Tisya Farida Abdul Halim\[1\]<sup>\*</sup>,Raziff Jamaluddin<sup>2</sup>, Nuraini Abdullah<sup>3</sup>, Mohd Khairulnizam Zahari<sup>4</sup>, Nur Syuhadah Kamaruddin<sup>5</sup>, Bannu A/P Subramanian<sup>6</sup>

<sup>1,2,3,4,5,6</sup>Faculty of Business and Communication, Universiti Malaysia Perlis (UniMAP), S2-L1-20, Kampus UniCITI Alam, Sungai Chuchuh, 02100, Padang Besar, Perlis, Malaysia.

<table>
<tbody>
<tr class="odd">
<td>ARTICLE INFO</td>
<td></td>
<td>ABSTRACT</td>
</tr>
<tr class="even">
<td><p><em>Article history:</em></p>
<p>Received XX Month 2024</p>
<p>Revised XX Month 2024</p>
<p>Accepted XX Month 2024</p>
<p>Online first</p>
<p>Published 1 September 2024</p></td>
<td></td>
<td>This study investigates the impact of social media marketing on the performance of small and medium-sized enterprises (SMEs) in the restaurant industry in Penang. The primary aim is to explore how different social media platforms, content quality, and posting frequency influence key performance indicators such as service quality ratings and reviews. Employing a quantitative research design, the study collected data through surveys distributed to SME restaurant owners, co-owners, managers, workers, and others in Penang. The analysis revealed strong positive correlations between content quality (r = 0.828) and posting frequency (r = 0.805) with SME performance. The findings highlight the importance of high-quality, engaging content and optimal post-timing in maximizing customer interaction and business outcomes. These insights suggest that SMEs in Penang's restaurant industry can achieve a competitive edge and sustainable growth by effectively leveraging social media marketing strategies. The study contributes to the existing body of knowledge by providing empirical evidence on the effectiveness of tailored social media marketing strategies for SMEs, offering practical implications for business owners and policymakers. Future research could explore the integration of social media with other marketing elements and the impact of emerging digital tools on SME performance.</td>
</tr>
<tr class="odd">
<td><p><em>Keywords:</em></p>
<p>SME Performance</p>
<p>Social Media Marketing</p>
<p>Restaurant Industry</p>
<p>Content Quality</p>
<p>Customer Engagement</p>
<p>Digital Marketing Strategies</p>
<p><em>DOI:</em></p>
<p>10.24191/jcrinn.v9i2</p></td>
<td></td>
<td></td>
</tr>
</tbody>
</table>

# 

# INTRODUCTION

## The Digital Edge: Social media and SMEs

Social media platforms, such as Facebook, Instagram, and Twitter, have become common in contemporary business practices, allowing Small and Medium Enterprise (SMEs) to engage with customers and build brand awareness beyond traditional geographical limitations (Kaplan & Haenlein, 2010; Kietzmann et al., 2011). Most social media platforms that survived the last decade have shifted significantly in what they offer users. More than 88% of businesses use Twitter to promote their brands, and more than 50 million businesses have Facebook accounts (Dwivedi et al., 2021). For example, Twitter initially didn’t allow users to upload videos or images. However, more than 50% of the content viewed on Twitter now includes images and videos, enabling (SMEs) to engage with customers, promote products, and build brand awareness beyond traditional geographical limitations (Kaplan & Haenlein, 2010; Kietzmann et al., 2011).

The widespread adoption of the Internet in the 1990s sparked a revolution in global communication and information sharing. The 21st century has witnessed the rise of internet-based communication through social media platforms (Yamin, 2019). As of January 2021, over 4.66 billion internet users exist, with more than 4.2 billion actives on social media. People increasingly view social media applications as an essential part of daily life, moving their interactions to virtual platforms. According to Okazaki and Taylor (2013), content on social media can be presented audibly, graphically, textually, or in a combination of these modes. Consumer behavior, including awareness, information gathering, attitudes, and purchase decisions, is greatly influenced by these platforms. Social media has developed into a potent marketing and communication tool for SMEs. According to Okazaki and Taylor (2013), content on social media can be presented audibly, graphically, textually, or in a combination of these modes. Consumer behavior, including awareness, information gathering, attitudes, and purchase decisions, is greatly influenced by these platforms. Social media has developed into a potent marketing and communication tool for SMEs.

## Bridging the Digital Divide

By 2023, nearly 5.3 billion people, representing 65.7% of the world's population, were actively using the Internet. Of this total, 4.95 billion, or 61.4% of the population, were social media users (Ani Petrosyan, 2023). Social media has significantly altered the marketing landscape, especially for SMEs, in recent years (Doe, 2021). Penang, the culinary capital of Malaysia, boasts a vibrant tapestry of flavors influenced by Malay, Chinese, Indian, and Peranakan cuisines. As of 2020, its population stood at approximately 1.74 million residents, with the island city of Penang accounting for nearly 46% of the state’s population

In Penang, small and medium-sized businesses (SMEs), particularly eateries, find it difficult to successfully include social media marketing into their plans. Only 26% of SMEs use social media efficiently to reach potential customers and increase sales (Taneja & Toombs, 2014). These establishments face significant challenges in reaching a wider audience, engaging with customers in real time, and establishing brand loyalty, impacting their competitiveness. The rapid advancement of digital technology and increasing reliance on online platforms underscores the importance of social media marketing. However, many SMEs in Penang lack the resources, expertise, and strategic understanding to utilize these platforms fully. This gap hinders their ability to compete with larger businesses and limits their growth prospects in a digital-first marketplace.

Addressing the issue of social media utilization is essential to empower SME owners and marketers in Penang to optimize their use of these platforms, leading to informed decision-making and improved business outcomes (Ahmad, 2019). Despite the growing importance of social media, many SMEs struggle to understand their full potential, which limits their competitiveness and growth. Bridging the knowledge gap and enhancing the understanding of social media's impact on SMEs can provide valuable insights with significant economic ramifications (Omar, 2021). This study aims to investigate how SMEs in Penang can overcome these challenges and leverage social media marketing to enhance their business performance and competitive edge.

## Research Objectives

**Research Objective 1:** To determine the relationship between social media platforms used that engage in social media marketing and their SME performance.

**Research Objective 2:** To determine the relationship between the content quality that engages in social media marketing and their SME performance.

**Research Objective 3:** To determine the relationship between the frequency and timing of posts that engage in social media marketing and their SME performance.

# LITERATURE REVIEW

## Overview of Social Media Marketing

Social media marketing involves using social media platforms to connect with audiences to build a brand, increase sales, and drive website traffic. It includes publishing content, engaging with followers, analyzing results, and running advertisements (Felix, Rauschnabel, & Hinsch, 2021). Social media has become an essential tool for organizations as a result of the enormous transformation of the marketing landscape brought about by the rise of digital marketing. Social media has changed how information is delivered, structured, and shared, leading SMEs to embrace social media marketing to thrive in the competitive economic environment (Taneja, 2014). When used correctly, social media has minimal drawbacks and can greatly enhance business impact, especially with the growing features on platforms like Facebook, Instagram, Twitter, and TikTok.

