INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)

ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XI November 2025

Adoption of Social Networking Sites for Clothing Purchases: A

UTAUT-Based Study

Lileth O. Ulbeda¹, Gerwine J. Medio, Ph.D²

¹North Eastern Mindanao State University

²Cebu Technological University

DOI: https://dx.doi.org/10.47772/IJRISS.2025.91100343

Received: 01 December 2025; Accepted: 05 December 2025; Published: 10 December 2025

ABSTRACT

This study investigates the adoption of social networking sites (SNS) for clothing purchases using the Unified

Theory of Acceptance and Use of Technology (UTAUT) framework. It examines how performance expectancy,

effort expectancy, social influence, and behavioral intention influence consumers’ acceptance of SNS as

platforms for clothing purchases. A descriptive–correlational research design was employed with 100

participants recruited from an academic institution. Data were gathered through a validated questionnaire and

analyzed using descriptive statistics and Pearson correlation. Findings indicate high levels of SNS adoption,

with performance expectancy emerging as the strongest predictor of behavioral intention. All UTAUT

constructs showed significant positive relationships, indicating that perceived usefulness, ease of use, and social

influence substantially shape consumers’ intention to use SNS for clothing purchases. The study reinforces the

relevance of UTAUT in explaining technology acceptance within online shopping contexts, specifically in

clothing-related purchases.

Keywords: Social Networking Sites, Clothing Purchases, UTAUT, Behavioral Intention, Technology Adoption

INTRODUCTION

Social networking sites (SNS) have transformed from basic communication tools into powerful platforms for

digital marketing and online shopping, significantly shaping consumer behavior in the clothing industry (Chen,

X., Xie, & Qu, 2024). SNS provide users with convenient access to product information, opportunities to interact

with brands, and peer or influencer recommendations, which strongly influence purchasing decisions (Bazi et

al., 2024). As online shopping continues to integrate into daily life, understanding the factors driving consumers’

adoption of SNS for clothing purchases has become essential (Heuritech, 2022).

The Unified Theory of Acceptance and Use of Technology (UTAUT) offers a robust framework to study

technology adoption by identifying key determinants of user behavior: performance expectancy, effort

expectancy, social influence, and facilitating conditions (Venkatesh et al., 2003). Within the context of SNS-

based shopping, these constructs explain why consumers prefer SNS platforms, emphasizing the role of

perceived usefulness, ease of use, and social encouragement in shaping behavioral intentions (Kim & Johnson,

2019).

Clothing purchases on SNS are strongly influenced by visual presentation, social recommendations, and content

quality, which enhance user engagement and affect purchase decisions (Ko, 2018). Social influence is

particularly important, as consumers are more likely to purchase products endorsed by friends, influencers, or

online communities (Amath & Kajendra, 2025).

Despite the growing popularity of SNS commerce, research specifically investigating clothing purchases through

the UTAUT framework remains limited, especially in local academic settings. This study aims to fill this gap by

examining how UTAUT constructs relate to consumers’ behavioral intention to use SNS for clothing purchases.

Using a descriptive–correlational research design, the study provides empirical evidence on how performance

expectancy, effort expectancy, and social influence influence Social Networking sites adoption for clothing-

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INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)

ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XI November 2025

related transactions.

LITERATURE REVIEW

The Unified Theory of Acceptance and Use of Technology (UTAUT), developed by Venkatesh et al. (2003),

integrates previous models such as the Technology Acceptance Model (Davis, 1989) and the Theory of Planned

Behavior (Ajzen, 1991) to explain users’ acceptance and use of technology. It identifies four primary

constructs—performance expectancy, effort expectancy, social influence, and behavioral intention—that

determine technology adoption. Recent studies have applied UTAUT to online shopping, e-commerce, and social

media contexts, providing robust evidence for its applicability in consumer behavior research.

Performance expectancy

Performance expectancy refers to the degree to which users believe that using a system will improve their

performance or outcomes. In online shopping contexts, this translates to the perceived usefulness of digital

platforms in facilitating purchases. Albugami and Zaheer (2023) found that performance expectancy

significantly predicts online shopping intention during the COVID 19 pandemic, highlighting that consumers

adopt platforms when they perceive clear benefits. Similarly, Hebshibha and Chitra (2024) demonstrated that

engaging and visually appealing social media content increases consumer satisfaction and loyalty in fashion

retail, reinforcing the role of performance expectancy in digital purchasing decisions.

