Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1
Javier Cabeza-Ramírez
 -- 2584 2023-12-19 10:01:34 |
2 Reference format revised.
Lindsay Dong
 -7 word(s) 2577 2023-12-22 01:40:58 |

Video Upload Options

Do you have a full video?
Send video materials Upload full video

Confirm

Are you sure to Delete?
Yes No
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Ali-Alsaadi, A.A.; Cabeza-Ramírez, L.J.; Sántos-Roldán, L.; Loor-Zambrano, H.Y. Digital Marketing and Fast-Food Intake. Encyclopedia. Available online: https://encyclopedia.pub/entry/52914 (accessed on 29 April 2024).
Ali-Alsaadi AA, Cabeza-Ramírez LJ, Sántos-Roldán L, Loor-Zambrano HY. Digital Marketing and Fast-Food Intake. Encyclopedia. Available at: https://encyclopedia.pub/entry/52914. Accessed April 29, 2024.
Ali-Alsaadi, Ali Ahmed, L. Javier Cabeza-Ramírez, Luna Sántos-Roldán, Halder Yandry Loor-Zambrano. "Digital Marketing and Fast-Food Intake" Encyclopedia, https://encyclopedia.pub/entry/52914 (accessed April 29, 2024).
Ali-Alsaadi, A.A., Cabeza-Ramírez, L.J., Sántos-Roldán, L., & Loor-Zambrano, H.Y. (2023, December 19). Digital Marketing and Fast-Food Intake. In Encyclopedia. https://encyclopedia.pub/entry/52914
Ali-Alsaadi, Ali Ahmed, et al. "Digital Marketing and Fast-Food Intake." Encyclopedia. Web. 19 December, 2023.
Digital Marketing and Fast-Food Intake
Edit
This entry is adapted from the peer-reviewed paper 10.3390/foods12224089

The connection between digital marketing and consumption behavior in the fast-food industry among the adult population provides a series of essential practical implications for marketing professionals and companies in the sector. The adult population often has a higher purchasing power and more autonomous purchase decisions compared to younger populations, it is vital that companies understand how to influence this demographic segment responsibly. In relation to firm-generated content (FGC), it is essential that brands invest in creating genuine, relevant, and attractive content that resonates with the adult population, warning of harmful consumption patterns. Strategies that go beyond simple promotions and focus on values, healthy lifestyles, and social responsibility might have a more profound impact on this demographic group.

fast-food consumption patterns social media engagement digital marketing health implications consumer behavior

1. Introduction

In the current society, digitization and the rise of social media have dramatically transformed how businesses engage with their customers and consumers [1][2][3]. In particular, the fast-food industry has exhibited remarkable adaptability to these shifts, strategically incorporating social media platforms as a core component of their marketing strategy [4][5][6]. One of the most notable transitions has been the gradual shift from traditional communication and advertising channels (television, radio, and press) to a new landscape where they coexist with social media advertising [4][7]. Within these platforms, company-generated content plays an essential role in shaping consumer behavior [1][8][9]. This tool serves as direct promotion, facilitating interaction and engagement with the audience, allowing for bidirectional information flows [4][5][10][11][12].
In this context, international fast-food franchises frequently advertise their latest creations and products on these platforms: “Indulge in the Signature Crafted Recipes collection by McDonald’s and discover the sweet and savory flavors from our menu of mouthwatering burgers”; “Enjoy our delicious recipes on single or double 100% fresh beef patties that are sizzled and seasoned on our flat iron grill right when you order” [13]. These campaigns are intensively promoted on the brand’s portal and social media, encompassing text, graphics, photos, videos, or reviews from culinary influencers [1][4][14]. Within hours, the company-generated content becomes available to millions of users [4][9][11]. Any potential social media user can interact with the brand’s post, make an online purchase, try and taste the product, and share their own experience [6][10][15]. For instance, a gourmet burger designed by a renowned chef, accompanied by a special sauce that promises to revolutionize the consumer’s palate [16][17]. This type of advertising strategy, rooted in brand-generated content, is easily replicable for businesses across sizes and sectors [15][18].
Concurrently, political, social, and academic concerns about the effects of exposure to fast-food advertisements on social media have been escalating [19][20][21]. This is, in part, due to repeated warnings from the World Health Organization (WHO) on the health implications of promoting unhealthy diets: “fast food, sugar-sweetened beverages, and chocolate and confectionery” [22]. Recent research has aimed to calibrate these effects, especially among more vulnerable groups like children and adolescents [5][21][23][24][25][26]. However, few studies have focused on the repercussions of advertising on consumption patterns among adults. In this regard, prior investigations like those by Bragg, Pageot, Amico, Miller, Gasbarre, Rummo, and Elbel [4] identified varying interaction behaviors with advertisements based on the target audience. This ties into the potential of fast food (ultra-processed) as a possible trigger for obesity and related health issues [27]. Accordingly, various studies have underscored how cumulative exposure to advertising correlates with fast-food consumption in adults [8][9][28].

