Feast Your Eyes: How Image Features Serves Up Sales on UberEats
Research Article
Open Access
CC BY

Feast Your Eyes: How Image Features Serves Up Sales on UberEats

Pinran Zhao 1*
1 Zhengzhou Shengda University
*Corresponding author: 1477054520@qq.com
Published on 20 July 2025
Volume Cover
AEMPS Vol.203
ISSN (Print): 2754-1177
ISSN (Online): 2754-1169
ISBN (Print): 978-1-80590-275-1
ISBN (Online): 978-1-80590-276-8
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Abstract

The rapid expansion of digital platforms has significantly transformed how information is represented, particularly in the online food delivery industry. On these platforms, consumers make purchasing decisions by browsing images provided by restaurants. Within this evolving landscape, visual imagery plays a crucial yet underexplored role in shaping purchasing decisions on platforms like Uber Eats. This study examines how specific image attributes in food photography impact restaurant sales performance. Leveraging a unique dataset of restaurants from Uber Eats, we employ advanced image-processing techniques to extract 12 key visual features. By applying regression models, we quantify the impact of these visual attributes on restaurant sales. Our findings reveal that texture difference and Saturation positively influence sales, enhancing food appeal and engagement. Conversely, excessive Brightness Contrast has a negative impact, likely due to visual discomfort or diminished product detail. This research contributes to the growing literature on visual marketing and digital commerce by offering empirical evidence on how image design in online food delivery platforms affects purchasing behavior. Our findings provide practical recommendations for food delivery platforms, marketers, and restaurant owners to optimize visual content, ultimately improving consumer engagement, brand perception, and sales performance.

Keywords:

Digital Economy, Visual Perception, Image Quality, Sales Performance, Online Food Delivery

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Zhao,P. (2025). Feast Your Eyes: How Image Features Serves Up Sales on UberEats. Advances in Economics, Management and Political Sciences,203,23-43.

References

[1]. Vasan, S., Rao, A. A., & Gupta, N. (2025). Investigating the opportunities and challenges influencing consumer purchase behaviors and media influence in online food ordering: a thematic analysis. British Food Journal, 127(6), 1984-1998.

[2]. The Times. (2024, October 31). Uber takes hit as weekend customers spoil the party. Retrieved June 20, 2025, from https: //www.thetimes.com/business-money/technology/article/uber-takes-hit-as-weekend-customers-spoil-the-party-9g385bwqj?region=global

[3]. Avery, J. A., Carrington, M., Ingeholm, J. E., Darcey, V., Simmons, W. K., Hall, K. D., & Martin, A. (2025). Automatic engagement of limbic and prefrontal networks in response to food images reflects distinct information about food hedonics and inhibitory control.Communications Biology, 8(1), 270.

[4]. Dong, Yifan, et al. "The effect of picture attributes of online ordering pages on visual attention and user experience."International Journal of Industrial Ergonomics96 (2023): 103477.

[5]. Lee, Jinha, and Heejin Lim. "Visual aesthetics and multisensory engagement in online food delivery services."International Journal of Retail & Distribution Management51.8 (2023): 975-990.

[6]. Zhang, M., & Luo, L. (2023). Can consumer-posted photos serve as a leading indicator of restaurant survival? Evidence from Yelp.Management Science, 69(1), 25-50.

[7]. Leyssen, M. H., Linsen, S., Sammartino, J., & Palmer, S. E. (2012). Aesthetic preference for spatial composition in multiobject pictures.i-Perception, 3(1), 25-49.

[8]. Satcharoen, K. (2017, November). The influence of colour on intention to adopt food delivery service mobile app. InProceedings of the 3rd International Conference on Communication and Information Processing(pp. 87-91).

[9]. Sari, N. L. D. I. D., Negara, I. N. S., & Dewi, A. K. (2018, November). Packaging Design Of Betutu Chicken Special Merchandise From Bali. In3rd International Conference on Creative Media, Design and Technology (REKA 2018)(pp. 108-112). Atlantis Press.

[10]. Zhang, S., Lee, D., Singh, P. V., & Srinivasan, K. (2022). What makes a good image? Airbnb demand analytics leveraging interpretable image features.Management Science, 68(8), 5644-5666.

