Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1726 https://internationalpubls.com Factors Influencing Consumer Behavior towards Fast Food and the Role of Social Media Marketing on Consumers Fast Food Purchase Decision in Delhi NCR Pranita Sah1*, Dr. Gaurav Bathla1, Dr. Varinder Singh Rana2 1 Department of Hospitality Management, CT University, Ludhiana, Punjab, India 2 Hospitality and Tourism Management, City University Ajman, UAE Corresponding author’s e-mail id: pranisims@gmail.com Article History: Received: 12-12-2024 Revised: 25-01-2025 Accepted: 05-02-2025 Abstract: The research paper "Factors Influencing Consumer Behavior Toward Fast Food and the Role of Social Media Marketing on Consumers' Fast Food Purchase Decision in Delhi NCR" is an analysis of how social media marketing influences fast food consumption in Delhi NCR. The determinants of consumer behavior, consumer awareness, impact of social media platforms, and their relationship with fast food consumption are studied in this paper. A self-constructed questionnaire was utilized through convenience sampling via Google Forms, and 270 consumers responded; however, valid responses were available for only 220. The demographic, fast-food habits, and social media habits of the participants were recorded using a five-point Likert scale to gather data on 16 consumer behavior variables. Using SPSS, reliability analysis reflected strong internal consistency with Cronbach's alpha from 0.924 to 0.958. The key methodologies included Principal Component Analysis that was used in identifying the dimensions of consumer behavior and descriptive analysis in quantifying awareness levels, ranking the influential social media platforms with Friedman tests, and Spearman correlation for the assessment of relationships between social media usage and behavior. Results found two key behavior dimensions: Convenience and Value- Oriented Consumption and Social and Cultural Influences. High consumer awareness, especially on health and hygiene, reflects an informed market. Social media, such as YouTube, WhatsApp, and Instagram, played a very significant role in influencing purchasing decisions. The correlation analysis established strong relationships between the use of social media and consumer behavior, emphasizing the need for digital engagement. Findings give actionable insights for fast food brands to realign strategies according to consumer preferences, utilize influential social platforms, and improve customer engagement and satisfaction in a competitive market. Keywords: Consumer Behavior, Fast Food, Social Media Marketing, Purchase Decision, Delhi- NCR. 1. INTRODUCTION Fast food is an essential component of a modern urban lifestyle. Exponential growth has been noted in the fast-food industry over the past few decades (Baig & Saeed, 2012). The metropolitan regions like Delhi NCR have also experienced increased consumption of fast food as they have rapidly mailto:pranisims@gmail.com Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1727 https://internationalpubls.com urbanized places with fast lifestyles and an elevated disposable income that make people opt for fast food regardless of age and gender. However, the factors that influence consumer behavior regarding fast food are multifaceted, including personal preference, cultural influence, and marketing strategies (Dassanayake, 2023). Among those factors, social media marketing emerged as a powerful tool by shaping consumer attitudes and decision-making processes through specific targeting, influencer advertising, and interactive content (Anjorin et al., 2024; Vrontis et al., 2021). Understanding consumer behavior toward fast food requires a holistic approach to examine various elements, including taste, convenience, affordability, peer influence, and health consciousness (Aisha et al., 2024). The appeal of fast food lies in its ability to respond to the need of the consumer for instant gratification, providing an answer to hunger while also offering flexibility in a busy schedule (Roberts, 2014). Growing health concerns and the awareness about nutritional implications add another level of complexity to the process (Hoek et al., 2021). But for many of these buyers, the fast- food shopping decision is a delicate balance between indulgence and mindfulness which balances personal values and situational factors (Priporas et al., 2022). Fast food brands have popularized the use of social media sites like Instagram, Facebook, Twitter, and YouTube to connect with their target audience (Hill-Mends, 2022). Businesses can engage with their consumers at a very personal level through these portals, using visually appealing content, offers, and interactive campaigns to gain brand loyalty. Social media marketing has not only increased brand visibility of fast foods, but it has also influenced how consumers perceive these brands: by creating a sense of community and shared experience (Celine Bernadette, 2016). Such user-generated content as the reviews, food photography and videos of "must try" items usually drive consumers' interest and encourage in-store trials (Philp et al., 2022). This research paper aims to explore the complex interplay of factors that influence consumer behavior towards fast food in Delhi NCR. The primary objective is to identify and analyze the various determinants that drive fast food purchase decisions, ranging from demographic factors and taste preferences to marketing tactics and lifestyle trends. In addition, the research focuses on understanding the levels of consumer awareness about fast food. It investigates how health, quality, and brand reputation perceptions influence consumers' decisions. The most important emphasis in this paper is on social media marketing as a determinant of consumer behavior. Through this research, it tries to find out which social media channels have the greatest impact and what mechanisms transform digital engagement into real-world purchasing decisions. Such a discussion is significantly essential in determining the capability of platforms such as Instagram to create visually compelling narratives or that of Twitter to drive conversations around trending food items. The study will delve deeper into the relationship that social media sites have with the factors of consumer buy choice identified. This explores the interaction of different variables in social media marketing sites with traditional drivers of the purchase decision of consumers. In doing so, the paper will provide actionable insights for fast food marketers so that they can customize their strategies to enhance consumer engagement and satisfaction. Thus, the growing consumption of fast food in Delhi NCR calls for a more profound understanding of the underlying factors influencing consumer behavior. With social media marketing increasingly driving these behaviors, this study aims to bridge a critical gap in the literature by making a nuanced analysis of the intersection of digital platforms and consumer preferences. The research findings are expected to enrich the general discourse on consumer behavior and marketing strategy for both academic and industry stakeholder Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1728 https://internationalpubls.com audiences. 