Social media connection helps businesses connect with their target audience, increasing product exposure and driving interest and purchases. For instance, searching for shoes on social media can lead to related product suggestions, enhancing business growth. Secondly, social media interaction engagement measures how users interact with content through likes, comments, shares, and mentions (Eckstein, n.d.). Humorous and trendy content can increase engagement and followers, as 28% of social media users seek funny content (Marketing Charts, 2022; Square, 2020). Thirdly, social media customer data includes metrics and demographic information collected through analytics tools (Newberry, 2022). This data helps businesses understand audience preferences and popular social media sites, allowing for effective campaign creation (Whatagraph team, 2021). Social media customer engagement is the integration between customers and companies that is inherent in terms of communication, experiences, and online communities on social media (Hollebeek et al. 2014). To build consumer loyalty, marketing planning is needed for customer engagement.

## The Relationship Between Social Media Platforms and SME Performance

Social media platforms differ in terms of their platform reach and audience engagement. Each social media platform, including Facebook, Instagram, and Twitter, has its own user base and features. The selection of platforms utilized by small and medium- sized enterprises (SMEs) can significantly impact their capacity to efficiently reach their intended audience. Platforms that have a bigger number of users and higher rates of user engagement have the potential to result in increased visibility for brands and more interactions with customers, which can have a beneficial impact on the performance of small and medium-sized enterprises (SMEs) (Smith, J., & Johnson, A.2023).

A comparative analysis of platform impacts on business success involves assessing various metrics like service quality ratings and reviews, which gauge how effectively a platform can attract, interact with, persuade, satisfy, and retain customers (Nick Routley, 2022). However, the influence of each platform can vary depending on factors such as restaurant service offerings, customer demographics, and competitive landscape. The existing literature on social media platform impacts on SME performance is scant and narrowly focused, typically examining individual platforms such as Facebook, Twitter, Instagram, and YouTube without comparing their effects comprehensively across SMEs. Research findings highlight that Facebook, Twitter, and WhatsApp are widely used among enterprises in Kenya, with WhatsApp being particularly popular for frequent engagement 43% of firms reported hourly visits, compared to 32% for Facebook. This underscores social media's significant potential as a versatile tool for global, real-time communication between consumers and businesses or among consumers themselves, making it particularly advantageous for SMEs with limited resources like funding and technical expertise (Rana, Barnard, Baabdullah, Rees, & Roderick, 2019).

The content strategy employed on social media platforms can influence the perception of small and medium-sized enterprises (SMEs) in the restaurant industry. Due to their emphasis on visual material, social media sites like Instagram are ideal for showcasing culinary selections and creating a compelling corporate brand. Several successful businesses are implementing visual content marketing, producing material in a most attractive, genuine, and relevant manner (Ikeni & Tonye, 2022). On the other hand, sites such as Twitter are more suited for participating in immediate discussions and customer service contacts. The congruence between the content strategy and the selected platform(s) can influence how the brand is perceived and how loyal customers are, ultimately impacting the performance indicators of small and medium- sized enterprises (SMEs), such as sales and customer retention rates (Brown, C., & Lee, M. 2023).

SMEs have the ability to monitor and examine consumer feedback, messages, and reviews on social media sites like Facebook and Yelp. Through this approach, SMEs can gain important insights into consumer preferences, promptly resolve any issues brought up, and maintain a favorable reputation for their brand. The correlation between SME performance and social media platforms also includes the effect of social media marketing on real business outcomes, such as ROI and sales conversions. This emphasizes how crucial it is to gauge how well social media marketing initiatives are producing these particular outcomes. Various platforms provide different advertising alternatives and targeting capabilities, which can impact the cost- effectiveness and performance of marketing efforts. Small and medium-sized enterprises (SMEs) should evaluate the impact of their social media marketing activities on each platform by analyzing metrics such as click-through rates, conversion rates, and total return on investment (ROI). This analysis will help them decide the most efficient allocation of resources and achieve the best possible performance results Wang & Liu (2022).

## The Relationship Between Content Quality and SME Performance 

The success of social media marketing heavily depends on the calibre of content distributed across these platforms. The quality of content, balancing accuracy, engagement, and technical finesse, plays a pivotal role in establishing trust and achieving success. According to research by Smith et al. (2022), factual inaccuracies and unreliable sources can erode trust among audiences, leading to disengagement and damage to brand reputation. Conversely, adhering to meticulous fact-checking and best practices, as emphasized by Jones et al. (2020), enhances credibility and positions a brand as a dependable source of information.

Moreover, content relevance and usefulness, highlighted by Lee et al. (2019), act as guiding principles that steer content towards its intended audience. Addressing audience needs and providing valuable solutions not only impacts SEO rankings and organic traffic but also builds loyalty and advocacy by resonating with audience interests. Research by Lee et al. (2018) indicates that overly technical and complex content can confuse users and impede engagement. Opting for clear language, logical organization, and avoiding unnecessary complexity ensures that the core message is retained, effectively informing and empowering the audience.

High-quality information possesses the capacity to exert influence over customer behaviour and sway purchase decisions. Compelling and influential content, such as evaluations, endorsements, and notable menu items, have the power to influence potential customers to patronize the restaurant or make a purchase. SMEs can enhance their performance outcomes by effectively influencing customer perceptions and driving sales through the provision of meaningful information and content that addresses consumer needs and preferences (Smith & Johnson, 2023). In a highly competitive market such as the restaurant business, small and medium-sized enterprises (SMEs) can set themselves apart from their rivals and build a distinct brand identity by offering high-quality content. Emphasizing the restaurant's distinctive selling points, such as the use of locally sourced foods, chef-inspired dishes, or themed events, can garner attention and differentiate the restaurant from others in the vicinity. An established brand identity and unique positioning can enhance customer loyalty and market share, thereby positively influencing the performance of small and medium-sized enterprises (SMEs) (Brown & Lee, 2020).

High-quality content can boost word-of-mouth marketing and foster brand advocacy among satisfied customers. Earned media occurs when a brand receives free media, and the consumers serve as the conduit rather than having to pay for it. Another name for the spread of information is word-of-mouth marketing, or WOM (Sofie Biaudet, 2017). Social media users are inclined to disseminate content that they perceive as valuable, interesting, or informative to their networks, resulting in natural reach and exposure for small and medium-sized enterprises (SMEs). Positive word-of-mouth recommendations and user-generated content, resulting from high-quality material, can significantly increase the restaurant's online visibility and credibility. This, in turn, enhances the brand's reputation and ultimately boosts the performance of small and medium-sized enterprises (SMEs) (Garcia & Martinez, 2022).

