Scroll, Click, Abandon: Unraveling the Impact of Social Media Engagement on Cart Abandonment Behavior Among Gen Z
Jeevana Kalla
Research Scholar,
National Institute of Technology Raipur
Dr. Chetna Sharma Rajput
Assistant Professor,
National Institute of Technology Raipur
Abstract
This study examines how social media engagement (active vs. passive users) affects cart abandonment behavior among Gen Z consumers in India. With e-commerce growth and social media's increasing role in decision-making, cart abandonment remains a major challenge. Using theories such as the Theory of Planned Behavior, Elaboration Likelihood Model, and Social Identity Theory, this research explores psychological and behavioral factors influencing abandonment. A two-phase experiment with 64 Gen Z participants measured cart abandonment rates after exposure to social media advertisements, first without and then with celebrity endorsements. Findings show that active users had lower abandonment rates (68.4% in Phase 1, 66.9% in Phase 2), while passive users abandoned significantly more (78.9% and 84.5%, respectively). Regression analysis confirmed that social media engagement significantly predicts cart abandonment (β = -0.33, p = 0.008), with celebrity endorsements increasing abandonment among passive users (β = 0.29, p = 0.045). Active users develop stronger brand connections, reducing abandonment, while passive users experience decision fatigue and lack emotional investment. The study suggests e-commerce brands should use engagement-driven marketing for active users and social proof, urgency tactics, and personalized recommendations for passive users. Limitations include the focus on Gen Z in India, suggesting future research should explore broader demographics, platform-specific differences, and longitudinal trends. Overall, this study provides insights into how social media engagement influences online shopping behavior and offers strategies for reducing cart abandonment in digital marketing.
Keywords: Social media, Digital Marketing, Online Shopping, Cart Abandonment
Introduction
Background of the Study
E-commerce Growth
E-commerce has been growing fast in India, aided by rising smartphone penetration and internet use in urban and semi-urban regions (Sanwal et.al, 2016; Khosla & Kumar, 2017). There will be 500 million people buying online by the year 2025, which will drive e-commerce growth evenfurther (IBEF,2024). But this progress has also opened the door for cart abandonment in which customers will place items on their carts and never follow up on the purchases (Rajamma et.al, 2009; Kukar-Kinney & Close,2010).
Social Media Influence
Social media has contributed a lot to consumer behavior, particularly among Gen Z (Priporas et.al, 2017; Seemiller & Grace, 2018). Social media platforms such as Instagram, Twitter, and TikTok have become a necessity in product discovery and shopping, where almost 50% of Gen Z consumers are influenced by social media when making purchasing decisions (Childers & Boatwright,2021;Pradhan et.al,2023).
Cart Abandonment
Cart abandonment is a major problem for online retail, with an estimated 70% of online carts being abandoned worldwide (Gokwik,2024). High shipping prices, lengthy checkout processes, and security issues are factors that are contributing to cart abandonment (Kukar-Kinney & Close, 2010; Erdil, 2018). Social media's role in averting or increasing cart abandonment is being researched, particularly in terms of user interaction (Hutter et.al, 2013; Balakrishnan et.al,2014).
Relating Social Media and Cart Abandonment
This study examines the effect of social media usage (active versus passive users) on cart abandonment. Active users, who use content regularly, might make more purchases, while passive users could have higher rates of abandonment. These behaviors may give insight into cart abandonment causes.
Research Question and Objectives
Main Research Question:
How do levels of social media engagement (active vs. passive users) affect cart abandonment behavior of GenZ consumers in India?
Research Aims:
1. To investigate how social media use (active vs. passive) affects decision-making in online shopping, specifically cart abandonment.
2. To ascertain if active social media users are more or less likely to abandon carts than passive users.
3.To determine the psychological drivers of cart abandonment, such as emotional reactions and social media content effects.
Significance of the Study
Contribution to E-commerce:
The research increases knowledge on cart abandonment by associating social media consumption patterns with buying behavior. Understanding how social media interaction affects abandonment can enable e- commerce companies to streamline their sales processes and minimize cart drop-offs.
Implications for Social Media Marketing:
The findings will assist brands in tailoring social media marketing strategies to better engage Gen Z, especially distinguishing between active and passive users. Personalized calls to action and targeted incentives may be needed to reduce abandonment and boost conversion rates.
Literature Review
Social Media and Consumer Behavior
A General Impact on Consumer Behavior
The rise of social media has dramatically altered consumer behavior patterns. Recently, platforms such as Instagram, Facebook, Twitter, and TikTok have been embraced by consumers to interact with brands, learn about products, and arrive at buying decisions. Social media has incredible powers to influence consumers' attitudes and behaviors concerning buying decisions (Akar & Topçu, 2011; Lee, 2013; Stephen, 2016; Lim et.al, 2017; Duffett, 2017). According to a study conducted by Forbes (2022), about 80% of consumers consult social media for product research before a purchase. On one hand, continual exposure to ads, influencer endorsements, and user-generated content generates a community and trust for the brand, significantly influencing consumer decisions (Hollebeek & Macky, 2019; Nyberg, 2024). Social media has existed as a top-of-the-line communication channel, evolving over time to direct marketing avenues through which brands and consumers can interact, hence efficiently attracting and retaining consumer interest.