2. REVIEW OF LITERATURE 2.1 Concept of Fast-Food The concept of fast food is focused on providing quick, accessible, and cheap meals to the consumers looking for efficiency in dining (Story et al., 2002). Fast food dates back to the beginning of the 20th century when it evolved as a global trend through standardized procedures of preparation, ready-to- eat or partly cooked raw materials, and fast service (Espinoza, 2013). It is basically for urban populations with hectic lives, where time binds are the main reasons, and people prefer convenience over homemade food (Hubbard & Hubbard, 2017). Fast food chains like QSRs offer multiple options on their menu. The menu items include burgers, pizzas, fried chicken, sandwiches, and drinks. These menu items have something for everyone's taste (Manhas et al., 2024). Industry is booming on efficiency, scalability, and affordability and is primarily relying upon advanced technologies, automation, and innovation in supply chains to be able to cater to consumers' demands (Liberty et al., 2024). Even though fast food provides convenience and meets the hunger of many, it has been criticized about its health effects as most products are high in calories, fats, sugars, and sodium (Janssen et al., 2018). Still, the fast-food industry has been more accommodating in order to respond to shifting consumer needs and has added sustainability, customization, and cultural diversity into its services (Maumbe, 2012). That is why fast food not only changes eating behavior around the world but also has a significant impact on urban social life and the world's food economy (Hawkes et al., 2017). 2.2 Factors Influencing Consumer Behavior Towards Fast-Food Consumer behavior in the fast-food industry is highly driven by an intricate interaction of drivers for buying and preference mechanisms. Fast food restaurants have today become extremely attractive to consumers because they are convenient, affordable, and offer quick service (Hanaysha, 2016). The fast-food industry has dramatically changed to accommodate various tastes, dietary needs, and health-conscious dietary choices in response to changing consumer demands. Inhibitive factors on consumers are derived from the interlinked combination of intrinsic and extrinsic determinants, like lifestyle, cultural values, marketing strategies, peer influence, and trends in social media (Sharma & Joshi, 2021). Digital channels should not be underestimated because their influence in public opinion can be reflected through the form of social media campaigns, reviews in online platforms, and even endorsements by influencers, leading to consumer decisions (Dwivedi et al., 2021). At the same time, the boom of technology has also fostered convenience through mobile apps, ordering via the internet, and door-delivery services, making it easier than ever to eat fast food (Akram et al., 2020). Brands have often incorporated pricing strategies, promotions, and loyalty programs to appeal to repeated customers and build loyalty, which is more pronounced in young markets that are keen on making value-for-money purchases (Reinartz, 2009). Consumerism as influenced by healthy trends and awareness of nutrition has found its way into fast-food outlets in the form of healthier foods, nutritional ingredient labeling, and greener practices (Guthrie et al., 2015). However, yet and forever indulgence is all the stronger pull, besides comfort foods primarily because of stress-induced conditions and public happenings. Besides these, factors like brand image, quality of food items, Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1729 https://internationalpubls.com serving time, as well as environment of restaurants also come into play, and in deciding consumers choices (Yi et al., 2018). The companies in the fast-food business are constantly evolving according to these changing consumer preferences through the use of data analytics for more efficient understanding of behavior patterns to make their products relevant (Madureira et al., 2018). This is further facilitated by changing nature of urban life, as eating out has increasingly turned into lifestyles and social activities during the daily routine of individuals, hence fast food further cementing itself in the modern culture. 2.3 Consumer Awareness Towards Fast-food Consumption Consumer awareness about fast-food is the most crucial factor required to be changed in current fast- moving world for a change in eating behaviors and health outcomes (Farah & Shahzad, 2020). Awareness refers to what a consumer knows about nutritional information, health effects, environmental implications, and ethical considerations that apply to fast-food (Sharma et al., 2022). With growing health consciousness all over the world, consumers have started paying attention to calorie counts, fat content, and additives in their food items, although awareness is a matter of demographical differences among the consumers according to age, education, and socio- economic status (Eze & Mena, 2024). It has been found that in the urban areas, where it is accessible, convenient, and at a reasonable cost, most consumers acknowledge that fast-food is associated with health risks such as obesity, heart diseases, and diabetes, but this acknowledgment often does not translate into healthier choices due to preferences over the dimensions of taste, convenience, and affordability (Bahadoran et al. 2016; Stender et al., 2007). Fast-food chains' awareness campaigns usually get diluted because their advertisements focus on taste, speed, and value, but they do not