Keywords

Congruence Theory, Social Network Advertising, Generation X, Generation Y, Generation Z, Generational Cohort.

Introduction

Those who use internet and smartphones are bound to use social networks for various purposes and it has become a vital part of everyone’s life. (ComScore, 2022) report indicated that 97 percent of internet users in India has used social media networks between 2021 and 2022 September and report also revealed 470 million unique visitors have visited the social media platforms during the same period. According to the same report 82.9 percentage of Indian internet users access social media through their mobile devices and it also revealed that since 2019 total time spent by the Indian social media users has been tripled. With an increased smartphones and social media usage the prominent thought which arises is that how come marketers and advertisers can seize the opportunity and attain their business interest which can be plausible by understanding the consumers attitudes across different generations in social media. Advancement in the field of marketing and advertising has created a revelation in getting the attention of consumer in the form of traditional advertising and new advertising media. In spite of this difference in getting the attention of the consumers; the core value of the advertisement remains unchanged which is to make the advertisement to create awareness and make the consumer to want the product (Cano, 1994). Advancement in internet technology has created more opportunity to engage with more consumers (Mir et al., 2015). Social networking sites (SNS) can be defined as “web-based services that allow individuals to construct a public or semi-public profile within a bounded system, articulate a list of other users with whom they share a connection, and view and traverse their list of connections and those made by others within the system” (Ellison 2007). thus, the social network has become a great tool for the marketing companies to reach consumers at a low cost (Brown et al. 2007). In the present scenario consumer themselves getting exposed to the product through social networks such as Facebook, Instagram, Twitter and Instagram, which enables the advertisers to enhance their e-reputation by forging partnership with social network influencers and brand ambassadors to promote their product or service (Santana et al., 2019).

Prior studies have been conducted in this domain has focused primarily on mobile advertisements and their mechanisms such as creative elements, personalization, interaction and engagement and similar studies have also been done on the basis of gender differences (Grewal et al., 2016; Ha et al., 2014; Ho et al., (2020); Li et al., (2021); Lin & Bautista, 2018). However, there have been some studies which has been done in the area of smartphone usage and its influence on consumer behavioural practices (Priporas et al., 2017). (Van der Goot et al., 2018); Xie et al., (2004) investigated a study on difference in advertising attitudes and avoidance of media channels such as social media, television, mobile phones, newspapers and websites based on a cross sectional study in six countries (Germany, Spain, United Kingdom, United States, France, and the Netherlands) using dimension such as informativeness, entertainment, trustworthiness, intrusiveness, and irritation to measure the generational differences in advertising attitude and avoidance. Smith, (2019) explored the attitude and preference of digital natives towards mobile advertising content, style, functionality and personalisation. A literature gap exists in the usage of social media networks and their influence on consumer perception and attitudes based on generational cohorts in the Indian context. Thus, this study aims to examine intergenerational attitudinal differences towards social media advertising.

Research Background and Hypothesis formation

According to congruency theory (Osgood & Tannenbaum, 1955: 43) “changes in evaluation are always in the direction of increased congruity with the existing frame of reference”; this theory will help us to understand the intergenerational perception and social network advertising. Although People experience of information in the form advertisement happens because of the predetermined patterned relevancy or congruency of information but the role of existing schema to interpret the information can also never be overlooked (Misra & Beatty, 1990). To build positive attitude and draw the attention of consumer towards a commercial products brand, companies must better avoid incongruent disgust appeal (Dens et al., 2008). According to Ryder (1985) individuals who are born around the same period of time and experienced a typical socio cultural and economic environment can be considered as generational cohort; the people who are born in same period of time tend possess a similar attitude towards their worldview. Since the same generational people experienced a similar events and experience during the formative years of adolescence and socialisation they can be characterised as generation (Strauss & Howe, 1991). Each generations possess a particular belief, value systems, expectation and exhibits unique behaviour which can be characterised by the influence of undergoing similar social and economic events and also influenced by popular cultures, peer and parents (Fortunati et al., 2019). The differences of adoption of mobile technology and attitude between the generation cohorts of millennials and Gen Z has been revealed by(Dimock, 2019). The division suggested can be used as a base for studying the intergenerational attitudinal differences between Gen X (digital immigrants) (Prensky, 2005), Gen Y -digital natives (Jones et al., 2010);and Gen Z - mobile natives (Chaney et al., 2017; Ozkan & Solmaz, 2015) towards social networks advertisement. According to Roth-Cohen O et al., (2022) generational incongruency exists among the generation in response to mobile advertisement but Gen X, Gen Y and Gen Z all reacted similar in terms of negative reaction towards mobile advertisement.

