QUBAHAN ACADEMIC JOURNAL

VOL. 4, NO. 2, April 2024

https://doi.org/10.48161/qaj.v4n2a514

Beyond Likes and Shares: Unveiling the Sequential Mediation of

Brand Equity, Loyalty, Image, and Awareness in Social Media
Marketing's Influence on Repurchase Intentions for High-Tech
Products
K Laveen Kumar 1 and S Anjani Devi 2*

1 GITAM School of Business GITAM (Deemed to be University), Visakhapatnam 530045, Andhra Pradesh, India.
2 GITAM School of Business, GITAM (Deemed to be University), Visakhapatnam 530045, Andhra Pradesh, India.
Corresponding author: Email: asureddy@gitam.edu *

ABSTRACT: The purpose of the study is to investigate the impact of social media marketing
activities (SMMA) on repurchase intention (RPI) with the mediating role of brand equity
(BE), Brand loyalty (BL), Brand image (BI), and Brand awareness (BA) on high-tech products.
This study utilized a purposive sampling technique. The data collection process through a
structured questionnaire technique from 385 consumers. The descriptive data analysis
through SPSS and hypothesis testing through SMART PLS (3.330). The results demonstrate
that SMMA positively influences RPI. Additionally, BL, BA, and BI positively mediate the
relationship between the SMMA and RPI. Finally, BE negatively mediates the relationship
between SMMA and RPI. In theory, it enhances our comprehension of the mechanisms by
which SMM impacts consumer behaviour, illuminating the intermediate functions of brand-
related notions. In essence, the results provide useful information for marketers who want to
use social media platforms efficiently to increase the likelihood of customers buying high-
tech products again.

Keywords: Social media marketing activities, brand image, brand loyalty, brand awareness,
brand equity, High-tech products, Repurchase intention.

I. INTRODUCTION
High-tech companies, known for their fast-paced innovation and intense competition, are increasingly
utilizing SMM as a strategic tool to engage with technologically savvy consumers, boost brand exposure, and
encourage repeat purchases[1]. Gaining a comprehensive understanding of the complex processes by which
SMM impacts consumer likelihood to repurchase high-tech products is crucial for companies seeking to stay
ahead in the digital era[2]. Social media platforms like Facebook, Instagram, Twitter, and YouTube, have
become influential avenues for high-tech firms to interact with consumers, share product information, get
feedback, and cultivate brand communities[3]. By creating specific and tailored content, running interactive
campaigns, collaborating with influencers, and engaging in real-time interactions, brands may develop
significant connections with technology enthusiasts, promoting a strong sense of loyalty and advocacy[4].
Over the past few years, the marketing industry has experienced a significant change, mostly driven by the
introduction and widespread use of social media platforms[5]. These platforms have become crucial spaces for
brands to interact with their fans, spread messages, and cultivate connections. One of the most interesting
aspects to research in the digital revolution is the impact of social media marketing on consumer behaviour,
specifically in terms of repurchase intention[6]. Understanding the relationship between social media
marketing and consumer repurchase intention is crucial in the high-tech industry, where innovation and quick