speak about the health issues linked to frequent consumption (Kolhe, 2023). In fact, the influence of packaging and labeling on the consumer towards awareness is under researched, whereby consumers have tended to pay less attention to the nutritional data printed on the packaging of fast-food products (Penzavecchia et al., 2022; Soraghan, 2019). Despite such challenges, there is a shift towards healthier and sustainable choices, as reflected in the demand for organic, low-fat, and plant-based options in fast-food menus (Greene et al., 2024). These initiatives along with a strong media presence have enabled increased public health campaigns that have also sought to urge the consumer's mind beyond just immediate gratification to reflect on how their food intake will pan out in the long run. Although this gap remains, even in less literate populations or where the alternative may not be so readily accessible, intervention targeting fast food consumers to take informed choices is needed. 2.4 Impact of Social Media Marketing Strategies on Consumers Fast-Food Purchase Behavior It has basically transformed the consumption approach used by individuals to engage with fast foods, altering their patterns of buying habits to a significant extent (Lee et al., 2018). This is where the huge increase in social media such as Instagram, Facebook, Twitter, and most especially TikTok enables fast foods to utilize all these new media for strong online brand building and directly interacting with the target market (Cash et al., 2022). These strategies encompass some of the most widely followed tactics-from influencer partnerships and sponsored posts to interactional campaigns and user-created content, all with the final aim of getting attention for consumer interest. Brands make content Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1730 https://internationalpubls.com appealing and shareable on a larger scale with regards to convenience, novelty, and community through engaging visuals, videos, or real-time engagement (Montgomery & Chester, 2009). The use of appealing visual content, such as images of food and promotional videos, increases brand recall and triggers impulse buying, making consumers make rapid decisions, particularly if matched with special offers and exclusive promotions that are posted on social media (Linder, 2018). In addition, social media sites enable brands to engage directly with customers, respond to questions, solicit feedback, and improve customer service (Tsimonis & Dimitriadis, 2014). This interactivity further reinforces brand loyalty since the consumers feel they belong and are personally connected to the brands they follow. Social media also acts as a critical tool for creating trends, especially when viral challenges and hashtags related to new menu items or special deals are widely shared, resulting in increased visibility and consumer curiosity (Silberschneider, 2018). Such effects are more pronounced when it comes to collaborative marketing with social media influencers since there is a lot of trust held among followers that such influencers would influence their purchasing preference, encourage experimentation, especially to new consumers, and through the real-time nature of the social media platform, brand advertisements respond rapidly to consumers and trends within the market, which allows the promotional activity to be responsive in its activities through adjustments based on the current way of thinking in the consumer market (Mahoney & Tang, 2024). Through targeted advertisements, brands are able to further fine-tune the strategy by analyzing data-driven insights that allow them to reach a specific demographic and tailor the content to appeal to their preferences and behavior. Social media algorithms provide personalization such that users are exposed to content that aligns with previous interactions, making the journey from awareness to purchase seamless. This is both boosting consumer interest, ensuring promotions go into the right audience at the right time, thus increasing and more effective engagement of the consumers in addition to chances that would possibly lead to buying at this given time. Most fast-food brands have this in their strategy so not only enhancing brand perception, but rather creating an aspect of eagerness for its items (Daradkeh et al., 2023). Beyond short-term sales increases, these approaches define long-term consumer preference and build a digital community of brand advocates who will share positive experiences and encourage friends to make purchases, thereby making the consumer an active participant in the brand's growth and success. 3. OBJECTIVES OF THE STUDY • To examine the factors influencing consumers behavior towards consumption of fast- food in Delhi NCR. • To analyze the consumers awareness level towards fast-food in Delhi-NCR. • To determine the most important social media platform which influence consumers purchase behavior towards fast-food in Delhi NCR. • To examine the correlation between social media platforms and extracted factors of consumer behavior influencing fast-food consumption in Delhi-NCR. 4. HYPOTHESES OF THE STUDY Null Hypothesis (H01): There are no factors influencing consumer behavior towards consumption of Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1731 https://internationalpubls.com fast food in Delhi NCR. Alternative Hypothesis (H1): There are significant factors influencing consumer behavior towards consumption of fast food in Delhi NCR. Null Hypothesis (H02): Consumers in Delhi-NCR have a low level of awareness towards fast- food. Alternative Hypothesis (H2): Consumers in Delhi-NCR have a high level of awareness towards fast-food. Null Hypothesis (H03): No specific social media platform significantly influences consumers' purchase behavior towards fast food in Delhi NCR. Alternative Hypothesis (H3): At least one specific social media platform significantly influences consumers' purchase behavior towards fast food in Delhi NCR. Null Hypothesis (H04): There is no significant correlation between social media platforms and the extracted factors of consumer behavior influencing fast-food consumption in Delhi NCR. Alternative Hypothesis (H4): There is a significant correlation between social media platforms and the extracted factors of consumer behavior influencing fast-food consumption in Delhi NCR. 5. RESEARCH METHODOLOGY The study titled "Factors