The Power of Digital Engagement: Unveiling How Social Media Shapes Customer Responsiveness in the Food and Beverage Industry

Abstract

Social media platforms have become essential tools for businesses aiming to engage audiences through innovative communication, particularly in the food and beverage industry. This study explores the impact of three core digital marketing strategies, namely, social media advertisements, electronic word of mouth, and digital influencers, on customer responsiveness in the Lebanese food and beverage sector. Based on a cross-sectional survey of 400 participants, the findings reveal that social media advertisements significantly and positively influence customer responsiveness (β = 0.227, p < 0.001). Likewise, electronic word of mouth strongly predicts customer responsiveness (β = 0.453, p < 0.001), affirming the power of customer-generated content in shaping brand perceptions. Furthermore, the presence of digital influencers emerged as a significant predictor of consumer reaction (β = 0.236, p < 0.001), suggesting that consumers regard influencers as credible sources when making food-related decisions. Among all predictors, electronic word of mouth demonstrated the strongest effect. Control variables such as gender, age, and social media usage intensity showed no significant effect on customer responsiveness. These findings underscore the strategic value of rich media content and peer influence in shaping consumer behavior in the food and beverage industry. The study offers practical insights for marketers seeking to enhance customer engagement and brand responsiveness in digital spaces.

1. Introduction

Social media has become extremely embedded in consumers’ daily lives, prompting widespread interdisciplinary research due to its transformative effect on communication, business practices, and human behavior (Dodds et al., 2024; Maalouf et al., 2024). Its integration into marketing strategies has revolutionized how businesses engage with audiences, using tools such as influencer partnerships, targeted advertisements, and user-generated content campaigns (Kumar et al., 2024). These tools allow businesses to deliver personalized, visual, and interactive content that resonates with consumers in a fast-paced digital environment (Atherton, 2023; Okonkwo & Awad, 2023). Particularly, social media facilitates global outreach (Nair & Kumar, 2024) and dynamic customer-brand interactions that are increasingly shaping modern consumer behavior.

Among the sectors most affected by this shift is the Food and Beverage (F&B) industry. Social media’s visual nature makes it an ideal channel for promoting culinary products and experiences, including ambiance, food aesthetics, and menu offerings. It has become a strategic avenue for showcasing dishes, reaching potential customers, and encouraging feedback and engagement (Kulkarni, 2025). In this study, the F&B industry includes businesses such as restaurants, cafés, and fast-food outlets operating in Lebanon. These businesses heavily rely on social media to market their services, build brand awareness, and foster customer loyalty.

Despite the widespread use of social media in the F&B sector, the specific ways in which these platforms influence consumer behavior, particularly customer responsiveness, remain underexplored. Customer responsiveness, which refers to how customers react to marketing efforts through behaviors like inquiries, visits, purchases, and feedback, is a critical performance metric for F&B businesses. Understanding the digital pathways that shape customer responsiveness is especially vital in Lebanon, where political instability, economic hardship, and the aftermath of the COVID-19 pandemic have compounded the operational challenges for F&B establishments (Al Maalouf & Al Baradhi, 2024; Al Maalouf et al., 2023; Jabbour Al Maalouf et al., 2024; Yacoub & Al Maalouf, 2023).

This study investigates how key social media engagement mechanisms, namely, social media advertisements (SMAs), electronic word of mouth (e-WOM), and social media influencers (SMIs) affect customer responsiveness in Lebanon’s F&B industry. These components represent not only the tools available to marketers but also the behaviors and perceptions of customers exposed to them. The study leverages two theoretical perspectives: media richness theory (Daft & Lengel, 1986), which explains the persuasive power of rich digital media, and social influence theory (Kelman, 1958; Deutsch & Gerard, 1955), which accounts for the influence of peer-generated content and opinion leaders on individual behavior. Together, these frameworks guide the investigation into how digital communication formats and social dynamics influence customer reactions.

The research question driving this study is “What is the impact of social media on customer responsiveness in the F&B industry in Lebanon?” The following sub-questions are addressed:

RQ1: What is the impact of social media ads on customer responsiveness in the F&B industry in Lebanon?

RQ2: What is the impact of e-WOM on customer responsiveness in the F&B industry in Lebanon?

RQ3: What is the impact of social media influencers on customer responsiveness in the F&B industry in Lebanon?

To explore these questions, a quantitative approach was employed using a self-administered online questionnaire targeting 400 respondents. The collected data underwent exploratory and confirmatory factor analysis to assess construct validity, followed by Structural Equation Modeling to evaluate the proposed relationships between social media engagement and customer responsiveness.

