

The results of path analysis are shown in

Table 7. The path analysis.

Path	Stdev	Std	T Value	p Value
H1a: SM→SN	0.044	0.171	3.873	0.000
H1b: SM→VA	0.042	0.217	5.130	0.000
H1c: SM→CC	0.044	0.106	2.428	0.015
H2a: EV→SN	0.042	0.129	3.080	0.002
H2b: EV→VA	0.044	0.182	4.188	0.000
H2c: EV→CC	0.044	0.218	4.930	0.000
H3a: PR→SN	0.045	0.251	5.633	0.000
H3b: PR→VA	0.045	0.202	4.460	0.000
H3c: PR→CC	0.044	0.178	4.019	0.000
H4a: OM→SN	0.041	0.199	4.894	0.000
H4b: OM→VA	0.045	0.145	3.225	0.001
H4c: OM→CC	0.042	0.205	4.927	0.000
H5: SN→CB	0.047	0.158	3.369	0.001
H6: VA→CB	0.044	0.132	3.000	0.003
H7: CC→CB	0.044	0.124	2.810	0.005
H8: CB→SDG11	0.033	0.462	14.035	0.000
H9: CB→SDG12	0.032	0.491	15.435	0.000

and Figure 2, and those of mediation effects in

Table 8. Results of mediation effects.

Mediator Variable	Path	Std	Stdev	T Statistics	95% CI of the Difference
					LL	UL
SN	SM→SN→CB	0.027	0.011	2.509 *	0.009	0.050
	EV→SN→CB	0.020	0.009	2.307 *	0.006	0.040
	PR→SN→CB	0.040	0.014	2.827 **	0.015	0.070
	OM→SN→CB	0.032	0.012	2.655 **	0.011	0.057
VA	SM→VA→CB	0.029	0.011	2.519 *	0.009	0.054
	EV→VA→CB	0.024	0.010	2.419 *	0.007	0.047
	PR→VA→CB	0.027	0.011	2.333 *	0.008	0.053
	OM→VA→CB	0.019	0.009	2.230 *	0.005	0.038
CC	SM→CC→CB	0.013	0.008	1.703	0.002	0.031
	EV→CC→CB	0.027	0.012	2.327 *	0.007	0.053
	PR→CC→CB	0.022	0.009	2.342 *	0.006	0.043
	OM→CC→CB	0.025	0.010	2.416 *	0.007	0.048

Note: * p value < 0.05; ** p value < 0.01.

.

6. Discussion

This study explores the consumption behavior of tourists, which is influenced by SM and the following three influencing factors: subjective norms, values, and communication channels. We found that SM can have a positive and significant effect on SN. According to the extensive application of the TPB, the importance of SN in influencing behavior change has been proven. Moreover, SN will affect consumers’ behavioral intentions. As mentioned earlier, recent research has also proved the moderating effect of SN on behavior [79]. We emphasize the sustainability of tourists’ consumption behavior, and SN affects green consumption [71]. People attach importance to the influence of SN on behaviors, and our study helps to prove the influence of SN on consumer behaviors, not only the moderating effect but also the mediating effect.

He et al. emphasize the value-driven aspect, and H6 helps to prove this point [80]. Empirical evidence demonstrates that when consumers perceive alignment between SMP and their personal value systems, along with recognizing these platforms’ capacity to facilitate goal attainment, they exhibit greater behavioral engagement [6,36]. Van et al. identified internal values and social norms as significant determinants of environmentally sustainable actions [16]. The formulation of Hypotheses 5 and 6 (H5, H6) has extended the investigative parameters of behavioral studies, particularly elucidating the distinct influence mechanisms of these factors on behavioral outcomes. Notably, our analysis reveals that VA mediates the relationship between SM initiatives and consumer behaviors. Recent studies have reviewed the literature on VA for sustainable consumer behaviors and called for an investigation of the causal mechanism between VA and sustainable consumer behaviors [81]; our results respond to this call.

Different CC or information dissemination channels affect the quality of SM implementation and consumer behaviors. As early as more than 10 years ago, Van Dijk noted that CC can influence consumption behaviors [65]. With the proliferation of digital technologies, online platforms have become increasingly beneficial [82]. Past researchers have investigated how information influences behaviors and alters consumers’ choices of consumption [83]. The mediating effect of CC between SM and consumer behavior helps us understand how to guide behavior change.

When combined with specific topics, Hypotheses 8 and 9 support the role of consumer behavior in promoting public transportation and energy conservation and, to some extent, support Agya, who emphasizes the impact of consumer behavior on food waste [84], and Ismail, who emphasizes the role of transportation in alleviating climate change research [85]. Tourists adopt environmentally friendly consumption habits, which can not only reduce waste pollution but also help conserve energy and minimize waste. Building upon current theoretical developments, subsequent investigations would benefit from the extended application of this framework across diverse facets of sustainable consumer behavior. Our study similarly addresses this research imperative [86].