2. Digital Marketing and Fast-Food Intake

Analysis of the effects of advertisements and marketing communications on food and nutrition has become an emerging research line [29][30][31]. Various studies have provided evidence on the potential adverse effects of advertising on the consumption patterns of unhealthy foods [9][23][25][31]. Research focused on fast food faces the absence of a universally accepted definition of the concept [32].
Within this framework, the impact of advertising on fast food consumption patterns shows significant variations across cultures, influenced by distinct traditions, values, and mindsets [33][34]. While Western societies amplify the promotion of convenience and speed, in cultures with deep culinary traditions, such as Japan or Korea, advertising tends to focus on quality and the fusion of traditional flavors with modern fast-food formats [35][36]. This cultural dichotomy is even more pronounced in the United Arab Emirates, where a massive expatriate population intersects with a rich cultural heritage to create a unique backdrop. Here, the efficacy of social media advertising is shaped by a complexity of sociocultural factors, requiring marketing campaigns to balance universally appealing attributes with local values such as hospitality and family communion during meals [37][38]. Several European studies have shown that food products commonly promoted on television do not adhere to international guidelines (European nutrient profile model of the World Health Organization); for instance, Gallus et al. [39], in a study in Italy, concluded that most food advertisements during children’s viewing times violated these directives. Similarly, in Brazil, based on content analysis of advertisements from different brands associated with fast food, Pereira [40] found the same trend. In New Zealand, Vandevijvere et al. [41] mapped convenience stores, fast food, and takeaway outlets, showing that the country’s schools are surrounded by marketing of unhealthy foods.
In this vein, the troubling connection between fast-food advertising and public health issues like obesity is evident, underlining notable cultural differences [9][42][43][44]. Although advertising for high-energy, low-nutrient foods is associated with an increasing prevalence of obesity across cultures, reactions to these advertising practices vary widely [5][8][43]. In places where obesity is prevalent, fast-food advertising faces scrutiny and stricter regulations are put in place, demanding that companies promote healthy habits and avoid messages that exploit the most vulnerable [31][45]. Conversely, in cultures with traditionally low obesity rates and an emphasis on dietary moderation, advertising has focused less on health and more on the taste and convenience of fast foods [35][36][46]. However, even these societies are not immune to change, as the growing influence of Western lifestyles and the availability of fast food are introducing new public health challenges that demand attention [31][47].

2.1. Relationships between Firm-Generated Content (FGC), Attitudes towards Social Media Advertising (ASMA), Social Media Engagement (SME), and Online Shopping Behavior

Kumar, Bezawada, Rishika, Janakiraman, and Kannan [18] conceptualized firm-generated content (FGC) as messages directly emanated by brands on their official platforms and social networks, emphasizing its capability to fortify relationships with customers through the interactive dynamics that social media provides. This variable manifests not only as a conduit offering essential information on products, prices, and promotions, but is also augmented by consumer interactions and evaluations, both positive and negative. In this context, FGC encompasses a variety of content crafted by the brand, including texts, images, videos, and other formats [15][48]. Such content has been shown to have a profound impact in areas like brand recognition, loyalty, and purchase intention [48]. Beyond its intrinsic goals of promotion and engagement [15][48], FGC sways consumer attitudes and values [49], and when paired with positive experiences with products and corporate practices, can result in favorable sentiments [50].
In alignment with this, FGC emerges as a pivotal agent in shaping and adjusting consumer attitudes towards social media advertising (ASMA) [42][48]. This content not only informs but, acting as a paramount source of information, holds the potential to persuade and reshape perceptions [15]. Moreover, due to its ability to incorporate playful and creative elements [38], FGC captures and sustains consumer attention [51]. An illustrative case could be a fast-food restaurant campaign, which, by employing humor and appealing visual design, evokes a more positive response to its social media advertising [52]. This interactive nature of FGC, granting consumers the freedom to express their approval or share content, boosts their engagement [15][48], and could serve as a social endorsement, positively shifting the perceptions of other consumers [53]. Consequently, in juxtaposition with other advertising formats, it may be perceived as more authentic, especially if synergized with user-generated content [15][54].
Recent studies on FGC have suggested that messages disseminated on company-owned social media platforms have the potential to evoke a positive perception and brand image in consumers [55]. However, they emphasize that further research is still needed regarding the impacts of the two types of FGC (emotional and informational) on consumer engagement behaviors (likes, shares, comments). Social media engagement (SME) signifies the level of commitment and interactions evoked by the brand’s content [8]. It acts as a catalyst by offering relevant, appealing, or emotional content for the consumer [8][55]. Frequently, this FGC is designed to be highly shareable, thus encouraging active user participation. For instance, content that encourages sharing pictures enjoying food at an establishment in exchange for a promotion [15][18][53][54]. Cheng, Liu, Qi, and Wan [55] previously found a relationship between informational and emotional FGC with SME, thereby corroborating earlier findings like those of Pansari and Kumar [56]. Additionally, FGC might include specific calls to action aimed at deeper consumer engagement, such as subscribing to newsletters, taking part in contests, engaging in online communities, and can serve to establish feelings of belonging [15][18][53][54]. 
Online shopping behavior refers to the actions that consumers take in the online environment related to the search, selection, purchase, and post-purchase of products or services [57]. This behavior can be influenced by various factors [58][59], including marketing stimuli such as FGC [26]. Given that FGC serves as a primary source of information for the consumer looking to better understand products [56], FGC can enhance the shopping experience by providing a social and emotional context that enriches the consumer’s interaction with the brand [55]. This is especially relevant in the realm of online shopping, where the lack of physical interaction can make consumers feel uncertain [58][59]. 

