Satisfaction on the Driving Seat: Exploring the Influence of Social Media Marketing Activities on Followers’ Purchase Intention in the Restaurant Industry Context

Abstract

Recently, social media marketing has become an effective tool for restaurants to gain visibility, increase customer engagement, and boost sales. Through social media marketing activities (SMMAs) including customization (CUST), entertainment (ENTR), trendiness (TRND), and interaction (INTR), restaurants can connect with their customers in a dynamic way that may affect their satisfaction and purchasing behavioral intention. Hence, this study primarily aims to empirically explore the individual influence of SMMAs namely CUST, ENTR, TRND, and INTR on social media followers’ satisfaction and purchase intention in a sample of casual-dining restaurants in Saudi Arabia. Furthermore, drawing on the Stimulus-Organism-Response (S-O-R) model, we also seek to investigate the influence of customer satisfaction as a mediating variable in the relationship between CUST-PI, ENTR-PI, TRND-PI, and INTR-PI. Furthermore, to examine the direct influence of CS on PI. In order to meet these objectives, an online survey was created to collect data from a convenience sample of restaurant social media followers. Data from 415 followers were analyzed using the PLS-SEM with a bootstrapping technique to confirm the research hypotheses. The findings of the study illustrated the significant positive effect of CUST, ENTR, and INTR on followers’ purchase intention, respectively. Trendy social media marketing activities did not significantly affect purchase intention. Additionally, CS partially mediated the relationships between CUST, ENTR, INTR, and PI but fully mediated the trendiness-purchase intention relationship. The results from this research can assist restaurant operators to leverage the benefits of social media more effectively by understanding how SMMAs influence customers’ purchase intentions and enhancing their understanding of how customer satisfaction can be used to capitalize on the benefits of social media.

1. Introduction

The influence of social media on consumer behavior has been tremendous. Social media has become a vital component of people’s day-to-day lives, and its influence extends to how they make decisions as consumers [1,2]. People now use social media to research products, compare prices, ask friends for recommendations, keep abreast of current trends, and even purchase items directly from sites like Instagram and Facebook [3,4]. This shift in the buying process has caused companies to rethink their marketing strategies and adapt to the ever-changing demands of customers. Social media marketing activities (SMMAs) including customization (CUST), entertainment (ENTR), trendiness (TRND), as well as interaction (INTR) have an important role in influencing consumer behavioral intentions, particularly purchase intention (PI) [5,6]. Companies can now use social media to create more personalized experiences for consumers, target specific audiences with ads, and interact directly with customers through comments and reviews [7]. Visual content such as GIFs, videos, and photographs are highly engaging and can keep customers hooked to the brand and be more likely to stay interested in its product or service [5,6]. Social media also allows companies to build long-term relationships with their customers by offering them valuable content and engaging them in conversations about their products or services [8]. Overall, the power of social media has altered how consumers make decisions when it comes to buying products and services. In addition, social media marketing activities can have a significant impact on a business’s sustainability [9]. By using social media platforms to connect with their target audience and promote their products or services, businesses can increase their visibility, reach more potential customers, reduce marketing costs, and generate more sales or revenue. This can improve their economic sustainability and help them stay competitive in the market [10]. At the same time, social media can also be used to promote corporate social responsibility (CSR) initiatives, which can have a positive impact on social sustainability by addressing social issues and improving stakeholder relationships [11]. With respect to environmental sustainability, social media can be used to promote eco-friendly practices and products such as reducing waste, conserving resources, and raise customers’ awareness about environmental issues [12].

The relationship between SMMAs, CS, and PI has been a subject of growing interest and research. Through various studies, it has been established that CS plays an important role in influencing purchase intention [13,14]. Customer satisfaction is increased when companies engage in SMMAs such as CUST, ENTR, TRND, and INTR [3,5,6]. By providing customers with personalized content and experiences, customers feel valued, and this increases their chances of making a purchase. In contrast, if customers feel that a company does not meet their expectations, they are less likely to make a purchase [13,14]. In the context of the restaurant industry, exploring the association between SMMAs, CS, and PI is an important topic to understand and study. The importance of SMM for restaurants cannot be underestimated. Social media marketing can be a powerful tool for restaurants to reach and engage with potential customers [15]. By being active on social media, restaurants can create meaningful conversations with their target customers and build awareness for their restaurants [4,15]. Social media is also an effective platform for restaurants to showcase their products and services. Restaurants can use the visuals available on social media platforms such as Instagram, and YouTube to create an online portfolio of their food and services [8]. By posting pictures, videos, and reviews, restaurants can attract new customers and increase their customer base [1].

In response to the recommendations of Bushara et al. [16], in addition to the fact that most previous studies have examined the influence of SMMAs, as a whole, on the consumers’ PI and satisfaction, we attempt in this study to uncover the individual impact of each element of SMMAs namely CUST, ENTR, TRND, and INTR on consumers’ attitudes and behavior toward satisfaction and purchase intention, instead of assessing the effect of SMMAs as a whole. We believe this research can provide valuable insights into the direct and indirect effect of each element on these relationships. Furthermore, although some previous studies have suggested a substantial association between SMMAs and purchase intention (i.e., [16,17,18]), there have also been some studies that have found that the influence of SMMAs or some of them was not significant [6,19,20,21]. This has produced inconsistent findings and suggests the need for further empirical research in order to gain a better understanding of the SMMAs-purchase intention relationship. Additionally, the research conducted in Saudi Arabia is believed to be the first of its kind, as there have been relatively few studies investigating the role of customer satisfaction as a mediator in the relationship between social media marketing activities and purchase intentions. While there is some existing research on this subject, it remains limited and has not been widely explored in the context of the restaurant industry in developing nations. Therefore, this study makes an important contribution to the literature by shedding light on the relationship between these variables in this specific context. Hence, we aim to empirically explore how SMMAs (namely, CUST, ENTR, TRND, and INTR) directly influence the satisfaction and purchase intention of restaurant social media followers. We also seek to examine the influence of CS, as an intermediating variable, in the relationships between CUST-PI, ENTR-PI, TRND-PI, and INTR-PI using the S-O-R model. Furthermore, we aim to demonstrate the direct impact of CS on PI in a sample of casual-dining restaurants in Saudi Arabia. To reach these aims, this research attempts to answer the following queries: (1) To what extent do CUTS, ENTR, TRND, and INTR of social media marketing activities influence restaurant social media followers’ PI? (2) To what extent do CUTS, ENTR, TRND, and INTR of SMMAs influence CS? (3) To what extent does CS influence restaurant social media followers’ PI? (4) What is the potential intermediating effect of CS on CUST-PI, ENTR-PI, TRND-PI, and INTR-PI relationships?

