The Effect of Gaze and Product Salience on Digital Visual Engagement: An Experimental Research
DOI:
https://doi.org/10.53276/eligible.v1i2.16Keywords:
Visual Content, Digital Media, Engagement, Purchase IntentionAbstract
This study investigates the effects of gaze and product salience in visual content, which can build engagement on social media. The variables used were visual social semiotics, digital visual engagement, attitude, and the purchase intention. Two hundred participants were recruited using Amazon Mechanical Turk. To see the interaction between gaze and product salience, a 2x2 experimental design was used. Regression was used to see the relationship between digital visual engagement with attitude and purchase intention. This study offers empirical evidence that there is an interaction between gaze and product salience on digital visual engagement, with a positive effect on digital visual engagement from the direct gaze and high product salience condition. Furthermore, this study found a relationship between digital visual engagement with attitude and purchase intention. The results show that digital visual engagement positively influences attitude and purchase intention. This hypothesis is tested on a single product category. Further studies might replicate this experiment with other products, visual content, online platforms, and factors based on visual social semiotics theory. This study offers managers knowledge on making visual content that will produce more engagement, especially in social media ads, which can influence the attitude and purchase intention of their audience.
References
Alalwan, A. A. (2018). Investigating the impact of social media advertising features on customer purchase intention. International Journal of Information Management, 42, 65–77.
Arapakis, I., Lalmas, M., Cambazoglu, B. B., Marcos, M. C., & Jose, J. M. (2014). User engagement in online N ews: Under the scope of sentiment, interest, affect, and gaze. Journal of the Association for Information Science and Technology, 65(10), 1988-2005.
Arora, A., Bansal, S., Kandpal, C., Aswani, R., & Dwivedi, Y. (2019). Measuring social media influencer index- insights from Facebook, Twitter and Instagram. Journal of Retailing and Consumer Services, 49, 86–101.
Balakrishnan, B. K. P. D., Dahnil, M. I., & Yi, W. J. (2014). The Impact of Social Media Marketing Medium toward Purchase Intention and Brand Loyalty among Generation Y. Procedia - Social and Behavioral Sciences, 148, 177–185.
Barcaccia, B., Baiocco, R., Pozza, A., Pallini, S., Mancini, F., & Salvati, M. (2019). The more you judge the worse you feel. A judgemental attitude towards one’s inner experience predicts depression and anxiety. Personality and Individual Differences, 138, 33–39.
Barger, V., Peltier, J. W., & Schultz, D. E. (2016). Social media and consumer engagement: a review and research agenda. Journal of Research in Interactive Marketing, 10(4), 268-287.
Beldona, S., Schwartz, Z., & Zhang, X. (2018). Evaluating hotel guest technologies: does home matter? International Journal of Contemporary Hospitality Management, 30(5), 2327–2342.
Berry, C. T., Kranenburg, K. E., James, K. E., & Clow, K. E. (2006). The relationship of the visual element of an advertisement to service quality expectations and source credibility. Journal of Services Marketing, 20(6), 404–411.
Bilgihan, A. (2016). Gen Y customer loyalty in online shopping: An integrated model of trust, user experience and branding. Computers in Human Behavior, 61, 103–113.
Borges-Tiago, M. T., Tiago, F., & Cosme, C. (2019). Exploring users' motivations to participate in viral communication on social media. Journal of Business Research, 101, 574-582.
Buhrmester, M., Kwang, T., & Gosling, S. D. (2011). Amazon’s Mechanical Turk: A New Source of Inexpensive, Yet High-Quality, Data? Perspectives on Psychological Science, 6(1), 3–5.
Can, L., & Kaya, N. (2016). Social Networking Sites Addiction and the Effect of Attitude towards Social Network Advertising. Procedia - Social and Behavioral Sciences, 235, 484–492.