2.2. Relationships between Attitudes towards Social Media Advertising (ASMA), Social Media Engagement (SME), Online Shopping Behavior, and Fast Food Pattern (FFP)

The consumer’s attitude towards social media advertising (ASMA) not only has the potential to amplify their engagement with certain brands [15][48] but also plays a pivotal role in shaping online purchasing patterns and consumption decisions [43]. This linkage between attitude and engagement is underpinned by the notion that a positive perception of ads can catalyze heightened interaction with the advertising content [42][48]. Furthermore, it has been posited that the attitude towards advertising serves as a significant predictor for both social media participation [60] and online shopping behavior [57][59][61]. In essence, when an individual holds a favorable view of the ads on social media platforms, they are more inclined to interact with brand content [62], which is mirrored in increased digital engagement [63]. For instance, studies have shown that exposure to digital marketing can enhance attitudes and bolster interest in products such as energy drinks [64] and other food items [43]. From a theoretical standpoint, these arguments align with the theory of planned behavior [65] and resonate with the motivations and rewards derived from interacting with advertising [66][67]. In accordance with this theory, positive attitudes towards a product or its advertising often lead to proactive behaviors on social media. Additionally, a favorable attitude towards ads is commonly associated with the perceived utility, entertainment, or informational value they provide [66][67]. In the realm of brand-generated content, a positive attitude towards advertising can manifest in actions like “liking” posts, sharing content, or engaging in brand-related conversations, thereby amplifying the overall engagement rooted in attitudes towards such content [15][18][53][54], and can be an influencing factor in online shopping behavior [58][59][61].
The construct Fast Food Intake Pattern (FFIP) refers to the trends and consumption habits associated with fast food. This variable has been less frequently studied in the academic literature as a dependent variable. Understanding it could be crucial to discern how consumer preferences and behaviors translate into specific food choices, or dietary habits, particularly in the context of fast food. Santoso et al. [68], in their work on sodium intake, outline how consumption patterns are defined by repetitive behavior in a given situation. While the development of habits and patterns in daily routines (like eating) optimizes decisions, they might not always lead to positive outcomes if the products consumed are not healthy [5][21][23][24][25][26]. Given this, an individual’s attitude towards social media advertising could influence their fast-food consumption patterns in various ways. A positive attitude towards ads might make the consumer more inclined to try new products or frequent fast-food restaurants more often [1][6][37][69]. This reasoning is grounded in the Theory of Classical Conditioning [70], where repeated exposure to positive stimuli (in this case, attractive ads on social media) can lead to favorable behavioral responses, such as the choice to consume fast food [71]. For instance, if someone sees a social media ad about a new gourmet burger at a fast-food restaurant and has a positive attitude towards that ad, they are more likely to decide to try that burger on their next restaurant visit. This behavior could become a pattern if the individual finds the experience satisfying [68]. Previous studies in marketing and consumer psychology have demonstrated that attitudes towards advertising can influence purchasing decisions and, by extension, consumption patterns [9][29][43][65][72]. 
Online shopping behavior (OSB) encompasses the actions and decisions that consumers make when purchasing products online [58][59]. This variable has been extensively studied in the e-commerce context and has been shown to have a significant impact on various aspects of consumer behavior [73][74]. There may be a relationship between online shopping behaviors and fast-food consumption patterns. The underlying logic of this relationship is that individuals more accustomed to shopping online may be more inclined to use fast food delivery services or mobile apps for ordering [75]. This is based on the Technology Acceptance and Use Theory, suggesting that familiarity with technology and usage behavior facilitate the adoption of similar behaviors (placing orders online) [76], and this acceptance could shape their consumption patterns [68]. For instance, those individuals used to purchase other products online might find it easier and more convenient to use apps to order food from fast-food restaurants, rather than physically visiting the establishment. This behavior might lead to an increase in the frequency with which that person consumes that kind of food, thus establishing a pattern. Furthermore, previous studies have shown that convenience and ease of use are key factors influencing online shopping behavior [59][77].