This study adds to the current social media marketing literature by exploring the individual direct impact of SMMAs namely CUST, ENTR, TRND, and INTR on CS and PI in the Saudi Arabian casual-dining restaurant context. Furthermore, based on the S-O-R model, the study empirically investigates the indirect effect of SMMAs on PI through CS, where CUST, ENTR, TRND, and INTR were employed as stimuli (S), and CS utilized as organism (O), meanwhile PI represents the response (R). By understanding the results of this study, businesses can use this knowledge to inform their social media marketing strategies and improve CS in order to increase PI. Additionally, businesses can consider how they can target customers with marketing activities that will increase customer satisfaction. Furthermore, businesses can use the findings of the research to explore how their SMMAs can affect customer purchase intention in a more direct and indirect way.

This research focuses on the followers of casual-dining restaurants due to the increasing market share of the casual-dining market in recent times [22]. Casual-dining marketers utilize social networking sites to increase interaction with the public [23]. They are capitalizing on the advantages of social media platforms to enlarge their reach, target their desired customer groups (in particular, the younger generation), and generate more sales. The segment of social media users that are highly engaged and active in the digital world [23,24] provides a suitable population for this research as it is simpler to retrieve their opinion for research purposes.

2. An Overview of the Theoretical Background and the Development of Hypotheses

2.1. Social Media Marketing Activities (SMMAs)

In the contemporary digital era, social media marketing (SMM) has become an essential part of marketing strategies. SMM is recognized as the process of using social media platforms to promote and market a product or service [25]. SMM is a powerful tool for businesses of any size to reach their target audience, boost their brand engagement and visibility, and drive sales and leads [3,5]. It encompasses designing and distributing content on social media networks in order to realize promotional and branding objectives. It can be used to generate awareness, increase brand presence and recognition, build relationships with customers, promote products and services, and more [21]. SMM is viewed as an essential part of any digital marketing strategy, giving businesses the potential to reach a wider audience and fully activate their target market [1,18].

In relation to SMMAs, numerous studies have been carried out to examine the activities/efforts of SMM in various contexts. For example, Kim and Ko [21] in the luxury fashion brand context as well as Seo et al. [26] in the airline industry both categorized SMMAs into five components including INTR, CUST, ENTR, TRND, and e-WoM. Furthermore, Sano [27] used CUST, INTR, perceived risk, and TRND as dimensions of SMM in the assurance services environment. Others explored the impact of SMM on customer loyalty in the e-commerce industry and categorized its activities into five parts: interactivity, informativeness, word-of-mouth, personalization, and trendiness [28]. Meanwhile, Cheung et al. [7] in the luxury cosmetic brand settings conceptualized SMM as a multidimensional variable comprising four components: ENTR, CUST, INTR, and TRND. They excluded e-WoM as they viewed it as a behavioral outcome resulting from SMM adoption. This study employs customization, entertainment, trendiness, and interaction to explore the influence of SMMAs on CS and PI.

Customization of social media marketing involves tailoring content, ad campaigns, and other elements of SMM to the specific needs and preferences of the target audience [29]. Customization can take many forms, such as creating custom visuals featuring a company’s logo or colors, writing content that speaks directly to the user’s interests, and creating customized contests or promotions that incentivize for customers to engage with the brand [30]. Businesses can also use customization to create personalized experiences for users by targeting specific segments of their audience by offering exclusive discounts or promotions based on user data [31].

With regard to entertainment as one of the SMMAs, marketers use social media platforms to evoke customers’ positive emotions and facilitate participation with entertaining content, such as photos, videos, and games [7]. Entertainment marketing has become a critical element in the success of many businesses, as it provides a platform to reach potential customers and engage them in creative ways [32]. Research has found that entertainment activities on social media can have a positive impact on brand awareness and engagement where these activities create an enjoyable user experience that encourages customers to engage with the platform repeatedly [26]. Companies can spread the word about their latest products and services using posts and stories and keep fans abreast of new developments [20]. This can be particularly effective in the case of movies and TV shows, as fans are always eager to learn more about the brands that interest them [7].

Additionally, trendiness is an effective activity of SMM for businesses. With the right strategies, businesses can utilize social media platforms to offer timely updates for products and services, which enables them to stay top-of-mind with their customers and keep them informed about new products or services quickly [33]. Furthermore, businesses can also use trendiness to create campaigns. By executing timely campaigns that capture current trends and interests, businesses can create interest in their products or services and increase brand awareness [34]. By staying on top of the latest information and news in the industry, businesses can use this to build on current trends and ensure their message is always timely and relevant [29].

In SMM, the interaction involves engaging with customers on social media through comments, likes, shares, and other methods [31]. By responding to customer inquiries, providing helpful advice and feedback, or simply posting content that customers are likely to respond to, businesses can build relationships with their customers and facilitate a more meaningful connection [3]. Interaction not only helps to build relationships with customers, but it can also have a positive impact on customers’ perceptions of businesses. By interacting with consumers, companies can ensure that they are aware of the advantages of the brand and the features of its products. Studies have shown that when customers interact with brands on social media, it increases their loyalty and engagement with the brand [7].