7. Conclusions and Implications

This study addresses a gap in sustainable tourism research by systematically analyzing the mechanisms through which SM influences tourist behavior. Although prior research confirms SM’s significant impact, the mediating processes remain unclear, particularly in the context of tourist consumption behavior. Current social marketing studies primarily focus on corporate or organizational strategies, with limited exploration of their effects on tourist consumption patterns. Furthermore, the Chinese sociopolitical context differs from overseas settings, as government-led initiatives often dominate social marketing efforts, resulting in insufficient private-sector involvement. By examining the relationship between tourist consumption behavior and SM, this study offers practical insights to strengthen public–private collaboration and encourage corporate participation in social marketing initiatives.

Our investigation builds upon prior contributions to tourist consumption intention research by identifying the following three key determinants: SN, values, and CC. The research reveals a persistent discrepancy between tourists’ stated support for sustainable consumption and their actual behavioral patterns. To bridge the intention–action gap and foster meaningful progress toward sustainability goals, we emphasize the urgent need for effective interventions that translate environmental awareness into informed, concrete consumption decisions. By analyzing the mediating effects of SN, values, and CC within the “SM–consumer behavior” pathway, we develop and test a conceptual model that elucidates differential impact patterns. The findings provide empirical insights that advance our knowledge about how targeted SM can contribute to the achievement of SDG11 and SDG12.

This study proposes a multipath framework, “SM-influencing factors–tourist’s behavior-SDG11&12”, to address the inherent challenges in consumer behavior within SM. Significantly, we shift the analytical focus from direct marketing-behavior effects to examining the mediating mechanisms of influential factors. The findings demonstrate that distinct SM media exert differential positive effects on the following three key mediators: SN, values, and CC. Our analysis reveals that in traditional SM media, including events, PR, and OM, all three mediators (SN, values, and CC) function as significant intermediaries in shaping tourist consumption behavior. However, SMP and CC show a weak intermediary role. This may be because social media is a powerful platform for companies to connect with customers while marketing products and services [87]. Social media can serve as a platform for professional education and development, organizational promotion, or a tool for communicating with others [88]. DMOs should pay attention to the choice of social media when carrying out activities and expand the use of social media to reach as many communication channels as possible for tourists.

The study further establishes that tourist consumption behaviors positively contribute to the attainment of SDG 11 and SDG 12. Building on these empirical results, we derive practical recommendations for both academic researchers and tourism industry practitioners.

7.1. Theoretical Implication

This study examines the mechanisms of SM and the antecedents of tourist consumption behavior by identifying the aforementioned three factors as mediating variables. It empirically validates the influence pathway of “SM—influence factors—consumer behavior”, offering significant implications for tourism scholars and enriching the knowledge on sustainable tourism.

First, this study advances the theoretical application of SM in sustainable tourism by examining its role in shaping tourist consumption behavior. The existing literature demonstrates the effects of diverse marketing approaches on tourism consumption, yet SM remains understudied in green tourism consumption compared to other methods. Our research offers novel insights into the influence pathways that link SM and consumer behavior.

Second, we systematically examine the mediating roles of SN, values, and CC in the relationship between SM and consumer behavior. While prior studies have explored antecedent factors in behavioral pathways, their specific connections to SM require deeper investigation. By clarifying the mechanisms through which SM affects green consumption, this study enhances the theoretical understanding of how these factors function within sustainable tourism. Additionally, by integrating the TPB, we extend its application in tourism research, particularly by elucidating the impact of subjective norms on behavioral outcomes. As an important part of the TPB, this study combines SM and TPB to construct a behavior model suitable for China and further introduces values and CC to enhance the explanatory power of the model for Chinese tourists’ behavior. The study demonstrates that values influence tourist behavior, and environmental protection and sustainable information must be aligned with personal values. At the same time, we should change our perspective and regard CC as an active factor in promoting behavior change, breaking through the limitations of traditional TPB in tourism, and providing a more systematic theoretical framework for tourism behavior intervention in the digital era.

Ultimately, this study utilizes the SDGs as a conceptual framework to evaluate SM’s contribution to sustainable tourism development. It constructs a tripartite analytical model that connects SM, consumer behavior, and the SDGs, offering a new perspective for future research at the intersection of marketing strategy and sustainability. Altogether, this research advances theoretical understanding by integrating SM with the mediating mechanisms of SN, values, and CC. The findings strengthen the theoretical foundation of sustainable tourism research and also provide empirical evidence for future investigations into the role of SM in achieving SDGs. Notably, with the 2030 Agenda having passed its midpoint, the adoption of multiple pathways encompassing both direct and indirect impacts can help the UN ensure the attainment of its targets. This finding can also provide theoretical support for policymakers and provide a theoretical basis for tourism-related personnel to design more effective sustainable tourism promotion strategies.