Congruency and Ease of Use

Consumers' perceived ease of use of technology plays a vital role in adopting new technology (Davis 1989; Davis et al. 1989). According to Selamat et al., (2009), technologies perceived as complex experience slower rates of adoption and acceptance by consumers. Thus, social media websites that require low cognitive effort, are easy to understand, and have simple navigation controls are perceived to foster favorable attitudes towards the website and encourage purchasing (Childers et al., 2001). Consequently, social network advertisements that require low cognitive effort, leading to easy understanding, processing, and clear information provision, engender positive attitudes towards social media ads. Hence, we posit that

H₁: Perceived ease of use has a positive influence on Gen X,Y,Z attitudes toward social network advertising.

Congruency and Perceived Usefulness

According to Merisavo et al., (2007), the primary factor driving acceptance toward mobile advertising is perceived usefulness and the utilization of contextual information within a mobile advertisement. Calder et al., (2009) assert that when consumers have a positive utilitarian experience with a website, it enhances their engagement because they believe the site offers information to assist them in making important decisions and achieving goals in their lives (322). Bauer et al. (2008) also acknowledge that consumer attitudes toward mobile advertising are influenced by the informational value provided by advertisements. Furthermore, advertisements that offer useful information to consumers are more likely to be accepted. Therefore, we hypothesize that.

H₂: Perceived usefulness has a positive influence on Gen X, Y, Z consumers’ attitudes toward social network advertising.

Congruency and Advertisement Intrusiveness

According to Brehm (1989), the Theory of Psychological Reactance states that people's reactions are heavily influenced by their perceived threat to their individual freedom. Li et al., (2002) assert that advertisement intrusiveness is "a psychological reaction to ads that interfere with consumers' ongoing cognitive processes". McCoy et al., (2007) revealed that consumer irritation with online advertisements is influenced by the intrusiveness of the advertisement. Bond (2010) identified that social network advertisements unfavorably intervene with users' online activities, raising concerns among social network users about the inappropriate use of their personal information. According to Rettie (2001), when online advertisements such as banners and pop-ups disrupt people's online activities, it creates a negative attitude toward ads. Thus, we posit that. According to Youn & Kim (2019), Gen-Y and Z perceive that the interference of online push advertisements in their online activities can be equated with interference in their online freedom of action.

H₃: Advertisement Intrusiveness has a negative influence among Gen X, Y, Z consumers’ attitudes toward social network advertising.

Congruency and Incentive Offering

According to Ho and Thuy (2022) advertisers’ adoption of offering incentives in web-based advertising have found to be influencing the consumers attitude towards advertisement. After consumer exposure the incentive stimuli, it attracts more consumer towards the company websites which offer incentives (Donthu et al., 2004). Robinson et al., (2007) identified that advertisement which offers incentives generates more clicks on the advertisement than the advertisements which don’t provide any incentive. Hence, we posit that:

H₄: Incentive offering has a positive influence on Gen X, Y, Z consumers’ attitudes toward social network advertising.