Influencing Consumer Behavior Towards Fast Food and the Role of Social Media Marketing on Consumers Fast Food Purchase Decision in Delhi NCR" is designed to examine the dynamics of consumer behavior and the impact of social media platforms on fast food consumption decisions in the Delhi NCR region. The questionnaire was developed with utmost care and attention, as the research objectives and hypotheses had to be achieved. It was done after an in- depth review of the existing literature and seeking guidance from the research supervisors on all the relevant aspects. Google Forms was used for developing the questionnaire for ease of distribution and collection of data. Convenience sampling was made to reach the consumers within the Delhi NCR region through e-mail and social networking sites, ensuring varied participants. Data collection was done in December 2024, and the questionnaire was administered to 270 consumers out of whom 225 consumers' responses were obtained. After removing invalid or incomplete responses, 220 valid responses were considered for analysis. The questionnaire consisted of five categories. The first category acquired demographic information about the subjects. These include age and gender, income, education, and other demographic items. The second category would cover the profile of their consumers and how they relate to such consumption behavior with their usage of other social media applications. The third section consisted of questions on 16 variables that influence consumer behavior towards fast food consumption, which were measured using a five-point Likert scale from "Not at all Influential" to "Extremely Influential." The fourth section measured the awareness level of consumers about fast food by using a five-point Likert scale from "Not at all Aware" to "Extremely Aware." The fifth section measured the influence of social media on consumers' decisions regarding fast food purchases, which was also measured using a five-point Likert scale from "Not at all Influential" to "Extremely Influential." SPSS software is used for the analysis of data. The reliability of the questionnaire will be assessed using Cronbach's Alpha, and the obtained results are as follows: Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1732 https://internationalpubls.com the overall reliability of the 54-item questionnaire stands at 0.934; the reliability of the 16 items measuring the variables influencing consumer purchase behavior is 0.958; the reliability of the 12 items measuring the consumer awareness levels is 0.955; the reliability of the 12 items measuring the influence of the social media platforms is 0.924. These values reflect good internal consistency throughout all parts of the questionnaire. In data analysis, different statistical tools were used to achieve the objectives of the study. For the first objective, PCA was performed to derive the underlying factors driving consumer behavior toward fast food consumption. For the second objective, descriptive analysis was done by calculating the weighted mean to determine consumer awareness levels regarding fast food. To achieve the third objective, mean ranks were employed by applying the Friedman test in ranking the social media sites based on their influence on the fast- food purchasing decisions of consumers. By adopting Spearman correlation analysis to test the relationship between the extracted factors of consumer behavior, where the data is not normatively distributed, the present study aims to achieve its fourth objective. This methodology therefore provides a robust framework whereby in a systematic manner, a country can examine the factors, be it awareness level, a role of social media platform, and the correlation among the factors and consumer behavior at the fast-food sector within Delhi NCR. 6. DATA ANALYSIS AND INTERPRETATION 6.1 Demographic Profile of Consumers Table 1: Demographic profile of respondents Parameter Variables Frequency Percentage Gender Male 114 51.8 Female 106 48.2 Age 18-25 Years 90 40.9 26-35 Years 49 22.3 36-45 Years 60 27.3 46-55 Years 21 9.5 Aove 55 Years -- -- Marital Status Single 117 53.2 Married 103 46.8 Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1733 https://internationalpubls.com Educational Qualification Intermediate 53 24.1 Graduate 91 41.4 Postgraduate 51 23.2 Doctorate 8 3.6 Others 17 7.7 Occupation Student 72 32.7 Government Employee 42 19.1 Private Job 38 17.3 Self-Business 43 19.5 Others 25 11.4 Annual Income Not Earning 89 40.5 Up to 3 Lakhs 33 15 3-6 Lakhs 36 16.4 6-10 Lakhs 32 14.5 More than 10 Lakhs 30 13.6 Family Status Nuclear Family 141 64.1 Joint Family 79 35.9 Residential Status in Delhi NCR Local Resident 168 76.3 Visitor 52 23.6 5.2 Profile of respondents related to Fast-food Consumption and Social Media Usage Table 2: Profile of respondents related to their fast-food consumption and social media usage Parameter Variables Frequency Percentage Frequency of Eating Fast Food Daily 25 11.4 2-3 times a week 83 37.7 Once a week 54 24.5 Occasionally 41 18.6 Rarely 17 7.7 Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1734 https://internationalpubls.com Normally Preferred Fast Food North Indian (Samosa, Chole Bhature etc.) 97 44.1 South Indian (Idli/Dosa with Sambhar) 31 14.1 East Indian (Momos) 33 15 West Indian (Pav Bhaji, Vada pav etc.) 4 1.8 Italian (Pasta) 8 3.6 Chinese (Chowmein, Chilli Paneer) 47 21.4 How do you usually order fast food? Online Delivery Apps 88 40 Visiting Outlets 112 50.9 Drive Through 3 1.4 Others 17 7.7 Place you prefer to eat fast food Quick Service Restaurants (McDonald’s, Domino’s Pizza, KFC etc.) 73 33.2 Cafes and Coffee Shops (Starbucks, Costa Coffee etc.) 30 13.6 Food Courts in Malls 14 6.4 Street Food Vendors 81 36.8 Others 22 10 Primary mode of assessing social media Smartphone 207 94.1 Tablet 4 1.8 Laptop/Computer 1 0.5 Smart TV 6 2.7 Others 2 0.9 Time spend on social media Less than 1 hour 24 10.9 1-2 hours 98 44.5 3-4 hours 58 26.4 More than 4 hours 40 18.2 Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1735 https://internationalpubls.com 6.3 Factors Influencing Consumer Behavior Towards Fast-Food Consumption The first objective of the study is to examine the factors influencing consumers behavior towards consumption of fast-food in Delhi NCR. Null Hypothesis (H01): There are no factors influencing consumer behavior towards consumption of fast food in Delhi NCR. Alternative