Building on existing knowledge, this research provides a novel empirical investigation into how social media marketing elements, specifically ads, e-WOM, and influencers, shape customer responsiveness in the unique context of Lebanon’s F&B industry. It contributes both academically, by extending theoretical understanding in emerging and crisis-prone markets, and practically, by guiding strategic digital engagement, where digital transformation is both a challenge and an opportunity for survival and growth.

This paper proceeds as follows: Section 2 provides a review of the literature and the theoretical framework. Section 3 describes the methodology used. Section 4 presents the study’s findings. The paper concludes with key contributions, implications, and suggestions for future research.

2. Literature Review

2.1. Social Media Ads and Customer Responsiveness in the F&B Industry

Ample literature delved into the nexus between social media advertisements and customer responsiveness in the F&B realm. Acar et al. (2021) pinpointed that consumers who actively engage with social media F&B-related content are often swayed by social media ads sharing customers’ experiences and choices in the selection of food or beverages. Along these lines, Wareebor et al. (2025) postulate that social media restaurants’ promotional ads significantly influence consumers’ intentions to share the restaurants’ posts offering online food sales or promotions, and this engagement is, in turn, a strong predictor of their online food buying intentions. Further to this, social media video advertisements are heightened as creative advertising elements, which advance effectiveness in swaying consumers’ responses via media involvement and customer engagement with social media advertisements (Yang et al., 2022; Elder et al., 2025). In the same vein, Sreejesh et al. (2020) intend that media interactivity and social media ads’ relevant communicated message aspects, both mitigate consumers’ attention and reaction towards social media advertisements, signaling informational social media content to exert the most influence on customer responsiveness. T. N. Lam (2023) highlights that customers are most likely to respond positively to F&B brands when they perceive social media tools as user-friendly and beneficial. In this perspective, Singh (2022) provides a refined study model for digital engagement strategy in the F&B industry, highlighting the strategic imperatives for F&B brands to enhance customer engagement and responsiveness through strategic digital initiatives. Plus, Alagappan (2023) notes that social media engagement, reflected through likes, comments, shares, and video views, serves as a key indicator of customer responsiveness in the F&B industry. By leveraging social media engagement effectively, F&B brands can enhance customer responsiveness and drive business success in the digital age. As such, based on the findings of prior studies, the following hypothesis is stipulated:

H₁: 

Social media ads have a positive impact on customer responsiveness in the F&B industry.

2.2. e-WOM and Customer Responsiveness in the F&B Industry

In today’s digital era, e-WOM has become an indispensable tool for communication, information sharing, and marketing intermediaries for businesses in the F&B industry, as it facilitates access to desired information and organizes both the quality and structure of the circulating information (Bushara et al., 2023). Stratified findings have outlined several players in rendering e-WOM, notably the degree of competition merchants face in the catering industry negatively influencing e-WOM, while the services of reservation and group buying are positively associated with e-WOM (Hao et al., 2023). Within this realm, restaurant authenticity is recognized to shape diners’ e-WOM intention, while both service quality and customer satisfaction mediate such correlation (H. P. Lam & Nguyen, 2024). Also, Puspita and Dhewi (2022) found that F&B companies that provide e-service quality establish a direct positive and significant effect on e-WOM. Conversely, recently delivered results outline e-WOM linked with different angles of customer responsiveness. Duong et al. (2025) stipulate that F&B brand image, tailored by conveying unverified news via social media platforms, mediates the relationship between e-WOM and consumers’ buying intentions. In the same perspective, e-WOM is conceptualized to be an influential factor in consumers’ purchase intent in the context of the fast-food industry (Shashikala & Thilina, 2020); on their perceived value of food products and services (Tsaia & Wang, 2023); and on customers’ attraction and loyalty (Widjaya et al., 2022). Following Haverila et al. (2024), e-WOM is significant in tailoring consumers’ decisions and choices about F&B products or services, alongside their responsiveness, since it entails an online marketing mix covering an exchange of negative and positive opinions and reviews based on former customers’ experiences of a good restaurant or food service. Additionally, Suhaily and Soelasih (2017) postulate that information gathered from e-WOM positively and significantly impacts the intention to purchase a food product. Likewise, Chatzigeorgiou (2017) suggests that e-WOM is a process of personal influencing, where positive and satisfying consumer experiences can enhance positive word of mouth, leading to repeat restaurants’ drop-in and increased online sales. Further to this, Ramadan et al. (2018) highlight the significant sway of e-WOM on consumer responsiveness in the F&B realm; as such, customers’ online feedback and comments, including product recommendations, influence their engagement with F&B-delivered products and services, as well as their purchase intentions. In turn, Joshi et al. (2025) suggest that the F&B brand’s partnership with influential figures on social media contributes to spreading positive reviews and experiences, reaching a wider audience, thereby building consumers’ perceived brand credibility and trust, ultimately enhancing the positive image of the F&B brand. Hence, based on prior evidence, the following hypothesis is formulated:

H₂: 

e-WOM has a positive impact on customer responsiveness in the F&B industry.