Casey, S. (2017). 2016 Nielsen social media report. Retrieved April 11, 2019, from Nielsen: https://www.nielsen.com/content/dam/corporate/us/en/reports-downloads/2017-reports/2016-nielsen-social-media-report.pdf
Gaudette, E. (2019). 2019 Report: engaging your audience with visual content. Retrieved August 6, 2019, from Contently: https://contently.com/2019/04/23/visual-content-report-libris/
Cecchetto, F. H., & Pellanda, L. C. (2014). Construction and validation of a questionnaire on the knowledge of healthy habits and risk factors for cardiovascular disease in schoolchildren. Jornal de Pediatria, 90(4), 415–419.
Charlton, A. B., & Cornwell, T. B. (2019). Authenticity in horizontal marketing partnerships: A better measure of brand compatibility. Journal of Business Research, 100, 279–298.
Chen, S. H., Pascale, C., Jackson, M., Szvetecz, M. A., & Cohen, J. (2016). A limited survey-based uncontrolled follow-up study of children born after ooplasmic transplantation in a single centre. Reproductive BioMedicine Online, 33(6), 737–744.
Chiou, W. J. P., Knewtson, H. S., & Nofsinger, J. R. (2019). Paying attention to social media stocks. International Review of Economics & Finance, 59, 106-119.
Chu, K. H., Allem, J. P., Cruz, T. B., & Unger, J. B. (2017). Vaping on Instagram: cloud chasing, hand checks and product placement. Tobacco control, 26(5), 575-578.
Dehghani, M., & Tumer, M. (2015). A research on effectiveness of Facebook advertising on enhancing purchase intention of consumers. Computers in Human Behavior, 49, 597–600.
Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes. Harcourt Brace Jovanovich College Publishers.
Eigenraam, A. W., Eelen, J., van Lin, A., & Verlegh, P. W. J. (2018). A consumer-based taxonomy of digital customer engagement practices. Journal of Interactive Marketing, 44, 102–121.
Erkan, I. (2015). Electronic word of mouth on Instagram: customers’ engagements with brands in different sectors. International Journal of Management, Accounting and Economics, 2(12), 1435–1444.
Ewing, L., Rhodes, G., & Pellicano, E. (2010). Have you got the look? Gaze direction affects judgements of facial attractiveness. Visual Cognition, 18(3), 321-330.
Gómez, M., Lopez, C., & Molina, A. (2019). An integrated model of social media brand engagement. Computers in Human Behavior, 96, 196–206.
Hamid, S., Bukhari, S., Ravana, S. D., Norman, A. A., & Ijab, M. T. (2016). Role of social media in information-seeking behaviour of international students: A systematic literature review. Aslib Journal of Information Management, 68(5), 643–666.
Harrison, C. (2003). Visual social semiotics: Understanding how still images make meaning. Technical Communication, 50(1), 46–60.
Hauser, D. J., & Schwarz, N. (2016). Attentive Turkers: MTurk participants perform better on online attention checks than do subject pool participants. Behavior Research Methods, 48(1), 400–407.
Holden, C. J., Dennie, T., & Hicks, A. D. (2013). Assessing the reliability of the M5-120 on Amazon’s Mechanical Turk. Computers in Human Behavior, 29(4), 1749–1754.
Hollebeek, L. D., & Macky, K. (2019). Digital content marketing’s role in fostering consumer engagement, trust, and value: framework, fundamental propositions, and implications. Journal of Interactive Marketing, 45, 27–41.
Ilbeigi, M., Lurkin, V., & Garrow, L. A. (2019). Using Internet-based marketplaces to conduct surveys: An application to airline itinerary choice models. Transportation Research Part C: Emerging Technologies, 103, 129–141.
Jaakonmäki, R., Müller, O., & Vom Brocke, J. (2017, January). The impact of content, context, and creator on user engagement in social media marketing. In Proceedings of the 50th Hawaii international conference on system sciences.
Jia, Y., & Han, M. (2013). Category-independent object-level saliency detection. In Proceedings of the IEEE international conference on computer vision (pp. 1761-1768).
Johnston, C., & Davis, W. E. (2019). Motivating exercise through social media: Is a picture always worth a thousand words? Psychology of Sport and Exercise, 41, 119–126.