2.2. Customer Satisfaction (CS)

Psychologically, CS is regarded as a sense of pleasure, enjoyment, and well-being that customers experience when they receive what they are expected from an attractive product or service [35]. In other words, CS is derived from comparing customers’ expectations with their perceptions after the consumption of products or services [36]. According to Oh et al. [37], consumer satisfaction necessitates the fulfillment of client expectations for services and products. It could be said that the consumer is satisfied if the satisfaction measurement matches their expectations. They are disappointed/dissatisfied if the performance metric does not target their expectations [38]. Customers will be highly satisfied and delighted if product quality and service performance exceed their expectations [39]. Being able to satisfy customers’ needs and wants is the key to customer satisfaction. Customers will be more satisfied if a company can determine their needs and wants and satisfy them. Generally, the greater the satisfying customers’ needs and wants, the higher customer satisfaction [40,41].

According to Haralayya [42] as well as Flott [43], an organization’s dissatisfied customer is more likely to inform nearly 9 to 10 other people about his/her unsatisfactory experience. However, a satisfied one is more likely to tell four or six others about his/her positive experiences. Furthermore, compared to just satisfied customers, very satisfied customers are almost six times more likely to repeat purchases, be loyal, and/or recommend the company’s products and services [43]. In the restaurant industry context, customer satisfaction is one of the key determinants of positive customer behavioral intentions. Numerous studies revealed that CS significantly influences intention to purchase, revisit intention, intention to recommend positive WoM, and willingness to pay a premium price [44,45,46].

2.3. Purchase Intention (PI)

PI refers to the level of psychological commitment a client has to purchasing a product or service [47,48]. It is also referred to the extent to which a customer is likely to buy a product due to their perceived benefits, emotions, and experiences [49]. In the social media marketing context, Choedon et al. [2] defined PI as “a user’s probability and willingness to purchase a recommended product after using social networking websites”. Purchase intention is an important concept in marketing because it can be used to measure and predict consumer behavior [50]. In general, purchase intention is determined by a variety of factors including attitude toward the product, perceived price, perceived quality, perceived value, perceived availability, and customer satisfaction [13,51]. Additionally, social influence and environmental factors may also contribute to a customer’s purchase intention [50,52]. In the fast-food restaurant context, food quality, as well as reasonable price, significantly affected PI [53]. In the SMM setting, advertising and brand reputation can also affect consumer purchase intention [16,17,54]. If a company has created an effective ad campaign that draws in customers, those who have seen the advertisement will likely be more inclined to consider buying the product. In addition, if a company has a positive image and longstanding reputation, a consumer may be more likely to purchase from them than a newcomer [55,56]. In the sustainable marketing context, in addition to its antecedents, increasing sustainable purchasing intentions can have a positive impact on the business’ sustainability, as it can drive demand for sustainable products and services [57,58]. By promoting sustainable practices and products, businesses can attract consumers who prioritize sustainability and are willing to pay a premium for eco-friendly options. This can, in turn, incentivize companies to invest in renewable energy, water and waste management, and other sustainability initiatives that can reduce their environmental impact leading to a more sustainable industry overall [59].

2.4. The Impact of SMMAs on PI

Social media marketing activities can have a significant impact on sustainable purchasing intentions in several ways [16,60]. First, these activities can be used to promote sustainable products and practices, raising consumer awareness and interest in these issues. This can, in turn, influence their green purchasing decisions and drive demand for sustainable products and services [61]. Second, social media marketing can communicate a company’s sustainability initiatives to its stakeholders, helping to build trust and credibility with consumers. This can lead to increased brand loyalty and positive perceptions of the company’s commitment to sustainability, which can, in turn, influence purchasing behavior. Third, social media can facilitate engagement and dialogue between companies and consumers, allowing companies to receive feedback and suggestions from consumers on how they can improve their sustainability practices. This can help companies to continuously improve and evolve their sustainability initiatives to better meet the needs and expectations of their stakeholders [62,63,64].

Numerous studies have examined the SMMAs–PI relationship and illustrated that SMM and its related activities significantly contributed to increasing customer PI. For instance, with special reference to brands of luxury fashion, Gutama, and Sharma [17] revealed that SMMAs significantly contributed to increasing consumers’ PI. They recommended that in order to understand the consumers’ purchase intentions more precisely, luxury fashion brands’ marketers should incorporate SMMAs into their marketing strategies. Furthermore, Moslehpour et al. [20] investigated the influence of SMMAs on PI, in the Indonesian GO-JEK business context, and concluded that consumers’ purchase intentions for GO-JEK are directly affected by SMMAs (β = 0.32, p < 0.01). In other words, they suggested that the PI of the consumer will increase even more when the SMM is managed effectively.

In more detail, SMMAs including customization, entertainment, trendiness as well as interaction significantly individually contributed to fostering consumers’ purchase intent. For example, among the previous activities, Moslehpour et al. [20] concluded that only entertainment activities are significant. More specifically, the results of the research suggested that entertainment-related activities on social media can efficiently increase the engagement of customers with a brand’s social media campaigns and ultimately increase their purchase intentions. However, the findings of another investigation applied to the luxury fashion brands context proved only the effectiveness of entertainment and interaction in enhancing customer PI [21]. They illustrated that in addition to entertainment as an effective activity in promoting customer purchase intention, the success of social media marketing lies in its interactivity. Companies must ensure they are actively engaging with their customers and stakeholders, providing content that is relevant, and engaging and encourages interaction [3]. By observing interactions and looking at what customers respond positively to, businesses can gain a better understanding of what types of content and campaigns customers are attracted to [30].

Concerning the trendiness-consumer purchase intention relationship, earlier studies emphasized that trendiness activity has a substantial role in predicting customer PI. For instance, during the COVID-19 pandemic, the empirical research performed by Shuyi et al. [65] on Chinese consumers indicated that trendiness significantly positively influenced consumer behavioral intention to purchase smartphones. In addition, in the handcraft products context, trendiness was perceived as the most effective factor in involving the investigated users in social media platforms, which leads to improving their intent to purchase (β = 0.697, p < 0.001) [66]. Hence, with the right strategies, businesses can capitalize on what is trending and use it to reach more people, increase engagement, and drive sales. By leveraging trendiness, businesses can make their content more engaging, build awareness and stay competitive, which may eventually increase consumer purchase intention. Moreover, in terms of the nexus between customization and PI, the result of the research performed by Wijayaa et al. [67] on a sample of 217 Indonesian smartphone consumers found that among the investigated SMMAs only customization had a substantial positive influence on consumer PI (β = 0.551, p < 0.001). Their conclusion was that enhancing customization would significantly increase purchase intentions. More specifically, by responding promptly and thoughtfully to customer inquiries and engaging with them in meaningful conversations, businesses can foster trust and loyalty between the customer and the brand. As a result of this type of relationship-building, companies are more likely to build a loyal customer base that purchases their products and services in the future. Considering the previous explanations, we can develop the following hypotheses:

Hypothesis (H1).