2.3. Social Media Influencers and Customer Responsiveness in the F&B Industry

Influencer marketing exhibits considerable potential in advocating healthy food options and swaying social media users’ purchasing choices of healthy promoted food products via strong online ties and parasocial interactions built with their followers, leading to online trust (Folkvord & Hermans, 2020). According to Vrontis et al. (2021) and Manaf (2021), social media influencers (SMI) exert a significant impact on consumer responsiveness in the F&B industry. Also, Satı and Kazancoglu (2020) delineate that influencers’ published content holds considerable power on customers’ purchasing decisions, particularly in exploring and experiencing food offerings. In effect, online consumers often make dining decisions after engaging with influencer posts that showcase the taste and overall experience of trying different cuisines. Influencers play a crucial role as trusted guides, leading followers to discover new dishes, menus, and dining venues (Chen et al., 2018; Silver et al., 2019). In turn, Jamil et al. (2022) explored the influence of SMIs on customer responsiveness within the F&B industry and pinpointed how the presence, endorsements, and collaborations with digital influencers contributed to enhancing brand engagement and responsiveness among customers. In the same vein, food influencers are presented as a new line of inquiry in recent years and are depicted as influencers who use their social media platforms to deliver home-cooking recipes, share cooking tips, and do restaurant reviews with their following audience (Weber et al., 2021). Satı and Kazancoglu (2020) evidenced that food influencers sway consumers’ food-buying choices by conveying food products or service-related information. Likewise, Sokolova et al. (2024) articulate that social media users’ food-related purchasing decisions are based on social media food influencers’ recommendations. Based on the heightened previous observations, the following hypothesis is suggested:

H₃: 

Social media influencers have a positive impact on customer responsiveness in the F&B industry.

3. Theoretical Background

This study integrates two theoretical lenses to examine the mechanisms through which social media engagement shapes customer responsiveness in the F&B industry, namely, media richness theory (MRT) and social influence theory (SIT).

First, MRT, which was proposed by Daft and Lengel (1986), posits that communication media differ in their ability to convey information effectively. Media richness is defined by the capacity of a medium to facilitate shared understanding through immediate feedback, multiple cues, personalization, and language variety. Social media platforms offer high richness through multimedia content (videos, images, live stories), which enhances the clarity, emotional appeal, and engagement potential of digital advertisements. Rich media can reduce ambiguity and strengthen message comprehension, which is particularly critical in marketing contexts where persuasion and engagement are essential (Dennis & Kinney, 1998). Within the F&B context, Shandy et al. (2023) provide empirical evidence that social media richness, particularly through video and interactive content, significantly enhances consumer engagement and brand equity for small restaurants and food businesses, confirming MRT’s relevance in this domain.

Further, SIT, which was discussed by Deutsch and Gerard (1955) and Kelman (1958), explains how individuals’ attitudes and behaviors are shaped by the influence of others in their social environment. SIT identifies three main processes, which are compliance, identification, and internalization. Those three guide how social actors affect decisions. Within digital ecosystems, e-WOM serves as a powerful form of informational and normative social influence, where user-generated content such as reviews, comments, and shares shapes consumer decisions (Cheung & Thadani, 2012). Similarly, social media influencers act as credible opinion leaders, driving consumer behavior through identification and perceived expertise (Lou & Yuan, 2019). Their endorsements, content styles, and authentic interactions foster trust and engagement, thereby enhancing customer responsiveness toward promoted F&B brands and products. Dinc (2023) demonstrated that trust in influencer content significantly affects restaurant selection behavior, supporting the influence of digital endorsements on F&B responsiveness.

By leveraging these theoretical perspectives, the current study postulates that the richness of social media ads (H₁) and the social influence exerted through e-WOM (H₂) and social media influencers (H₃) collectively shape consumer responsiveness in the Lebanese F&B industry.

As such, all studied determinants are conceptualized in the developed study model presented in Figure 1.

This study focuses on Lebanon as a context due to its dynamic yet underexplored F&B market in digital transformation. In this study, the F&B industry refers to businesses such as restaurants, cafés, and fast-food outlets operating within Lebanon. These businesses increasingly rely on digital platforms to engage with consumers, especially through social media.