Hypothesis (H1): There are significant factors influencing consumer behavior towards consumption of fast food in Delhi NCR. Factor analysis is performed to determine the most important factors influencing consumers behavior towards consumption of fast-food in Delhi NCR. Table 3: KMO and Bartlett test KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .940 Bartlett's Test of Sphericity Approx. Chi-Square 3207.301 Df 120 Sig. .000 Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett's test of sphericity (homogeneity of Variance) has been applied to check the appropriateness of the data. 0.940 is the KMO measure of sampling adequacy value that presents the applicability of the factor analysis for the data being analyzed. Likewise, the value of Bartlett's test of sphericity is significant at p < 0.001 which represents the presence of ample correlation between variables for analyzing. Table 4: Total variance explained Total Variance Explained Compone nt Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative % 1 9.832 61.447 61.447 9.832 61.447 61.447 6.278 39.238 39.238 2 1.535 9.595 71.043 1.535 9.595 71.043 5.089 31.804 71.043 3 .895 5.595 76.638 4 .564 3.526 80.164 Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1736 https://internationalpubls.com 5 .506 3.160 83.324 6 .427 2.671 85.995 7 .377 2.356 88.350 8 .315 1.971 90.322 9 .281 1.758 92.080 10 .257 1.608 93.689 11 .219 1.370 95.059 12 .194 1.213 96.271 13 .181 1.134 97.406 14 .155 .967 98.373 15 .140 .876 99.248 16 .120 .752 100.000 Extraction Method: Principal Component Analysis. Interpretation: In above table, output lists the 16 variables associated with each linear component (factor) before extraction, after extraction and after rotation. Before extraction, Output has identified 2 linear components within the data set. After extraction and rotation, the most important factor 1 explained 61.447% of total variance and factor 2 explained 9.595% of total variance that can be extracted. As evident from the above table (Total Variations Explained) it was found that from the total 2 components, 1st factor is most important and can be extracted. Table 5: Rotated component matrix Rotated Component Matrixa Component 1 2 Food Quality .844 Valur for money .822 Taste .816 Discount/Offers .769 Affordability .740 Health-conscious choices .716 Variety of options .696 Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1737 https://internationalpubls.com Speed of service .678 Location .674 Ease of ordering .658 Cultural preferences .849 Social media impact .827 Promotions and advertising .820 Brand reputation .792 Packaging Appeal .709 Peer influence .693 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 3 iterations. Factor analysis of the 16 variables influencing consumer behavior toward fast food consumption in the Delhi NCR region revealed two distinct factors. They were extracted using principal component analysis, which was rotated with the Varimax method for better interpretation. The rotated component matrix reports the loadings of every variable on the two factors that were extracted. We interpret the factors with the help of factor loadings, provide appropriate names, and discuss the sub-variables with their respective values and possible reasons for the results. Factor 1: "Convenience and Value-Oriented Consumption" Factor 1 captures the practical and economic factors that influence consumer behavior toward fast food consumption in Delhi NCR. This includes food quality (0.844), value for money (0.822), taste (0.816), and discounts/offers (0.769), which show the preference of consumers for affordability and quality. The high load for affordability (0.740) speaks to the fact that consumers within this region are very sensitive to cost, looking for value in the offer versus the price paid. The other two factors most strongly represented are health-conscious offerings (0.716) and a variety of options (0.696), showing consumers' increasing desire for healthy and more customized fast-food experiences. Attributes such as speed of service (0.678), location (0.674), and ease of ordering (0.658) establish the significance of convenience in busy urban lifestyles where time- efficient living is considered paramount. The results are congruent with the busy, cost-sensitive, and health-conscious lifestyles that are prevalent in Delhi NCR. With this factor, consumers converge in terms of these factors to indicate a priority on fast food options that not only are affordable but also quick and accessible and meet their quality and variety expectations. Factor 2: Social and Cultural Influences Factor 2 includes the social and cultural forces that play a significant role in consumer behavior. Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1738 https://internationalpubls.com Variables such as cultural preferences (0.849) and impact of social media (0.827) suggest the role of cultural fit and digital media in consumer decision-making. In a culturally diverse region like Delhi NCR, fast food chains that resonate with local tastes and customs are at an advantage. This means that promotions and advertising (0.820) and brand reputation (0.792) are more significant indicators of effective marketing campaigns and consumer trust, which leads to preference building. Peer influence (0.693) and packaging appeal (0.709) also appear as significant indicators; aesthetics play a role in the buying decision, as do social circles. Attractive packaging increases perceived value and augments convenience, which are among the features of fast food. Peer recommendations and social validation are very important factors in building trust and promoting trial, especially among younger consumers. Together, this factor underscores how external influences, including cultural norms and digital marketing strategies, shape consumer perceptions and drive fast food consumption in the region. There were two primary dimensions indicated from the factor analysis related to fast food consumption in Delhi NCR. First was concerning the functional and practicality of fast-food consumption for its convenience, affordability, and variety. The second, on the other hand, emphasized the external influence in terms of social media, advertising, and what one thinks their peers would do or expect. These insights are critical for fast food businesses in tailoring their strategies to cater to the nuanced preferences and behaviors of consumers in the region. With results from factor analysis, the Alternative Hypothesis (H1) is accepted as significant factors influencing consumer behavior toward fast food consumption in Delhi NCR were found. 