Customization of SMM significantly contributes to increasing customer PI in the restaurant industry context.

Hypothesis (H2).

The entertainment of SMM significantly contributes to increasing customer PI in the restaurant industry context.

Hypothesis (H3).

The trendiness of SMM significantly contributes to increasing customer PI in the restaurant industry context.

Hypothesis (H4).

The interaction of SMM significantly contributes to increasing customer PI in the restaurant industry context.

2.5. The Impact of SMMAs on CS

Numerous scholars and practitioners have focused attention on customer satisfaction as a key marketing issue [68,69]. A brand’s success and building sustainable competitive advantage are directly related to the satisfaction of its customers; thus, looking at the determinants of CS is highly important. SMM and associated activities (namely customization, entertainment, trendiness, and interaction) are one of the key predictors of enhancing customer satisfaction [3,5,70]. More specifically, customization allows customers to receive tailored content and services that are specifically designed to meet their needs and desires [71]. Entertainment is another factor that can influence customer satisfaction. Using creative and amusing content can help spark customer engagement [72]. Trendy may also be an important factor for customer satisfaction. Social media trends keep changing and it is essential for firms to keep up with these trends to stay relevant [29]. Immersing in the latest trends helps brands appear active and connected to their customers [33]. Furthermore, interactions with customers are also essential for customer satisfaction [73]. Businesses should solicit feedback from customers and also respond to comments and posts. This helps in building relationships with customers and keeps them engaged with the brand. Additionally, businesses should respond quickly to customer queries and complaints as a high response rate reflects well on the brand’s customer service [69]. From the previous, it could be assumed that SMMAs could significantly contribute to enhancing restaurant social media followers’ satisfaction. Hence, we assume the following hypotheses.

Hypothesis (H5).

Customization of SMM significantly contributes to enhancing CS in the restaurant industry context.

Hypothesis (H6).

The entertainment of SMM significantly contributes to enhancing CS in the restaurant industry context.

Hypothesis (H7).

The trendiness of SMM significantly contributes to enhancing CS in the restaurant industry context.

Hypothesis (H8).

The interaction of SMM significantly contributes to enhancing CS in the restaurant industry context.

2.6. The Impact of CS on PI

CS has long been recognized as a crucial factor in predicting customers’ purchase intentions. Many studies have been performed to explore the influence of CS on PI and its implications for companies. A study by Dash et al. [13] examined the influence of CS on PI in the setting of marketing in the real estate industry. They found a highly positive relationship between CS and PI, and that this relationship is greater when the customer is more committed to the service provider. Another study by Bai et al. [14] explored the influence of CS on PI in the Chinese hospitality industry setting. The results showed that CS substantially contributed to enhancing PI. The study also highlighted that customer satisfaction is an important factor in inspiring customers to buy more when the quality of the hotel website was high. Furthermore, in the yoga tourism context, providing a higher level of service quality helps create satisfied customers, which, in turn, leads to increased customer purchase intention [41]. Similarly, Majeed et al. [74] investigated the effect of CS on hospitality online user purchase intent in Ghana. The findings of PLS-SEM indicated a direct, positive association and indirect (via Customer Engagement) link between CS and hospitality online user purchase intentions. Furthermore, it was determined that this association is stronger when customers possess a higher level of satisfaction. Overall, the findings from various studies indicate that CS plays a vital role in determining PI. As a result, it could be assumed that.

Hypothesis (H9).

CS has a significant positive influence on PI in the restaurant industry context.

2.7. The Intervening Role of CS in the Relationship between SMMAs and PI

To examine the potential mediating role of CS in the SMMAs–PI relationship, the theoretical framework of this research is constructed on the S-O-R model. The S-O-R framework determines behavior based on three factors namely stimulus (S), organism (O), and response (R). Mehrabian and Russell first proposed this model in 1974, which argued that environmental stimuli affect one’s emotional and cognitive reactions, which ultimately result in behavioral responses [75,76]. Based on this model, this study assumes that customers react to external stimuli (S) in the marketplace, which includes SMMAs (customization, entertainment, trendiness, and interaction), and their response I, which referred to purchase intention, is impacted by circumstances (O), referring to CS, that influence their decision-making. The S-O-R model suggests that marketers need to understand how external stimuli can influence customers’ decisions and reactions. By understanding the dynamics of the S-O-R model and how to effectively use it, businesses can better measure and assess the impact of SMMAs on PI directly and indirectly. Accordingly, the higher the perceived customized, entertaining, interactive, and trendy social media marketing may significantly contribute to enhancing CS, which eventually may increase customers’ purchase intentions. Hence, we could hypothesize that.

Hypothesis (H10).

CS has a significant positive mediation effect on the relationship between customization and customers’ purchase intention in the restaurant industry context.

Hypothesis (H11).

CS has a significant positive mediation effect on the relationship between entertainment and customers’ purchase intention in the restaurant industry context.

Hypothesis (H12).

CS has a significant positive mediation effect on the relationship between trendiness and customers’ purchase intention in the restaurant industry context.

Hypothesis (H13).

CS has a significant positive mediation effect on the relationship between interaction and customers’ purchase intention in the restaurant industry context.

Figure 1 depicts the conceptual framework suggested for this study. The S-O-R model considers customization, entertainment, trendiness, and interaction as independent variables (S) with purchase intention as the dependent oI(R). To assess the influence of (Ion (R), an intermediating variable (O) of customer satisfaction was used.