It is expected that by 2025, revenues in the F&B market in Lebanon will amount to USD 6.35bn, as the industry is experiencing mild growth and is expected to expand annually by 8.66% (Statista, 2025). The rising demand for convenience food, the popularity of traditional Lebanese cuisine, along the increasing awareness of healthy eating among consumers are all contributing factors to the expansion of the Lebanese F&B market incomes. 3.4% of total generated revenue is reserved for online sales in 2025 (Statista, 2025). Within this realm, many trends are underscored in the F&B Lebanese industry. Notably, the F&B market is experiencing a surge in online food delivery services, as Lebanese consumers heighten convenience, prompting more businesses to invest in digital platforms and delivery logistics (Al Maalouf et al., 2025). Further to this, there is a growing demand for healthier, organic, and locally sourced food products, as Lebanese society is now more health-conscious and environmentally aware, which has resulted in a surge in specialty food stores and farmers’ markets (Statista, 2025). As such, these trends are not only tailoring Lebanese consumers’ preferences but also offering opportunities for F&B industry players to expand their market reach and streamline operations via technological advancements.

Prior observations evidenced how the significant presence of social media is swaying the Lebanese F&B landscape. Bakkar and Hawi (2021) delineated favorable links between Lebanese cuisine restaurants’ brand loyalty and social media marketing activities, urging Lebanese restaurants to put more effort towards e-WOM on social media sites, notably, promotion and customization marketing tools. Ghanem (2022) posits that the F&B industry in Lebanon is influenced by the evolution of online platforms, e-commerce, e-reputation, influencers, and changing consumer activism. Influencer marketing has distinct preferences among audiences, with followers favoring content related to restaurants, food consumption, and cuisines. Internet users seek information that enhances their consumption decisions and inspires them, as well as promotional offers and unique news about brands and products. Additionally, Mawlawi et al. (2023) suggest that Lebanese consumers’ engagement has undergone a significant shift through social media platforms and influencers, transforming them from passive observers to active participants in their purchasing decisions.

These contextual insights demonstrate Lebanon’s suitability for investigating how digital engagement strategies (social media ads, e-WOM, and influencer marketing) impact customer responsiveness in the F&B industry. The country’s unique socio-economic environment presents a valuable case for exploring the effectiveness of social media-driven marketing in an emerging, crisis-prone economy.

4. Methodology

This research employs a positivist study philosophy and a deductive approach, alongside a quantitative method that was employed in the making of this investigation. A self-report questionnaire was circulated using closed-ended questions for demographic factors and a five-point Likert scale stratified from 1 = Strongly Agree to 5 = Strongly Disagree for the examined dependent and independent variables. Thus, the designed online cross-sectional survey was structured into three parts: The first section tackles the socio-demographic variables, including age, gender, their involvement within social media (SM) marketing and the Lebanese F&B industry, while the second section is reserved for social media measurements and the final section covers participants’ responsiveness as customers of the F&B sector.

To ensure measurement consistency and alignment with the study’s objectives, each construct was assessed using multiple items adapted from validated instruments in prior studies, as shown in

Table 1. Summary of constructs and sources.

Construct	# of Items	Adapted From
SMA	8	Acar et al. (2021); Wareebor et al. (2025)
e-WOM	6	Bushara et al. (2023); Jeong and Jang (2011)
SMI	5	Vrontis et al. (2021); Sokolova et al. (2024)
CRI	7	Cheng et al. (2024); Nguyen (2021)

. The SMA construct was measured using eight items adapted from Acar et al. (2021) and Wareebor et al. (2025). The e-WOM construct included six items adapted from Bushara et al. (2023) and Jeong and Jang (2011). The SMI construct comprised five items adapted from Vrontis et al. (2021) and Sokolova et al. (2024). Lastly, customer responsiveness (CRI) was captured using seven items adapted from Cheng et al. (2024) and Nguyen (2021). All items were rated on a five-point Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree).

To ensure linguistic and cultural appropriateness of the measurement scales in the multilingual Lebanese context, all survey items originally developed in English were translated into Arabic using a double-translation approach. First, a bilingual expert translated the instrument into Arabic, followed by a back-translation into English by an independent translator to verify semantic equivalence. Discrepancies were discussed and resolved collaboratively. Moreover, the translated version was reviewed by three academic experts familiar with the Lebanese F&B and marketing landscape to ensure cultural relevance and clarity. A pilot test with 15 professionals confirmed the instrument’s clarity and contextual appropriateness, leading to minor wording adjustments where needed.

Participants in the cross-sectional survey were provided with substantial information about the research objectives, data usage, and their rights as research subjects. All the respondents provided written informed consent, validating their voluntary consensus to partake in this study. Also, ethical consideration was held regarding the provision of server confidentiality; thereby, all of the participants’ names were not disclosed for privacy reasons. Lastly, ethical approval was secured from the Research Ethics Committee (REC) of the Higher Center for Research (HCR) at the Holy Spirit University of Kaslik under the number HCR/EC 2025-040.