2.3. The Influence and Moderating Role of Word of Mouth (WOM) on Fast-Food Intake Patterns (FFP)

Word of mouth (WOM) refers to the act of sharing information, opinions, or recommendations about products or services among consumers [78][79]. This phenomenon has been extensively researched in the marketing literature and is deemed one of the most influential methods affecting consumer behavior [80][81].
The linkage between WOM and fast-food consumption patterns (FFPs) is predicated on the notion that recommendations and opinions shared among friends, family, or even influencers concerning brand-generated content can significantly sway an individual’s dietary choices [82][83][84]. This aligns with the Theory of Planned Behavior, suggesting that attitudes and social influences can shape intention and subsequent behavior through subjective norms (consumer’s opinion referents) [85]. For instance, if a close friend positively endorses a newly tried burger from their favorite fast-food restaurant, the likelihood of one being inclined to taste the said food increases. Such endorsements could escalate the frequency of such food consumption, fostering specific consumption patterns [68].
The previous literature suggests that WOM can serve as a moderating factor in various consumer behavior relationships [86][87], including the impact of advertising on purchase decisions [87][88]. In the context of attitudes towards social media advertising (ASMA) and fast-food consumption patterns (FFP), WOM might play a moderating role. Peer or influencer opinions could either bolster or counteract advertising messages, adding another layer of influence on the consumer’s decision-making process. For instance, a consumer might be positively swayed by an advertisement for a new burger at a fast-food restaurant. However, prior to finalizing the purchase decision, they may come across unfavorable online reviews, prompting them to reconsider. This negative WOM could diminish or even negate the initial positive effect that the advertisement had on their attitude [80][86][89]. Therefore, it is plausible to posit that WOM might moderate the relationship between attitudes towards social media advertising and fast-food consumption patterns. 