Generation Z Consumer Behavior
Among all demographic groups, members of Generation Z—born between 1997 and 2012—are the most active in their use of social media and internet platforms. Almost 98% of Gen Z consumers own smartphones, with the average user spending between three and four hours each day on social media, according to a report from the Pew Research Center (2024). The digital content perception of these consumers drives their preferences, buying behaviors, and trust in brands. This generation cares about authenticity, diversity, and responsible business behavior. Gen Z consumers gravitate toward social media content that promotes any values they hold dearly [like sustainability or inclusivity] (Uche, 2018; Wong, 2021, Narayanan, 2022; Seyfi et.al, 2024). Apart from that, they tend to trust the influencer marketing options and recommendations offered by peers when making a purchasing decision and consider social media a highly important source of brand discovery (Artemova, 2018; Dobre et.al, 2021; Sun et.al, 2022; Rachmad, 2024). The influence of social media concerning information-gathering is only one small section of the influence landscape, which continues into Gen Z actually buying through apps or using social digital platforms like Instagram that put shopping capabilities right into their social feed.
Active and Passive Users
Consumers can be identified as either active or passive users depending on how deeply they engage. Active users participate in the news regularly by liking, sharing, commenting, following brands, and following influencers. Active users tend to emotionally engage in a larger way with brands and therefore might display more loyalty to those brands (Men et.al, 2013). Passive users participate less and view content rather than contribute or interact with it. Research conducted by Godey et al. (2016) found that engagement levels dictate consumer behavior: Those with active social media involvement show more intent to purchase and complete a sale compared to passive users. Passive users who lack strong emotional incentives toward a brand may be more likely to drop their shopping cart-especially if the ads or content fail to feel personal or engaging to them. This distinction serves as the basis for understanding how varying social media users behave differently through an e-commerce environment.
Cart Abandonment in E-commerce
Abandonment of carts has been a persistent problem in e-commerce for years. Baymard Institute estimates that about 70% of all online shopping carts are abandoned prior to completing the checkout process (Statista, 2024). Several reasons cause this high rate of cart abandonment. Such causes include, among others, the high unexpected costs such as taxes and delivery fees, the perceived complexity of the checkout process, low trust regarding payment security, and delivery delays (Kukar-Kinney & Close, 2010; Goel et.al, 2024). Other external factors, such as difficulties in website navigation and slow-speed loading pages, are likely to degrade the user experience and lead to ultimate effects of cart abandonment (Xu & Huang, 2015; Huang et.al, 2018; Erdil, 2018; Rubin et.al, 2020). Although these practical issues could cause someone to abandon his/her cart, there are some deeper psychological and behavioral factors that come into play as well, which drive consumers to dull out items in their cart without completing the sales transaction.
Psychological Factors in Cart Abandonment
Psychologically complex reasons lead to abandonment in the cart. There are many theories that can explain consumer decision-making. One among them is decision fatigue. When a consumer has too many choices, he or she might choose to defer the decision, or even altogether abandon the cart (Ding et.al, 2017; Kim, 2021; Wang et.al, 2023). Kahneman performed studies in 2011 which emphasized that long decision-making processes could end-up with mental exhaustion, thereby causing some individuals to delay or cancel their purchases (Kahneman, 2011). Price sensitivity plays a very important role when it comes to abandonment behavior. It is possible that a customer might place an item into a shopping cart but leave it without being purchased because he or she finds the final price to be very high or because he or she is not sure if it is worth the amount (Rochanapon et.al, 2021). Another one is cognitive dissonance wherein consumers feel conflicting emotions toward a purchase, especially when he or she is quite unsure whether the product goes hand in hand with his or her values or needs (Sondhi, 2017; Mishra et.al, 2021).
Bridging Social Media and the Abandonment of Carts
Numerous studies have explored the connection between social networking and cart abandonment. Social media advertisements, mainly of an influencer or celebrity, influence choice making in that it brings a level of credibility and trust (Cooley & Parks-Yancy, 2019; Lou & Yuan, 2019). Nevertheless, the presence of a celebrity or influencer does not always lead to completed transactions. Influencer endorsements were effective in increasing the brand awareness but not necessarily associated with raising the intention of purchase (Weismueller et.al, 2020). This was sometimes because consumers would be overwhelmed by too much advertising or because the emotional response would be negative as it was too commercialized. The overexposure of celebrity-driven advertisements in social media might also result in advertisement fatigue, and that would increase the chances of having a cart-abandoned final result, especially in passive users who are less likely to have serious emotional connections with the brand or product.
Patterns of Social Media Use with Online Shopping
Active Engagement and Purchase Behavior
Active contacts in social media are now proven to be highly influential in purchasing behavior. Schivinski & Dabrowski (2016) mentioned that the involved activities like liking, sharing, or commenting on posts indicate higher involvement and connection of a particular consumer to the brand. These consumers seem to be more willing to buy, as their emotional bonds with the brand are stronger and with more exposure to personalized contents. Furthermore, active users develop social commerce-direct purchase through social media channels-making this relationship more solid when it comes to purchases through the platforms. Of such popular platforms with e-commerce features, Instagram's Shop or Facebook Marketplace is for active users who then complete purchases without leaving that platform.