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technical improvements are prevalent[7]. Advanced technological products, including smartphones, laptops,
wearable devices, and smart home appliances, make up a substantial part of consumer expenditure and face
fierce competition.
This study seeks to investigate the complex correlation between social media marketing efforts and the
intention of customers to make repeat purchases, particularly in the field of high-tech products[8]. This area is
characterized by rapidly changing consumer behaviour that is influenced by multiple factors. This study
distinguishes itself by examining the various ways in which brand equity, brand loyalty, brand image, and
brand awareness influence this relationship[9]. Although previous studies have extensively investigated the
influence of social media marketing on consumer behaviour, there is a lack of research that has thoroughly
explored the specific ways in which this influence happens, particularly about high-tech products. This study
offers a complete analysis of the impact of social media marketing activities on repurchase intention in a specific
product category, taking into account potential mediators such as brand equity, brand loyalty, brand image,
and brand awareness.
Additionally, the study fills a gap [6,10–12]in the existing body of research by specifically examining high-
tech products, which frequently exhibit distinct attributes and consumer perspectives in contrast to
conventional consumer goods. This specialized investigation not only adds to theoretical progress in marketing
research but also provides practical knowledge for marketers working in the high-tech industry, allowing them
to customize their social media strategies in a way that efficiently improves repurchase intention. This study
intends to examine the complex relationship between social media marketing activities and repurchase
intention. It also investigates the role of key variables such as brand equity, brand loyalty, brand image, and
brand awareness in mediating this relationship. Our goal is to understand the fundamental processes by which
social media initiatives impact customer behaviour in the field of high-tech products.
This study aims to contribute to the theoretical knowledge of consumer behaviour and marketing dynamics
while providing practical insights for marketers and practitioners in the high-tech industry to optimize their
social media strategies. Amidst the fast-paced changes in the digital world, it is crucial to have a sophisticated
comprehension of the interplay between customer preferences and technology advancements. This
understanding is necessary to achieve long-term success and stay ahead of the competition. This study is
structured as follows. The first section contains an introduction to the study. the second section contains a
literature review of variables. The third section contains methodology and research design. The fourth section
demonstrates the data analysis. the fifth section includes results and discussion. The final section concludes
with conclusion, implications, limitation and future direction.

II. LITERATURE REVIEW

Small and medium-sized IT/ITEs businesses (SMEs) around the world, In this study, [13,14]provided
evidence of the effectiveness of luxury brands' social media marketing (SMM) in terms of enhancing customer
connections and buying intent. They also proposed a methodology for enhancing brand performance by
identifying the crucial factors that influence these outcomes. The results indicated that the social media
marketing (SMM) of the chosen brand possesses distinct elements in comparison to the outcomes of traditional
marketing. Each component of a luxury brand's social media marketing (SMM) had a favourable effect on
consumer relationships and purchase intention. However, entertainment had the most significant influence
among all the parts. [15,16]focused their research on brand pages on Facebook, which is the most widely used
social media platform for brands. A digital quantitative survey was carried out with individuals who have
liked the pages of well-known brands on Facebook. The results indicated that user engagement had a
significant, positive, and immediate effect on brand recognition. User engagement has a major impact on brand
attitude, although this relationship is influenced by brand awareness.
In their study, [17,18]examined the components of SMMA and their influence on BE, specifically in terms
of BA, BL, and BI. The study focused on Malaysian consumers of portable technology devices. The study's
findings indicated that (TRE), (CUS), and Electronic Word-of-Mouth (EWOM) had substantial and
advantageous impacts on Brand Building Activities (BBA) and Brand Building Investments (BBI). The variable
INT was shown to have no statistically significant impact on BBA and BBI. In addition, BBI and BBA facilitated
the interactions between SMMA components and WPP. Their study, [19]examined the relationship between
SMM and BI, the relationship between SMM and PI, the relationship between BI and PI, and the relationship

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between Social Media Marketing and Purchase Intention mediated by Brand Image. The study established a
distinct correlation between Brand Image (BRI) and Purchase Intention (PI).

1. BRAND EQUITY
In 1993, [20–23] Keller and Jones introduced a conceptual framework that explains brand equity from the
viewpoint of individual consumers. Customer-based brand equity refers to the difference in how brand
awareness affects consumer responses to a brand's marketing efforts. In addition to addressing several subjects
about the development, monitoring, and upkeep of customer-based brand equity, the paper also highlighted
potential areas that warrant additional examination. In their study, [21] examined how brand equity, brand
attachment, product involvement, and repurchase intention influence brand choices and participation in
activities of bicycle consumers. Researchers conducted a study in the northern parts of Taiwan, specifically
focusing on individuals who engaged in recreational cycling in designated bike lanes. The study found that
brand equity had a favourable impact on brand attachment, repurchase intention, and product participation.
Furthermore, product participation has a positive influence on brand attachment, repurchase intention, and
indirect brand attachment. It has an indirect impact on the probability of repurchasing products through the
influence of brand loyalty and product participation.