References

  1. Hanaysha, J.R. Impact of social media marketing features on consumer’s purchase decision in the fast-food industry: Brand trust as a mediator. Int. J. Inf. Manag. Data Insights 2022, 2, 100102.
  2. Sashi, C.M.; Brynildsen, G.; Bilgihan, A. Social media, customer engagement and advocacy. Int. J. Contemp. Hosp. Manag. 2019, 31, 1247–1272.
  3. Trivedi, J.; Sama, R. Determinants of consumer loyalty towards celebrity-owned restaurants: The mediating role of brand love. J. Consum. Behav. 2021, 20, 748–761.
  4. Bragg, M.A.; Pageot, Y.K.; Amico, A.; Miller, A.N.; Gasbarre, A.; Rummo, P.E.; Elbel, B. Fast food, beverage, and snack brands on social media in the United States: An examination of marketing techniques utilized in 2000 brand posts. Pediatr. Obes. 2020, 15, e12606.
  5. Gaber, H.R.; Wright, L.T. Fast-food advertising in social media. A case study on Facebook in Egypt. J. Bus. Res. Retail Manag. Res. 2014, 9, 52–63.
  6. Daradkeh, F.M.; Hassan, T.H.; Palei, T.; Helal, M.Y.; Mabrouk, S.; Saleh, M.I.; Salem, A.E.; Elshawarbi, N.N. Enhancing Digital Presence for Maximizing Customer Value in Fast-Food Restaurants. Sustainability 2023, 15, 5690.
  7. Kumar, V.; Choi, J.B.; Greene, M. Synergistic effects of social media and traditional marketing on brand sales: Capturing the time-varying effects. J. Acad. Mark. Sci. 2017, 45, 268–288.
  8. Hanaysha, J.R. An examination of social media advertising features, brand engagement and purchase intention in the fast food industry. Br. Food J. 2022, 124, 4143–4160.
  9. Azzam, Z.A.; Hamdan, A.; Ali, N.; Aggad, K. Impact of digital advertising via social media tools on the buying behavior of fast food consumers. A case of Jordan. In Artificial Intelligence (AI) and Finance; Alareeni, B.A.M., Elgedawy, I., Eds.; Springer Nature: Cham, Switzerland, 2023; pp. 461–472.
  10. Cabeza-Ramírez, L.J.; Sánchez-Cañizares, S.M.; Santos-Roldán, L.M.; Fuentes-García, F.J. Exploring the effectiveness of fashion recommendations made by social media influencers in the centennial generation. Text. Res. J. 2023, 93, 3240–3261.
  11. Cabeza-Ramírez, L.J.; Sánchez-Cañizares, S.M.; Santos-Roldán, L.M.; Fuentes-García, F.J. Impact of the perceived risk in influencers’ product recommendations on their followers’ purchase attitudes and intention. Technol. Forecast. Soc. Chang. 2022, 184, 121997.
  12. Farhat, K.; Aslam, W.; Mokhtar, S.S.M. Beyond Social Media Engagement: Holistic Digital Engagement and a Social Identity Perspective. J. Internet Commer. 2021, 20, 319–354.
  13. Mourdoukoutas, P. McDonald’s Cannot Beat Shake Shack and Wendy’s on Gourmet Burgers. Forbes 2019. Available online: https://www.forbes.com/sites/panosmourdoukoutas/2019/04/27/mcdonalds-cannot-beat-shake-shack-and-wendys-on-gourmet-burgers/?sh=6a16750514ed (accessed on 20 September 2023).
  14. Meyerding, S.G.H.; Marpert, J.D. Modern pied pipers: Child social media influencers and junk food on YouTube—A study from Germany. Appetite 2023, 181, 106382.
  15. Santiago, J.; Borges-Tiago, M.T.; Tiago, F. Is firm-generated content a lost cause? J. Bus. Res. 2022, 139, 945–953.
  16. Otto, N.; Johnston, J.; Baumann, S. Moral Entrepreneurialism for the Hamburger: Strategies for Marketing a Contested Fast Food. Cult. Sociol. 2021, 16, 190–211.
  17. Stefanik-Sidener, K. Nature, Nurture, or That Fast Food Hamburger: Media Framing of Diabetes in the New York Times from 2000 to 2010. Health Commun. 2013, 28, 351–358.
  18. Kumar, A.; Bezawada, R.; Rishika, R.; Janakiraman, R.; Kannan, P.K. From Social to Sale: The Effects of Firm-Generated Content in Social Media on Customer Behavior. J. Mark. 2016, 80, 7–25.
  19. Fleischhacker, S.E.; Evenson, K.R.; Rodriguez, D.A.; Ammerman, A.S. A systematic review of fast food access studies. Obes. Rev. 2011, 12, e460–e471.
  20. Janssen, H.G.; Davies, I.G.; Richardson, L.D.; Stevenson, L. Determinants of takeaway and fast food consumption: A narrative review. Nutr. Res. Rev. 2018, 31, 16–34.
  21. Smith, R.; Kelly, B.; Yeatman, H.; Boyland, E. Food Marketing Influences Children’s Attitudes, Preferences and Consumption: A Systematic Critical Review. Nutrients 2019, 11, 875.