Khan, M. L. (2017). Social media engagement: What motivates user participation and consumption on YouTube? Computers in Human Behavior, 66, 236–247.
Kilger, M., & Romer, E. (2007). Do measures of media engagement correlate with product purchase likelihood? Journal of Advertising Research, 47(3), 313-325.
Kim, C., & Yang, S.-U. (2017). Like, comment, and share on Facebook: How each behavior differs from the other. Public Relations Review, 43(2), 441–449.
Kim, Y. H., Kim, D. J., & Wachter, K. (2013). A study of mobile user engagement (MoEN): Engagement motivations, perceived value, satisfaction, and continued engagement intention. Decision Support Systems, 56, 361-370.
Kress, G. R., & Van Leeuwen, T. (1996). Reading images: The grammar of visual design. Psychology Press.
Kumar, N., Nagalla, R., Marwah, T., & Singh, M. (2018). Sentiment dynamics in social media news channels. Online Social Networks and Media, 8, 42-54.
Kusumasondjaja, S., & Tjiptono, F. (2019). Endorsement and visual complexity in food advertising on Instagram. Internet Research.
Le Roux, I., & Maree, T. (2016). Motivation, engagement, attitudes and buying intent of female Facebook users. Acta Commercii, 16(1), 1–11.
Lee, A., Martin, R., Thomas, G., Guillaume, Y., & Maio, G. R. (2015). Conceptualizing leadership perceptions as attitudes: Using attitude theory to further understand the leadership process. The Leadership Quarterly, 26(6), 910–934.
Lee, S., & Xenos, M. (2019). Social distraction? Social media use and political knowledge in two US Presidential elections. Computers in Human Behavior, 90, 18–25.
Lewis, N., & Sznitman, S. R. (2019). Engagement with medical cannabis information from online and mass media sources: Is it related to medical cannabis attitudes and support for legalization? International Journal of Drug Policy.
Lien, C.-H., Wen, M.-J., Huang, L.-C., & Wu, K.-L. (2015). Online hotel booking: The effects of brand image, price, trust and value on purchase intentions. Asia Pacific Management Review, 20(4), 210–218.
López-Sánchez, D., Arrieta, A. G., & Corchado, J. M. (2019). Visual content-based web page categorization with deep transfer learning and metric learning. Neurocomputing.
Malhotra, N., Nunan, D., & Birks, D. (2017). Marketing Research: An Applied Approach. (5 ed.) Pearson.
Manic, M. (2015). Marketing engagement through visual content. Bulletin of the Transilvania University of Brasov. Economic Sciences. Series V, 8(2), 89.
Martins, J., Costa, C., Oliveira, T., Gonçalves, R., & Branco, F. (2019). How smartphone advertising influences consumers’ purchase intention. Journal of Business Research, 94, 378–387.
McCay-Peet, L., Lalmas, M., & Navalpakkam, V. (2012, May). On saliency, affect and focused attention. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 541-550). ACM.
Nisar, T. M., Prabhakar, G., & Strakova, L. (2019). Social media information benefits, knowledge management and smart organizations. Journal of Business Research, 94, 264-272.
Parker, G., McCraw, S., Tavella, G., & Hadzi-Pavlovic, D. (2018). Measuring the consequences of a bipolar or unipolar mood disorder and the immediate and ongoing impacts. Psychiatry Research, 269, 70–74.
Peterson, R. A. (1994). A Meta-Analysis of Cronbach’s Coefficient Alpha. Journal of Consumer Research, 21(2), 381–391.
Pfeiffer, U. J., Vogeley, K., & Schilbach, L. (2013). From gaze cueing to dual eye-tracking: Novel approaches to investigate the neural correlates of gaze in social interaction. Neuroscience & Biobehavioral Reviews, 37(10, Part 2), 2516–2528.
Poria, S., Cambria, E., Howard, N., Huang, G. B., & Hussain, A. (2016). Fusing audio, visual and textual clues for sentiment analysis from multimodal content. Neurocomputing, 174, 50-59.