2. SMMA ON RPI
Current research emphasizes the substantial impact of SMM efforts on the likelihood of customers making
repeat purchases RPI in several sectors. Research has demonstrated that actively interacting with consumers
on social media platforms such as Facebook, Instagram, and Twitter has a positive effect on the Return on
Investment (RPI) by promoting customer loyalty, increasing brand recognition, and influencing how
consumers perceive the company. Furthermore, social media marketing (SMM) facilitates customized
communication and interactive involvement, resulting in more profound emotional bonds between companies
and customers, ultimately stimulating recurring sales [25]. Moreover, the contagious quality of social media
intensifies verbal endorsements and material created by users, hence enhancing RPI. Additionally, research
highlights the significance of content excellence, pertinence, and genuineness in social media marketing
endeavours to uphold consumer confidence and allegiance in the long run [26]. In summary, the increasing
amount of research highlights the crucial impact of social media marketing (SMM) on consumer purchase
intention (RPI). It emphasizes the importance for businesses to create thorough social media strategies to
successfully interact with consumers and encourage them to make repeat purchases in today's interconnected
digital market.
H1: SMMA has a positively related to RPI

3. SMMA ON BE, BI, BA AND BL

Multiple studies have investigated the correlation between social media marketing (SMM) activities and
brand equity, emphasizing the substantial influence of digital platforms on brand perception and the
generation of value. A study conducted by Aaker and [27,28] indicates that brand equity is composed of
multiple characteristics, including brand awareness, brand associations, perceived quality, and brand loyalty.
Social media marketing (SMM) activities are essential for improving brand communication, engagement, and
relationship-building with consumers [29]. Furthermore, research conducted by [30] highlights the significance
of social media marketing (SMM) in influencing brand image and brand personality, both of which are essential
elements of brand equity. Social media marketing (SMM) platforms offer brands the chance to strengthen
positive connections, enhance brand visibility, and distinguish themselves from rivals by utilizing user-
generated content, viral marketing campaigns, and interactive communication [31]. In summary, the literature
indicates that effectively using social media marketing (SMM) can boost brand equity through the
reinforcement of brand-consumer connections, promotion of brand loyalty, and overall increase in brand value
in the digital age.
Social media marketing is widely recognized as an effective way of developing relationships with
consumers [25]. In addition, these interactions will foster trust and alleviate any hesitations that may deter
customers from engaging with the brand [28], as well as facilitate online transactions [30]. Consumers view
social media as reliable sources of information, and their trustworthiness is beneficial for marketing strategies.

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[2,31] provided evidence in their study that social media marketing characteristics have a beneficial impact on
brand trust. Companies are leveraging the social media platform to effectively connect, interact, and engage
with customers. This enables them to provide value and experiences, ultimately improving customers'
behavioural responses towards the brand. Consumers' impressions of Internet marketing efforts can improve
their responses.
H2: SMMA negatively relates to BE
H3: SMMA positively relates to BL
H4: SMMA positively relates to BA
H5: SMMA positively relates to BI

4. BE ON RPI
The correlation between brand equity and repurchase intention has been thoroughly examined in marketing
literature, highlighting the significance of comprehending how consumers' opinions of a brand impact their
probability of making a repeat purchase. Brand equity refers to the worth and influence that a brand holds in
the perceptions of consumers. It incorporates multiple aspects including brand awareness, brand loyalty,
perceived quality, and brand associations. Multiple studies consistently show a direct correlation between
brand equity and the likelihood of customers repurchasing a product or service. Greater brand equity fosters
trust, loyalty, and perceived value among consumers, resulting in higher inclinations to repurchase. Research
has demonstrated that a robust brand reputation not only encourages customers to make repeat purchases but
also provides a defence against competitive forces and customer sensitivity to price changes. Furthermore,
brand equity functions as a means of gaining a competitive edge, allowing companies to charge higher prices
and retain their market position. By implementing successful branding tactics, organizations can develop a
high brand value, which subsequently enhances the likelihood of repeat purchases and adds to sustained
corporate prosperity [32,33]. In summary, the research emphasizes the crucial impact of brand equity on
customers' likelihood to repurchase and emphasizes the significance of investing in the development and
maintenance of strong brands.
H6: BE negatively mediates the relationship between SMMA and RPI.
H7: BI Positively mediates the relationship between SMMA and RPI.
H8: BA Positively mediates the relationship between SMMA and RPI.
H9: BL Positively mediates the relationship between SMMA and RPI.
Based on the rigorous literature the conceptual framework was developed.