To ensure comprehensive representation in the context of customer responsiveness, across diverse customer sociodemographic information within Lebanon’s F&B establishments, a non-random convenience sampling technique was employed. This technique was selected due to its practical advantages in reaching active social media users who engage with restaurants, cafés, fast-food outlets, and other F&B businesses. Given the limitations in accessing a complete sampling frame, convenience sampling was deemed appropriate to efficiently gather data from a digitally engaged population relevant to the study’s objectives. A sample of 400 respondents was obtained after collecting data from the circulated questionnaires via Google Forms from April 2025 to May 2025. To examine the relationships among the key constructs, structural equation modeling (SEM) was employed. The analysis was conducted using JASP (Version 18.3). SEM was chosen over simpler regression techniques because it allows for the simultaneous testing of multiple interrelated hypotheses, assessment of the measurement model’s validity and reliability, and evaluation of the structural model within a comprehensive, theory-driven framework grounded in MRT and SIT. The use of SEM in this study ensured a more rigorous and holistic evaluation of the relationships between the observed indicators and their respective latent variables, while also testing the hypothesized paths across constructs in a single, integrated model.

5. Results

5.1. Sample Profile

As illustrated in

Table 2. Sample profile.

Category	Subcategory	Percentage (%)
Gender	Female	55.3
	Male	44.7
Age	Between 18 and 24 years	35.2
	Between 25 and 31 years	26.4
	Between 32 and 38 years	19.7
	Above 38 years	18.7
Social Media Usage	1 to 2 years	13.4
	3 to 4 years	18.3
	More than 4 years	68.3

, the gender distribution outlines that 55.3% of the participants are female, while 44.7% are male. Regarding respondents’ age, most of them fall either within the 18–24 age group (35.2%), or within the 25–31 age group (26.4%). Regarding social media usage (SMU), the majority of the participants have experience with using social media for more than four years (68.3%), and only 13.4% have used social media for 1 to 2 years.

5.2. Factor Analysis

To evaluate the dimensional structure and validity of the measurement scales used in this study, an exploratory factor analysis (EFA) was conducted. The main objective of this analysis was to examine whether the observed survey items correctly represented their respective latent constructs. The Kaiser–Meyer–Olkin (KMO) test yielded a value of 0.903, indicating excellent sampling adequacy for factor analysis. Additionally, Bartlett’s test of sphericity was significant (χ² = 9162.870, df = 325, p < 0.001), confirming that the correlation matrix was suitable for factor extraction.

Table 3. Kaiser–Meyer–Olkin (KMO) test.

Indicator		MSA
SMA1: When I choose an F&B business, I make sure it is popular on social media.		0.952
SMA2: I am easily drawn to F&B businesses offering free delivery through social media.		0.934
SMA3: Social media ads affect my decision in selecting F&B businesses.		0.928
SMA4: I am affected by the video ads shared by F&B businesses on social media.		0.946
SMA5: I am easily attracted by percentage-off promotions (ex., buy 1 get 1 free) from F&B businesses selling online through social media.		0.924
SMA6: Social media ads are important information sources during my F&B business selection process.		0.942
SMA7: I collect information about the F&B business on social media before visiting it.		0.933
SMA8: I think that F&B businesses on social media offer better-quality services.		0.936
SMI1: Reading comments made by social media influencers increases my perceived credibility towards the influencers and F&B businesses.		0.842
SMI2: If the social media influencer’s content about F&B businesses fits my personality and interests, I am willing to follow the influencer’s advice.		0.868
SMI3: I engage with social media influencers’ campaign giveaways on social media.		0.824
SMI4: I rely on the recommendations made by influencers while choosing F&B businesses.		0.948
SMI5: The F&B items presented by the influencer on their social media accounts are attractive to me.		0.826
eWOM1: I check online opinions and comments that people write when they visit F&B businesses.		0.906
eWOM2: Satisfactory experiences with F&B service employees trigger me to express positive feelings on social media.		0.949
eWOM3: A positive experience with food influences and motivates me to post positive comments about the restaurant.		0.846
eWOM4: e-WOM about F&B businesses stimulates my interest in visiting them.		0.917
eWOM5: e-WOM communicates the image and values of F&B businesses.		0.904
eWOM6: Online recommendations from trusted people influence me to try F&B businesses.		0.897
CRI1: I know F&B businesses based on their social media presence.		0.895
CRI2: I am willing to take part in the F&B business’s social media promotional campaigns, such as discounts and giveaways.		0.866
CRI3: Based on social media feedback, I decide whether to visit or re-visit F&B businesses.		0.892
CRI4: I have a high level of interest in the rating and review section of an F&B business social media page.		0.910
CRI5: I am willing to try out sponsored or advertised F&B businesses that appear on my social media feed.		0.849
CRI6: I prefer not to wait a lot of time to receive social media responses from F&B businesses in terms of chat, message, comment, and feedback.		0.931
CRI7: Food and drinks promoted media are among my most interesting posts, followed by the content of discount and giveaway campaigns.		0.858
Overall		0.903
Bartlett’s test of sphericity
Χ2	df	p
9162.870	325	<0.001

presents the individual measure of sampling adequacy (MSA) scores for each item, all of which exceeded the acceptable threshold of 0.60, with most items scoring above 0.90. This indicates strong shared variance among variables within their respective constructs and justifies their inclusion in further analysis, such as SEM.