[11]. Vermeir, I., & Roose, G. (2020). Visual design cues impacting food choice: A review and future research agenda.Foods, 9(10), 1495.

[12]. Bajari, P., Cen, Z., Chernozhukov, V., Manukonda, M., Vijaykumar, S., Wang, J., ... & Wan, S. (2023). Hedonic prices and quality adjusted price indices powered by AI.arXiv preprint arXiv: 2305.00044.

[13]. Saad, A. T. (2021). Factors affecting online food delivery service in Bangladesh: an empirical study.British Food Journal, 123(2), 535-550.

[14]. Vindytia, M., & Balqiah, T. E. (2024). AI Marketing Impact on Consumer Behavior: An SOR Model Analysis of Online Food Delivery Services.JDM (Jurnal Dinamika Manajemen), 15(2), 215-228.

[15]. Amirshahi, S. A., Hayn-Leichsenring, G. U., Denzler, J., & Redies, C. (2014). Evaluating the rule of thirds in photographs and paintings.Art & Perception, 2(1-2), 163-182.

[16]. Gritz, W., Hoppe, A., & Ewerth, R. (2025, April). Unraveling the Impact of Visual Complexity on Search as Learning. InEuropean Conference on Information Retrieval(pp. 17-33). Cham: Springer Nature Switzerland.

[17]. Li, J., Xu, L., Tang, L., Wang, S., & Li, L. (2018). Big data in tourism research: A literature review.Tourism management, 68, 301-323.

[18]. Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2017). A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism.Tourism Management, 58, 51-65.

[19]. Obrist, M. (2021). Multisensory Experiences: Where the Senses Meet Technology. InHuman-Computer Interaction–INTERACT 2021: 18th IFIP TC 13 International Conference, Bari, Italy, August 30–September 3, 2021, Proceedings, Part I 18(pp. 9-13). Springer International Publishing.

[20]. Ma, B., Wong, Y. D., Teo, C. C., & Sun, S. (2024). Quantifying consumers’ cost-value trade-offs on on-demand food delivery services: Value-of-time framework and partitioned pricing.Journal of Retailing and Consumer Services, 81, 104027.

[21]. Tavitiyaman, P., Tsang, W. S. L., & Lo, S. K. J. (2024). Customers’ perceived values and purchase intention through satisfaction: Differences based on food delivery application platform and buying power.International Journal of Hospitality & Tourism Administration, 25(4), 709-737.

[22]. Chatterjee, A. (2003). Prospects for a cognitive neuroscience of visual aesthetics.

[23]. Spence, C., Okajima, K., Cheok, A. D., Petit, O., & Michel, C. (2016). Eating with our eyes: From visual hunger to digital satiation.Brain and cognition, 110, 53-63.

[24]. Liu, S. Q., Wu, L. L., Yu, X., & Huang, H. (2022). Marketing online food images via color saturation: A sensory imagery perspective.Journal of business research, 151, 366-378.

[25]. Thorud, H. M. S., Helland, M., Aarås, A., Kvikstad, T. M., Lindberg, L. G., & Horgen, G. (2012). Eye-related pain induced by visually demanding computer work.Optometry and vision science, 89(4), E452-E464.

[26]. Garber Jr, L. L., Hyatt, E. M., & Starr Jr, R. G. (2000). The effects of food color on perceived flavor.Journal of Marketing Theory and Practice, 8(4), 59-72.

[27]. Michel, C., Velasco, C., Fraemohs, P., & Spence, C. (2015). Studying the impact of plating on ratings of the food served in a naturalistic dining context.Appetite, 90, 45-50.

[28]. Peng, Y., & JEMMOTT III, J. B. (2018). Feast for the eyes: Effects of food perceptions and computer vision features on food photo popularity.International Journal of Communication (19328036), 12.

[29]. Pieters, R., Wedel, M., & Batra, R. (2010). The stopping power of advertising: Measures and effects of visual complexity.Journal of marketing, 74(5), 48-60.

[30]. Labrecque, L. I., & Milne, G. R. (2013). To be or not to be different: Exploration of norms and benefits of color differentiation in the marketplace.Marketing Letters, 24, 165-176.

[31]. Zellner, D. A., Lankford, M., Ambrose, L., & Locher, P. (2010). Art on the plate: Effect of balance and color on attractiveness of, willingness to try and liking for food.Food Quality and Preference, 21(5), 575-578.