The relationship between content on social media platforms and the success of small and medium-sized enterprises (SMEs) in the restaurant sector in Penang is intricately linked. High-quality content not only impacts how people perceive a brand, engage with it, and make purchasing decisions, but it also helps to set the brand apart from competitors, gives it an edge, and encourages positive word-of-mouth marketing. SMEs can effectively utilize social media platforms to increase performance and achieve business objectives by focusing on creating and sharing high-quality content that is specifically customized to their target audience (Wang & Liu, 2023). Ensuring technical quality is vital for content performance on social media platforms. Poor image resolution or incompatible video formats, identified by Brown et al. (2023), can detract from the message and frustrate users. Adhering to platform-specific standards ensures that content not only delivers information effectively but also maintains visual appeal and accessibility.

## The Relationship Between Posting Frequency and SME Performance

Optimizing the timing of posts to coincide with peak hours or when the target audience is most active online can greatly enhance exposure and engagement. This, in turn, can have a significant impact on key performance indicators for small and medium-sized enterprises (SMEs), such as customer acquisition and retention rates (Kim & Lee, 2019). Consistently uploading content on social media profiles guarantees that the restaurant's online presence remains active and up to date with new and relevant information. Current and pertinent material is more inclined to captivate the interest of social media users and stimulate engagement. SMEs can optimize interest and engagement levels, resulting in good performance outcomes like enhanced website traffic, foot traffic, and sales, by strategically adjusting the number and timing of postings according to content relevancy and audience behaviour (Lee & Park, 2018).

Social media algorithms determine the impact and reach of material by giving priority to characteristics such as recency, interaction, and relevancy. Increasing the frequency of posts might potentially enhance the chances of content being viewed by a wider audience since it indicates to the platform's algorithm that the account is active and interactive. Furthermore, publishing content at optimal moments when the audience is highly engaged can further amplify the exposure and extend the reach of articles. SMEs may enhance their performance by comprehending and utilizing social media algorithms to optimize the number and timing of their posts. This will result in maximizing organic reach and engagement (Yang & Chen, 2022).

Small and medium-sized businesses (SMEs) can build stronger relationships over time and communicate consistently with their target audience by posting on social media on a regular and timely basis. SMEs can cultivate a feeling of community and loyalty among their followers by offering valuable material, updates, and promotions at appropriate intervals and times. Customers who are engaged and loyal are more inclined to promote the restaurant, generate positive word-of-mouth marketing, and sustain the business by making repeated visits and purchases. This ultimately enhances the performance and sustainability of the small and medium-sized enterprises (SMEs) (Wang & Liu, 2024).

Essentially, the connection between how often and when social media postings are made and the performance of small and medium-sized enterprises (SMEs) in the restaurant industry in Penang is crucial for effective digital marketing strategies. Strategically controlling how often and when posts are made can help small and medium-sized enterprises (SMEs) expand their audience, increase interaction, make their content more relevant, and improve customer connections. This can ultimately result in good outcomes such as more brand visibility, acquiring more customers, and generating more income.

## Research Framework

Fig. 1. Conceptual framework of current study

As depicted in Fig.1., the conceptual framework of this research focuses on the effect of social media marketing on SME performance, incorporating variables identified from the literature review which are social media platforms used, content quality, frequency and timing of posts. The framework integrates these variables, illustrating their interconnections. The figure shows that the framework consists of one dependent variable which is SME Performance, and three independent variables social media platforms used, content quality, and frequency and timing of posts. Additionally, it outlines the foundation on which the hypotheses are formulated.

Social media platforms such as Facebook, Instagram, TikTok, and Twitter are popular choices for SMEs in Penang due to their broad reach and ability to engage directly with local and international audiences. These platforms offer diverse content formats, including photos, videos, and stories, which allow restaurants to showcase their culinary offerings and dining experiences effectively. Content quality is crucial as it influences audience perception and engagement levels. High-quality visuals, compelling descriptions, and user-generated content contribute to building brand identity and attracting potential customers. In terms of frequency and timing of posts, consistent and strategic scheduling is essential to maintain audience interest and visibility. Posting during peak engagement times, such as evenings and weekends, can maximize reach and interaction.

Hence, this framework highlights the importance of strategic social media usage in enhancing SME performance. By analysing how different social media platforms, posting schedules, and content quality affect business outcomes, SMEs can tailor their strategies to maximize benefits. Supporting studies, such as those by Kaplan and Haenlein (2010), Kietzmann et al. (2011), and Gensler et al. (2013), provide insights into the functional building blocks of social media and effective brand management strategies. These studies reinforce the framework's relevance, suggesting that well-planned social media activities can significantly improve SME performance in a competitive digital landscape.

### Underpinning Theory

Based on Resource-Based View (RBV), a conceptual model for this study could include constructs such as social media resources (e.g., platform used, content quality) and their impact on SME performance. The model would hypothesize that valuable, rare, inimitable, and non-substitutable social media practices positively influence performance metrics like customer engagement and sales growth. Key RBV constructs can be operationalized by measuring variables such as content quality (e.g., engagement rates, user feedback), platform effectiveness (e.g., follower growth, reach), and posting frequency (e.g., number of posts per week) (Kechik et. al., 2023).

The RBV framework defines resources as the full range of assets, capabilities, processes, and knowledge under a firm's control that enables strategic conception and implementation. These resources can be tangible, for example, capital, physical assets, or intangible such as brand reputation, or proprietary technology. For a resource to sustain a competitive advantage, it must meet the VRIN criteria: it should be valuable, rare, inimitable, and non-substitutable. In the context of social media marketing's impact on SME performance, RBV emphasizes the strategic value of firm-specific resources like content quality, platform use, and posting frequency. This framework is particularly suitable for this study as it focuses on internal resources and their contribution to competitive advantage, contrasting with market-based views that emphasize external factors. Empirical studies using RBV have shown how unique social media capabilities can enhance brand performance and customer engagement among SMEs. However, criticisms of RBV include its static nature and limited consideration of dynamic capabilities needed for adaptation in a changing environment. Integrating RBV with dynamic capabilities and knowledge-based views can offer a more comprehensive understanding of how SMEs leverage social media for sustained performance and competitive advantage.

### Development of Hypotheses

H1: There is a positive relationship between the social media platforms used that engage in social media marketing and their SME performance.

H2: There is a positive relationship between the content quality that engages in social media marketing and their SME performance.

H3: There is a positive relationship between the frequency and timing of posts in social media marketing and their SME performance.

# RESEARCH METHODOLOGY

## Data Collection and Sampling Technique

A pilot study was conducted as a preliminary investigation to assess the feasibility and refine the methodologies of a larger-scale research endeavor on the effect of social media marketing on SME performance in restaurants in Penang. The primary objective of the pilot study was to ensure the clarity and practicality of the study methods, rather than addressing specific research questions. According to the pilot study rresults, each item in the questionnaire demonstrated the potential for acceptance, with a reliability value exceeding 0.7, as indicated in the Table 1 below.