FIGURE 1. Conceptual framework

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III. MATERIAL AND METHOD

1. CONTEXT
High-tech products are typically intricate, with features that may not be immediately comprehensible to
consumers. Social media offers a medium for companies to enlighten consumers on the characteristics,
capabilities, and advantages of these products [1]. This contributes to the reduction of information asymmetry
and the enhancement of consumer confidence in their purchasing decisions. Social media enables
uninterrupted interaction with users, which is vital for high-tech items that frequently necessitate continuing
assistance, upgrades, and problem-solving. Companies may cultivate a feeling of community among users,
offer immediate help, [34] and collect input for product enhancement by actively engaging on social networking
sites. Creating a unique brand identity is crucial in highly competitive marketplaces where many other
companies offer identical items [35,36]. Social media marketing allows organizations to highlight the distinctive
characteristics and value propositions of their advanced products, aiding in setting them apart from rivals and
establishing brand value.

2. DATA COLLECTION AND SAMPLING TECHNIQUE

The data collection process started with 2 parts. The first part includes pre-testing through 10 interviews
with customers. The pilot study was done through 50 samples. Here all value items were significant. The
second part starts with the data collection process through structured questionnaires distributed to customers.
Finally, we get 420 samples. The geographical area of responses from Andhra Pradesh. The data collection
period is 06-08-2023 to 06-03-2024. Finally, we removed late responses and missing information. Finally, the
sampling of the study is 385. This study utilized the “non-probability sampling technique” especially this study
concentrated on the “purposive sampling method”. We have checked the “non-response bias test as well as
common method bias test” " The CMV value is 38.42 which is less than the threshold value of 50%. This study
has no variances.

3. MEASURES
Social media marketing activities scale was adopted from [35] . the repurchase intention scale was adopted
from[37,38]. The brand equity scale was adopted from [20,22,39]. The brand loyalty, Brand image, brand
awareness scale was adopted from[19,36,40] . this study utilized five point lickert scale (1= strongly disagree 5=
strongly agree).

4. DEMOGRAPHIC PROFILE OF RESPONDENTS

The table 1 provides demographic and social media usage statistics. Regarding gender, the male population
accounts for 63.11% while the female population accounts for 36.89%. The age distribution has a very even
distribution across different age groups, with the highest proportion (27.27%) lying within the 29-38 age
bracket, and the lowest proportion (4.15%) in the group aged 59 and above. In terms of occupation, students
constitute the highest proportion (26.75%), followed closely by the employed (29.61%) and then the
unemployed (25.71%). Notably, YouTube (44.15%) and Instagram (40%) are the dominant platforms for social
media consumption, suggesting a strong inclination towards visual and video-oriented material. LinkedIn,
Facebook, and Twitter have somewhat lower utilization rates. In summary, the data indicates that there is a
wide range of people from different backgrounds and professions who are actively using social media
platforms, notably YouTube and Instagram. This information is vital to consider when developing focused
marketing or outreach initiatives.