[32]. Delwiche, J. F. (2012). You eat with your eyes first.Physiology & behavior, 107(4), 502-504.

[33]. Lee, B. P., & Spence, C. (2022). Crossmodal correspondences between basic tastes and visual design features: A narrative historical review.i-Perception, 13(5), 20416695221127325.

[34]. Carvalho, J. S., Oliveira, J. D. S. C., & SÃO JOSÉ, J. F. B. D. (2022). Consumers’ knowledge, practices, and perceptions about conventional and sustainable food packaging.Food Science and Technology, 42, e06722.

[35]. Zhao, W., Wu, Q., Yang, C., & Yan, J. (2023). Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD'23.

[36]. Lu, A. C. C., & Gursoy, D. (2015). A conceptual model of consumers’ online tourism confusion.International Journal of Contemporary Hospitality Management, 27(6), 1320-1342.

[37]. He, R., & McAuley, J. (2016, February). VBPR: visual bayesian personalized ranking from implicit feedback. InProceedings of the AAAI conference on artificial intelligence(Vol. 30, No. 1).

[38]. Azman, F. A. M., & Mustaffa, N. (2023). The impact of user generated content on food purchase intention through Tiktok platform.Al-i’lam-Journal of Contemporary Islamic Communication and Media, 3(2).

[39]. Itti, L., & Koch, C. (2000). A saliency-based search mechanism for overt and covert shifts of visual attention.Vision research, 40(10-12), 1489-1506.

[40]. Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews.Journal of marketing research, 43(3), 345-354.

[41]. Luca, M. (2016). Reviews, reputation, and revenue: The case of Yelp. com.Com (March 15, 2016). Harvard Business School NOM Unit Working Paper, (12-016).

[42]. Hou, Y., Yang, W., & Sun, Y. (2017). Do pictures help? The effects of pictures and food names on menu evaluations.International Journal of Hospitality Management, 60, 94-103.

[43]. Celona, L., Leonardi, M., Napoletano, P., & Rozza, A. (2022). Composition and style attributes guided image aesthetic assessment.IEEE Transactions on Image Processing, 31, 5009-5024.

[44]. Li, X., Wang, M., & Chen, Y. (2014). The impact of product photo on online consumer purchase intention: an image-processing enabled empirical study.

[45]. Liu, L., Chen, R., Wolf, L., & Cohen‐Or, D. (2010, May). Optimizing photo composition. InComputer graphics forum(Vol. 29, No. 2, pp. 469-478). Oxford, UK: Blackwell Publishing Ltd.

[46]. Gambetti, A., & Han, Q. (2022). Camera eats first: exploring food aesthetics portrayed on social media using deep learning.International journal of contemporary hospitality management, 34(9), 3300-3331.

[47]. Juricevic, I., Land, L., Wilkins, A., & Webster, M. A. (2010). Visual discomfort and natural image statistics.Perception, 39(7), 884-899.

[48]. Quek, G., Wienold, J., Khanie, M. S., Erell, E., Kaftan, E., Tzempelikos, A., ... & Andersen, M. (2021). Comparing performance of discomfort glare metrics in high and low adaptation levels.Building and environment, 206, 108335.

[49]. Tahir, G. A., & Loo, C. K. (2021, December). A comprehensive survey of image-based food recognition and volume estimation methods for dietary assessment. InHealthcare(Vol. 9, No. 12, p. 1676). MDPI.

[50]. Yarlagadda, S. K., Montserrat, D. M., Güera, D., Boushey, C. J., Kerr, D. A., & Zhu, F. (2021). Saliency-aware class-agnostic food image segmentation.ACM Transactions on Computing for Healthcare, 2(3), 1-17.

[51]. Ferreira, B. M. (2019). Packaging texture influences product taste and consumer satisfaction.Journal of Sensory Studies, 34(6), e12532.

[52]. Matz, S. C., Segalin, C., Stillwell, D., Müller, S. R., & Bos, M. W. (2019). Predicting the personal appeal of marketing images using computational methods.Journal of consumer psychology, 29(3), 370-390.