Table 1. Pilot Test

<table>
<thead>
<tr class="header">
<th><strong>Variable</strong></th>
<th><blockquote>
<p><strong>No of Item</strong></p>
</blockquote></th>
<th><blockquote>
<p><strong>Cronbach’s Alpha</strong></p>
</blockquote></th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>SME Performance</td>
<td><blockquote>
<p>7</p>
</blockquote></td>
<td><blockquote>
<p>0.842</p>
</blockquote></td>
</tr>
<tr class="even">
<td>Social Media Platforms Used</td>
<td><blockquote>
<p>7</p>
</blockquote></td>
<td><blockquote>
<p>0.718</p>
</blockquote></td>
</tr>
<tr class="odd">
<td>Content Quality</td>
<td><blockquote>
<p>7</p>
</blockquote></td>
<td><blockquote>
<p>0.864</p>
</blockquote></td>
</tr>
<tr class="even">
<td>Frequency and Timing of Posts</td>
<td><blockquote>
<p>7</p>
</blockquote></td>
<td><blockquote>
<p>0.863</p>
</blockquote></td>
</tr>
</tbody>
</table>

The target population for this study comprises all SMEs in the restaurant sector in Penang, totaling 3,991 establishments. The total 3991 SME Restaurants in Penang were collected from official pages such as *SME Penang* ( <span class="underline">https:/[/www](http://www.SMEpenang.org.my/).</span>[<span class="underline">SMEpenang.org.my/)</span>.](http://www.SMEpenang.org.my/) This population includes a diverse range of restaurants, from small family-owned eateries to larger, more established dining establishments. The aim is to capture a comprehensive view of how social media marketing practices affect SME performance across this entire sector. By focusing on this well-defined population, the study ensures that the findings will be relevant and applicable to the broader restaurant industry in Penang.

A sample of 351 questionnaires were distributed online (utilizing Google Forms as the primary tool for data collection) to restaurant owners, managers, and workers in Penang. This method was chosen for its reliability, simplicity, direct response mechanisms, ease of administration, and the integration of Likert scale questions. The large sample size aimed to provide robust data for analysis and interpretation, ensuring comprehensive insights into the relationship between social media marketing and SME performance in the restaurant industry in Penang.

In Section A, participants are categorized based on several demographic variables: age (under 25, 25-35, 36-45, 46 and above), gender (male, female), income level (RM) (less than 2500-4849), years of experience in the restaurant industry (less than 1 year, 1-5 years, 6-10 years, more than 15 years), position in the restaurant (Owner, Co-owner, Manager, workers and other). The survey examines which social media platforms are used for marketing purposes, with options such as Facebook, Instagram, Twitter, TikTok, YouTube, and others.

In Sections B, C, D, and E, questions are designed to seek respondent’s views on the effect of social media marketing on SME Performance. In the last part of this Section B, C, D, and E questions were designed to identify the dependent variable and Independent Variables, social media marketing on SME performance. Respondents are requested to choose from a set of multiple-choice questions in the questionnaire given.

To achieve a representative sample from the target population, convenience sampling method were employed, ensuring that every restaurant has an equal chance of being selected. It involves selecting participants who are readily available and willing to participate. It is easy to implement and cost-effective. In this research, restaurant owners, co-owners, managers, workers such as chefs, servers, and bartenders, and others were selected which are roles not specified in the main categories in the restaurant organization chart such as part- time employees, temporary staff, and consultants from SME Restaurant Penang who are available and willing to discuss their social media marketing strategies on SME performance.

# Results and discussion

The research analyzed the questionnaire and came up with the results of this study analysing the effect of social media marketing on SME performance. The data are interpreted using SPSS Version 27. The analysis consists of independent variables such as social media platforms used, content quality, and frequency and timing of posts, while the dependent variable is SME Performance.

The data collected took three months to complete, beginning in April 2024 and ending in June 2024. This study is projected to receive 351 responses in total. Fortunately, Google has provided authentic email addresses for each SME restaurant. Thus, 351 sets of questions were successfully gathered. This showed that the answer rate contributed 100% to this survey. All 351 questionnaire sets were found to be usable. This fraction exceeds the expected amount for surveys sampled at random with no prior engagement with each respondent. Table 2 summarizes the total number of questionnaires distributed and collected.