Methods and Measurements

Procedure

The present study was conducted at the end of 2023 using an internet survey method among a sample of respondents aged between 17 and 50 who actively used social media networks via smartphones and computers. A quantitative research methodology was adopted to efficiently gather and analyze data. The study used a structured questionnaire to gather the data regarding the attitudes towards social media networks based on the questionnaire adopted by (Luna-Nevarez & Torres, 2015). The questionnaire was divided into two parts: the initial section aimed to capture demographic information about the respondents, while the second section focused on the research constructs. This section consisted of 37 questions designed to measure attitudes towards advertisements. Additionally, it included questions aimed at gathering the respondents' socio-demographic profiles and their habits regarding social network usage. The questionnaire items which aimed to measure following dimensions were adopted from: perceived usefulness (Davis 1989), incentive offering (Luna-Nevarez & Torres,2015), perceived ease of use (Davis 1989), advertisement intrusiveness (Li et al. 2002) and attitude towards social network advertising (Olney et al.,1991). All the five dimensions was measured by adopting five-point Likert scale questions; 1 being strongly disagree to 5 being strongly agree. The study employed convenience sampling, a non-probability technique, to select participants. Questionnaires were distributed electronically via email and various social media platforms to enhance the data collection process. Incomplete or partially filled questionnaires were excluded from the analysis to maintain data integrity and ensure result validity.

Data Analysis and Interpretation

The Table 1 Model Summary for Generation X (Gen X) indicates that the regression model explains approximately 44.7% of the variance in attitudes toward social network advertising. The Adjusted R Square, which considers model complexity, is 43.2%. The Standard Error of the Estimate, reflecting the accuracy of predictions, is 0.605.

Table 1 Model Summary for Gen X (Dependent Variable X)
Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.668a	.447	.432	.605

In the ANOVA Table 2 for Gen X, the F-statistic of 30.899 with a p-value of 0.000 suggests overall statistical significance for the model, indicating that at least one predictor significantly contributes to explaining the variance in Gen X attitudes.

Table 2 Anova for Gen X
ANOVAa
Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	45.265	4	11.316	30.899	.000b
	Residual	56.033	153	.366
	Total	101.297	157

Examining the Coefficients Table 3 for Gen X, perceived usefulness is a statistically significant positive predictor (p-value = 0.000), indicating a positive influence on Gen X attitudes. Incentive offering is also a significant positive predictor (p-value = 0.000). However, perceived ease of use and advertisement intrusiveness do not significantly impact Gen X attitudes Table 4.

Table 3 Coefficients for Gen X
Coefficientsa
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant)	.693	.361		1.919	.057
	Ease of Use	.003	.068	.003	.040	.968
	Perceived Usefulness	.406	.081	.364	4.995	.000
	Advertisement Intrusiveness	.072	.076	.074	.948	.345
	Incentive Offering	.358	.067	.391	5.334	.000

Table 4 Model Summary for Gen Y (Dependent Variable Y)
Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.478a	.229	.209	.732

The Model Summary for Generation Y (Gen Y) indicates that the regression model explains around 22.9% of the variance in attitudes toward social network advertising, with an Adjusted R Square of 20.9%. The Standard Error of the Estimate is 0.732.

The ANOVA Table 5 for Gen Y shows statistical significance (F-statistic = 11.353, p-value = 0.000) for the overall model, suggesting the presence of at least one significant predictor.

Table 5 Anova for Gen Y
ANOVAa
Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	24.344	4	6.086	11.353	.000b
	Residual	82.017	153	.536
	Total	106.361	157

In the Coefficients Table 6 for Gen Y, perceived usefulness is a statistically significant positive predictor (p-value = 0.000), indicating a positive influence on Gen Y attitudes. Incentive offering is also a significant positive predictor (p-value = 0.012). However, perceived ease of use, advertisement intrusiveness, and the intercept are not statistically significant predictors for Gen Y attitude.