[53]. Wagemans, J., Elder, J. H., Kubovy, M., Palmer, S. E., Peterson, M. A., Singh, M., & Von der Heydt, R. (2012). A century of Gestalt psychology in visual perception: I. Perceptual grouping and figure–ground organization.Psychological bulletin, 138(6), 1172.

[54]. Kostyk, A., & Huhmann, B. A. (2021). Perfect social media image posts: Symmetry and contrast influence consumer response.European Journal of Marketing, 55(6), 1747-1779.

[55]. Al Maalouf, N. J., Sayegh, E., Makhoul, W., & Sarkis, N. (2025). Consumers' attitudes and purchase intentions toward food ordering via online platforms.Journal of Retailing and Consumer Services, 82, 104151.

[56]. Thalji, Z. (2022). Using Multiple linear regression model to predict The Customers’ Purchase Decision based on After-Sales Services.

[57]. Kutner, M. H., Nachtsheim, C. J., Neter, J., & Li, W. (2005).Applied linear statistical models. McGraw-hill.

[58]. Wooldridge, J. M. (2016).Introductory Econometrics: A Modern Approach 6rd ed. Cengage learning.

[59]. Long, J. A., Xiao, J., McCray, S., Ağaoğlu, E., Alajmi, A. M., Akalonu, C., & Xu, Y. Artificial Impressions: Trust and Credibility in AI-Enhanced Profile Pictures.

[60]. Pillai, S. G., Kim, W. G., Haldorai, K., & Kim, H. S. (2022). Online food delivery services and consumers' purchase intention: Integration of theory of planned behavior, theory of perceived risk, and the elaboration likelihood model.International journal of hospitality management, 105, 103275.

[61]. Qi, M., Ono, K., Mao, L., Watanabe, M., & Huang, J. (2024). The effect of short-form video content, speed, and proportion on visual attention and subjective perception in online food delivery menu interfaces.Displays, 82, 102671.

[62]. Chan, I. C. C., Chen, Z., & Leung, D. (2023). The more the better? Strategizing visual elements in social media marketing.Journal of Hospitality and Tourism Management, 54, 268-289.

[63]. Karimi, S., & Wang, F. (2017). Online review helpfulness: Impact of reviewer profile image.Decision Support Systems, 96, 39-48.

[64]. Cai, R., & Leung, X. Y. (2020). Mindset matters in purchasing online food deliveries during the pandemic: The application of construal level and regulatory focus theories.International journal of hospitality management, 91, 102677.

[65]. Kapoor, A. P., & Vij, M. (2018). Technology at the dinner table: Ordering food online through mobile apps.Journal of retailing and consumer services, 43, 342-351.

[66]. King, A., Niederdeppe, J., & Dahl, E. (2021). Visual juxtapositions as exemplars in messages promoting healthy dietary behavior.Health Communication, 36(10), 1200-1215.

References

[1]. Vasan, S., Rao, A. A., & Gupta, N. (2025). Investigating the opportunities and challenges influencing consumer purchase behaviors and media influence in online food ordering: a thematic analysis. British Food Journal, 127(6), 1984-1998.

[2]. The Times. (2024, October 31). Uber takes hit as weekend customers spoil the party. Retrieved June 20, 2025, from https: //www.thetimes.com/business-money/technology/article/uber-takes-hit-as-weekend-customers-spoil-the-party-9g385bwqj?region=global

[3]. Avery, J. A., Carrington, M., Ingeholm, J. E., Darcey, V., Simmons, W. K., Hall, K. D., & Martin, A. (2025). Automatic engagement of limbic and prefrontal networks in response to food images reflects distinct information about food hedonics and inhibitory control.Communications Biology, 8(1), 270.

[4]. Dong, Yifan, et al. "The effect of picture attributes of online ordering pages on visual attention and user experience."International Journal of Industrial Ergonomics96 (2023): 103477.

[5]. Lee, Jinha, and Heejin Lim. "Visual aesthetics and multisensory engagement in online food delivery services."International Journal of Retail & Distribution Management51.8 (2023): 975-990.

[6]. Zhang, M., & Luo, L. (2023). Can consumer-posted photos serve as a leading indicator of restaurant survival? Evidence from Yelp.Management Science, 69(1), 25-50.

[7]. Leyssen, M. H., Linsen, S., Sammartino, J., & Palmer, S. E. (2012). Aesthetic preference for spatial composition in multiobject pictures.i-Perception, 3(1), 25-49.