Table 2. Sample Profile of Survey

<table>
<thead>
<tr class="header">
<th><blockquote>
<p><strong>Variables</strong></p>
</blockquote></th>
<th><blockquote>
<p><strong>Categories</strong></p>
</blockquote></th>
<th><blockquote>
<p><strong>Frequency</strong></p>
</blockquote></th>
<th><blockquote>
<p><strong>Percentage (%)</strong></p>
</blockquote></th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td><blockquote>
<p>Age</p>
</blockquote></td>
<td><blockquote>
<p>Under 25 years old</p>
</blockquote></td>
<td><blockquote>
<p>101</p>
</blockquote></td>
<td><blockquote>
<p>28.8</p>
</blockquote></td>
</tr>
<tr class="even">
<td></td>
<td><blockquote>
<p>26- 35 years old</p>
</blockquote></td>
<td><blockquote>
<p>130</p>
</blockquote></td>
<td><blockquote>
<p>37.0</p>
</blockquote></td>
</tr>
<tr class="odd">
<td></td>
<td><blockquote>
<p>36-45 years old</p>
</blockquote></td>
<td><blockquote>
<p>70</p>
</blockquote></td>
<td><blockquote>
<p>19.9</p>
</blockquote></td>
</tr>
<tr class="even">
<td></td>
<td><blockquote>
<p>46- 55 years old</p>
</blockquote></td>
<td><blockquote>
<p>37</p>
</blockquote></td>
<td><blockquote>
<p>10.5</p>
</blockquote></td>
</tr>
<tr class="odd">
<td></td>
<td><blockquote>
<p>55 years and above</p>
</blockquote></td>
<td><blockquote>
<p>13</p>
</blockquote></td>
<td><blockquote>
<p>3.7</p>
</blockquote></td>
</tr>
<tr class="even">
<td><blockquote>
<p>Gender</p>
</blockquote></td>
<td><blockquote>
<p>Male</p>
</blockquote></td>
<td><blockquote>
<p>149</p>
</blockquote></td>
<td><blockquote>
<p>57.5</p>
</blockquote></td>
</tr>
<tr class="odd">
<td></td>
<td><blockquote>
<p>Female</p>
</blockquote></td>
<td><blockquote>
<p>202</p>
</blockquote></td>
<td><blockquote>
<p>42.5</p>
</blockquote></td>
</tr>
<tr class="even">
<td><blockquote>
<p>Income Level</p>
</blockquote></td>
<td><blockquote>
<p>Less than 2,500</p>
</blockquote></td>
<td><blockquote>
<p>72</p>
</blockquote></td>
<td><blockquote>
<p>20.5</p>
</blockquote></td>
</tr>
<tr class="odd">
<td></td>
<td><blockquote>
<p>2,500 - 3,169</p>
</blockquote></td>
<td><blockquote>
<p>98</p>
</blockquote></td>
<td><blockquote>
<p>27.9</p>
</blockquote></td>
</tr>
<tr class="even">
<td></td>
<td><blockquote>
<p>3,170 - 3,969</p>
</blockquote></td>
<td><blockquote>
<p>93</p>
</blockquote></td>
<td><blockquote>
<p>26.5</p>
</blockquote></td>
</tr>
<tr class="odd">
<td></td>
<td><blockquote>
<p>3,970 – 4,849</p>
</blockquote></td>
<td><blockquote>
<p>88</p>
</blockquote></td>
<td><blockquote>
<p>25.1</p>
</blockquote></td>
</tr>
<tr class="even">
<td><blockquote>
<p>Years of experience in the restaurant industry</p>
</blockquote></td>
<td><blockquote>
<p>Less than 1 Year</p>
</blockquote></td>
<td><blockquote>
<p>15</p>
</blockquote></td>
<td><blockquote>
<p>4.3</p>
</blockquote></td>
</tr>
<tr class="odd">
<td></td>
<td><blockquote>
<p>1 - 5 years</p>
</blockquote></td>
<td><blockquote>
<p>29</p>
</blockquote></td>
<td><blockquote>
<p>8.3</p>
</blockquote></td>
</tr>
<tr class="even">
<td></td>
<td><blockquote>
<p>6 - 10 years</p>
</blockquote></td>
<td><blockquote>
<p>72</p>
</blockquote></td>
<td><blockquote>
<p>20.5</p>
</blockquote></td>
</tr>
<tr class="odd">
<td></td>
<td><blockquote>
<p>11 - 15 years</p>
</blockquote></td>
<td><blockquote>
<p>132</p>
</blockquote></td>
<td><blockquote>
<p>37.6</p>
</blockquote></td>
</tr>
<tr class="even">
<td></td>
<td><blockquote>
<p>More than 15 years</p>
</blockquote></td>
<td><blockquote>
<p>103</p>
</blockquote></td>
<td><blockquote>
<p>29.3</p>
</blockquote></td>
</tr>
<tr class="odd">
<td><blockquote>
<p>Position in the restaurant</p>
</blockquote></td>
<td><blockquote>
<p>Owner</p>
</blockquote></td>
<td><blockquote>
<p>129</p>
</blockquote></td>
<td><blockquote>
<p>36.8</p>
</blockquote></td>
</tr>
<tr class="even">
<td></td>
<td><blockquote>
<p>Co-Owner</p>
</blockquote></td>
<td><blockquote>
<p>134</p>
</blockquote></td>
<td><blockquote>
<p>38.2</p>
</blockquote></td>
</tr>
<tr class="odd">
<td></td>
<td><blockquote>
<p>Manager</p>
</blockquote></td>
<td><blockquote>
<p>65</p>
</blockquote></td>
<td><blockquote>
<p>18.5</p>
</blockquote></td>
</tr>
<tr class="even">
<td></td>
<td><blockquote>
<p>Workers</p>
</blockquote></td>
<td><blockquote>
<p>14</p>
</blockquote></td>
<td><blockquote>
<p>4</p>
</blockquote></td>
</tr>
<tr class="odd">
<td></td>
<td><blockquote>
<p>Others</p>
</blockquote></td>
<td><blockquote>
<p>9</p>
</blockquote></td>
<td><blockquote>
<p>2.5</p>
</blockquote></td>
</tr>
<tr class="even">
<td><blockquote>
<p>Which social media platform is the most effective for advertising your restaurant?</p>
</blockquote></td>
<td><blockquote>
<p>Facebook</p>
</blockquote></td>
<td><blockquote>
<p>52</p>
</blockquote></td>
<td><blockquote>
<p>14.8</p>
</blockquote></td>
</tr>
<tr class="odd">
<td></td>
<td><blockquote>
<p>Instagram</p>
</blockquote></td>
<td><blockquote>
<p>64</p>
</blockquote></td>
<td><blockquote>
<p>18.2</p>
</blockquote></td>
</tr>
<tr class="even">
<td></td>
<td><blockquote>
<p>Twitter</p>
</blockquote></td>
<td><blockquote>
<p>60</p>
</blockquote></td>
<td><blockquote>
<p>17.1</p>
</blockquote></td>
</tr>
<tr class="odd">
<td></td>
<td><blockquote>
<p>TikTok</p>
</blockquote></td>
<td><blockquote>
<p>62</p>
</blockquote></td>
<td><blockquote>
<p>17.7</p>
</blockquote></td>
</tr>
<tr class="even">
<td></td>
<td><blockquote>
<p>YouTube</p>
</blockquote></td>
<td><blockquote>
<p>57</p>
</blockquote></td>
<td><blockquote>
<p>16.2</p>
</blockquote></td>
</tr>
<tr class="odd">
<td></td>
<td><blockquote>
<p>Other</p>
</blockquote></td>
<td><blockquote>
<p>56</p>
</blockquote></td>
<td><blockquote>
<p>16.0</p>
</blockquote></td>
</tr>
</tbody>
</table>

In section A, 6 questions were prepared under Demographic which are age, gender, income level (RM), Years of experience in the Restaurant Industry, Position in the restaurant industry, and the effectiveness of social media platforms in restaurants. The demographic analysis of the respondents provides insightful data for understanding the effect of social media marketing on SME Performance.

Table 2 classifies participants into five age brackets and emphasizes the most significant group as persons aged 26-35 years (37.0%, 130 individuals). This age group is crucial for comprehending social media marketing because of their professional obligations and active involvement (Alalwan et al., 2017). The second most populous demographic consists of individuals under the age of 25, accounting for 28.8% of the total population with a count of 101 individuals. This group is notable for its significant involvement with digital platforms (Appel et al., 2020). The age categories of 36-45 years, 46-55 years, and 55 years and beyond constitute 19.9% (70 persons), 10.5% (37 individuals), and 3.7% (13 individuals), respectively, offering valuable information about distinct market sectors. The gender distribution is approximately equal, with males accounting for 57.5% (149 individuals) and females comprising 42.5% (202 persons).

The respondents' income levels are divided into four categories, with the first group earning less than RM 2,500 (20.5%, 72 persons), reflecting the lower-income population. The second category, with an income range of RM 2,500 - RM 3,169, has the greatest proportion at 27.9% (98 persons), indicating a probable representation of the lower-middle- class (Barrera-Verdugo & Villarroel-Villarroel, 2022). The third group, with an income range of RM 3,170 - RM 3,969, consists of 26.5% (93 persons), signifying a middle-class status characterized by a greater ability to make purchases. The fourth group, comprising 88 people, represents 25.1% of the total population. They earn a monthly salary ranging from RM 3,970 to RM 4,849, placing them in the upper-middle-income category. This group possesses considerable discretionary spending power.