Passive Engagement and Its Limitations
On the opposite side, passive users, those who just consume content-in this case, advertisements-without interacting, are found to more likely abandon their shopping carts, according to research by Dholakia in 2006. Passive users develop weak brand attachments, making them more easily discouraged or distracted at the time they are ready to purchase. Consequently, their lack of engagement leaves them other misgivings about the product's or service's worth. In addition, passive users are open to competing ad campaigns or other offers that will keep them from completing the purchasing transaction.
Important Role of Social Media in Promoting Trust and Persuasion
Trust thus becomes a most significant factor in e-commerce transactions, especially those of online purchasing, as it can either build or break consumer trust in the brand on behalf of the consumers, depending on how social media is used. Social proof-the psychological phenomenon whereby people tend to follow the actions of others-becomes a very important aspect in shopping online (Amblee & Bui, 2011; Salmon et.al, 2015; Talib et.al, 2017; Naeem, 2021). In particular, positive reviews, testimonials, and influencer endorsements can establish credibility and, thus, help consumers feel confident in their purchases. Misuse in influencer marketing or hyper-commercialized content, however, can account for blackening a brand's reputation, thereby decreasing consumers' trust and leading to higher cart abandonment rates.
Summary and Gaps in Literature
To summarize prior research, it points to the notable role of social media in consumer behavior, with clear distinctions in engagement levels and purchase behavior between active and passive users. While active users engage deeply in social media content and brand involvement, they tend to have a stronger emotional connect with the product and are highly inclined toward completing the purchase. Passive users, however, stand a high chance of abandoning their carts, having no strong brand attachment or emotional engagement. On the other hand, cart abandonment continues to be a grave challenge for e-commerce and is being triggered by different external and psychological factors. While several studies shall prove the association between social media use and cart abandonment, there is still a gap in understanding the cart abandonment experiences of Gen Z consumers in India in the context of engaging with social media in an active or passive way.
The literature clearly demands the need for further studies that will help elucidate the different ways social media engagement affects cart abandonment in the Indian context. There is sparse research for the second segment that centers on Gen Z consumers in India, characterized as being heavily into social media use and maintaining extreme behavioral pattern differences in purchases. The intention of this study is to bridge this gap to generate useful inputs for e-commerce companies toward minimizing cart abandonment rates by understanding the role of social media usage patterns in consumer decision-making processes.
Theoretical Framework
The impact of social media use on cart abandonment can be understood using a combination of psychological, social, and behavioral theories, which discuss how different levels of engagement (passive and active users) influence consumers' decision-making processes.
Theory of Planned Behavior
Ajzen's (1991) Theory of Planned Behavior postulates that attitudes, subjective norms, and perceived control influence behavior. Active users, who are active with brands on social media, perceive themselves to be more in control of their choices, thus abandoning less. Passive users, who are less active, are more likely to abandon carts.
Uses and Gratifications Theory (UGT)
UGT posits that consumers actively seek content that satisfies their needs (Katz et al., 1973). Active users, connected to brands via personal values, are less likely to abandon carts, while passive users, less invested, are more likely to do so.
Elaboration Likelihood Model (ELM)
The ELM (Petty & Cacioppo, 1984) asserts that active consumers process advertising carefully, minimizing cart abandonment, while passive consumers use shallow cues, which can cause greater abandonment.
Social Identity Theory (SIT)
SIT (Tajfel & Turner, 1979) asserts that active consumers create strong ties with brands and influencers, which prevent them from abandoning their carts. Passive consumers do not have such ties and can easily abandon their carts.
Empirical S-O-R Model
The S-O-R Model (Mehrabian & Russell, 1974) postulates that emotional reactions to stimuli (e.g., advertisements) drive behavior. Engaged active users with strong emotional reactions are more likely to make purchases, whereas passive users with less emotional reactions are likely to leave carts.
Consumer Decision-Making Process Model
Active users progress through phases such as information search and evaluation, resulting in completed purchases. Passive users bypass these phases, making impulsive purchases that result in frequent cart abandonment (Kotler & Keller, 2015).
Social Cognitive Theory
Bandura's Social Cognitive Theory (1986) focuses on learning through observation. Active users, watching influencers, develop strong product attitudes, resulting in reduced abandonment rates. Passive users do not establish trust, resulting in increased cart abandonment.
Commitment-Trust Theory
Active users, who continuously interact with brands, build trust and commitment, decreasing abandonment. Passive users, having no emotional or cognitive investment, tend to abandon their carts (Morgan, 1994).
Technology Acceptance Model (TAM)
TAM (Davis et al., 1989) suggests that perceived ease of use and perceived usefulness influence the adoption of technology. Active users are aware of e-commerce platforms, decreasing abandonment, whereas passive users tend to abandon carts as they get frustrated or are disengaged.