6.4 Consumers Awareness Level Towards Fast-Food in Delhi-NCR The second objective of the study is to analyze the consumers awareness level towards fast-food in Delhi-NCR. Consumers of fast-food in Delhi-NCR were asked questions on 12 parameters. Null Hypothesis (H02): Consumers in Delhi-NCR have a low level of awareness towards fast-food. Alternative Hypothesis (H2): Consumers in Delhi-NCR have a high level of awareness towards fast- food. Table 6: Descriptive statistics of consumers awareness level towards fast-food Descriptive Statistics N Minimum Maximum Mean Std. Deviation Awareness of fast-food brands 220 1 5 2.96 1.466 Awareness of nutritional content of fast food 220 1 5 3.11 1.330 Awareness of ingredients in fast food 220 1 5 3.09 1.345 Awareness of health risks of fast food 220 1 5 3.29 1.416 Awareness of hygiene standards 220 1 5 3.36 1.422 Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1739 https://internationalpubls.com Awareness of calorie count 220 1 5 3.15 1.338 Awareness of marketing strategies of fast food 220 1 5 3.10 1.334 Awareness of discounts/deals/loyalty programs offered by fast food outlets 220 1 5 3.16 1.334 Awareness of promotional campaigns 220 1 5 2.95 1.252 Awareness of packaging and sustainability 220 1 5 3.20 1.304 Awareness of ethical/local sourcing 220 1 5 3.04 1.271 Awareness of consumers rights towards fast food 220 1 5 2.85 1.392 Valid N (listwise) 220 Table no. 6 highlights critical inputs into the perception and knowledge that consumers within Delhi- NCR have related to fast foods, compared across 12 dimensions. Results show that a moderate-to- high level of awareness of consumers is evidenced at several junctures because mean values across parameters predominately exceed the midpoint of a 5-point scale. It goes to indicate that fast-food consumers in the region are somewhat well-informed, after all, with some deviation in terms of the chosen parameter. The results from the descriptive analysis reveal consumer awareness toward fast food to have varying levels in Delhi-NCR, with parameters ranked starting from the highest to lowest basis on their mean values. Top is awareness of hygiene standards, with a mean score of 3.36 (SD = 1.422). It is evident that hygiene and safety are top priorities among consumers. This may be the result of heightened public interest in health and hygiene in recent times, mainly following the COVID-19 pandemic. Close behind is awareness of the health risks of fast food, with a mean of 3.29 (SD = 1.416). This indicates that most customers are aware of the negative impacts associated with fast food consumption, including obesity and other lifestyle diseases. Packaging and sustainability knowledge follows with a mean of 3.20 (SD = 1.304). This reflects an increasing consciousness about environmental issues and responsible practices. In the same direction, knowledge of discounts, deals, and loyalty schemes scores 3.16 (SD = 1.334), which reflects economic incentives as a driver for consumer behavior. Meaningful awareness of calorie count is 3.15, SD = 1.338 and mean for nutritional content of fast food is 3.11, SD = 1.330, which signifies that most consumers are well aware of the dietary information. Most of the respondents also seem to be aware of marketing strategies (mean 3.10, SD = 1.334) and ingredients in fast food (mean 3.09, SD = 1.345). These indicators show that, although consumers notice the marketing activities of fast-food brands and the composition of their foods, these issues are not of high importance to them. Even knowledge about ethical and local sourcing (mean 3.04, SD = 1.271) shows a moderate concern for sustainable and ethical food sourcing practices, but the interest in such matters is growing, although not very popular. Awareness of fast-food brands stands at a mean score of 2.96 (SD = 1.466), while awareness of fast- food brand names reflects that while people are aware of the most popular names, they might not Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1740 https://internationalpubls.com know smaller brands. In addition, knowledge of advertising campaigns also shows that there is a mean score of 2.95 (SD = 1.252), indicating fairly limited engagement with or recalling specific advertisements. Consumer rights awareness ranked the lowest at the bottom with the lowest mean score at 2.85, SD = 1.392. This implies an important gap in knowledge about what legal protection exists and what consumer entitlements exist in the case of food quality, refunds, or redress. The overall results show that Delhi-NCR consumers have fairly good awareness about the crucial parameters like hygiene standards, health risks, calorie content, and economic benefits through discounts and deals. It would indicate an urban consumer population, with high exposure to the diversified fast-food products along with aggressive marketing of big brands. However, lower awareness levels in parameters such as consumer rights and ethical sourcing call for increased communication efforts on the part of fast-food outlets and awareness campaigns by consumer organizations. Since the mean scores for most parameters are near or above 3, the Alternative Hypothesis, H2 is accepted. Delhi-NCR consumers, therefore, have high fast-food awareness, so also reject the Null Hypothesis (H02). This can be accounted by the fact that consumers belonging to this region have the urban and educated population with widespread media exposure and increased accessibility towards health and nutritional information. 