The respondents' years of experience in the restaurant sector indicate varying levels of understanding. persons who have less than one year of experience (4.3%, 15 persons) are now in the learning phase, whereas those with 1 to 5 years of expertise (8.3%, 29 individuals) provide first insights into social media techniques (Bastian et al., 2023). Approximately one-fifth (20.5%, 72 people) possess a professional background of 6 to 10 years, demonstrating expertise in both operational and managerial aspects. The most extensive cohort (37.6%, 132 individuals) possesses an experience range of 11 to 15 years, which enables them to offer a profound understanding of enduring patterns. Individuals who possess over 15 years of experience, which accounts for 29.3% of the total (103 individuals), possess a wealth of information and a deep understanding of historical background.

The allocation according to positions inside the restaurant emphasizes the viewpoints of various stakeholders regarding the influence of social media marketing. The primary decision-making authority is with the owners, who constitute 36.8% (129 individuals), and the co-owners, who make up 38.2% (134 individuals). Managers, comprising 18.5% of the total workforce (65 individuals), have a crucial responsibility in executing strategies, whereas workers, accounting for 4% (14 individuals), provide realistic input on the impact of marketing efforts. The "Others" category, comprising 2.5% of the total workforce with 9 workers, consists of part-time employees, temporary staff, and consultants. These individuals offer valuable perspectives on the wider marketing effects.

Based on the examination of restaurant advertising preferences on social media platforms, Instagram is shown to be the most favoured platform (18.2%, 64 respondents) because of its strong visual content appeal (Li et al., 2021). Twitter is highly proficient in immediate interaction, as indicated by 17.1% of the 60 respondents. On the other hand, TikTok is renowned for its captivating and widely shared marketing campaigns (Nair et al., 2022), as reported by 17.7% of the 62 respondents. YouTube, with the support of 16.2% of 57 respondents, is known for its ability to facilitate precise brand storytelling. On the other hand, Facebook, with a support of 14.8% from 52 respondents, is valued for its large and diverse user base. Additional platforms (16.0%, 56 responders) encompass specialized networks such as LinkedIn and Snapchat, which serve specialized marketing objectives within the industry.

## Descriptive Analysis of Variables

Table 3. Descriptive Analysis

<table>
<thead>
<tr class="header">
<th></th>
<th><blockquote>
<p><strong>N</strong></p>
</blockquote></th>
<th><blockquote>
<p><strong>Minimum</strong></p>
</blockquote></th>
<th><blockquote>
<p><strong>Maximum</strong></p>
</blockquote></th>
<th><blockquote>
<p><strong>Mean</strong></p>
</blockquote></th>
<th><blockquote>
<p><strong>Std. Deviation</strong></p>
</blockquote></th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td><blockquote>
<p>SME Performance</p>
</blockquote></td>
<td><blockquote>
<p>351</p>
</blockquote></td>
<td><blockquote>
<p>16.00</p>
</blockquote></td>
<td><blockquote>
<p>35.00</p>
</blockquote></td>
<td><blockquote>
<p>30.71</p>
</blockquote></td>
<td><blockquote>
<p>4.74</p>
</blockquote></td>
</tr>
<tr class="even">
<td><blockquote>
<p>Social Media Platforms Used</p>
</blockquote></td>
<td><blockquote>
<p>351</p>
</blockquote></td>
<td><blockquote>
<p>13.00</p>
</blockquote></td>
<td><blockquote>
<p>35.00</p>
</blockquote></td>
<td><blockquote>
<p>30.85</p>
</blockquote></td>
<td><blockquote>
<p>4.45</p>
</blockquote></td>
</tr>
<tr class="odd">
<td><blockquote>
<p>Content Quality</p>
</blockquote></td>
<td><blockquote>
<p>351</p>
</blockquote></td>
<td><blockquote>
<p>7.00</p>
</blockquote></td>
<td><blockquote>
<p>35.00</p>
</blockquote></td>
<td><blockquote>
<p>30.55</p>
</blockquote></td>
<td><blockquote>
<p>5.12</p>
</blockquote></td>
</tr>
<tr class="even">
<td><blockquote>
<p>Frequency and Timing of Posts</p>
</blockquote></td>
<td><blockquote>
<p>351</p>
</blockquote></td>
<td><blockquote>
<p>7.00</p>
</blockquote></td>
<td><blockquote>
<p>35.00</p>
</blockquote></td>
<td><blockquote>
<p>30.51</p>
</blockquote></td>
<td><blockquote>
<p>5.18</p>
</blockquote></td>
</tr>
</tbody>
</table>

Table 3 provides the descriptive analysis in a detailed overview of four key variables collected from 351 small and medium-sized enterprises (SMEs) such as SME Performance, Social Media Platforms Used, Content Quality, and Frequency and Timing of Posts. For SME Performance, the scores range from 16.00 to 35.00, with an average score of 30.71 and a standard deviation of 4.74, indicating that SMEs generally perform well, though there is some variability in performance levels. The Social Media Platforms Used variable shows scores between 13.00 and 35.00, with an average of 30.85 and a standard deviation of 4.45, indicating that most SMEs are actively using a considerable number of social media platforms with relatively consistent usage patterns.

Content Quality has a broader range of scores from 7.00 to 35.00, an average of 30.55, and a higher standard deviation of 5.12, indicating that while most SMEs produce high-quality content, there is a wider variation in content quality. Similarly, the Frequency and Timing of Posts range from 7.00 to 35.00, with a mean of 30.51 and a standard deviation of 5.18, reflecting that while many SMEs post frequently and at strategic times, there is significant variation in posting habits. Overall, the data reveals that SMEs typically perform well and engage extensively with social media, producing high-quality content and posting frequently.

## Scale Measurement

### 4.2.1 Reliability Analysis

Table 4 presents the reliability test analysis, including the number of items, Cronbach’s Alpha values, and the internal consistency of the dependent variable, which is SME performance, and the independent variables, which are social media platform used, content quality, and frequency and timing of posts. Generally, Cronbach's alpha was used to measure the reliability, and values of less than 0.60 are poor, whereas those close to 0.70 are considered good and those over 0.80 are high (Amiri et al., 2010).