3. Materials and Methods

3.1. Measures and Instrument Development

The proposed study seeks to explore the influence of CUST, ENTR, TRND, and INTR (SMMAs) on social media followers’ PI and CS of casual-dining restaurants in Saudi Arabia. Furthermore, to determine the influence of CS on followers’ PI. Additionally, to empirically investigate the intermediating effect of CS in the CUST-PI, ENTR-PI, TRND-PI, and INTR-PI relationships. To accomplish these objectives, an online questionnaire was developed and distributed using Google Forms to collect data from restaurant followers. Using online questionnaires for data collection is advantageous as it is not limited to a single geographical area, is more time- and cost-effective, and produces faster responses [77].

In the first part of the questionnaire, the participants were asked to provide personal details and their social media usage, such as gender, age, educational level, favored social media platform, and the time spent daily on social media platforms. The second area of the survey examined the participants’ views on SMMAs (CUST, ENTR, TRND, and INTR). The third part sought to calculate participants’ CS. Finally, the items used to measure participants’ PI were presented in the fourth section. In terms of the measures of the study, the researchers utilized items drawn from previous studies to ensure the reliability and validity of the measurements. All items were assessed using a 5-point Likert-type scale where “1” (strongly disagree), and “5” (strongly agree).

To examine the perceptions of the surveyed participants regarding CUST, ENTR, TRND, and INTR activities on social media, four scales based on Cheung et al. [7] were applied. Each scale consisted of three items. The samples of these items are “Restaurant X’s social media provide lively feed information I am interested in” (CUST), “The content found in restaurant X’s social media seems interesting” (ENTR), “Using restaurant X’s social media is very trendy” (TRND), and “It is possible to have two-way interaction through restaurant X’s social media” (INTR). In terms of measuring CS, a five-item scale based on Hanaysha [70] was adapted and employed. A sample of these items is “Overall, I am satisfied with this restaurant”. To measure followers’ purchase intentions, a three-item scale based on Chrisniyanti and Fah [78] was utilized. An example of one of these items might be “I plan to purchase products that I have seen advertised through social media”. The scales of this research can be found in Appendix A.

The survey was first formed in English, then adapted to the native Arabic of the respondents. Two experts who were highly skilled in both the English and Arabic languages were responsible for a back-translation of the questionnaire to ensure that the English and Arabic versions were identical. Furthermore, three hospitality specialists well-versed in the area of SMM reviewed the questionnaire in depth to check its content validity. The survey was also tested by a sample of 35 participants to guarantee that the wording of the questions was straightforward and clear. Modifications were made after addressing the feedback from these pilot participants, resulting in the questionnaire having acceptable content validity.

3.2. Sample of the Study and Data Collection

The research subjects of this study were social media users who followed and interacted with casual-dining restaurant pages on Facebook and Twitter in Saudi Arabia. Convenience sampling was utilized to reach the population of interest. Participants were provided a link to the survey, as well as a message of welcome that gave details on the purpose of the study and also mentioned that completion was voluntary. For a duration of six weeks (November–January 2023), a total of 422 forms were returned and only 415 were suitable for analysis.

The sample size was calculated following Nunnally’s [79] criteria of 1:10 of items to samples, so 10 times the 20 items were 200 participants was acceptable. Furthermore, this number of 415 also complied with Hair et al.’s [80] suggestion of a maximum of 150 samples and Boomsma’s [81] recommendation of 200 samples for structural equation modeling. A total sample size of 415 respondents was used in this study, 61.7% of whom were male and 38.3% were female. Of the 415 participants, nearly two-thirds (66. 5%, N = 276) were aged between 20–30, 66. Regarding their educational level, 63.1% (N = 262) had a university degree, and 21.9% (N = 91) had post-graduate degrees. The results also indicated that the majority of respondents (73.5%, N = 305) reported spending 3–5 h/day on social media. The most widely used social media platforms were Twitter (38.6%), followed by Facebook (29.2%).

3.3. Data Analysis

In this study, SPSS v. 25 and SmartPLS v. 4.0.8.7 were employed for data analysis. A variety of techniques including frequency, percentage, outer factor loading, Cronbach’s alpha, composite reliability (CR), average variance extracted (AVE), Harman single-factor test, Fornell–Larcker criterion, Hetero-trait-Monotrait Ratio (HTMT), coefficient of determination (R²), Q² predicts, variance inflation factor (VIF), and PLS-SEM with the bootstrapping technique were employed to examine the demographic characteristics, reliability and validity, common method variance, convergent and discriminant validity, predictive ability, multicollinearity, and hypothesis testing of the data.

4. Results

4.1. Common Method Variance (CMV)

The researchers used measures of anonymity, confidentiality, and honesty to ensure responses were accurate and to reduce the chances of CMV. They informed participants that their responses would remain confidential and only be utilized for research. Anonymity was employed to reduce potential biases, and honesty was prioritized for reliable results. Additionally, Harman’s single-factor test was used to detect CMV, and the results showed that only one factor could account for 36.29% of the variance, signifying that CMV was not a problem. Podsakoff et al. [82] suggested that CMV might be a problem if a significant proportion of the variance (more than 50%) is attributed to a single factor.

4.2. Results of Measurement Model Assessment

In accordance with Hair et al. [80], the initial step in evaluating the measurement model involves examining indicator loadings, with an outer loading of over 0.708 indicating that the construct explains more than half of the indicator’s variability. Results in

Table 1. The properties of multicollinearity, reliability, and validity of the study’s constructs.