6.5 Analysis of Social Media Platforms Which Influences Consumers Purchase Behavior Towards Fast-Food The third objective of the study is to determine the most important social media platform which influence consumers purchase behavior towards fast-food in Delhi NCR. Null Hypothesis (H03): No specific social media platform significantly influences consumers' purchase behavior towards fast food in Delhi NCR. Alternative Hypothesis (H3): At least one specific social media platform significantly influences consumers' purchase behavior towards fast food in Delhi NCR. Table 7: Friedman test for ranking social media platforms Ranks Mean Rank Instagram 7.83 Facebook 7.12 You Tube 8.31 Tik Tok 5.58 Snapchat 6.26 Twitter 5.88 Pinterest 6.01 Linkedin 5.60 Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1741 https://internationalpubls.com Reddit 5.51 Whatsapp 8.15 WeChat 5.85 Quora 5.90 The Friedman test was performed to check the significance of different social media platforms on consumer purchasing behavior for fast food in Delhi NCR. It is found that the mean ranks assigned to the different sites differ significantly. It implies that not all the platforms are equally effective in influencing the consumer behavior. YouTube has been identified as the most influencing platform with the highest mean rank at 8.31. This outcome shows the strength of the platform in molding consumer behavior mainly because of its ability to present appealing video content that is visually stimulating and informative. It enables brands to have appealing adverts, influencer endorsements, and tutorials that influence fast food purchases. The algorithm has been accurate in recommending relevant content to users, therefore ensuring brands target the relevant audiences. WhatsApp is another platform with a mean rank of 8.15, highly influential. WhatsApp is one of the most private and direct forms of communication; also, WhatsApp Business is becoming increasingly popular for promotional messages to reach consumers. The use of WhatsApp by fast-food brands for personalized offers and discounts has positioned the application as an influencer in consumer choice decisions. With a mean rank of 7.83, Instagram ranks high because its contents are visually rich and often very influencer and user-generated content-driven. The ability to fit in promotional campaigns is quite impressive since the aesthetics of the application help integrate them smoothly with the feeds and stories. Facebook, having a mean rank of 7.12, remains influential for most consumers, especially within an aged demographic. The website hosts significant numbers of users, thus being able to accommodate and involve diverse audiences, by brands through its instruments of ads. Platforms such as Snapchat ranked with a mean at 6.26, Pinterest a mean of 6.01, and Twitter 5.88 have a moderate level of influences since they mostly represent the specialized audience. Snapchat appeals to younger users, Pinterest appeals to those interested in ideas and inspiration, and Twitter allows for brand visibility through discussions and trending topics, though not as strong as YouTube or Instagram. Platforms like WeChat, 5.85 and Quora, 5.90, also exhibit moderate influence probably because they are able to present information in detail and allow the creation of meaningful interactions. Quora enables users to go as deep as possible on the questions regarding fast food brands. WeChat integrates communication with promotional features. At the lower end, there is TikTok, 5.58, LinkedIn, 5.60, and Reddit, 5.51, with the least influence. TikTok, though popular, is more entertainment-oriented and may not necessarily align with purchase intent for fast food. LinkedIn is professional and not as relevant to the promotion of fast food. Reddit is community- driven and may not appeal broadly to fast-food consumers. These findings suggest that platforms with a combination of aesthetics, direct communication, and a good content algorithm—such as YouTube, WhatsApp, and Instagram—are the most impactful in influencing consumer behavior towards fast food in Delhi Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1742 https://internationalpubls.com NCR. On the other hand, niche audience or professional networking sites have low influence. The findings highlight that fast-food brands should focus on effective marketing strategies on high-impact platforms and take into account the specific nature and styles of engagement on each social media site. The great variation in mean ranks implies that certain social media have varying effectiveness in influencing consumer purchase decision about fast food. Since the Friedman test revealed significant differences between the ranks, the alternative hypothesis H3 is confirmed, which means that at least one of the social media platforms statistically influences consumer purchase behavior. The findings highlighted the need for fast food brands to strategically concentrate their digital marketing efforts on platforms such as YouTube, Instagram, and WhatsApp, where they can reach people and influence them more effectively by using attractive and engaging visuals. 6.6 Correlation Between Social Media Platforms and Extracted Factors Of Consumer Behavior The fourth objective of the study is to examine the correlation between social media platforms and extracted factors of consumer behavior influencing fast-food consumption in Delhi-NCR. Null Hypothesis (H04): There is no significant correlation between social media platforms and the extracted factors of consumer behavior influencing fast-food consumption in Delhi NCR. Alternative Hypothesis (H4): There is a significant correlation between social media platforms and the extracted factors of consumer behavior influencing fast-food consumption in Delhi NCR. The results of correlation analysis between social media platforms and the extracted factors of consumer behavior influencing fast-food consumption are presented in Table 8 for Delhi NCR, showing various significant relationships. This analysis was conducted for testing the null hypothesis, H04, which hypothesizes that there exists no significant correlation between the social media platforms and factors of consumer behavior, as against the alternative hypothesis H4, which suggests an existence of a significant relationship. Factor 1: "Convenience and Value-Oriented Consumption" refers to factors that consumers are guided by, mainly related to value for money, food quality, taste, discounts, health considerations, variety, speed of service, distance, and order ease. The study revealed that convenience and value-oriented consumption, on its part, have a highly significant positive association with the use of Instagram (r = 0.325, p < 0.01); therefore, Instagram users would be guided by convenience and value-oriented consumption considerations. Similarly, YouTube (r = 0.292, p < 0.01) and WhatsApp (r = 0.100, p < 0.05) also have a positive correlation with this factor, showing that these platforms contribute to consumer behavior that emphasizes convenience and cost- effectiveness. The positive