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Table 1. Demographic profile(sample=385)

Particulars Frequency Percentage

Gender

Male 243 63.11

Female 142 36.89

Age

18-28 102 26.49

29-38 105 27.27

39-48 87 22.59

49-58 75 19.48

above 59 16 4.15

Occupation

employed 114 29.61

unemployed 99 25.71

students 103 26.75

housewife 69 17.93

Social media site

Instagram 154 40

youtube 170 44.15

LinkedIn 35 9.09

Facebook 20 5.19

Twitter 6 1.56

IV. DATA ANALYSIS

1. ASSESSMENT OF MEASUREMENT MODEL

The table provides loadings, reliability coefficients, and validity indices for various variables in a
measurement model [41,42]. Loadings indicate the level of correlation between each variable and its underlying
construct. Significant loadings (0.70) suggest robust connections. Reliability coefficients, such as Cronbach's

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alpha (CA), rho-A, and composite reliability (CR), are used to evaluate the internal consistency of the constructs.
Values that exceed 0.70 indicate a higher level of reliability. The Average Variance Extracted (AVE) measures
the extent to which the construct captures variance compared to measurement error. Higher AVE values,
usually above 0.5, are indicative of strong convergent validity. VIF is a useful tool for evaluating
multicollinearity between variables. Typically, VIF values that are below 5 are considered acceptable. Many
variables show significant loadings, suggesting a strong connection to their corresponding constructs. The
reliability coefficients and AVE values indicate strong internal consistency and convergent validity.
Nevertheless, certain variables exhibit elevated VIF values[43], indicating the presence of potential
multicollinearity concerns that may require attention. In general, the model seems to possess robust
psychometric properties, although additional analysis may be necessary to address concerns related to
multicollinearity.

Table 2. Composite reliability

Variable Item loadings CA rho-A CR AVE VIF

SMMA SMMA1 0.799 0.932 0.933 0.943 0.622 2.816

SMMA10 0.744 2.360

SMMA2 0.813 3.004

SMMA3 0.753 2.583

SMMA4 0.806 2.854

SMMA5 0.767 2.425

SMMA6 0.791 2.354

SMMA7 0.820 2.795

SMMA8 0.784 2.588

SMMA9 0.804 3.154

BA BA1 0.818 0.797 0.801 0.880 0.710 1.676

BA2 0.868 1.992

BA3 0.842 1.605

BE BE1 0.867 0.837 0.839 0.902 0.754 1.994

BE2 0.894 2.238

BE3 0.844 1.794

BI BI1 0.699 0.797 0.790 0.833 0.626 1.123

BI2 0.807 2.195

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BI3 0.859 2.329

BL BL1 0.859 0.858 0.866 0.913 0.779 2.082

BL2 0.866 2.054

BL3 0.922 2.723

RPI RPI1 0.860 0.884 0.885 0.915 0.684 2.693

RPI2 0.826 2.202

RPI3 0.833 2.338

RPI4 0.809 1.977

RPI5 0.805 1.966

Source : authors own creation from smart pls

1. 1 Former larcker criterion

The table3 presents the correlation matrix that depicts the relationships between the variables. By comparing
the square root of AVE (Average Variance Extracted) with the correlations between constructs, the Fornell-
Larcker criterion examines the discriminant validity of a proposition [44]. According to [45] the criterion, the
square root of the average variance extracted (AVE) for each construct ought to be higher than the correlations
that correlations have with other constructs. This particular instance demonstrates that the discriminant
validity is good because all of the diagonal components (square roots of AVE) are higher than the equivalent
off-diagonal elements (correlations between constructs). This illustrates that each construct is distinct from the
others, which lends credence to the validity of the model for further investigation.

Table 3. Former larcker criterion

Variables BA BE BI BL RPI SMMA

BA 0.843

BE 0.443 0.869

BI 0.760 0.595 0.791

BL 0.481 0.809 0.645 0.883

RPI 0.334 0.509 0.750 0.583 0.827

SMMA 0.534 0.786 0.618 0.780 0.605 0.788

Source : authors own creation from smart pls

1.2 HTMT criterion

By comparing the correlations across constructs to the correlations within constructs, the HTMT ratio, also
known as the Heterotrait-monotrait ratio [45], is used to evaluate the discriminant validity of some constructs.
To get a level of discriminant validity that is satisfactory, the HTMT values should be lower than 0.85. All of