Construct	Item	Outer Loading	VIF	α	CR	AVE
Customization	CUST1	0.832 ***	1.763	0.766	0.865	0.682
	CUST2	0.871 ***	1.925
	CUST3	0.772 ***	1.356
Entertainment	ENTR1	0.822 ***	1.657	0.838	0.903	0.756
	ENTR2	0.905 ***	2.550
	ENTR3	0.879 ***	2.253
Trendiness	TRND1	0.857 ***	1.746	0.814	0.890	0.729
	TRND2	0.856 ***	1.855
	TRND3	0.848 ***	1.791
Interaction	INTR1	0.830 ***	1.831	0.830	0.897	0.744
	INTR2	0.892 ***	2.004
	INTR3	0.865 ***	1.890
Customer satisfaction	CS1	0.806 ***	1.912	0.879	0.912	0.675
	CS2	0.799 ***	1.872
	CS3	0.881 ***	2.940
	CS4	0.853 ***	2.607
	CS5	0.763 ***	1.768
Purchase Intention	PI1	0.769 ***	1.763	0.758	0.803	0.576
	PI2	0.732 ***	1.925
	PI3	0.776 ***	1.356

Note: VIF = variance inflation factor, α = Cronbach’s alpha, CR = composite reliability, AVE = average variance extracted, *** p < 0.001.

indicate that all factor loadings are above the desired threshold of 0.70. and are statistically significant. Additionally, internal consistency reliability was evaluated by applying Cronbach’s alpha and CR. In Table 1, Cronbach’s alpha value (α) ranged from 0.758 to 0.879, and CR scores ranged from 0.803 to 0.912, all meeting Hair et al.’s [80] threshold of 0.70, assuring good internal consistency reliability. The third step in assessing the measurement model is testing convergent validity, which is carried out by determining the AVE. A higher level of AVE, equal to or higher than 0.50, is suggested [80]. The AVE of the study variables varied from 0.576 to 0.756, confirming acceptable convergent validity.

To determine the presence of multicollinearity in the study model, the VIF was employed. If a VIF score is higher than 3, then multicollinearity is present and must be addressed [80]. There is no serious issue of multicollinearity among the variables in the study model, indicated by VIF values all being below 3, which can be seen in Table 1. Additionally, the researchers evaluate the discriminant validity via two methods namely, the Fornell–Larcker criterion, and the HTMT. First, based on the Fornell and Larcker [83] argument, the discriminant validity of a construct can be confirmed if the square root of the construct average variance extracted (AVE) is higher than its correlation with any of its other measured constructs in the model. The square root of the AVE for each construct was larger than its correlation with the other constructs in the structural model, as demonstrated in

Table 2. Discriminant validity according to the Fornell–Larcker criterion.

Construct	1	2	3	4	5	6
1. Customer satisfaction	0.822
2. Customization	0.607	0.826
3. Entertainment	0.600	0.478	0.869
4. Interaction	0.660	0.501	0.508	0.863
5. Purchase Intention	0.640	0.625	0.568	0.577	0.759
6. Trendiness	0.723	0.615	0.552	0.707	0.619	0.854

Note: The diagonal bold values represent AVE’s square root.

, demonstrating its excellent discriminant validity.

Second, HTMT was utilized to guarantee to construct discriminant validity. Hair et al. [80] and Henseler et al. [84] proposed that a threshold of 0.90 or lower is satisfactory. Meaning that an HTMT score greater than 0.90 weakens discriminant validity. As demonstrated in

Table 3. Discriminant validity based on the HTMT.

Construct	1	2	3	4	5	6
1. customer satisfaction
2. Customization	0.738
3. Entertainment	0.697	0.598
4. Interaction	0.763	0.624	0.603
5. Purchase Intention	0.855	0.885	0.776	0.776
6. Trendiness	0.852	0.781	0.667	0.850	0.857

Note: The HTMT values are lower than 0.90.

, all the HTMT values among the study constructs are below 0.90, indicating that distinct validity was obtained effectively.

4.3. Assessment of the Predictive Ability of the Structural Model

To investigate the predictive ability of the model, R², and the Q² predict values for each predicted construct were determined. Statistically, R² shows how much of the variation in a dependent variable can be accounted for by its independent variable(s). The R² value of 0.25 is described as weak, 0.50 is described as moderate, and 0.75 is described as substantial [80,85].

Table 4. Predictive accuracy and relevance of the structural model.

Construct	R2	Q2 Predict
Customer satisfaction	0.630	0.619
Purchase Intention	0.551	0.526

shows the share of variance explained for each endogenous construct. The model’s predictive accuracy was shown to be good, as SMMAs explained 63% of the variance in CS. Furthermore, SMMAs and CS together explained 55.1% of the variance in PI.

In addition to the coefficient of determination (R²), Q² Predict values were calculated to estimate the model’s predictive relevance. As suggested by Hair et al. [80] Shmueli and et al. [86], for good predictive relevance, the Q² prediction value should be higher than zero. As presented in Table 4, the Q² value for all endogenous constructs is greater than zero, signifying the model’s predictive relevance.

4.4. Hypotheses Testing

The path coefficient and significance of the relationships between the exogenous and endogenous constructs were tested using the PLS-SEM algorithm and bootstrapping with a subsample of 5000. The results are represented both in

Table 5. Structural Parameter Estimates.

Hypothesized Path	Path Coefficient	t-Value	Confidence Intervals Bias Corrected		Result
			2.5%	97.5%
Direct Path
H1: CUST → PI	0.288	5.643 ***	0.191	0.388	Accepted
H2: ENTR → PI	0.191	3.851 ***	0.092	0.286	Accepted
H3: TRND → PI	0.105	1.731 NS	−0.012	0.229	Rejected
H4: INTR → PI	0.143	2.564 **	0.035	0.252	Accepted
H5: CUST → CS	0.190	5.012 ***	0.118	0.264	Accepted
H6: ENTR → CS	0.213	4.771 ***	0.121	0.299	Accepted
H7: TRND → CS	0.331	6.643 ***	0.233	0.432	Accepted
H8: INTR → CS	0.223	4.162 ***	0.113	0.326	Accepted
H9: CS → PI	0.179	2.820 **	0.059	0.304	Accepted
Indirect path
H10: CUST → CS → PI	0.034	2.447 *	0.011	0.066	Accepted
H11: ENTR → CS → PI	0.038	2.241 *	0.013	0.085	Accepted
H12: TRND → CS → PI	0.059	2.608 **	0.020	0.110	Accepted
H13: INTR → CS → PI	0.040	2.266 *	0.011	0.079	Accepted

Note: CUST = customization, ENTR = entertainment, TRND = trendiness, INTR = interaction, CS = customer satisfaction, PI = Purchase Intention, *** p < 0.001, ** p < 0.01, * p < 0.05, ^NS = not significant.

and Figure 2.