Transactional Model of Stress and Coping
This model (Lazarus, 1984) proposes that active users cope with stress while shopping, minimizing abandonment. Passive users, stressed and less experienced, tend to abandon their carts.
Figure 1: Theoretical Framework
Integrating these theories brings about an integrative picture of the ways through which social media activity impacts cart abandonment behavior. Through analysis of psychological and behavior determinants, the multi-theory approach facilitates the understanding of how decision making by Indian Gen Z consumers unfolds in a case of e-commerce.
Methodology
Research Design
This study uses an experimental and quantitative design to explore the relationship between social media usage patterns (active vs. passive) and shopping cart abandonment behavior among Gen Z consumers in India. The experiment consists of two phases: showing advertisements to measure actions of adding or abandoning items in the cart. The experimental design allows for manipulation of variables (e.g., celebrity endorsements), enabling cause-and-effect analysis. A quantitative approach provides measurable data on cart additions, abandonment rates, and social media usage for statistical correlation.
Participants
The participants were 64 Gen Z students (18-21 years old) from a public technical research institute in India, selected for their high engagement with social media and online shopping. The sample was evenly split by gender, allowing for a comprehensive understanding of shopping behaviors. Inclusion criteria required daily social media users who had shopped online in the last six months, while exclusions included non-regular users or those with digital marketing experience.
Data Collection
Data collection consisted of two parts:
Data collection ensured uniformity, minimizing distractions and external influences.
Measurement Tools
Cart abandonment was measured by tracking participants' actions in both phases, calculating the abandonment rate as the number of abandoned carts divided by initiated carts. Social media engagement was quantified using the Social Media Usage Patterns Scale, with active users engaging more and passive users less. Data from both measures were correlated to assess the relationship between social media engagement and cart abandonment, using regression analysis and ANOVA for statistical testing.
Results
Descriptive Statistics
The descriptive statistics offer an initial overview of the data, focusing on the number of products added to carts, the number of items abandoned, and the breakdown of active vs. passive social media users. The participants in this study were categorized into active users (those who frequently engage with content on social media platforms such as liking, commenting, and sharing) and passive users (those who passively consume content without much engagement).
Phase 1: Without Celebrities
Phase 2: With Celebrities
Figure 2: Cart Abandonment Rates by Social Media Engagement and Phase
The data clearly shows that passive users have a higher abandonment rate than active users, both in Phase 1 and Phase 2. Furthermore, while both user groups have higher abandonment rates in Phase 2 (with celebrities), passive users showed a more significant increase in abandonment, especially in the celebrity endorsement phase.
Inferential Analysis
To assess the relationship between social media engagement patterns and cart abandonment, several statistical tests were conducted, including regression analysis and ANOVA.
Regression Analysis
A multiple regression analysis was conducted to explore the impact of social media engagement levels (active vs. passive users) on cart abandonment across both phases. The regression model included the following predictors: social media engagement level, phase of advertisement (with or without celebrity), and user gender.
Figure 3: Regression Analysis
Results:
ANOVA
A Two-Way ANOVA was used to analyze the effects of two independent variables—social media engagement (active vs. passive) and phase (Phase 1 vs. Phase 2)—on the cart abandonment rate. The dependent variable was the cart abandonment rate.
Results:
Comparison of Cart Abandonment Rates
Comparison of Phase 1 and Phase 2:
Figure 4: Comparison of Abandonment rates
The ANOVA results reveal that the introduction of celebrity endorsements increased abandonment rates for passive users significantly, but had a marginal effect on active users. This suggests that celebrity endorsements may act as a psychological deterrent for passive users, likely due to a mismatch between the brand's perceived value and the user's actual interests or preferences.
Discussion of Findings
The results of this research shed significant insights on social media use and cart abandonment in e-commerce. The following are the principal findings based on the analysis:
In summary, social media interaction is an important factor in the decision to abandon shopping carts, with active participants being more inclined to follow through with their purchase. Celebrity endorsement, though, has a dual impact—visibility is enhanced but so is a psychological element which can contribute to cart abandonment, especially among inactive users. These findings hold insightful implications for online commerce companies with the potential for reducing cart abandonment levels, most importantly among passive users.
Discussion
Interpretation of Results
These findings will provide a vital clue on how social media usage patterns, especially the disparity between active and passive users, influence cart abandonment in e-commerce in general. This is important for e-commerce brands as they target Gen Z consumers who are social media active and swaying potential purchases more or less by online contacts.
Further, for active social media users, the lower rates of cart abandonment suggest stronger connections of involvement with the brand to a completed purchase. Active users are more closely related to an item when looking at it, so they are less likely to be distracted and hesitant before making a purchase. That means the e-commerce channels should focus on providing the personalized interactive dynamic content keeping active users online. For example, live chats, exclusive deals, or even virtual shopping can increase user engagement and reduce cart abandonment.
On the other hand, passive users who observe content without engaging with the latter have exhibited significantly higher cart abandonment rates even at the second phase. These users may require some stronger and more direct action towards their call of action to convert it into a purchase from the main intent. Such people are mostly emotionally far away from the brand and that is why they abandon their carts so easily mostly when something else distracts their mind or they feel doubting the actual value of the products. To help passive abandoners, online marketplaces can also include clear communication methods such as time-constraint messages, sales pitch hidden customer votes, and free shipping as a sense of urgency.