5.3. Validity and Reliability

The average variance extracted (AVE) values generally reflect the amount of variance a measured variable gains from its indicators relative to measurement error. An AVE value higher than 0.50 suggests that a construct explains more than 50% of the variance of its items, indicating good convergent validity. As shown in

Table 4. Average variance extracted.

Factor	AVE
Factor 1	0.682
Factor 2	0.613
Factor 3	0.532
Factor 4	0.580

, all factors have AVE above 0.50, positing strong convergent validity.

To further assess discriminant validity, the Fornell–Larcker criterion was applied. This approach requires that the square root of each construct’s AVE exceed its correlations with all other constructs. As shown in

Table 5. Fornell–Larcker discriminant validity matrix.

Constructs	Factor 1	Factor 2	Factor 3	Factor 4
Factor 1	0.826	0.514	0.612	0.514
Factor 2	0.514	0.783	0.622	0.533
Factor 3	0.612	0.622	0.729	0.643
Factor 4	0.514	0.533	0.643	0.762

, the diagonal values (square roots of AVE) are greater than the corresponding inter-construct correlations (off-diagonal elements), confirming discriminant validity among constructs.

The heterotrait–monotrait (HTMT) ratio is useful for examining discriminant validity, ensuring that constructs are distinct from one another. As shown in

Table 6. Heterotrait–monotrait ratio.

Factor 1	Factor 2	Factor 3	Factor 4
1.000
0.514	1.000
0.612	0.622	1.000
0.514	0.533	0.643	1.000

, all HTMT values are significantly lower than 0.85, implying strong discriminant validity among constructs.

As for reliability tests, all values of coefficient α and coefficient ω in

Table 7. Reliability tests.

	Coefficient ω	Coefficient α
Factor 1	0.941	0.943
Factor 2	0.835	0.896
Factor 3	0.875	0.868
Factor 4	0.884	0.910
total	0.926	0.947

are higher than 0.7, pointing out that all constructs are reliable.

5.4. Assessment of the Measurement Model

The model was evaluated using multiple fit indices, including the comparative fit index (CFI), Tucker–Lewis index (TLI), standardized root mean square residual (SRMR), and root mean square error of approximation (RMSEA). As shown in

Table 8. Model Fit.

Index	Threshold	Value Obtained	Interpretation
CFI	≥0.90 (acceptable)	0.948	Good fit; model compares well to a null model.
	≥0.95 (excellent)
TLI	>0.90 (good)	0.911	Good fit; adjusts for model complexity.
	>0.95 (excellent)
SRMR	<0.08 (good)	0.044	Excellent fit; low standardized residuals.
	<0.05 (excellent)
RMSEA	<0.05 (excellent)	0.04	Excellent fit; minimal approximation error.
	0.05–0.08 (reasonable)
	>0.10 (poor)

, all values meet or exceed commonly accepted thresholds, indicating a good overall model fit.

Table 9. SEM results.

Outcome	Predictor	Estimate	Std. Error	z-Value	p
CRI	SMA	0.227	0.058	3.941	<0.001
	SMI	0.236	0.064	3.68	<0.001
	eWOM	0.453	0.085	5.315	<0.001
	Gender *	0.001	0.042	0.016	0.987
	SM Usage *	−0.029	0.037	−0.783	0.434
	Age *	−0.046	0.033	−1.394	0.163

entails the results of the SEM.

First, social media ads significantly and positively predict customer responsiveness in the F&B industry (β = 0.227, p < 0.001). This confirms that the more social media users engage with F&B-related online promotions on social media, their customer responsiveness is amplified.

Second, SMI is found to be a positive predictor of customer responsiveness (β = 0.236, p < 0.001), suggesting that social media influencers’ endorsed content for F&B businesses positively affects consumers’ reactions towards those businesses’ related services and products. This shows that Lebanese customers perceive social media influencers as a credible source to retrieve information valuable to make F&B purchases, visit new restaurants, or try new menus.

Third, e-WOM significantly and positively predicts customer responsiveness (β = 0.453, p < 0.001). Thus, e-WOM is a powerful advertising tool on social media platforms. The more F&B businesses invest in e-WOM for their digital marketing strategies, it creates a sense of instant gratification for customers, which leads to higher customer responsiveness.

Finally, gender, social media usage intensity, and age were included as control variables denoted by a “*” in Table 9. None showed a statistically significant effect on customer responsiveness, and their inclusion did not alter the strength or significance of the main predictors.