In terms of the direct relationships between activities of social media marketing and purchase intention, the results in Table 5 revealed that CUST significantly contributed to enhancing restaurant social media followers’ PI (β = 0.288, t-value = 5.643, p < 0.001), supporting H1. Furthermore, ENTR significantly contributed to enhancing followers’ PI (β = 0.191, t-value = 3.851, p < 0.001), accepting H2. On the contrary, the results of the PLS-SEM indicated that TRND does not significantly influence followers’ PI (β = 0.105, t-value = 1.731, p < 0.05), implying that H3 is rejected. With regard to INTR, the results demonstrated the significant positive effect of INTR on PI (β = 0.143, t-value = 2.564, p < 0.01), supporting H4.

In the context of the SMMAs–CS relationships, the results in Table 5 and Figure 2 confirmed the significant positive influence of TRND, INTR, ENTR, and CUST on CS, respectively. The results support H5, which postulated that CUST significantly contributes to enhancing CS (β = 0.190, t-value = 5.012, p < 0.001). In addition, ENTR also has a significant positive effect on CS (β = 0.213, t-value = 4.771, p < 0.001), confirming H6. Similarly, the results revealed that CS is significantly impacted by TRND and INTR (β = 0.331, t-value = 6.643, p < 0.001, β = 0.223, t-value = 4.162, p < 0.001), respectively, suggesting that H7 and H8 are accepted. Furthermore, the results shown in Table 5 also illustrated that CS significantly positively influences followers’ PI (β = 0.179, t-value = 2.820, p < 0.01), which supports H9.

Concerning the indirect paths between SMMAs and PI through the CS, the results confirmed that CS significantly positively mediates the relationships between TRND-PI, INTR-PI, ENTR-PI, and CUST-PI, respectively, supporting H10, H11, H12, and H13. Examining the effect of CS on the link between SMMAs and PI, the ideas put forward by Kelloway [87] and Zhao et al. [88] were employed. They demonstrated that full mediation is only achievable when the indirect effect is statistically significant and the direct effect is not, while partial mediation can only be ascertained if both pathways (direct and indirect) are significant. As shown in Table 5, CS has a significant partial intermediating effect on the relationships between CUST, ENTR, INTR, and PI because both paths are significant. Meanwhile, CS has a significant full mediation effect on the TRND-PI relationship where the indirect path was significant while the direct path was insignificant.

5. Discussion and Conclusions

As previously mentioned, this research aimed to explore the influence of CUST, ENTR, TRND, and INTR (SMMAs) on social media followers’ PI and CS in terms of casual-dining restaurants in Saudi Arabia. Furthermore, to determine the influence of CS on followers’ PI. Additionally, to empirically investigate the intermediating effect of CS in the CUST-PI, ENTR-PI, TRND-PI, and INTR-PI relationships. This study’s hypotheses tests have yielded substantial discoveries, including the following: first, three of the SMMAs namely CUST, ENTR, and INTR have a significant positive influence on restaurant social media followers’ PI. Customization activities were the most effective, followed by ENTR, and INTR. These findings foster the results of the previous studies, which suggested that SMMAs significantly affected PI [2,16,17,20,89]. More specifically, the study’s findings support those concluded by Moslehpour et al. [20] who revealed that ENTR was the only activity that significantly encouraged PI. This also fosters the finding of Kim and Ko [21] who demonstrated that ENTR and INTR were the only activities that significantly positively affected PI. On the other hand, these findings were inconsistent with those concluded by Wijayaa et al. [67] who indicated that CUST is the only significant factor in the PI of Indonesian smartphone consumers. As a result, it appears to be suggested that the more customized, entertaining, and interactive restaurant social media marketing is, the greater the perceived influence it is likely to have on its followers’ PI. Second, contrary to the expectations, the findings of the study revealed that the influence of TRND activities on followers’ PI was insignificant, implying that by just incorporating trending topics into their posts and keeping up with what is the latest information and popularity in their industry, casual-dining restaurants may not be able to significantly contribute to encouraging PI. These findings were in line with the results of the prior studies, which assured the insignificant relationship between TRND and PI in the luxury fashion brands and Indonesian smartphone industry contexts [21,67].

Third, in terms of the influence of SMMAs on CS, the findings revealed that all of the examined activities significantly contributed to increasing CS. In other words, TRND followed by INTR, ENTR, and CUST activities significantly positively affected CS, respectively. These findings support the significant positive link between SMMAs and CS, which was confirmed in earlier studies (i.e., [3,5,70]) signifying the substantial role of SMMAs in predicting CS. Khashman [90] highlighted that for companies to be successful in enhancing CS, it is necessary for them to go beyond customer requirements, make use of social networking sites, such as Instagram and Twitter, and monitor comments and conversations on their associated online platforms. In addition, when customers feel that their values and preferences are being considered in the products and services they receive, it may build trust and increase their satisfaction [91]. Hence, it can be deduced that there is likely to be an elevated level of customer satisfaction if casual-dining restaurant marketers stay up to date with trends in their industry, have an individualized approach when interacting with customers; respond in a timely manner to customer queries and complaints, create entertaining content; and tailor their messages to the appropriate customer segment.

Fourth, the findings also illustrated that followers’ purchase intention is significantly positively influenced by CS, confirming the vital role of CS in predicting PI, which has been mentioned in different settings. The earlier studies assured that when customers feel satisfied with the products or services that they receive, it creates an emotional connection that makes them more likely to make purchases in the future [13,14,41,51]. Accordingly, it is important to emphasize that when customer satisfaction is perceived to be high, customers are more likely to view casual-dining restaurants favorably, resulting in an increased likelihood of purchase intention.

Fifth, regarding the mediating effect of CS in the SMMAs–PI relationship, the research findings demonstrated a significant positive partial mediation effect on CUST-PI, ENTR-PI, and INTR-PI relationships as well as a significant positive full mediation effect on the TRND-PI relationship, indicating the substantial mediation role of CS in how successful social media marketing activities are in influencing customer purchase decisions. In other words, the findings of this research demonstrated that by augmenting the trendiness, interactivity, entertainment, and customization of their social media marketing, restaurants have the potential to increase customer satisfaction. Consequently, this would result in an improved likelihood of customers’ purchase intention. These findings agreed with the conclusions of Jamil et al. [3] that customer satisfaction plays a significant intermediating role in the connection between SMMAs and customers’ intentions to make purchases. As a result, it could be suggested that the more trendy, interactive, and personalized social media marketing a restaurant employs, the higher customer satisfaction they are likely to perceive, which subsequently leads to a higher likelihood of customers’ intention to make a purchase.