The psychological factors motivating cart abandonment also explain these findings. There may be high decision fatigue, price-sensitivity, or perceived worth factors. Relative to active users with few cognitive burdens and with much assurance in decisions regarding purchases, the passive ones will likely be prone to decision fatigue in many cases especially if paired with celebrity endorsements, which will feel inappropriate in that situation. Here too, the perceived worth of the product decreases, and the user ends up abandoning the cart due to ambiguity on whether or not to purchase it.
So, even though the celebrity endorsement effect may enhance the visibility of a product, in this study, it also shows evidence of increasing the dissonance perceived attached by passive users, especially should be tied to the celebrity endorser or the product. Finally, alluded psychological pressures can cause emotional experiences like regret or even guilt, which can lead toward non-completion. To the contrary, an active user views or even completely embraces the user's celebrity endorser because the user may have had some trust and familiarity already with the brand.
Implications
The results deal with certain important implications for social media marketing strategies that can eventually erase cart abandonment among different types of users.
For active consumers, brands focus on providing them with better content that is friendly and engaging. Sometimes, active users simply become very interested in content that speaks about their inclination and makes even a more effective possible interaction. Brands may introduce engagement opportunities in other creative ways as polls and quizzes as well as UGCs focusing on solidifying the emotional connection between the user and the brand. Add a loyalty point or exclusive discounts, reward them for doing so.
On the contrary, the passive might understand simpler yet direct messaging types that carry the object's promise and urgency. Some calls to action go for limited-time offers, discounts, or perhaps easy payment options, thus evading abandoning an item. Moreover, credibility shall come with the display of advertisements, when the same is visually striking and easily processable, waltzing against overwhelming content. The use of social proof- positive customer reviews- or user testimonials may also benefit passive users by boosting their confidence regarding purchases.
Another major initiative will include influencer marketing. In this way, active users can be highly saluted by an endorsing trusted influencer for a product, prompting low abandonment rate on such purchases. Influencers act as trusted guides in the purchasing process by providing added information and positive reinforcement, thus significantly decreasing abandonment rates.
In addition, brands should also watch out for the timing and frequency of their social marketing campaigns. Users exposed to overly repetitive ads will experience ad fatigue, especially passive ones, leading to increased abandonment rates. Therefore, the brands have to make sure the messaging is relevant as well to hit both timely and overwhelming advertisement.
Limitations of the Study
As the findings from this study show, the relationship of social media usage pattern with cart abandonment can be quite enlightening, but there are a few limitations. It is a very small sample of about 64 participants; besides that, it was taken only from Gen Z students in a public technical research institute in India. This indicates that the study's findings are not easily generalizable, since behavior is likely to vary across different demographic groupings around the world and even in other socioeconomic classes.
The study did not capture cart abandonment rates for different kinds of products-luxury versus everyday ones-or so it feels to be a significant factor in the psychology of the buying decision. While the two-phase experimental design gave some useful results, considered individually, it might not have captured adequately the richness and complexity of real e-commerce situations, where advertisements are often seen within a different context and on a multitude of touchpoints.
Future Directions
Perhaps, future studies could involve samples targeting people across the age spectrum from different regions and backgrounds. This would help achieve a more reasonable interpretation of the social media use pattern in relevance to cart abandonment across different segments of the population. Future research could also examine how much of an effect the specific social media platform (such as between Instagram and TikTok) can have on cart abandonment. Since the nature of engagement and advertising formats vary from each platform, the correlation may yield even deeper insights into platform-specific strategies influencing abandonment.
Further study may examine other product types with respect to cart abandonment-luxury versus basic ones. Perhaps, different motivations will come into play depending on the product; understanding those could really help in designing specific marketing strategies for specific product categories. Future research endeavors could look into the continued effects of social media working on consumer behavior and celebrity endorsements. Longitudinally, researchers would be able to track behavior change over periods of time and would be able to discover any possible trends of abandonment that arise due to sustained engagement or brand loyalty.
The findings of the study offer e-commerce brands some unique implications for tuning their marketing strategies by targeting cart abandonment. Enhanced marketing targeting of active vs. passive users could lead to higher engagement and conversion rates achieved by e-commerce platforms, thereby improving the consumer experience and ultimately the business's bottom line.
Conclusion
The study investigated how social media usage patterns-in particular, the dichotomy of active versus passive usage-influence cart abandonment behavior in e-commerce settings. The results indicate that active use of social media leads to lower cart abandonment than passive usage. Active users are those who engage with the content via liking, commenting, or sharing; they are more likely to finalize a purchase because of a greater level of brand engagement and trust. On the other hand, passive users-viewers who look at the content without engagement-become cart abandoners and abandon their carts due to celebrity endorsements. Those users do not have the emotional connection/branded engagement that could persuade them to follow up with an actual purchase.