  22. World Health Organization. Food Marketing Exposure and Power and Their Associations with Food-Related Attitudes, Beliefs and Behaviours: A Narrative Review; World Health Organization: Geneva, Switzerland, 2022.
  23. Boyland, E.J.; Whalen, R. Food advertising to children and its effects on diet: Review of recent prevalence and impact data. Pediatr. Diabetes 2015, 16, 331–337.
  24. Effertz, T.; Teichert, T.; Tsoy, M. Fast food, ads, and taste in a Russian child’s mind. Psychol. Mark. 2019, 36, 175–187.
  25. Henderson, J.; Coveney, J.; Ward, P.; Taylor, A. Governing childhood obesity: Framing regulation of fast food advertising in the Australian print media. Soc. Sci. Med. 2009, 69, 1402–1408.
  26. Story, M.; French, S. Food Advertising and Marketing Directed at Children and Adolescents in the US. Int. J. Behav. Nutr. Phys. Act. 2004, 1, 3.
  27. Machado, P.P.; Steele, E.M.; Levy, R.B.; da Costa Louzada, M.L.; Rangan, A.; Woods, J.; Gill, T.; Scrinis, G.; Monteiro, C.A. Ultra-processed food consumption and obesity in the Australian adult population. Nutr. Diabetes 2020, 10, 39.
  28. Scully, M.; Dixon, H.; Wakefield, M. Association between commercial television exposure and fast-food consumption among adults. Public Health Nutr. 2009, 12, 105–110.
  29. Pechmann, C.; Catlin, J.R. The effects of advertising and other marketing communications on health-related consumer behaviors. Curr. Opin. Psychol. 2016, 10, 44–49.
  30. Norman, J.; Kelly, B.; Boyland, E.; McMahon, A.-T. The Impact of Marketing and Advertising on Food Behaviours: Evaluating the Evidence for a Causal Relationship. Curr. Nutr. Rep. 2016, 5, 139–149.
  31. Deshpande, B.; Kaur, P.; Ferraris, A.; Yahiaoui, D.; Dhir, A. The dark side of advertising: Promoting unhealthy food consumption. Eur. J. Mark. 2023. ahead-of-print.
  32. Thiemann, L.; Roman-Alcalá, A. Fast Food Sovereignty: Contradiction in Terms or Logical Next Step? J. Agric. Environ. Ethics 2019, 32, 813–834.
  33. Reddy, G.; van Dam, R.M. Food, culture, and identity in multicultural societies: Insights from Singapore. Appetite 2020, 149, 104633.
  34. Khalid, H.; Lodhi, R.N.; Mahmood, Z. Exploring inside the box: A cross-cultural examination of stimuli affecting fast food addiction. Br. Food J. 2019, 121, 6–21.
  35. Bagozzi, R.P.; Wong, N.; Abe, S.; Bergami, M. Cultural and Situational Contingencies and the Theory of Reasoned Action: Application to Fast Food Restaurant Consumption. J. Consum. Psychol. 2000, 9, 97–106.
  36. Sawada, R.; Sato, W.; Toichi, M.; Fushiki, T. Fat Content Modulates Rapid Detection of Food: A Visual Search Study Using Fast Food and Japanese Diet. Front. Psychol. 2017, 8, 1033.
  37. Ponnaiyan, S.; Ababneh, K.I.; Prybutok, V. Determinants of fast-food restaurant service quality in the United Arab Emirates. Qual. Manag. J. 2021, 28, 86–97.
  38. Hanaysha, J.R.; Momani, A. An exploration of social media marketing features and brand loyalty in the fast food industry. J. Content Community Commun. 2021, 14, 81–92.
  39. Gallus, S.; Borroni, E.; Stival, C.; Kaur, S.; Davoli, S.; Lugo, A.; Effertz, T.; Garattini, S.; Scaglioni, S. Food advertising during children’s television programmes in Italy. Public Health Nutr. 2021, 24, 4663–4670.
  40. Pereira, B.T.F. A Publicidade das Marcas de Fast Food No Brasil: Uma Análise dos Recursos Criativos. Ph.D. Thesis, Universidade Fernando Pessoa (Portugal), Porto, Portugal, 2017.
  41. Vandevijvere, S.; Molloy, J.; Hassen de Medeiros, N.; Swinburn, B. Unhealthy food marketing around New Zealand schools: A national study. Int. J. Public Health 2018, 63, 1099–1107.
  42. Boateng, H.; Okoe, A.F. Determinants of Consumers’ Attitude towards Social Media Advertising. J. Creat. Commun. 2015, 10, 248–258.
  43. Cuesta-Valiño, P.; Rodríguez, P.G.; Núñez-Barriopedro, E. Perception of Advertisements for Healthy Food on Social Media: Effect of Attitude on Consumers’ Response. Int. J. Environ. Res. Public Health 2020, 17, 6463.
  44. Eagle, L.; Brennan, R. Beyond advertising: In-home promotion of “fast food”. Young Consum. 2007, 8, 278–288.
  45. Chung, A.; Zorbas, C.; Riesenberg, D.; Sartori, A.; Kennington, K.; Ananthapavan, J.; Backholer, K. Policies to restrict unhealthy food and beverage advertising in outdoor spaces and on publicly owned assets: A scoping review of the literature. Obes. Rev. 2022, 23, e13386.