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the HTMT values in this instance are lower than 0.85, which indicates that the discriminant validity is
satisfactory. The greatest possible HTMT value is 0.799, which falls somewhere in the middle of the BL and BI
constructions. This indicates that although there is a correlation between BL and BI, it is not so strong that it
would cause one to be concerned about the discriminant validity of the relationship between the two. In light
of this, the model exhibits sufficient discriminant validity, which provides evidence for the distinctiveness of
each component for further investigation.
Table 4. HTMT Criterion

Variables BA BE BI BL RPI SMMA

BA

BE 0.538

BI 0.033 0.752

BL 0.575 0.364 0.799

RPI 0.489 0.594 0.655 0.666

SMMA 0.609 0.488 0.241 0.369 0.664

Source : authors own creation from smart pls

2. ASSESSMENT OF STRUCTURAL MODEL

The results of the hypothesis testing demonstrate the robustness and statistical significance of the
relationships between variables in the model. Every hypothesis examines a distinct correlation between
predictor and result variables, where the beta coefficient quantifies the strength of the impact. The hypothesis
(BA -> RPI) is confirmed, revealing a substantial positive correlation between BA and RPI. An increase of one
unit in BA is correlated with a 0.610 standard deviation increase in RPI, with a p-value of 0.000, indicating high
statistical significance. The hypothesis that BE is causally related to RPI is rejected, suggesting that there is no
statistically significant association between BE and RPI. The beta coefficient has a negative value of -0.072,
indicating a negative relationship between the variables. However, the p-value of 0.267 is higher than the
commonly accepted threshold of significance of 0.05. The hypothesis (BI -> RPI) is confirmed, suggesting a
substantial and favourable correlation between BI and RPI. Increasing the BI by one unit is linked to a 0.156
standard deviation increase in RPI, with a p-value of 0.034. The hypothesis (BL -> RPI) is confirmed, revealing
a statistically significant and positive correlation between BL and RPI. An increase of one unit in BL is linked
to a 0.154 standard deviation increase in RPI, with a p-value of 0.038. The acronym SMMA stands for Business
Administration, Business Economics, Business Intelligence, Business Law, and Retail and Product Innovation.
All assumptions are confirmed, indicating substantial positive correlations between SMMA and BA, BE, BI, BL,
and RPI. The beta coefficients vary from 0.534 to 0.786, suggesting significant impacts, with all p-values at 0.000,
indicating strong statistical significance. The findings indicate that although BE does not have a significant
impact on RPI, all other predictors (BA, BI, BL, and SMMA) have statistically significant associations with RPI.
Furthermore, the Social Media Marketing Agency (SMMA) has substantial correlations with all the other
variables (Business Administration, Business Economics, Business Intelligence, Business Law, and Retail Price
Index) in the model.