Table 4. Reliability Analysis

<table>
<thead>
<tr class="header">
<th><blockquote>
<p><strong>Variables</strong></p>
</blockquote></th>
<th><blockquote>
<p><strong>Cronbach’s Alpha</strong></p>
</blockquote></th>
<th><blockquote>
<p><strong>Number of Items</strong></p>
</blockquote></th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td><blockquote>
<p>SME Performance</p>
</blockquote></td>
<td>0.860</td>
<td><blockquote>
<p><strong>7</strong></p>
</blockquote></td>
</tr>
<tr class="even">
<td><blockquote>
<p>Social Media Platforms Used</p>
</blockquote></td>
<td>0.842</td>
<td><blockquote>
<p><strong>7</strong></p>
</blockquote></td>
</tr>
<tr class="odd">
<td><blockquote>
<p>Content Quality</p>
</blockquote></td>
<td>0.886</td>
<td><blockquote>
<p><strong>7</strong></p>
</blockquote></td>
</tr>
<tr class="even">
<td><blockquote>
<p>Frequency And Timing of Posts</p>
</blockquote></td>
<td>0.878</td>
<td><blockquote>
<p><strong>7</strong></p>
</blockquote></td>
</tr>
</tbody>
</table>

Also, Table 4 presents the results of a reliability test analysis using Cronbach's Alpha for four variables: SME Performance, Social Media Platforms Used, Content Quality, and Frequency and Timing of Posts. Each variable was assessed using seven items. Cronbach's Alpha values range from 0 to 1, with higher values indicating better internal consistency among the items on a scale. Generally, values above 0.70 are considered acceptable, and values above 0.80 indicate high reliability.

The variable "SME Performance" has a Cronbach's Alpha value of 0.860, suggesting high consistency and reliability in the items used to measure it. "Social Media Platforms Used" shows a Cronbach's Alpha of 0.842, indicating strong internal consistency among the items measuring this variable. "Content Quality" has the highest Cronbach's Alpha value at 0.886, demonstrating excellent reliability in the measurement items. Lastly, "Frequency and Timing of Posts" has a Cronbach's Alpha of 0.878, also indicating high reliability. Overall, the high Cronbach's Alpha values for all four variables used to measure these constructs are highly consistent and reliable.

### 4.2.2 Pearson Correlation Analysis

The primary goal of this section is to explore the relationships between SME Performance, Content Quality, Frequency of Posts, and the number of Social Media Platforms used.

Table 5. Correlation Analysis

<table>
<thead>
<tr class="header">
<th></th>
<th><blockquote>
<p><strong>SME Performance</strong></p>
</blockquote></th>
<th><blockquote>
<p><strong>Social Media Platforms</strong></p>
</blockquote></th>
<th><blockquote>
<p><strong>Content Quality</strong></p>
</blockquote></th>
<th><blockquote>
<p><strong>Frequency and Timing of Post</strong></p>
</blockquote></th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td><blockquote>
<p><strong>SME</strong></p>
<p><strong>Performance</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>Pearson 1</strong></p>
<p><strong>Correlation</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>.828**</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>.805**</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>.780**</strong></p>
</blockquote></td>
</tr>
<tr class="even">
<td><blockquote>
<p><strong>Social media</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>Pearson .828**</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>1</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>.812**</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>.764**</strong></p>
</blockquote></td>
</tr>
<tr class="odd">
<td><blockquote>
<p><strong>Platforms</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>Correlation</strong></p>
</blockquote></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr class="even">
<td><blockquote>
<p><strong>Content</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>Pearson .805**</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>.812**</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>1</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>.912**</strong></p>
</blockquote></td>
</tr>
<tr class="odd">
<td><blockquote>
<p><strong>Quality</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>Correlation</strong></p>
</blockquote></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr class="even">
<td><blockquote>
<p><strong>Frequency And</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>Pearson .780**</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>.764**</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>.912**</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>1</strong></p>
</blockquote></td>
</tr>
<tr class="odd">
<td><blockquote>
<p><strong>Timing of Posts</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>Correlation</strong></p>
</blockquote></td>
<td></td>
<td></td>
<td></td>
</tr>
</tbody>
</table>

\*\*Correlation is significant at the 0.01 level (2-tailed).

The correlation analysis examines the relationships between SME Performance, Content Quality, Frequency of Posts, and the number of Social Media Platforms used. This analysis is essential for understanding how these variables interact and potentially influence each other in the context of SME performance. The Pearson correlation coefficients indicate the strength and direction of the relationships between the variables. The correlation coefficient between SME Performance and Content Quality is 0.828, suggesting a strong positive relationship. This means that higher content quality is significantly associated with better SME performance. The significance level (p-value) is 0.000, indicating that this correlation is statistically significant at the 0.01 level, meaning there is less than a 1% chance that this result is due to random variation.

Similarly, the correlation between SME Performance and Frequency and timing of posts is 0.805, also indicating a strong positive relationship. This suggests that more frequent posting is associated with better SME performance. Again, the p-value is 0.000, confirming the statistical significance of this relationship at the 0.01 level. The correlation between SME Performance and the number of Social Media Platforms used is 0.780, which represents a strong positive relationship. This means that using more social media platforms is associated with higher SME performance, and the p- value of 0.000 confirms the statistical significance of this correlation.

In conclusion, the results reveal that there are strong and significant positive correlations between SME Performance and the other three variables which are content quality, frequency of posts, and the number of social media platforms used.

### 4.2.3 Multiple Linear Regression Analysis

Table 6. Regression Analysis

### 

<table>
<thead>
<tr class="header">
<th><strong>Variables</strong></th>
<th><blockquote>
<p><strong>Beta</strong></p>
</blockquote></th>
<th><strong>t</strong></th>
<th><blockquote>
<p><strong>Sig.</strong></p>
</blockquote></th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td><strong>Social Media Platforms</strong></td>
<td><blockquote>
<p>0.497</p>
</blockquote></td>
<td><blockquote>
<p>10.626</p>
</blockquote></td>
<td><blockquote>
<p>0.000</p>
</blockquote></td>
</tr>
<tr class="even">
<td><strong>Content Quality</strong></td>
<td><blockquote>
<p>0.214</p>
</blockquote></td>
<td><blockquote>
<p>2.905</p>
</blockquote></td>
<td><blockquote>
<p>0.004</p>
</blockquote></td>
</tr>
<tr class="odd">
<td><strong>Frequency And Timing of Posts</strong></td>
<td><blockquote>
<p>0.205</p>
</blockquote></td>
<td><blockquote>
<p>3.079</p>
</blockquote></td>
<td><blockquote>
<p>0.002</p>
</blockquote></td>
</tr>
</tbody>
</table>

The regression study in Table 6 investigates the impact of three independent variables on a dependent variable. The factors consist of Social Media Platforms, Content Quality, and Frequency and Timing of Posts. The impact of each variable is assessed using its Beta coefficient, t-value, and significance level (Sig.). The variable "Social Media Platforms" has a Beta coefficient of 0.497, indicating a robust positive correlation with the dependent variable (Samat, 2020). The t-value of 10.626 and a significance level (Sig.) of 0.000 indicate that this association is statistically significant at the 0.001 level. This means that there is a less than 0.1% probability that this result is attributable to random fluctuation. The association between Content Quality and the dependent variable is positive, as indicated by a Beta coefficient of 0.214. The t-value is 2.905, and the significance level is 0.004. This suggests that Content Quality is a strong predictor, with a statistically significant link at the 0.01 level (meaning there is only a 1% possibility that the relationship is due to random chance) (Li et al., 2023). The Beta coefficient for the Frequency and Timing of Posts is 0.205, indicating a positive impact on the dependent variable (Lee et al., 2022). The variable has a t-value of 3.079 and a significance level of 0.002, indicating that the association is statistically significant at the 0.01 level. Overall, the three variables Social Media Platforms, Content Quality, and Frequency and Timing of Posts have a positive effect on the dependent variable and are statistically significant predictors in the regression model. Social media platforms exert the most significant influence, followed by the quality of content and the frequency and timing of posts.