Effort expectancy

Effort expectancy pertains to the ease of using a system. Platforms that are easy to navigate and interact with

encourage adoption by reducing perceived barriers. Amath and Kajendra (2025) emphasized that site efficiency

and user-friendly interfaces strongly influence purchase intentions for fashion items, showing that consumers

are more likely to engage with platforms that provide convenience and intuitive navigation. Likewise, Aprianto

et al. (2023) applied UTAUT2 to TikTok Shop adoption and found that effort expectancy strongly affects

behavioral intention in social commerce, suggesting that usability is critical in SNS based retail environments.

Social influence

Social influence captures the impact of peers, influencers, or online communities on users’ decisions. In social

media and e-commerce contexts, recommendations and endorsements strongly affect consumer behavior. Bazi

et al. (2024) demonstrated that visually appealing content and entertaining posts increase engagement, brand

loyalty, and purchase intention, confirming the importance of social influence in SNS adoption. Wu et al. (2023)

found that peer recommendations and online reviews enhance consumers’ repurchase intentions during periods

of social distancing, highlighting social influence as a critical determinant of continued usage in online

marketplaces

Behavioral intention

Behavioral intention represents the users’ motivation or plan to engage with a system in the future. Studies show

that when performance expectancy, effort expectancy, and social influence are positively perceived, users

develop stronger intentions to adopt technology. Kumar and Usman (2024) applied UTAUT2 in predicting e-

shopping adoption and found that behavioral intention is significantly shaped by perceptions of usefulness, ease

of use, and social encouragement. Moreover, Renaningtias et al. (2024) confirmed that UTAUT constructs

reliably explain the adoption of digital marketing tools among micro, small, and medium enterprises (MSMEs),

emphasizing that behavioral intention links technology adoption to practical outcomes

METHODOLOGY

This study employed a descriptive–correlational research design to examine the relationships between the

Unified Theory of Acceptance and Use of Technology (UTAUT) constructs—performance expectancy, effort

expectancy, social influence—and consumers’ behavioral intention to use social networking sites (SNS) for

clothing purchases. It enables the measurement of how perceived usefulness, ease of use, and social

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INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)

ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XI November 2025

encouragement affect users’ adoption of digital platforms in a natural setting. The study included 100

participants, selected using purposive sampling to ensure that respondents could provide relevant insights into

the research problem. Participants were chosen based on their active use of SNS and experience in browsing or

purchasing clothing online. Data were gathered through a structured questionnaire developed in alignment with

UTAUT constructs. The questionnaire comprised four sections: Performance expectancy, effort expectancy,

social influence, and behavioral intention. Responses were measured using a five-point Likert scale (1 = Strongly

Disagree, 5 = Strongly Agree). The instrument was validated by experts to ensure clarity, relevance, and

reliability, and it was designed to capture participants’ perceptions and attitudes toward using SNS for clothing

purchases.

Prior to the data collection, ethical clearance was obtained from the academic institution. Participants were

informed of the study’s objectives, voluntary participation, and the confidentiality of their responses. The

questionnaire was distributed online via Google Forms, and participants were given one week to respond. Data

were reviewed for completeness and accuracy before analysis.

Collected data were analyzed using descriptive statistics (mean and standard deviation) to summarize participant

responses. Pearson correlation analysis was conducted to examine the relationships between UTAUT

constructs—performance expectancy, effort expectancy, social influence—and behavioral intention. Throughout

the study, ethical standards were strictly observed, including informed consent, anonymity, confidentiality, and

participants’ right to withdraw at any time. No personally identifiable information was collected, and all data

were securely stored and used solely for research purposes.

RESULTS

Acceptability of Social Media Platforms Using UTAUT Constructs

Table 1. Performance Expectancy

Indicators

Mean

SD (σ)

0.69

Interpretation

VHA

I find social media platforms useful for discovering and purchasing clothing. 4.41

Using social media for clothing purchases helps me find better options more 4.38

efficiently.

0.72

VHA

Social media platforms improve my shopping experience by providing more 4.37

choices and detailed product information.

0.71

0.76

VHA

I believe that purchasing clothing through social media increases my chances 4.36

of finding trendy and high-quality products.

Overall Weighed Mean Interpretation

4.38

Very Highly Acceptable

Table 2. Effort Expectancy

Indicators

Mean

SD (σ)

Interpretation

VHA

My interaction with social media platforms for clothing purchases is clear 4.31

and understandable.