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Table 5. Hypothesis testing

Path
Hypothesis coefficient SD T value P Values Decision

BA -> RPI 0.610 0.061 10.045 0.000 Accepted

BE -> RPI -0.072 0.065 1.112 0.267 Rejected

BI -> RPI 0.156 0.073 2.129 0.034 Accepted

BL -> RPI 0.154 0.074 2.086 0.038 Accepted

SMMA -> BA 0.534 0.050 10.704 0.000 Accepted

SMMA -> BE 0.786 0.033 24.023 0.000 Accepted

SMMA -> BI 0.618 0.043 14.316 0.000 Accepted

SMMA -> BL 0.780 0.035 22.461 0.000 Accepted

SMMA -> RPI 0.605 0.046 13.014 0.000 Accepted

Source : authors own creation from smart pls

2.1 Mediation Analysis

The mediation study examines whether the association between the independent variable (SMMA) and the
outcome variable (RPI) is influenced by the mediator variables (BA, BE, BI, and BL). Here is the analysis of the
findings. The direct impact of SMMA on RPI is statistically significant (beta = 0.326, p < 0.001), demonstrating
that SMMA has a favourable influence on RPI. The indirect impact of SMMA on RPI through BA is also
substantial, as demonstrated by the considerable overall impact (which includes both direct and indirect
impacts) of SMMA on RPI. These findings indicate that BA plays a role in the link between SMMA and RPI,
but only to a certain extent. The confidence interval for the indirect impact (0.239 to 0.395) excludes the value
of zero, providing additional evidence of the statistical significance of the mediation effect. The direct influence
of SMMA on RPI, as indicated by the beta coefficient of -0.057 and p-value of 0.269, is not statistically significant.
This suggests that SMMA does not have a direct effect on RPI when it is mediated by BE. The little indirect
effect implies that BE does not serve as a mediator in the interaction between SMMA and RPI. The direct impact
of SMMA on RPI is statistically significant (beta = 0.096, p = 0.033), suggesting that SMMA has a favourable
influence on RPI. The substantial indirect effect indicates that BI serves as a partial mediator in the association
between SMMA and RPI. The direct impact of SMMA on RPI is statistically significant (beta = 0.121, p = 0.039),
indicating a favorable influence of SMMA on RPI. The notable indirect effect suggests that BL serves as a partial
mediator in the association between SMMA and RPI. BA, BI, and BL serve as partial mediators in the link
between SMMA and RPI, however, BE does not play a significant role as a mediator in this model. These data
offer a valuable understanding of the ways by which SMMA impacts RPI.

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Table 6. Mediation analysis (specific indirect effects)

Path LB UB
Hypothesis coefficient SD T value 2.5% 97.5% P value Decision

SMMA -> BA -> RPI 0.326 0.040 8.126 0.239 0.395 0.000 significant

SMMA -> BE -> RPI -0.057 0.051 1.107 -0.169 0.037 0.269 insignificant

SMMA -> BI -> RPI 0.096 0.045 2.140 0.016 0.190 0.033 significant

SMMA -> BL -> RPI 0.121 0.058 2.073 -0.005 0.220 0.039 significant

Source : authors own creation from smart pls

FIGURE 2. Measurement model

Source: author's own creation from smart pls.

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FIGURE 3. Structural model

V. DISCUSSION OF THE STUDY

The study examines the influence of social media marketing (SMM) on repurchase intention (RPI) for high-
tech products. It also explores the mediating effects of brand equity (BE), brand loyalty (BL), brand image (BI),
and brand awareness (BA) on consumer behaviour in the digital age. The direct impact of social media
marketing (SMM) on the retail price index (RPI) highlights the crucial role of social media in shaping consumer
buying choices[46]. Advanced technological products, which are known for their fast progress and intricate
features, necessitate efficient communication channels to effectively communicate their value propositions to
consumers [2,7,17,18,47]. Social media marketing (SMM) offers a dynamic platform for firms to communicate
with consumers, share product details, and cultivate relationships, ultimately influencing consumers'
likelihood to make repeat purchases in a favorable way.
The study's findings also indicate that BE, BL, BI, and BA have a mediation role in the link between SMM
activities and RPI. Brand equity (BE) is the measure of how customers perceive the value and reputation of a
brand [48]. It acts as a channel via which social media marketing (SMM) efforts improve return on investment
(RPI). BL, BI, and BA play a role in creating a positive brand perception among consumers, promoting loyalty,
molding brand image, and enhancing brand awareness[3,4,49,50]. As a result, they help to mediate the impact
of SMM activities on RPI. Moreover, the study's emphasis on high-tech items is especially relevant in the
current digital environment, where technological advancements are the key drivers of market competitiveness.
In the high-tech industry, brands frequently encounter obstacles such as quick obsolescence and fierce
competition. Therefore, it is essential for these brands to properly utilize social media marketing (SMM) in
order to distinguish themselves from competitors and foster a devoted consumer base.
The results also have tangible consequences for marketers. By comprehending the mediating impacts of
brand equity (BE), brand loyalty (BL), brand image (BI), and brand awareness (BA), marketers may customize
their social media marketing (SMM) tactics to successfully strengthen these brand-related concepts
[11,19,24,51,52]. Marketers may maximize the effectiveness of social media marketing (SMM) by creating
content that improves brand value, encourages customer loyalty, promotes a favorable brand reputation, and

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boosts brand recognition. the study highlights the importance of social media marketing (SMM) in influencing
how consumers perceive and decide to acquire high-tech products [53]. The study offers useful insights for
marketers aiming to effectively manage the digital ecosystem and promote sustainable business growth by
clarifying the methods by which SMM activities influence RPI across several mediation channels [26].