[8]. Satcharoen, K. (2017, November). The influence of colour on intention to adopt food delivery service mobile app. InProceedings of the 3rd International Conference on Communication and Information Processing(pp. 87-91).

[9]. Sari, N. L. D. I. D., Negara, I. N. S., & Dewi, A. K. (2018, November). Packaging Design Of Betutu Chicken Special Merchandise From Bali. In3rd International Conference on Creative Media, Design and Technology (REKA 2018)(pp. 108-112). Atlantis Press.

[10]. Zhang, S., Lee, D., Singh, P. V., & Srinivasan, K. (2022). What makes a good image? Airbnb demand analytics leveraging interpretable image features.Management Science, 68(8), 5644-5666.

[11]. Vermeir, I., & Roose, G. (2020). Visual design cues impacting food choice: A review and future research agenda.Foods, 9(10), 1495.

[12]. Bajari, P., Cen, Z., Chernozhukov, V., Manukonda, M., Vijaykumar, S., Wang, J., ... & Wan, S. (2023). Hedonic prices and quality adjusted price indices powered by AI.arXiv preprint arXiv: 2305.00044.

[13]. Saad, A. T. (2021). Factors affecting online food delivery service in Bangladesh: an empirical study.British Food Journal, 123(2), 535-550.

[14]. Vindytia, M., & Balqiah, T. E. (2024). AI Marketing Impact on Consumer Behavior: An SOR Model Analysis of Online Food Delivery Services.JDM (Jurnal Dinamika Manajemen), 15(2), 215-228.

[15]. Amirshahi, S. A., Hayn-Leichsenring, G. U., Denzler, J., & Redies, C. (2014). Evaluating the rule of thirds in photographs and paintings.Art & Perception, 2(1-2), 163-182.

[16]. Gritz, W., Hoppe, A., & Ewerth, R. (2025, April). Unraveling the Impact of Visual Complexity on Search as Learning. InEuropean Conference on Information Retrieval(pp. 17-33). Cham: Springer Nature Switzerland.

[17]. Li, J., Xu, L., Tang, L., Wang, S., & Li, L. (2018). Big data in tourism research: A literature review.Tourism management, 68, 301-323.

[18]. Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2017). A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism.Tourism Management, 58, 51-65.

[19]. Obrist, M. (2021). Multisensory Experiences: Where the Senses Meet Technology. InHuman-Computer Interaction–INTERACT 2021: 18th IFIP TC 13 International Conference, Bari, Italy, August 30–September 3, 2021, Proceedings, Part I 18(pp. 9-13). Springer International Publishing.

[20]. Ma, B., Wong, Y. D., Teo, C. C., & Sun, S. (2024). Quantifying consumers’ cost-value trade-offs on on-demand food delivery services: Value-of-time framework and partitioned pricing.Journal of Retailing and Consumer Services, 81, 104027.

[21]. Tavitiyaman, P., Tsang, W. S. L., & Lo, S. K. J. (2024). Customers’ perceived values and purchase intention through satisfaction: Differences based on food delivery application platform and buying power.International Journal of Hospitality & Tourism Administration, 25(4), 709-737.

[22]. Chatterjee, A. (2003). Prospects for a cognitive neuroscience of visual aesthetics.

[23]. Spence, C., Okajima, K., Cheok, A. D., Petit, O., & Michel, C. (2016). Eating with our eyes: From visual hunger to digital satiation.Brain and cognition, 110, 53-63.

[24]. Liu, S. Q., Wu, L. L., Yu, X., & Huang, H. (2022). Marketing online food images via color saturation: A sensory imagery perspective.Journal of business research, 151, 366-378.

[25]. Thorud, H. M. S., Helland, M., Aarås, A., Kvikstad, T. M., Lindberg, L. G., & Horgen, G. (2012). Eye-related pain induced by visually demanding computer work.Optometry and vision science, 89(4), E452-E464.

[26]. Garber Jr, L. L., Hyatt, E. M., & Starr Jr, R. G. (2000). The effects of food color on perceived flavor.Journal of Marketing Theory and Practice, 8(4), 59-72.