Table 6 Coefficients for Gen Y
Coefficientsa
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant)	1.729	.437		3.957	.000
	Ease of Use	.409	.083	.389	4.932	.000
	Perceived Usefulness	.016	.098	.014	.158	.875
	Advertisement Intrusiveness	-.038	.092	-.039	-.418	.677
	Incentive Offering	.206	.081	.220	2.542	.012

The Model Summary for Generation Z (Gen Z) Table 7 shows that the regression model explains approximately 33.6% of the variance in attitudes toward social network advertising, with an Adjusted R Square of 31.9%. The Standard Error of the Estimate is 0.743.

Table 7 Model Summary for Gen Z (Dependent Variable Z)
Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.580a	.336	.319	.743

The ANOVA Table 8 for Gen Z indicates statistical significance (F-statistic = 19.369, p-value = 0.000) for the overall model, suggesting the presence of at least one significant predictor.

Table 8 Anova for Gen Z
ANOVAa
Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	42.792	4	10.698	19.369	.000b
	Residual	84.505	153	.552
	Total	127.297	157

In the Coefficients Table 9 for Gen Z, perceived usefulness is a statistically significant positive predictor (p-value = 0.001), indicating a positive influence on Gen Z attitudes. Incentive offering is also a significant positive predictor (p-value = 0.018). However, perceived ease of use and advertisement intrusiveness do not show statistically significant effects on Gen Z attitudes. These results provide detailed insights into the influence of different factors on the attitudes toward social network advertising for each generation.

Table 9 Coefficients for Gen Z
Coefficients a
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant)	.431	.444		.972	.333
	Ease of Use	.211	.084	.184	2.514	.013
	Perceived Usefulness	.355	.100	.284	3.554	.001
	Advertisement Intrusiveness	.133	.093	.123	1.430	.155
	Incentive Offering	.197	.082	.192	2.396	.018

Conclusion

In conclusion, the analysis of the hypotheses concerning the influence of various factors on attitudes toward social network advertising across Generation X (Gen X), Generation Y (Gen Y), and Generation Z (Gen Z) yields valuable insights into consumer behavior within different generational cohorts. For Generation X, the regression model elucidates a substantial portion (44.7%) of the variance in attitudes toward social network advertising. However, contrary to Hypothesis 1 (H1), perceived ease of use does not significantly influence Gen X attitudes. Conversely, supporting Hypotheses 2 (H2) and 4 (H4), perceived usefulness and incentive offering positively impact Gen X attitudes. Notably, Hypothesis 3 (H3) regarding advertisement intrusiveness is not supported among Gen X consumers. Similarly, the model for Generation Y explains approximately 22.9% of the variance, with perceived usefulness and incentive offering positively influencing attitudes, as predicted by H2 and H4. However, ease of use, advertisement intrusiveness, and the intercept do not significantly predict Gen Y attitudes toward social network advertising. For Generation Z, the model accounts for about 33.6% of the variance, supporting H2 and H4. Perceived usefulness and incentive offering emerge as positive and significant predictors of Gen Z attitudes. Nevertheless, perceived ease of use and advertisement intrusiveness do not significantly impact Gen Z attitudes toward social network advertising. In summary, perceived usefulness and incentive offering consistently emerge as positive predictors across all three generations, while the effects of perceived ease of use and advertisement intrusiveness vary. These findings underscore the importance of tailored strategies for social network advertising based on the distinct preferences of different generational cohorts. By understanding the nuanced dynamics at play within each generation, marketers can refine their approaches to effectively engage with target audiences and cultivate positive attitudes toward social network advertising. This nuanced understanding of generational preferences can inform strategic decision-making and enhance the efficacy of advertising campaigns in an ever-evolving digital landscape.

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Received: 02-Mar-2026, Manuscript No. AMSJ-26-16996; Editor assigned: 03-Mar-2026, PreQC No. AMSJ-26-16996(PQ); Reviewed: 10-Mar-2026, QC No. AMSJ-26-16996; Revised: 17-Mar-2026, Manuscript No. AMSJ-26-16996(R); Published: 24-Mar-2026