0.73

It is easy for me to browse, select, and purchase clothing through social 4.40

media.

0.71

0.69

VHA

I find social media platforms easy to use for searching and evaluating 4.36

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INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)

ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XI November 2025

clothing items.

The purchasing process (adding to cart, payment, checkout) on social media 4.40

0.68

VHA

is simple and hassle-free.

Overall Weighed Mean Interpretation

4.37

Very Highly Acceptable

Table 3. Social Influence

Indicators

Mean

SD (σ)

Interpretation

VHA

My friends, family, or influencers recommend purchasing clothing via social 4.25

media.

0.75

Seeing others (friends, celebrities, influencers) buying clothing on social 4.19

media makes me more likely to do the same.

0.79

0.73

0.79

Online reviews and user-generated content influence my decision to purchase 4.37

clothing.

VHA

I trust social media recommendations when deciding on clothing purchases.

Overall Weighed Mean Interpretation

4.16

4.24

Very Highly Acceptable

Table 4. Behavioral Intention

Indicators

Mean

SD (σ)

0.76

Interpretation

VHA

I intend to purchase clothing through social media platforms in the future. 4.24

[I predict I will use social media more frequently for clothing purchases.

I plan to use on social media platforms for clothing shopping.

I would recommend purchasing clothing through social media to others.

Overall Weighed Mean Interpretation

4.19

4.16

4.09

4.17

0.79

0.75

0.77

Highly Acceptable

Table 5: Pearson’s Correlation of UTAUT Constructs with Behavioral Intention

Variables

Behavioral Intention r

0.8025

p-value

Interpretation

Performance Expectancy

Effort Expectancy

Social Influence

Strong positive correlation

0.7597

0.7563

At the 0.05 level of significance, all three UTAUT constructs—Performance Expectancy, Effort Expectancy,

and Social Influence—showed strong and significant correlations with behavioral intention to use social media

platforms. Thus, all corresponding null hypotheses were rejected.

H₀₁: There is no significant relationship between performance expectancy and behavioral intention to use

social media platforms.

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INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)

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Findings revealed a strong positive correlation (r = 0.8025, p < 0.05), leading to the rejection of the null

hypothesis. This indicates that users who perceive social media as useful, productive, and beneficial are more

likely to intend to use it consistently. Performance expectancy emerged as the strongest predictor among the

constructs.

This suggests that respondents recognize the value of social media in improving efficiency, accessing

information, and completing tasks. Platforms that provide clear benefits foster stronger behavioral intention,

making perceived usefulness a central factor in technology acceptance.

H₀₂: There is no significant relationship between effort expectancy and behavioral intention to use social

media platforms.

Results showed a strong positive correlation (r = 0.7597, p < 0.05), which also rejects the null hypothesis. This

demonstrates that ease of use significantly influences adoption. When platforms are simple, intuitive, and require

minimal effort, users are more willing to use them regularly.

This finding reflects that convenience and user-friendly features are key determinants of acceptability. Reducing

complexity enhances users’ intention to adopt and continue using social media platforms.

H₀₃: There is no significant relationship between social influence and behavioral intention to use social

media platforms.

A strong positive correlation was observed (r = 0.7563, p < 0.05), leading to the rejection of the null hypothesis.

This means that external influences—such as peers, family, colleagues, or influencers—significantly shape

users’ intention to adopt social media platforms.

The result highlights that social media adoption is socially reinforced. When users see others valuing or using

the platform, their intention to use it increases. Social validation and group norms play an important role, making

social influence a meaningful contributor to behavioral intention.

DISCUSSION

The results of this study demonstrate that social networking sites (SNS) are widely accepted as platforms for

clothing purchases, as evidenced by consistently high ratings across all UTAUT constructs. The findings

highlight the strong influence of performance expectancy, effort expectancy, and social influence on consumers’

behavioral intention, confirming the relevance of the UTAUT model in online shopping and social commerce

contexts.

Performance expectancy received the highest overall mean (4.38), indicating that participants view SNS as

highly beneficial for discovering, comparing, and purchasing clothing. This supports earlier findings showing

that perceived usefulness is a central determinant of technology adoption (Albugami & Zaheer, 2023). The strong

positive views toward SNS features—such as access to wider choices, detailed product information, and trendy

clothing options—suggest that consumers value the efficiency and convenience offered by these platforms.

These perceptions align with Yang (2025), who emphasized that consumers adopt digital shopping platforms

when they believe these tools enhance their purchasing outcomes.