Prentice, C., Han, X. Y., Hua, L.-L., & Hu, L. (2019). The influence of identity-driven customer engagement on purchase intention. Journal of Retailing and Consumer Services, 47, 339–347.
Pressgrove, G., Janoske, M., & Haught, M. J. (2018). Editors’ letter: New research and opportunities in public relations and visual communication. Public Relations Review, 44(3), 317-320.
Rahim, A., Safin, S. Z., Kheng, L. K., Abas, N., & Ali, S. M. (2016). Factors Influencing Purchasing Intention of Smartphone among University Students. Procedia Economics and Finance, 37, 245–253.
Ramos-Serrano, M., & Martínez-García, Á. (2016). Personal style bloggers: the most popular visual composition principles and themes on Instagram. Observatorio (OBS*), 10(2), 89-109.
Romaniuk, J., & Sharp, B. (2004). Conceptualizing and measuring brand salience. Marketing Theory, 4(4), 327–342.
Schmidt, G. B., & Jettinghoff, W. M. (2016). Using Amazon Mechanical Turk and other compensated crowdsourcing sites. Business Horizons, 59(4), 391–400.
Senju, A., & Hasegawa, T. (2005). Direct gaze captures visuospatial attention. Visual cognition, 12(1), 127-144.
Shaouf, A., Lü, K., & Li, X. (2016). The effect of web advertising visual design on online purchase intention: An examination across gender. Computers in Human Behavior, 60, 622-634.
Shareef, M. A., Mukerji, B., Dwivedi, Y. K., Rana, N. P., & Islam, R. (2019). Social media marketing: Comparative effect of advertisement sources. Journal of Retailing and Consumer Services, 46, 58–69.
Sheldon, P., & Newman, M. (2019). Instagram and American teens: understanding motives for its use and relationship to excessive reassurance-seeking and interpersonal rejection. The Journal of Social Media in Society, 8(1), 1–16.
Sokolova, K., & Kefi, H. (2019). Instagram and YouTube bloggers promote it, why should I buy? How credibility and parasocial interaction influence purchase intentions. Journal of Retailing and Consumer Services.
Solomon, E. (2018). The Nielsen CMO report 2018. Retrieved April 11, 2019, from Nielsen: https://www.nielsen.com/content/dam/nielsenglobal/ua/docs/nielsen-cmo-report-2018.pdf
Stathopoulou, A., Siamagka, N. T., & Christodoulides, G. (2019). A multi-stakeholder view of social media as a supporting tool in higher education: An educator-student perspective. European Management Journal.
Statitsa. (2019). Number of monthly active Instagram users from January 2013 to June 2018 (in millions). Retrieved April 11, 2019, from Statista: https://www.statista.com/statistics/253577/number-of-monthly-active-instagram-users/
Stone, A. A., Walentynowicz, M., Schneider, S., Junghaenel, D. U., & Wen, C. K. (2019). MTurk participants have substantially lower evaluative subjective well-being than other survey participants. Computers in Human Behavior, 94, 1–8.
Valentini, C., Romenti, S., Murtarelli, G., & Pizzetti, M. (2018). Digital visual engagement: influencing purchase intentions on Instagram. Journal of Communication Management, 22(4), 362–381.
Downloads
Published
How to Cite
Issue
Section
Citation Check
License
Copyright (c) 2022 Fathony Rahman, Jonathan Alpha Andreas, Kenny Irawan

This work is licensed under a Creative Commons Attribution 4.0 International License.
ELIGIBLE : Journal of Social Sciences is licensed under a Creative Commons Attribution 4.0 International License.
This means, under the CC-BY 4.0 license the author(s) allow, permitted, and encouraged to:
- The others to share and adapt the work (the material and the content of publications);
- Enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book)
- Post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
The users of ELIGIBLE : Journal of Social Sciences are required to cite the original source, including the author's names, ELIGIBLE : Journal of Social Sciences as the initial source of publication, year of publication, volume number, issue, and Digital Object Identifier (DOI).