  46. Collaborators, G.O. Health Effects of Overweight and Obesity in 195 Countries over 25 Years. N. Engl. J. Med. 2017, 377, 13–27.
  47. Jia, P.; Luo, M.; Li, Y.; Zheng, J.-S.; Xiao, Q.; Luo, J. Fast-food restaurant, unhealthy eating, and childhood obesity: A systematic review and meta-analysis. Obes. Rev. 2021, 22, e12944.
  48. Poulis, A.; Rizomyliotis, I.; Konstantoulaki, K. Do firms still need to be social? Firm generated content in social media. Inf. Technol. People 2019, 32, 387–404.
  49. Ma, Z.; Gu, B. The influence of firm-Generated video on user-Generated video: Evidence from China. Int. J. Eng. Bus. Manag. 2022, 14, 18479790221118628.
  50. Nisar, T.M.; Prabhakar, G. Trains and Twitter: Firm generated content, consumer relationship management and message framing. Transp. Res. Part A: Policy Pract. 2018, 113, 318–334.
  51. McShane, L.; Pancer, E.; Poole, M.; Deng, Q. Emoji, Playfulness, and Brand Engagement on Twitter. J. Interact. Mark. 2021, 53, 96–110.
  52. Chan, F.F.Y.; Lowe, B. Placing products in humorous scenes: Its impact on brand perceptions. Eur. J. Mark. 2021, 55, 649–670.
  53. Zhang, R.; Chen, X.; Wang, W.; Shafi, M. The effects of firm-generated content on different social media platforms on viral marketing. J. Consum. Mark. 2023, 40, 651–662.
  54. Tyrväinen, O.; Karjaluoto, H.; Ukpabi, D. Understanding the Role of Social Media Content in Brand Loyalty: A Meta-Analysis of User-Generated Content Versus Firm-Generated Content. J. Interact. Mark. 2023, 58, 400–413.
  55. Cheng, M.; Liu, J.; Qi, J.; Wan, F. Differential effects of firm generated content on consumer digital engagement and firm performance: An outside-in perspective. Ind. Mark. Manag. 2021, 98, 41–58.
  56. Pansari, A.; Kumar, V. Customer engagement: The construct, antecedents, and consequences. J. Acad. Mark. Sci. 2017, 45, 294–311.
  57. Rehman, S.U.; Bhatti, A.; Mohamed, R.; Ayoup, H. The moderating role of trust and commitment between consumer purchase intention and online shopping behavior in the context of Pakistan. J. Glob. Entrep. Res. 2019, 9, 43.
  58. Javadi, M.H.M.; Dolatabadi, H.R.; Nourbakhsh, M.; Poursaeedi, A.; Asadollahi, A.R. An analysis of factors affecting on online shopping behavior of consumers. Int. J. Mark. Stud. 2012, 4, 81.
  59. Lim, Y.J.; Osman, A.; Salahuddin, S.N.; Romle, A.R.; Abdullah, S. Factors Influencing Online Shopping Behavior: The Mediating Role of Purchase Intention. Procedia Econ. Financ. 2016, 35, 401–410.
  60. Dessart, L. Social media engagement: A model of antecedents and relational outcomes. J. Mark. Manag. 2017, 33, 375–399.
  61. Menon, B. Determinants of online purchase intention, towards firm generated content in Facebook. Int. J. Appl. Mark. Manag. 2017, 2, 47–56.
  62. Mukherjee, K.; Banerjee, N. Social networking sites and customers’ attitude towards advertisements. J. Res. Interact. Mark. 2019, 13, 477–491.
  63. Kamboj, S. Applying uses and gratifications theory to understand customer participation in social media brand communities. Asia Pac. J. Mark. Logist. 2020, 32, 205–231.
  64. Buchanan, L.; Kelly, B.; Yeatman, H. Exposure to digital marketing enhances young adults’ interest in energy drinks: An exploratory investigation. PLoS ONE 2017, 12, e0171226.
  65. Cheung, M.F.Y.; To, W.M. The influence of the propensity to trust on mobile users’ attitudes toward in-app advertisements: An extension of the theory of planned behavior. Comput. Hum. Behav. 2017, 76, 102–111.
  66. Zadeh, A.H.; Farhang, M.; Zolfagharian, M.; Hofacker, C.F. Predicting value cocreation behavior in social media via integrating uses and gratifications paradigm and theory of planned behavior. J. Res. Interact. Mark. 2023, 17, 195–214.
  67. Qin, Y.S. Fostering brand–consumer interactions in social media: The role of social media uses and gratifications. J. Res. Interact. Mark. 2020, 14, 337–354.
  68. Santoso, I.; Wijana, S.; Ismawati, A.; Sunarharum, W.B. Relationship between Hedonic Hunger and Health Interest on Habit and Sodium Intake Patterns in Food Consumption. Int. J. Food Sci. 2019, 2019, 9517140.
  69. Ababneh, K.I.; Ponnaiyan, S.; ElMelegy, A.R.; Prybutok, V. Determinants of customer satisfaction and behavioral intentions in fast-food restaurants among undergraduate students during the COVID-19 pandemic. Qual. Manag. J. 2022, 29, 104–124.