### 4.2.4 Results of Hypothesis Testing Summary

Table 7. Result of Hypothesis

<table>
<thead>
<tr class="header">
<th><blockquote>
<p><strong>No of Hypothesis</strong></p>
</blockquote></th>
<th><blockquote>
<p><strong>Hypothesis Statement</strong></p>
</blockquote></th>
<th><blockquote>
<p><strong>Results</strong></p>
</blockquote></th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td><blockquote>
<p>H1</p>
</blockquote></td>
<td><blockquote>
<p>There is a positive relationship between the social media platforms used that engage in social media marketing and their SME performance.</p>
</blockquote></td>
<td><blockquote>
<p>Accepted</p>
</blockquote></td>
</tr>
<tr class="even">
<td><blockquote>
<p>H2</p>
</blockquote></td>
<td><blockquote>
<p>There is a positive relationship between the content quality that engages in social media marketing and their SME</p>
<p>performance.</p>
</blockquote></td>
<td><blockquote>
<p>Accepted</p>
</blockquote></td>
</tr>
<tr class="odd">
<td><blockquote>
<p>H3</p>
</blockquote></td>
<td><blockquote>
<p>There is a positive relationship between the frequency and timing of posts in social media marketing and their SME performance.</p>
</blockquote></td>
<td><blockquote>
<p>Accepted</p>
</blockquote></td>
</tr>
</tbody>
</table>

# LIMITATION AND Conclusion

While this study provides valuable insights into the relationship between social media strategies and SME performance in Penang restaurants, it is essential to acknowledge several limitations that may impact the interpretation and generalizability of the findings such as lack of diversity in terms of restaurant types, demographics, or geographical locations may limit the generalizability of our findings to the broader population of Penang restaurants. However, despite these limitations, the study contributes valuable insights to the literature on social media strategies and SME performance in the restaurant industry. Acknowledging these limitations provides opportunities for future research to address these gaps and build upon our findings to advance knowledge in this area.

In this study, the analysis revealed strong positive correlations between content quality (r = 0.828) and posting frequency (r = 0.805) with SME performance. Therefore, the study's conclusion, which focuses on the social media platforms used, the quality of the material, and the frequency and timing of posts, states that social media marketing has a major impact on SME success. Beyond SME Performance metrics, effective social media strategies inform consumer decisions and promote local culture, fostering community identity and cohesion. Future research should explore new variables and methodologies to further understand social media's evolving role in SME business success. Overall, embracing these insights enables businesses to navigate challenges, capitalize on opportunities, and thrive in a competitive digital landscape.

# Acknowledgements/Funding

The authors sincerely appreciate the invaluable support from Universiti Malaysia Perlis (UniMAP) and all contributors who assisted in this research. Special thanks to the participating SMEs for their cooperation and insights. This study would not have been possible without the encouragement and expertise of our colleagues and mentors. Thank you.

# Conflict of interest statement

# 

The authors agree that this research was conducted in the absence of any self-benefits, commercial or financial conflicts and declare the absence of conflicting interests with the funders.

# Authors’ contributions

**Tisya Farida Abdul Halim**: Conceptualisation, methodology, and writing-original draft, supervision; **Raziff Jamaluddin**: Conceptualisation, methodology, writing-review and editing, and validation; **Nuraini Abdullah**: Conceptualisation, methodology, and validation; **Mohd Khairulnizam Zahari**: Conceptualisation, writing-review and editing, and validation; **Nur Syuhadah Kamaruddin**: Conceptualisation and Validation; **Bannu A/P Subramanian**: Conceptualisation, methodology, formal analysis, investigation and writing-original draft.

**About the Authors**

***Tisya Farida Abdul Halim**, PhD*, is a lecturer and researcher currently affiliated with Universiti Malaysia Perlis (UniMAP). She specializes in operations research and business analytics, with expertise in system dynamics and mathematical modeling. Her research focuses on optimizing SME performance, promoting sustainable business practices, and enabling data-driven decision-making. She is actively involved in developing business-oriented curricula, supervising postgraduate research, and contributing to impactful studies published in reputable journals and conferences. For collaboration or inquiries, she can be contacted at <tisyafarida@unimap.edu.my>

***Raziff Jamaluddin*,** has a strong background in academic writing, specializing in entrepreneurship, SMEs, and business performance. With extensive experience in research and analysis, Raziff focuses on contributing to scholarly works and aims to publish in recognized journals such as MyCite and Scopus. For inquiries or collaborations, he can be reached at raziff@unimap.edu.my.

***Nuraini Abdullah,** PhD is* a lecturer at Universiti Malaysia Perlis (UniMAP). Her current interest is in Behavioural Economics, Financial Literacy, Human Capital, Entrepreneurship. She has several articles in the Journal of Consumer and Family Economics, Journal of Human Ecology, Journal of Emerging Economics & Islamic Research, and Pertanika Journal of Social Science & Humanities. She can be reached through her email at <nuraini@unimap.edu.my>

***Mohd Khairulnizam Zahari*,** holds a PhD in Management from Universiti Teknologi Malaysia, Skudai, Johor. His doctoral research focused on supply chain management and sustainability. His research interests include technology management, supply chain management, operations management, and total quality management. He is currently affiliated with Universiti Malaysia Perlis and actively contributes to advancing knowledge in these fields. For further correspondence, he can be reached via email at nizamzahari@unimap.edu.my.

***Nur Syuhadah Kamaruddin*,** is a Senior Lecturer in the Faculty of Business & Communication under Business Division at the Universiti Malaysia Perlis (UniMAP). Her main area of research is operations management and supply chain management and has supervised and published in this area of study. She can be reached through her email at <syuhadah@unimap.edu.my>

***Bannu A/P Subramanian*,** holds a Bachelor of Business (International Business) degree from Universiti Malaysia Perlis (UniMAP). Her research, conducted as part of her final year project, focused on the impact of social media marketing on SME performance in the restaurant industry. She was actively involved in conceptualization, formal analysis, and investigation, contributing valuable insights into digital marketing strategies.

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1.  <sup>\*</sup> Corresponding author. *E-mail address*: tisyafarida@unimap.edu.my