The study also found that celebrity endorsements influenced both classes of users differently in their advertising. The support of celebrities enhanced engagement for active users, but for passive users, it produced more ambivalence and abandonment. These findings support the theory that passive users may feel a low degree of tie to the product or brand when introduced through a celebrity influencer and subsequently become indecisive and abandon their cart.
This study's findings underline the import of social media usage behaviors in determining consumer decision-making processes, especially concerning cart abandonment mitigation. E-commerce brands targeting Gen Z consumers should know that those different classes of users-active versus passive-require different marketing strategies. Towards active users, brands should invest in the creation of engaging and personalized content for strengthening brand loyalty and completion of purchase. As to passive users, effective calls to action and convictive messages may then be channeled to lead them through purchasing and reduce abandonment.
In aligning marketing strategies not only with social media usage pattern, e-commerce brands will increase their conversion rate and pertinently improve customer experience. This grasp of social media behavior will greatly aid in the ongoing process of creating more effective online shopping experiences, especially in the volatile digital landscape where Gen Z consumers have already become a major driver.
References
|
Ajzen, I. (1991). The Theory of planned behavior. Organizational Behavior and Human Decision Processes. |
|
Akar, E., & Topçu, B. (2011). An examination of the factors influencing consumers' attitudes toward social media marketing. Journal of internet commerce, 10(1), 35-67. |
|
Amblee, N., & Bui, T. (2011). Harnessing the influence of social proof in online shopping: The effect of electronic word of mouth on sales of digital microproducts. International journal of electronic commerce, 16(2), 91-114. |
|
Artemova, A. (2018). Engaging generation Z through social media marketing case: Hurja media Oy. |
|
Balakrishnan, B. K., 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. |
|
Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ, 1986(23-28), 2. |
|
Bhat, J. A., & Dhar, S. (2021). E-commerce and its role in the development of India's indigenous product base. In Handbook of Research on IoT, Digital Transformation, and the Future of Global Marketing (pp. 164-178). IGI Global. |
|
Childers, C., & Boatwright, B. (2021). Do digital natives recognize digital influence? Generational differences and understanding of social media influencers. Journal of Current Issues & Research in Advertising, 42(4), 425-442. |
|
Cooley, D., & Parks-Yancy, R. (2019). The effect of social media on perceived information credibility and decision making. Journal of Internet Commerce, 18(3), 249-269. |
|
Coursaris, C. K., Van Osch, W., & Balogh, B. A. (2016, January). Do Facebook likes lead to shares or sales? Exploring the empirical links between social media content, brand equity, purchase intention, and engagement. In 2016 49th Hawaii international conference on system sciences (HICSS) (pp. 3546-3555). IEEE. |
|
Dabbous, A., & Barakat, K. A. (2020). Bridging the online offline gap: Assessing the impact of brands’ social network content quality on brand awareness and purchase intention. Journal of retailing and consumer services, 53, 101966. |
|
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). Technology acceptance model. J Manag Sci, 35(8), 982-1003. |
|
Dholakia, U. M. (2006). How customer self-determination influences relational marketing outcomes: evidence from longitudinal field studies. Journal of Marketing Research, 43(1), 109-120. |
|
Ding, X., Zhang, X., & Wang, G. (2017). Do you get tired of shopping online? Exploring the influence of information overload on subjective states towards purchase decision. |
|
Dobre, C., Milovan, A. M., Duțu, C., Preda, G., & Agapie, A. (2021). The common values of social media marketing and luxury brands. The millennials and generation z perspective. Journal of Theoretical and Applied Electronic Commerce Research, 16(7), 2532-2553. |
|
Duffett, R. G. (2017). Influence of social media marketing communications on young consumers’ attitudes. Young Consumers, 18(1), 19-39. |
|
Erdil, M. (2018). Factors affecting shopping cart abandonment: Pre-decisional conflict as a mediator. Journal of Management Marketing and Logistics, 5(2), 140-152. |
|
Forbes, 2022. https://www.forbes.com/councils/forbesagencycouncil/2022/04/28/how-social-media-impacts-consumer-buying/ |
|
Godey, B., Manthiou, A., Pederzoli, D., Rokka, J., Aiello, G., Donvito, R., & Singh, R. (2016). Social media marketing efforts of luxury brands: Influence on brand equity and consumer behavior. Journal of business research, 69(12), 5833-5841. |
|
Goel, P., Patti, S., Garg, A., & Sharma, A. (2024). The unfinished order: examining shopping cart abandonment in food delivery apps. Journal of Foodservice Business Research, 1-28. |