Similarly, effort expectancy showed very high acceptance (4.37), reflecting users’ confidence in navigating SNS

for clothing purchases. The ease of browsing, selecting items, and completing payments reinforces the notion

that user-friendly platform interfaces significantly enhance adoption intentions. This supports Bangur and

Srivastava (2024), who found that intuitive and seamless interactions in mobile shopping environments

encourage consumers to shop more frequently. The result further aligns with findings from Aprianto et al. (2023),

who noted that simple and efficient features of social commerce applications strengthen users' intention to

repeatedly use these platforms.

The construct of social influence also recorded high acceptance (4.24). Participants acknowledged that

recommendations from peers, influencers, and online reviews play a significant role in influencing their shopping

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INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)

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decisions. This is consistent with the social commerce literature, where consumer behavior is often shaped by

endorsements, user-generated content, and the visibility of others’ purchases (Bazi et al., 2024). The impact of

social validation mirrors Amath and Kajendra’s (2025) findings, which showed that consumers are more likely

to purchase fashion items when exposed to peer and influencer engagement on social media.

In terms of behavioral intention, participants reported strong willingness to continue using SNS for clothing

purchases (4.17). Although slightly lower than the other constructs, the rating still indicates high acceptance and

sustained interest in social media–based shopping. This outcome confirms UTAUT’s proposition that perceived

usefulness, ease of use, and social influence collectively reinforce users’ intentions to adopt technology (Kumar

& Usman, 2024). The high level of intention suggests that SNS will remain an important channel for fashion-

related transactions.

The correlation analysis further strengthens these findings. Performance expectancy had the strongest correlation

with behavioral intention (r = 0.8025), suggesting that perceived usefulness is the most powerful predictor of

SNS adoption for clothing purchases. Effort expectancy and social influence also demonstrated strong positive

relationships with behavioral intention, indicating that both usability and social reinforcement shape consumers’

shopping behaviors. These strong correlations align with broader literature emphasizing the centrality of

functional benefits and social dynamics in technology adoption decisions (Yang et al., 2023).

Overall, the results confirm that SNS are not only convenient platforms but also socially reinforced and user-

friendly environments for purchasing clothing. The findings validate the applicability of the UTAUT framework

and provide empirical evidence that consumers’ adoption of SNS for fashion shopping is driven by perceived

usefulness, ease of use, and social influence.Performance Expectancy, Effort Expectancy, and Social Influence

CONCLUSIONS

This study examined the adoption of social networking sites (SNS) for clothing purchases using the Unified

Theory of Acceptance and Use of Technology (UTAUT) framework. The findings revealed that consumers show

a high level of acceptance of SNS as platforms for online shopping, with performance expectancy, effort

expectancy, and social influence receiving consistently high to very high ratings. Among the constructs,

performance expectancy emerged as the strongest predictor of behavioral intention, demonstrating that

consumers are primarily influenced by the perceived usefulness and benefits of using SNS for discovering,

evaluating, and purchasing clothing items. The results further indicate that users find SNS interfaces easy to

navigate, contributing to their intention to continue using these platforms for shopping purposes. This study

concludes that SNS function not only as communication tools but also as efficient, user-friendly, and socially

influenced environments that support clothing-related transactions. Overall, the findings affirm that consumers’

adoption of SNS for clothing purchases is driven by perceived usefulness, ease of use, and socially reinforced

perceptions, validating the relevance and applicability of UTAUT within online shopping and fashion retail

contexts.

RECOMMENDATIONS

Based on the findings, several recommendations are proposed to further strengthen SNS adoption for clothing

purchases. First, online sellers and clothing businesses should enhance the usefulness of their SNS platforms by

providing detailed product information, high-quality visuals, and updated catalogs to increase consumers’

performance expectancy. Second, platform developers and sellers should continue improving usability, ensuring

simple navigation, accessible features, and smooth payment processes to reinforce effort expectancy. Third,

stakeholders should maximize social influence by collaborating with influencers, encouraging customer reviews,

and promoting user-generated content, as these elements significantly affect consumer trust and intention.

For future researchers, it is recommended to expand the sample size and include diverse demographic groups to

increase generalizability. Researchers may also explore additional variables such as trust, perceived risk, and

customer satisfaction to enrich the understanding of SNS adoption in online clothing purchases. Finally, future

studies may apply mixed methods or experimental designs to capture deeper insights into consumer behavior

and platform engagement.

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