[27]. Michel, C., Velasco, C., Fraemohs, P., & Spence, C. (2015). Studying the impact of plating on ratings of the food served in a naturalistic dining context.Appetite, 90, 45-50.

[28]. Peng, Y., & JEMMOTT III, J. B. (2018). Feast for the eyes: Effects of food perceptions and computer vision features on food photo popularity.International Journal of Communication (19328036), 12.

[29]. Pieters, R., Wedel, M., & Batra, R. (2010). The stopping power of advertising: Measures and effects of visual complexity.Journal of marketing, 74(5), 48-60.

[30]. Labrecque, L. I., & Milne, G. R. (2013). To be or not to be different: Exploration of norms and benefits of color differentiation in the marketplace.Marketing Letters, 24, 165-176.

[31]. Zellner, D. A., Lankford, M., Ambrose, L., & Locher, P. (2010). Art on the plate: Effect of balance and color on attractiveness of, willingness to try and liking for food.Food Quality and Preference, 21(5), 575-578.

[32]. Delwiche, J. F. (2012). You eat with your eyes first.Physiology & behavior, 107(4), 502-504.

[33]. Lee, B. P., & Spence, C. (2022). Crossmodal correspondences between basic tastes and visual design features: A narrative historical review.i-Perception, 13(5), 20416695221127325.

[34]. Carvalho, J. S., Oliveira, J. D. S. C., & SÃO JOSÉ, J. F. B. D. (2022). Consumers’ knowledge, practices, and perceptions about conventional and sustainable food packaging.Food Science and Technology, 42, e06722.

[35]. Zhao, W., Wu, Q., Yang, C., & Yan, J. (2023). Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD'23.

[36]. Lu, A. C. C., & Gursoy, D. (2015). A conceptual model of consumers’ online tourism confusion.International Journal of Contemporary Hospitality Management, 27(6), 1320-1342.

[37]. He, R., & McAuley, J. (2016, February). VBPR: visual bayesian personalized ranking from implicit feedback. InProceedings of the AAAI conference on artificial intelligence(Vol. 30, No. 1).

[38]. Azman, F. A. M., & Mustaffa, N. (2023). The impact of user generated content on food purchase intention through Tiktok platform.Al-i’lam-Journal of Contemporary Islamic Communication and Media, 3(2).

[39]. Itti, L., & Koch, C. (2000). A saliency-based search mechanism for overt and covert shifts of visual attention.Vision research, 40(10-12), 1489-1506.

[40]. Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews.Journal of marketing research, 43(3), 345-354.

[41]. Luca, M. (2016). Reviews, reputation, and revenue: The case of Yelp. com.Com (March 15, 2016). Harvard Business School NOM Unit Working Paper, (12-016).

[42]. Hou, Y., Yang, W., & Sun, Y. (2017). Do pictures help? The effects of pictures and food names on menu evaluations.International Journal of Hospitality Management, 60, 94-103.

[43]. Celona, L., Leonardi, M., Napoletano, P., & Rozza, A. (2022). Composition and style attributes guided image aesthetic assessment.IEEE Transactions on Image Processing, 31, 5009-5024.

[44]. Li, X., Wang, M., & Chen, Y. (2014). The impact of product photo on online consumer purchase intention: an image-processing enabled empirical study.

[45]. Liu, L., Chen, R., Wolf, L., & Cohen‐Or, D. (2010, May). Optimizing photo composition. InComputer graphics forum(Vol. 29, No. 2, pp. 469-478). Oxford, UK: Blackwell Publishing Ltd.

[46]. Gambetti, A., & Han, Q. (2022). Camera eats first: exploring food aesthetics portrayed on social media using deep learning.International journal of contemporary hospitality management, 34(9), 3300-3331.

[47]. Juricevic, I., Land, L., Wilkins, A., & Webster, M. A. (2010). Visual discomfort and natural image statistics.Perception, 39(7), 884-899.

[48]. Quek, G., Wienold, J., Khanie, M. S., Erell, E., Kaftan, E., Tzempelikos, A., ... & Andersen, M. (2021). Comparing performance of discomfort glare metrics in high and low adaptation levels.Building and environment, 206, 108335.

[49]. Tahir, G. A., & Loo, C. K. (2021, December). A comprehensive survey of image-based food recognition and volume estimation methods for dietary assessment. InHealthcare(Vol. 9, No. 12, p. 1676). MDPI.