|
Gokwik, 2024. https://www.gokwik.co/blog/how-to-avoid-and-overcome-cart-abandonment-losses |
|
Goldring, D., & Azab, C. (2021). New rules of social media shopping: Personality differences of US Gen Z versus Gen X market mavens. Journal of consumer behaviour, 20(4), 884-897. |
|
Gupta, S., Raj, S., Garg, A., & Gupta, S. (2025). Analyzing shopping cart abandonment enablers: an ISM and MICMAC approach. International Journal of Quality & Reliability Management, 42(1), 61-85. |
|
Haddouche, H., & Salomone, C. (2018). Generation Z and the tourist experience: tourist stories and use of social networks. Journal of Tourism Futures, 4(1), 69-79. |
|
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(1), 27-41. |
|
Huang, G. H., Korfiatis, N., & Chang, C. T. (2018). Mobile shopping cart abandonment: The roles of conflicts, ambivalence, and hesitation. Journal of Business Research, 85, 165-174. |
|
Hutter, K., Hautz, J., Dennhardt, S., & Füller, J. (2013). The impact of user interactions in social media on brand awareness and purchase intention: the case of MINI on Facebook. Journal of product & brand management, 22(5/6), 342-351. |
|
IBEF (2024) https://www.ibef.org/industry/ecommerce |
|
Ismail, A. R., Nguyen, B., Chen, J., Melewar, T. C., & Mohamad, B. (2021). Brand engagement in self-concept (BESC), value consciousness and brand loyalty: a study of generation Z consumers in Malaysia. Young Consumers, 22(1), 112-130. |
|
Kahneman, D., Lovallo, D., & Sibony, O. (2011). Before you make that big decision. |
|
Katz, E., Blumler, J. G., & Gurevitch, M. (1973). Uses and gratifications research. The public opinion quarterly, 37(4), 509-523. |
|
Khosla, M., & Kumar, H. (2017). Growth of e-commerce in India: An analytical review of literature. IOSR Journal of Business and Management (IOSR-JBM), 19(6), 91-95. |
|
Kim, J. O. (2021). Consumer confusion, shopping fatigue, and negative purchasing behavior in internet shopping environment. The Research Journal of the Costume Culture, 29(4), 505-521. |
|
Kotler, P., & Keller, K. L. (2015). Analyzing Consumer Markets, The Buying Decision making Process: 5 stage model. In P. Kotler, & K. L. Keller, Marketing Management (pp. 194- 202). Harlow : Pearson. |
|
Kukar-Kinney, M., & Close, A. G. (2010). The determinants of consumers’ online shopping cart abandonment. Journal of the Academy of Marketing Science, 38, 240-250. |
|
Kusuma, I. G. W. A., Endayani, F., Krisnanto, A. B., & Khouroh, U. (2024). Social media marketing impact on Gen Z's brand engagement, awareness and image. Manajemen dan Bisnis (MABIS), 23(2), 480-490. |
|
Lazarus, R. S. (1984). Stress, appraisal, and coping (Vol. 464). Springer. |
|
Le, T. M. H., & Ngoc, B. M. (2024). Consumption-related social media peer communication and online shopping intention among Gen Z consumers: A moderated-serial mediation model. Computers in Human Behavior, 153, 108100. |
|
Lee, E. (2013). Impacts of social media on consumer behavior: decision making process. |
|
Lim, X. J., Radzol, A. M., Cheah, J., & Wong, M. W. (2017). The impact of social media influencers on purchase intention and the mediation effect of customer attitude. Asian journal of business research, 7(2), 19-36. |
|
Lou, C., & Yuan, S. (2019). Influencer marketing: How message value and credibility affect consumer trust of branded content on social media. Journal of interactive advertising, 19(1), 58-73. |
|
Men, L. R., & Tsai, W. H. S. (2013). Beyond liking or following: Understanding public engagement on social networking sites in China. Public Relations Review, 39(1), 13-22. |
|
Mishra, S., Malhotra, G., & Tiwari, S. R. (2021). Moderating effect of cognitive conflict on the relationship between value consciousness and online shopping cart abandonment. The International Review of Retail, Distribution and Consumer Research, 31(5), 511-530. |
|
Morgan, R. M. (1994). The commitment-trust theory of relationship marketing. Journal of Marketing. |
|
Munsch, A. (2021). Millennial and generation Z digital marketing communication and advertising effectiveness: A qualitative exploration. Journal of Global Scholars of Marketing Science, 31(1), 10-29. |
|
Naeem, M. (2021). The role of social media to generate social proof as engaged society for stockpiling behaviour of customers during Covid-19 pandemic. Qualitative Market Research: An International Journal, 24(3), 281-301. |
|
Narayanan, S. (2022). Does Generation Z value and reward corporate social responsibility practices?. Journal of Marketing Management, 38(9-10), 903-937. |
|
Nyberg, A. (2024). The impact of a sense of community on purchasing decisions: influencer marketing and organic user-generated content on TikTok. |
|
Petty, R. E., & Cacioppo, J. T. (1984). Source factors and the elaboration likelihood model of persuasion. Advances in consumer research, 11(1), 668-672. |
|
Pew Research Centre, 2024. https://www.pewresearch.org/internet/fact-sheet/mobile/ |
|
Pradhan, D., Kuanr, A., Anupurba Pahi, S., & Akram, M. S. (2023). Influencer marketing: When and why gen Z consumers avoid influencers and endorsed brands. Psychology & Marketing, 40(1), 27-47. |