In summary, it could be suggested that effective social media marketing activities coupled with customer satisfaction are critical components of business sustainability particularly economic sustainability. Effective social media marketing activities enable businesses to reach a wider audience than traditional marketing methods. This has opened up gateways to new markets and higher sales. Additionally, social media platforms have analytical tools to help businesses analyze feedback from customers, which can lead to better products and services that meet the needs of customers. Customer satisfaction leads to higher customer loyalty, which translates to repeat business and an increase in purchase intentions. This will lead to higher customer lifetime value and reduce churn rate, which is essential for translating social media marketing into increased revenue growth and overall business sustainability.

6. Theoretical and Practical Implications

6.1. Theoretical Implications

This research has extensively added to the literature on the influence of SMMAs including CUST, ENTR, TRND, and INTR on CS and PI within the casual-dining restaurant industry. This study provides an in-depth understanding of the essential SMMAs that had a marked, significant impact on CS enhancement (i.e., TRND, INTR, ENTR, and CUST) and improving followers’ PI (i.e., CUST, ENTR, and INTR) in the restaurant industry context. The finding revealed that CUST is the most effective variable in encouraging PI, meanwhile, TRND was the most effective variable in encouraging CS. These research findings contribute to the literature, which suggests that social media marketing strategies are becoming increasingly important in influencing customer behavior. Furthermore, regarding another novel contribution to SMM literature in the restaurant industry context, the findings of the study emphasized the substantial mediating effect of CS in exploring how SMMAs positively influenced followers’ PI toward restaurant products and services. To the best of the authors’ knowledge, this is the first study that examines the influence of SMMAs on followers’ PI in the existence of CS within the restaurant industry context. Furthermore, the research also confirmed the key role that CS plays in predicting the purchase intentions of social media followers. This provides further evidence of the potential power of CS in driving purchase decisions and contributes to the existing research on customer satisfaction and purchase intentions, particularly in SMM. In addition to the previous contributions, the findings also contributed to the extension of using the Stimulus-Organism-Response (S-O-R) model in social media marketing settings. Based on this model, SMMAs including TRND, INTR, ENTR, and CUST (stimuli), respectively, contributed to enhancing CS (organism), which sequentially leads to an increase in followers’ PI. Finally, this empirical investigation formulated and validated a novel model that encompasses CUST, ENTR, TRND, and INTR of social media marketing along with CS and PI. It has provided a noteworthy addition to the existing literature on SMM, which may be employed as a guidepost for future studies.

6.2. Practical Implications

The findings of this study provide important implications for restaurant operators and marketers that should be taken into consideration. Firstly, based on the study findings, CUST, ENTR, and INTR of social media marketing significantly promoted restaurant social media followers’ PI. Hence, restaurant operators and marketers looking to increase the PI of their social media followers should focus more heavily on customization, entertainment, and interaction in their social media marketing. This could include creating tailored posts that are relevant to the target audience, creating interesting and appealing social media posts, creating engaging content such as recipes and cooking tips that will draw people in, sharing interesting photos of dishes to generate interest and excitement, sharing customer reviews and testimonials to create authentic engagement and trust, running special promotions and contests on social media to drive customers to their restaurants, using exclusive offers and discounts to encourage customer purchase intentions, and finally tracking customer feedback and responding quickly to customer inquiries and complaints. All of these practices will substantially play an effective role in encouraging restaurant social media followers’ intention to purchase. Secondly, the findings also show the substantial effect of all the examined SMMAs on CS, particularly TRND. As a result, restaurant operators and marketers should strive to create and implement social media strategies that emphasize trendiness and stay up to date with consumer preferences. Additionally, they should focus on creating content that is visually appealing and attention-grabbing and ensure it is trendy. Furthermore, they should track their analytics to better understand customer behavior and preferences and use this data to make informed decisions about their social media strategies in order to ensure that their SMMAs are having the desired effect on customer satisfaction. Thirdly, our research showed that CS significantly contributed to enhancing restaurant followers’ PI and serves as a mediator between social media marketing activities, such as customization, entertainment, trendiness, interaction, and followers’ PI. Thus, when customers find value in the content or have a positive experience interacting with a brand on social media, it can lead to increased customer satisfaction, which, in turn, increases their PI. Accordingly, focusing on improving and maintaining customer satisfaction through social media activities and engagement is essential. By actively monitoring customers’ satisfaction, restaurant operators and marketers can create stronger relationships with their customers, which can lead to a higher purchase intention rate.

7. Research Limitations and Future Directions

This study has some limitations, such as its narrow focus on just casual-dining restaurant followers on social media in Saudi Arabia. Therefore, the results may not be applicable to other contexts. To gain further insights, additional research employing a larger and more varied sample size in other food service sector contexts would be beneficial. Furthermore, this study focused on the potential of CS to act as a mediator in the relationship between SMMAs and purchase intention. To add to the findings of this study, further research should investigate other potential mediating factors such as customer trust and engagement to gain a better understanding of the mechanisms affecting these relationships. Additionally, this study explored the influence of social media marketing activities on purchase intention. To gain a more comprehensive view of the impact of SMMAs on consumer behavior in the restaurant industry context, further research could examine their influence on other behavioral intentions such as repurchase intention, willingness to pay more, and intention to engage in positive e-word-of-mouth. Furthermore, the characteristics of the surveyed participants, including age, educational background, and period of social media usage, could potentially moderate the connection between SMMAs and users’ PI, although this has not been surveyed in the present study. Subsequent studies should evaluate the possible moderating effects of these elements in the relationships previously mentioned. Finally, another limitation relates to the methodology of data collection, which relied on the online questionnaire. To gain a more comprehensive understanding of the study’s subject, a combination of quantitative and qualitative methods may be more advantageous.