6. Discussion

6.1. Association Between Social Media Ads and Customer Responsiveness in the F&B Industry

The findings show that social media ads positively amplify customer responsiveness in the F&B sector (β = 0.227, p < 0.001), supporting H₁. The more social media users engage with F&B-related ads on social networks, the better their responsiveness towards the promoted F&B businesses. This result is in coherence with previous observations, such as Acar et al. (2021), who outline that consumers who actively engage with social media F&B-related content often are swayed by social media ads sharing customers’ experiences and choices in the selection of food or beverages. It also joins the findings of T. N. Lam (2023), Singh (2022), Alagappan (2023), Wareebor et al. (2025), Yang et al. (2022), and Elder et al. (2025), which highlight that social media restaurants’ promotional ads significantly influence consumers’ intentions to share the restaurants’ posts offering online food sales or promotions. Thus, customers are most likely to interact with F&B brand advertisements on social media platforms as they perceive these digital tools as user-friendly and valuable, aligning with this study’s result.

6.2. Association Between e-WOM and Customer Responsiveness in the F&B Industry

The results show that e-WOM positively sways consumers’ customer responsiveness to F&B businesses (β = 0.453, p < 0.001), supporting H₂. This postulates that e-WOM is an influential digital tool that tailors customers’ reactions toward the promotions and offers exhibited by F&B businesses online. This conclusion is congruous with prior findings pinning the nexus between e-WOM and consumers’ purchase intent in the context of F&B (Shashikala & Thilina, 2020; Haverila et al., 2024; Suhaily & Soelasih, 2017), their perceived value of food products and services (Tsaia & Wang, 2023), and customers’ attraction and loyalty (Widjaya et al., 2022; Puspita & Dhewi, 2022; Duong et al., 2025). In addition, our result is harmonious with the findings of Chatzigeorgiou (2017) who intended that e-WOM improves the satisfaction of consumers’ experiences and their online feedback and comments, leading to repeat restaurant visits, and Ramadan et al. (2018) who evidenced that e-WOM boosts customers’ engagement with F&B delivered products and services, as well as their purchase intentions.

6.3. Association Between Social Media Influencers and Customer Responsiveness in the F&B Industry

Third, the results elucidate that SMIs are active players, rendering consumers’ customer responsiveness (β = 0.236, p < 0.001), advocating H₃. Consumers are swayed by SMIs’ promotional content of F&B businesses. This agrees with prior findings depicted in Vrontis et al. (2021) and Manaf (2021), showing that SMIs’ published content holds considerable power on customers’ buying choices, notably in exploring and experiencing food offerings and discovering new dining venues, joining the results of Chen et al. (2018), Silver et al. (2019), and Jamil et al. (2022). In the same vein, Satı and Kazancoglu (2020) and Sokolova et al. (2024) suggested that food influencers are perceived as credible sources for convincing consumers to purchase recommended food or beverage products, echoing the study’s findings.

7. Theoretical Implications

This study contributes to theory by extending the application of the MRT and SIT to the context of digital marketing in the F&B industry, specifically within a Lebanese cultural setting.

First, it reinforces MRT as a robust framework for explaining how the richness of digital media via visual and interactive formats such as video ads, live stories, and multimedia posts enhances customer responsiveness. While MRT has traditionally been employed in organizational communication and decision-making, this study empirically demonstrates its applicability to consumer engagement in digital marketing, particularly in sectors where emotional resonance and immediacy are pivotal. By linking media richness to customer responsiveness, the findings support the theoretical assertion that rich media reduces ambiguity, facilitates understanding, and improves persuasive communication in dynamic and highly visual market environments like F&B.

Second, the study advances SIT by showcasing how both e-WOM and social media influencers function as digital agents of social persuasion. To our knowledge, this is among the first empirical studies to extend SIT to the context of F&B digital marketing in a developing economy, illustrating that compliance, identification, and internalization can be triggered in online environments through peer recommendations and influencer endorsements. This reinforces prior research on the role of perceived credibility, trust, and social validation in shaping online consumer behavior while offering new insights into how these mechanisms operate within culturally rich and economically volatile contexts like Lebanon.

Moreover, by integrating MRT and SIT into a unified conceptual framework, the study presents a dual-theoretical lens that captures both the technological and social dimensions of digital engagement. It highlights that customer responsiveness is not solely a result of message format (media richness), but also of social contextual cues (influence), offering a holistic and nuanced view of digital consumer behavior in social media environments.

Ultimately, this research contributes to the evolving theoretical discourse on digital consumer behavior by proposing and validating a model that bridges technological affordances (via MRT) and social dynamics (via SIT). This dual-theory approach opens new pathways for future research in digital marketing, consumer psychology, and cross-cultural social media communication, especially in the underexplored landscape of emerging markets.