|
Priporas, C. V., Stylos, N., & Fotiadis, A. K. (2017). Generation Z consumers' expectations of interactions in smart retailing: A future agenda. Computers in human behavior, 77, 374-381. |
|
Rachmad, Y. E. (2024). The Future of Influencer Marketing: Evolution of Consumer Behavior in the Digital World. PT. Sonpedia Publishing Indonesia. |
|
Rajamma, R. K., Paswan, A. K., & Hossain, M. M. (2009). Why do shoppers abandon shopping cart? Perceived waiting time, risk, and transaction inconvenience. Journal of Product & Brand Management, 18(3), 188-197. |
|
Rochanapon, P., Stankovic, M., Barber, M., Sung, B., & Lee, S. (2021). Abandonment issues: why consumers abandon online shopping carts. In Developing Digital Marketing: Relationship Perspectives (pp. 19-39). Emerald Publishing Limited. |
|
Rubin, D., Martins, C., Ilyuk, V., & Hildebrand, D. (2020). Online shopping cart abandonment: a consumer mindset perspective. Journal of Consumer Marketing, 37(5), 487-499. |
|
Russell, J. A., & Mehrabian, A. (1974). Distinguishing anger and anxiety in terms of emotional response factors. Journal of consulting and clinical psychology, 42(1), 79. |
|
Salmon, S. J., De Vet, E., Adriaanse, M. A., Fennis, B. M., Veltkamp, M., & De Ridder, D. T. (2015). Social proof in the supermarket: Promoting healthy choices under low self-control conditions. Food Quality and Preference, 45, 113-120. |
|
Sanwal, T., Avasthi, S., & Saxena, S. (2016). E-Commerce and its sway on the minds of young generation. International Journal of Scientific and Research Publications, 6(3), 112-117. |
|
Schivinski, B., & Dabrowski, D. (2016). The effect of social media communication on consumer perceptions of brands. Journal of Marketing Communications, 22(2), 189-214. |
|
Seemiller, C., & Grace, M. (2018). Generation Z: A century in the making. Routledge. |
|
Seyfi, S., Vo-Thanh, T., & Zaman, M. (2024). Hospitality in the age of Gen Z: a critical reflection on evolving customer and workforce expectations. International Journal of Contemporary Hospitality Management, 36(13), 118-134. |
|
Singh, D., Katoch, R., & Singh, P. (2022). Social media marketing and Gen Z: a study of brand attitude, self-brand connection and purchase intention. IUP Journal of Marketing Management, 21(3), 7-23. |
|
Sondhi, N. (2017). Segmenting & profiling the deflecting customer: understanding shopping cart abandonment. Procedia computer science, 122, 392-399. |
|
Statista, 2024. https://www.statista.com/statistics/477804/online-shopping-cart-abandonment-rate-worldwide/ |
|
Stephen, A. T. (2016). The role of digital and social media marketing in consumer behavior. Current opinión in Psychology, 10, 17-21. |
|
Subudhi, R., & Malhar, S. (2022). Digital Consumption Pattern and its Impact on Society: A Study on Semi-Urban Society of Odisha, India. Journal of Humanities & Social Sciences Research eISSN, 2682-9096. |
|
Sun, Y., Wang, R., Cao, D., & Lee, R. (2022). Who are social media influencers for luxury fashion consumption of the Chinese Gen Z? Categorisation and empirical examination. Journal of Fashion Marketing and Management: An International Journal, 26(4), 603-621. |
|
Tajfel, H., & Turner, J. C. (1978). Intergroup behavior. Introducing social psychology, 401(466), 149-178. |
|
Talib, Y. Y. A., & Saat, R. M. (2017). Social proof in social media shopping: An experimental design research. In SHS Web of Conferences (Vol. 34, p. 02005). EDP Sciences. |
|
Uche, S. C. (2018). Generation Z and corporate social responsibility (Master's thesis, Syracuse University). |
|
Wang, S., Cheah, J. H., & Lim, X. J. (2023). Online shopping cart abandonment: A review and research agenda. International Journal of Consumer Studies, 47(2), 453-473. |
|
Wang, S., Ye, Y., Ning, B., Cheah, J. H., & Lim, X. J. (2022). Why do some consumers still prefer in-store shopping? An exploration of online shopping cart abandonment behavior. Frontiers in Psychology, 12, 829696. |
|
Wang, Y., Mo, D. Y., & Ho, G. T. (2023, December). How Choice Fatigue Affects Consumer Decision Making in Online Shopping. In 2023 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (pp. 0128-0132). IEEE. |
|
Weismueller, J., Harrigan, P., Wang, S., & Soutar, G. N. (2020). Influencer endorsements: How advertising disclosure and source credibility affect consumer purchase intention on social media. Australasian marketing journal, 28(4), 160-170. |
|
Wong, M. C. (2021). Does corporate social responsibility affect Generation Z purchase intention in the food industry. Asian Journal of Business Ethics, 10, 391-407. |
|
Xu, Y., & Huang, J. S. (2015). Factors influencing cart abandonment in the online shopping process. Social Behavior and Personality: an international journal, 43(10), 1617-1627. |
|
Yadav, P., Jain, A., Pathak, N., & Sharma, N. (2024). Investigating the Behavior of Consumers Using Digital Payment: Comparative Study between Rural and Urban Areas. Intelligent Decision Technologies, 18(3), 2353-2370. |