7.2. Practical Implications

This study provides empirical evidence on the mechanisms through which SM influences consumer behavior, yielding practical implications for tourism destinations and industry practitioners. The findings reveal the following three key implications for sustainable tourism management: first, the results confirm SM’s pivotal role in fostering green consumption behaviors among tourists. Tourism operators should systematically integrate SM initiatives into their marketing strategies to showcase environmental stewardship and social responsibility. Effective implementation requires (1) conducting comprehensive assessments across different organizational types, (2) developing precise audience segmentation strategies based on demographic factors (e.g., age) and consumption patterns (e.g., tourism expenditure levels), and (3) utilizing localized communication platforms (e.g., social media platforms, and community events). Such targeted approaches can reduce barriers to sustainable behaviors while accounting for the normative influences of SN and values.

Second, the study demonstrates that combining positive incentives with normative constraints significantly increases the probability of tourists adopting sustainable practices. Tourism entities should develop integrated campaigns that simultaneously highlight benefits and emphasize social expectations.

Third, the research underscores the importance of explicit alignment between corporate sustainability practices and broader development goals. When tourism businesses visibly demonstrate their commitment to sustainable operations, they create powerful reference points that effectively guide tourists toward environmentally responsible choices.

Tourism organizations should strategically leverage diverse social marketing media through differentiated approaches: (1) utilizing mainstream social platforms with localized content strategies (e.g., collaborations with key opinion leaders); (2) designing multifaceted events including knowledge–dissemination activities (expert lecture series), participatory programs (eco-challenges), and festival-based initiatives (environmental commemorations); and (3) establishing authoritative information release systems with expert spokespersons while enhancing public relations through government–community partnerships. This multidimensional media deployment optimizes sustainable behavior modification through channel-specific advantages.

Second, our analysis identifies three mediating pathways through which SM operates: (i) SN: Tourists’ consumption choices are significantly influenced by referent groups and opinion leaders. DMOs should utilize communication data or social surveys from various social marketing media to correct tourists’ misunderstandings of norms and encourage sustainable consumption behavior to be transformed into convergence behavior within the group. Tourists may also purchase specific green products or services to establish a group identity. Therefore, managers should pay attention to group effect and group behavior change. (ii) Values: Individuals with strong environmental values demonstrate a greater propensity for eco-friendly consumption patterns, including product selection and waste reduction behaviors. By linking sustainable consumption behavior with higher-level values, tourists are encouraged to adjust their original values, thereby prioritizing individual environmental protection and sustainable values. (iii) CC: The effectiveness of information dissemination varies across platforms. Managers or publicity teams of destination marketing organizations should pay attention to the use of various channels, fully leverage the promotional role of official online platforms, and prioritize the participation of residents in tourism destinations. They can establish an interactive platform for tourists and residents, organize online and offline multi-channel cultural exchange activities, and enhance the possibility of real-world communication, ultimately promoting sustainable consumption practices.

Finally, the study empirically validates the connection between consumer behavior and the achievement of SDG 11 and SDG 12. According to the survey results, we found that tourists can reduce resource pollution by bringing their folding shopping bags, water cups, and other reusable packaging items, thereby reducing plastic use. Additionally, tourists can help minimize waste by strictly adhering to the destination’s waste classification regulations and participating in local recycling initiatives. To support these goals, tourism operators should expand the offerings of sustainable products and services, implement waste-reduction initiatives targeting packaging and energy use, and design interventions that systematically encourage sustainable consumption decisions among visitors. These findings provide a comprehensive framework for integrating SM principles with sustainable tourism development strategies. Tourists choosing more environmentally friendly products can not only reduce plastic waste but also contribute to a more sustainable future. The use of non-recyclable materials can reduce the pressure of environmental degradation and also encourage enterprises or organizations to adopt greener production methods, produce more environmentally friendly products, and form a virtuous circle.

7.3. Limitations and Suggestions for Future Research

Our study also has some limitations that warrant attention in the future. First, the current investigation was conducted exclusively within mainland China, where cultural and socioeconomic contexts may yield distinct outcomes. Especially in China, which values collectivism and face culture, the varying degrees of emphasis on group interests and individualism in SM can affect the likelihood of behavioral change. Meanwhile, the urban-rural development gap in China still exists, and in the future, more targeted recommendations can be obtained through stratified sampling based on urban-rural or income levels. Subsequent studies should incorporate cross-cultural comparisons to examine potential variations across different regions and demographic groups. Moreover, the classification of social marketing media is more general, particularly when compared to other media, which require a detailed analysis. Second, while the sampling strategy adopted a generalizable approach, future research would benefit from destination-specific analyses. Particular focus should be given to specialized tourism segments—such as cultural, sports, and wellness—where tourist consumption patterns may demonstrate significant variations. Such targeted investigations would yield more nuanced policy recommendations tailored to specific tourism typologies. Finally, the quantitative methodology employed in this study could be complemented by experimental designs. Controlled experiments comparing tourist consumption behaviors across different SM interventions would provide stronger causal evidence and enhance the robustness of findings.