8. Practical Implications

This investigation concludes that social media is a critical enabler of customer responsiveness in the F&B industry, notably via ads, e-WOM, and influencers. These findings are compelling for policymakers, food marketers, and F&B brand owners, aiming to enhance the overall responsiveness and acceptance of customers toward their F&B products and services. Specifically, examples of F&B businesses considered in this study include restaurants, cafés, fast-food chains, dessert shops, juice and smoothie bars, casual dining establishments, and specialty food outlets operating within Lebanon. These are businesses that rely heavily on social media presence to influence customer decisions and brand perception.

First, marketers should prioritize personalized digital interactions by tailoring content to customer preferences and behaviors. Initiatives such as online contests, giveaways, and collaborations with credible food influencers can generate excitement, build trust, and expand audience reach within local communities.

Second, F&B businesses are encouraged to promote user-generated content to foster authenticity and a sense of community, both of which are key drivers of customer loyalty. Encouraging satisfied customers to share their experiences on social media can amplify brand visibility and credibility.

Third, leveraging e-WOM as a strategic asset can be achieved by incentivizing positive online reviews and responding promptly to customer feedback. Such practices not only enhance brand reputation but also signal responsiveness and customer-centricity. Positive digital WOM, especially from peers or influencers, significantly boosts customer responsiveness.

Finally, regular monitoring of social media analytics is essential for optimizing campaign effectiveness. By tracking engagement metrics and audience sentiment, F&B marketers can refine their content strategies, ensuring continuous alignment with evolving consumer expectations.

In sum, the study highlights the need for a deliberate and data-driven digital strategy that integrates social influence, personalization, and interactivity, elements that are increasingly critical in today’s competitive F&B landscape.

9. Limitations and Future Studies

Although this study offers major valuable findings, it has some limitations that restrict its efficacy and the validity of its results.

Initially, a primary limitation stems from the cross-sectional survey design. This methodology captures data at a single point in time, providing a snapshot rather than insights into changes or developments over a period. Consequently, while we can identify associations and relationships between social media marketing and customer responsiveness, they are related at the time of data collection. Future longitudinal studies would be beneficial to track such dynamics.

Furthermore, due to the practical challenges of obtaining a comprehensive sampling frame of F&B customers across Lebanon, a non-probability convenience sampling technique was employed. While this approach allowed for efficient data collection, it inherently limits the generalizability of findings across diverse customer sociodemographic groups within Lebanon’s F&B establishments.

Further interventions in the context of the F&B sector can explore several areas to better comprehend the nexus between social media marketing and customer responsiveness. Investigating the impact of socio-political factors on consumer responsiveness towards F&B businesses during times of instability can provide valuable insights into adapting social media strategies. Additionally, exploring the effectiveness of localized content strategies tailored to diverse cultural and linguistic landscapes can shed light on content preferences among consumers. Future work can also consider investigating consumer perceptions of ethical and sustainable practices, and data privacy can provide valuable insights for shaping social media marketing strategies. Also, comparative studies benchmarking social media marketing strategies and customer responsiveness among F&B businesses across different cultures can identify the best practices and actionable insights for optimizing promotions. By exploring these research avenues, researchers and experts can deepen their visions of social media marketing dynamics and customer responsiveness within Lebanon’s unique socio-economic context, driving innovation and strategic decision-making in the F&B industry.

10. Conclusions

This study makes a distinctive contribution to the evolving field of digital marketing and consumer behavior by investigating the drivers of customer responsiveness within the Lebanese F&B industry. By integrating MRT and SIT, the study proposes a novel dual-theoretical framework that advances our understanding of how digital media content and social influence mechanisms jointly shape consumer reactions in emerging market contexts.

Theoretical contributions are twofold. First, the study extends the application of MRT beyond organizational communication by empirically validating its relevance in consumer-facing industries where visual appeal and message clarity are essential. Second, it broadens the scope of SIT to include digital forms of social persuasion such as e-WOM and influencer endorsements, demonstrating how these virtual interactions activate internalized behaviors like identification and trust, particularly in culturally rich and economically volatile settings like Lebanon.

Empirically, this research fills a gap by examining how specific digital marketing strategies affect customer responsiveness in the underexplored Lebanese F&B industry. By doing so, it contributes new data and context-specific insights to a literature base that has largely focused on Western or economically stable environments.

Finally, methodologically, the study applies a structured quantitative approach and validates its proposed model using established statistical procedures. This reinforces the rigor and replicability of its findings, offering a solid foundation for future comparative and longitudinal studies in similar emerging markets.

In brief, this study contributes a theoretically grounded and empirically supported framework that bridges technological affordances and social dynamics, offering scholars, practitioners, and policymakers actionable insights into enhancing consumer responsiveness in the digital age.