  70. Boakes, R.A. Performance on learning to associate a stimulus with positive reinforcement. In Operant-Pavlovian Interactions; Routledge: Abingdon-on-Thames, UK, 2021; pp. 67–101.
  71. Harris, J.L.; Fleming-Milici, F. Food marketing to adolescents and young adults: Skeptical but still under the influence. In The Psychology of Food Marketing and Overeating; Routledge: Abingdon-on-Thames, UK, 2019; pp. 25–43.
  72. Sama, R. Impact of Media Advertisements on Consumer Behaviour. J. Creat. Commun. 2019, 14, 54–68.
  73. Burt, S.; Sparks, L. E-commerce and the retail process: A review. J. Retail. Consum. Serv. 2003, 10, 275–286.
  74. Lăzăroiu, G.; Neguriţă, O.; Grecu, I.; Grecu, G.; Mitran, P.C. Consumers’ Decision-Making Process on Social Commerce Platforms: Online Trust, Perceived Risk, and Purchase Intentions. Front. Psychol. 2020, 11, 890.
  75. Dirsehan, T.; Cankat, E. Role of mobile food-ordering applications in developing restaurants’ brand satisfaction and loyalty in the pandemic period. J. Retail. Consum. Serv. 2021, 62, 102608.
  76. Jain, N.K.; Kaul, D.; Sanyal, P. What drives customers towards mobile shopping? An integrative technology continuance theory perspective. Asia Pac. J. Mark. Logist. 2022, 34, 922–943.
  77. Chopdar, P.K.; Korfiatis, N.; Sivakumar, V.J.; Lytras, M.D. Mobile shopping apps adoption and perceived risks: A cross-country perspective utilizing the Unified Theory of Acceptance and Use of Technology. Comput. Hum. Behav. 2018, 86, 109–128.
  78. Kimmel, A.J.; Kitchen, P.J. WOM and social media: Presaging future directions for research and practice. In Word of Mouth and Social Media; Routledge: Abingdon-on-Thames, UK, 2016; pp. 4–19.
  79. Shamhuyenhanzva, R.M.; van Tonder, E.; Roberts-Lombard, M.; Hemsworth, D. Factors influencing Generation Y consumers’ perceptions of eWOM credibility: A study of the fast-food industry. Int. Rev. Retail Distrib. Consum. Res. 2016, 26, 435–455.
  80. Buttle, F.A. Word of mouth: Understanding and managing referral marketing. J. Strateg. Mark. 1998, 6, 241–254.
  81. Donthu, N.; Kumar, S.; Pandey, N.; Pandey, N.; Mishra, A. Mapping the electronic word-of-mouth (eWOM) research: A systematic review and bibliometric analysis. J. Bus. Res. 2021, 135, 758–773.
  82. Soren, A.A.; Chakraborty, S. The formation of habit and word-of-mouth intention of over-the-top platforms. J. Retail. Consum. Serv. 2023, 75, 103460.
  83. Ferguson, P.P. Word of Mouth: What We Talk about When We Talk about Food; University of California Press: Oakland, CA, USA, 2014; Volume 50.
  84. Gupta, V.; Sajnani, M. Risk and benefit perceptions related to wine consumption and how it influences consumers’ attitude and behavioural intentions in India. Br. Food J. 2020, 122, 2569–2585.
  85. Ajzen, I. The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 1991, 50, 179–211.
  86. Zhang, Y.; Zhang, J.; Liu, C. Motives for Employees Communicate Positive Electronic Word of Mouth (eWOM) on Social Network Sites: Exploring Moderating Mechanisms. Australas. Mark. J. 2021, 30, 60–73.
  87. Li, S.; Jaharuddin, N.S. Influences of background factors on consumers’ purchase intention in China’s organic food market: Assessing moderating role of word-of-mouth (WOM). Cogent Bus. Manag. 2021, 8, 1876296.
  88. Chang, J.-H.; Wang, S.-H. Different levels of destination expectation: The effects of online advertising and electronic word-of-mouth. Telemat. Inform. 2019, 36, 27–38.
  89. Lai, I.K.W. An examination of satisfaction on word of mouth regarding Portuguese foods in Macau: Applying the concept of integrated satisfaction. J. Hosp. Tour. Manag. 2020, 43, 100–110.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license; additional terms may apply. By using this site, you agree to the Terms and Conditions and Privacy Policy.
Upload a video for this entry
Information
Subjects: Behavioral Sciences
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
Ali Ahmed Ali-Alsaadi
,
L. Javier Cabeza-Ramírez
,
Luna Sántos-Roldán
,
Halder Yandry Loor-Zambrano
View Times: 276
Revisions: 2 times (View History)
Update Date: 22 Dec 2023
Table of Contents
    1000/1000
    Hot Most Recent
    Feedback