VI. LIMITATIONS OF THE STUDY

The study's generalizability may be limited because it only focuses on high-tech devices. Subsequent
investigations should encompass a wide range of product categories to determine the wider relevance of the
results. The use of a cross-sectional design may restrict the capacity to establish a causal relationship between
variables. To capture changes in repurchase intention and the factors that mediate it over time, future research
could utilize longitudinal methods. Relying solely on self-reported data from surveys may induce biases in
responses and social desirability effects. Integrating surveys with objective metrics or employing different data
collection methods such as experimental research could strengthen the reliability of the results. When analyzing
various mediating variables, the study may fail to consider possible interactions or nonlinear correlations
among them. Further investigation could go into more advanced statistical methodologies to accurately capture
intricate mediation mechanisms. The study may have overlooked many pertinent contextual aspects that
influence the efficiency of social media marketing and the intention to repurchase. Further research could
investigate contextual factors such as cultural variations, market development, or competitive dynamics to gain
a fuller comprehension.

VII. IMPLICATION OF THE STUDY

The research on the influence of social media marketing activities on repurchase intention, specifically in
the field of high-tech products, produces numerous noteworthy consequences. First and foremost, it
emphasizes the significance of brand equity in the era of digital technology. Social media marketing can boost
brand equity by fostering favourable connections and opinions among consumers, ultimately resulting in
higher repurchase intention. Furthermore, the results emphasize the significance of brand loyalty in acting as
a mediator. Creating captivating and interactive social media content has the potential to cultivate more
profound relationships with consumers, therefore intensifying their devotion to the brand and boosting the
probability of repeat purchases. Furthermore, the study highlights the importance of brand image. Social
media platforms offer brands the chance to mould and strengthen their intended image, exerting influence over
consumers' views and intentions to make repeat purchases. Furthermore, it underscores the significance of
brand awareness. By implementing well-planned social media marketing strategies, firms may enhance their
exposure and expand their audience, leading to a greater level of brand recognition and ultimately influencing
customers to make repeat purchases. In summary, the findings indicate that companies in the high-tech
industry should sallocate resources towards effective social media marketing plans to develop strong brand
value, encourage customer loyalty, shape brand perception, and improve brand recognition. These efforts can
ultimately result in a higher likelihood of repeat purchases and long-term success in the market.

VIII. CONCLUSION
Ultimately, this study's results provide insight into the complex connection between social media marketing
efforts and the likelihood of customers making repeat purchases, specifically regarding advanced technological
products. Extensive investigation has uncovered that social media marketing activities substantially impact the
intention to repurchase. This impact is mediated by various characteristics such as brand equity, brand loyalty,
brand image, and brand awareness. The study highlights the significance of brand equity as a mediator,
suggesting that robust brand equity, achieved through successful social media marketing, has a favourable
influence on repurchase intention. Furthermore, the presence of brand loyalty serves as an important
intermediary factor, indicating that the creation of compelling social media content promotes consumer loyalty,
ultimately leading to an increase in the intention to repurchase. Furthermore, brand image acts as an
intermediary, emphasizing the importance of captivating visual and narrative material in influencing how
people perceive a company and encouraging them to make repeat purchases. Finally, brand awareness acts as
a mediator in the interaction, emphasizing the need of having a strong presence on social media to maintain a
high level of recall and influence repeat purchases. In summary, this study highlights the complex and diverse

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impact of social media marketing on customer behaviour towards high-tech items. This information offers
essential knowledge for marketers to create effective social media campaigns that not only improve how
consumers perceive a company but also increase their likelihood of making repeat purchases. Ultimately, this
contributes to long-term business success in the ever-changing digital environment.

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