[50]. Yarlagadda, S. K., Montserrat, D. M., Güera, D., Boushey, C. J., Kerr, D. A., & Zhu, F. (2021). Saliency-aware class-agnostic food image segmentation.ACM Transactions on Computing for Healthcare, 2(3), 1-17.

[51]. Ferreira, B. M. (2019). Packaging texture influences product taste and consumer satisfaction.Journal of Sensory Studies, 34(6), e12532.

[52]. Matz, S. C., Segalin, C., Stillwell, D., Müller, S. R., & Bos, M. W. (2019). Predicting the personal appeal of marketing images using computational methods.Journal of consumer psychology, 29(3), 370-390.

[53]. Wagemans, J., Elder, J. H., Kubovy, M., Palmer, S. E., Peterson, M. A., Singh, M., & Von der Heydt, R. (2012). A century of Gestalt psychology in visual perception: I. Perceptual grouping and figure–ground organization.Psychological bulletin, 138(6), 1172.

[54]. Kostyk, A., & Huhmann, B. A. (2021). Perfect social media image posts: Symmetry and contrast influence consumer response.European Journal of Marketing, 55(6), 1747-1779.

[55]. Al Maalouf, N. J., Sayegh, E., Makhoul, W., & Sarkis, N. (2025). Consumers' attitudes and purchase intentions toward food ordering via online platforms.Journal of Retailing and Consumer Services, 82, 104151.

[56]. Thalji, Z. (2022). Using Multiple linear regression model to predict The Customers’ Purchase Decision based on After-Sales Services.

[57]. Kutner, M. H., Nachtsheim, C. J., Neter, J., & Li, W. (2005).Applied linear statistical models. McGraw-hill.

[58]. Wooldridge, J. M. (2016).Introductory Econometrics: A Modern Approach 6rd ed. Cengage learning.

[59]. Long, J. A., Xiao, J., McCray, S., Ağaoğlu, E., Alajmi, A. M., Akalonu, C., & Xu, Y. Artificial Impressions: Trust and Credibility in AI-Enhanced Profile Pictures.

[60]. Pillai, S. G., Kim, W. G., Haldorai, K., & Kim, H. S. (2022). Online food delivery services and consumers' purchase intention: Integration of theory of planned behavior, theory of perceived risk, and the elaboration likelihood model.International journal of hospitality management, 105, 103275.

[61]. Qi, M., Ono, K., Mao, L., Watanabe, M., & Huang, J. (2024). The effect of short-form video content, speed, and proportion on visual attention and subjective perception in online food delivery menu interfaces.Displays, 82, 102671.

[62]. Chan, I. C. C., Chen, Z., & Leung, D. (2023). The more the better? Strategizing visual elements in social media marketing.Journal of Hospitality and Tourism Management, 54, 268-289.

[63]. Karimi, S., & Wang, F. (2017). Online review helpfulness: Impact of reviewer profile image.Decision Support Systems, 96, 39-48.

[64]. Cai, R., & Leung, X. Y. (2020). Mindset matters in purchasing online food deliveries during the pandemic: The application of construal level and regulatory focus theories.International journal of hospitality management, 91, 102677.

[65]. Kapoor, A. P., & Vij, M. (2018). Technology at the dinner table: Ordering food online through mobile apps.Journal of retailing and consumer services, 43, 342-351.

[66]. King, A., Niederdeppe, J., & Dahl, E. (2021). Visual juxtapositions as exemplars in messages promoting healthy dietary behavior.Health Communication, 36(10), 1200-1215.

Cite this article

Zhao,P. (2025). Feast Your Eyes: How Image Features Serves Up Sales on UberEats. Advances in Economics, Management and Political Sciences,203,23-43.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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Volume title: Proceedings of ICEMGD 2025 Symposium: Resilient Business Strategies in Global Markets

ISBN: 978-1-80590-275-1(Print) / 978-1-80590-276-8(Online)
Editor: Florian Marcel Nuţă Nuţă, Li Chai
Conference website: https://2025.icemgd.org/CAU.html
Conference date: 20 September 2025
Series: Advances in Economics, Management and Political Sciences
Volume number: Vol.203
ISSN: 2754-1169(Print) / 2754-1177(Online)

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