correlation of Facebook (r = 0.062, p = 0.359) with this factor, however, is not statistically significant and indicates a lesser relationship with convenience and value-oriented consumption. Factor 2: "Social and Cultural Influences" encompasses the role of social dynamics, cultural preferences, and marketing strategies in influencing consumer behavior. Both also here have a positive highly significant correlation with Instagram as r = 0.356, p <0.01 and with Youtube as r = 0.395, p<0.01 indicating significant positives, hence the presence on fast foods of social and cultural influential items, which may be an effect of tailored content together with targeted advertisement. Facebook is a highly positive correlation with a value of r = 0.379, p < 0.01, indicating its use in the dissemination of a Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1743 https://internationalpubls.com diverse audience through social interactions and advertisements. The TikTok app demonstrates a positive correlation of r = 0.270, p < 0.01, yet further underlines its power on consumer behavior through the popular contents and peer-driven promotion. Besides, Snapchat has r = 0.374, p < 0.01, with significant correlation indicating how transitory and interesting contents could have an effect on consumer perceptions and selections. The converse, however, is platforms that show weaker or even negative correlations. TikTok shows a negative correlation with Factor 1 (r = -0.171, p < 0.05). This means that while TikTok can influence social and cultural behavior positively, the influence on convenience and value-oriented consumption is less direct. It negatively correlates with Factor 1, r = -0.154, p < 0.05 and positively but weakly with Factor 2, r = 0.338, p < 0.01. That is to say that even though convenience-oriented behavior might not strongly be encouraged by Twitter, it is still significant in moulding social and cultural influences. WeChat negatively correlates with Factor 1 (r = -0.238, p < 0.01) and a very weak positive correlation with Factor 2 (r = 0.175, p < 0.01) and seems to be limited in comparison to the effect of other platforms. Platforms such as Pinterest (r = -0.112, p = 0.096) and Reddit (r = -0.102, p = 0.131) are not significant, which means that they might not be the primary factors in either of the factors related to fast food consumption in Delhi NCR. LinkedIn (r = -0.065, p = 0.339) also fails to demonstrate significant correlations, which shows that it has a minimal impact because of its professional nature. Quora (r = -0.072, p = 0.287) had no significant correlation with factor 1. In the final analysis, hypothesis testing reveals a valid reason to reject the null hypothesis (H04) and favor the alternative hypothesis (H4). The findings prove the existence of a significant correlation between the adoption of social media platforms like Instagram, YouTube, WhatsApp, and Facebook and factors related to fast-food consumption in Delhi NCR. These correlations underscore the importance of strategic social media engagement for fast-food brands that are trying to appeal to consumers who prioritize convenience, affordability, and cultural alignment, while also recognizing the different impact of different platforms in promoting these behaviors. Table 8: Spearman Correlation analysis between social media platforms and extracted factors of consumer behavior towards fast food Correlations Factor 1 ("Convenience and Value-Oriented Consumption" Factor 2 (Social and Cultural Influences) Spearm an's rho Instagram Correlation Coefficient .325** .356** Sig. (2-tailed) 0.000 0.000 N 220 220 Facebook Correlation Coefficient 0.062 .379** Sig. (2-tailed) 0.359 0.000 N 220 220 Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1744 https://internationalpubls.com You Tube Correlation Coefficient .292** .395** Sig. (2-tailed) 0.000 0.000 N 220 220 Tik Tok Correlation Coefficient -.171* .270** Sig. (2-tailed) 0.011 0.000 N 220 220 Snapchat Correlation Coefficient -0.042 .374** Sig. (2-tailed) 0.535 0.000 N 220 220 Twitter Correlation Coefficient -.154* .338** Sig. (2-tailed) 0.022 0.000 N 220 220 Pinterest Correlation Coefficient -0.112 .248** Sig. (2-tailed) 0.096 0.000 N 220 220 Linkedin Correlation Coefficient -0.065 .266** Sig. (2-tailed) 0.339 0.000 N 220 220 Reddit Correlation Coefficient -0.102 .287** Sig. (2-tailed) 0.131 0.000 N 220 220 Whatsapp Correlation Coefficient 0.100 .316** Sig. (2-tailed) 0.137 0.000 N 220 220 WeChat Correlation Coefficient -.238** .175** Sig. (2-tailed) 0.000 0.009 N 220 220 Quora Correlation Coefficient -0.072 .243** Sig. (2-tailed) 0.287 0.000 Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 1745 https://internationalpubls.com N 220 220 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). 7. CONCLUSIONS This study has analyzed the behavior of consumers toward fast food in Delhi NCR, focusing on key influencing factors and the role of social media marketing in shaping purchasing decisions. Factor analysis identified two primary dimensions: Convenience and Value-Oriented Consumption and Social and Cultural Influences. The first-dimension underscores practical considerations, such as affordability, quality, and convenience, which drive consumers' preferences for fast food. The second dimension highlighted the significance of cultural alignment, marketing efforts, and peer influence, illustrating how social factors and digital engagement are key in consumer choice. Consumer awareness levels were high, especially in areas such as hygiene, health risks, and economic incentives, which fit well with the region's informed and health-conscious population. Notably, social media has played the role of an impactful channel in decision-making about purchases; YouTube, WhatsApp, and Instagram were the most significant sources for such effects considering their capacity to facilitate entertaining, relevant content and personalized offers. The correlation analysis further supported these findings, with significant relationships between social media use and consumer behavior variables, underlining the importance of digital strategies in contemporary marketing. This study underscores the need for fast-food brands in Delhi NCR to adapt their marketing strategies to capitalize on impactful platforms and resonate with consumer desires for convenience, value, and cultural relevance. 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