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

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

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Factors Affecting Students’ Online Purchase Intention in Urban

Areas

Mariaton Safrina Baharuddin

, Muhammad Luqman Haqem Abd Wahab

Zabedah Othman

UNITAR University College Kuala Lumpur, Malaysia

University Technology MARA (UiTM)

*Corresponding Author

DOI: https://dx.doi.org/10.47772/IJRISS.2025.91100201

Received: 10 November 2025; Accepted: 20 November 2025; Published: 04 December 2025

ABSTRACT

The expansion of digital technologies has significantly reshaped consumer behavior, with online shopping

becoming increasingly prevalent. This study examines factors influencing online purchase intention among

urban university students in Malaysia, focusing on social influence, electronic word-of-mouth (eWOM),

website content, and attitude. A quantitative research design was employed using a structured online

questionnaire distributed to students in public and private universities. Data were analyzed to test hypotheses

regarding the relationships between independent variables and online purchase intention. Findings are expected

to provide valuable insights for online retailers and marketers in developing effective digital strategies targeted

at young, digitally active consumers. The study also contributes to the academic literature by clarifying how

social influence, eWOM, website content, and attitude jointly shape online purchase intention among urban

university students in Malaysia.

Keywords: Attitude, electronic word-of-mouth (eWOM), Malaysia, online purchase intention, social

influence, urban university students, website content

INTRODUCTION

The widespread adoption of digital technologies such as the internet, mobile applications, and social media

platforms has profoundly transformed consumer lifestyles and purchasing behaviors worldwide. As of January

2021, there were approximately 4.66 billion active internet users, representing 59.5% of the global population

(Statista, 2021). This digital proliferation has contributed to the rise of online shopping as a mainstream mode

of commerce.

Online shopping refers to the process of purchasing goods or services via internet-based platforms, typically

involving product selection, digital payment, and delivery logistics (Market Business News, 2021). This form

of commerce offers convenience, time efficiency, and flexibility, fueling its adoption among younger, tech-

savvy consumers.

The COVID-19 pandemic accelerated the digital shift, increasing consumer reliance on online channels for

essential and non-essential purchases (East, 2020). With improved trust in digital transactions and seamless

user experiences, traditional brick-and-mortar models are increasingly complemented—or replaced—by e-

commerce platforms (Saleem & Yaseen, 2022).

In Malaysia, the trend mirrors global patterns. According to the Malaysian Communications and Multimedia

Commission (MCMC, 2022), over 82% of Malaysians now engage in online transactions, with urban areas

leading adoption due to better infrastructure, smartphone penetration, and digital literacy. Prior studies

highlight that convenience, practicality, and trust significantly influence online purchase intention among

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

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

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Malaysian consumers (Ratih et al., 2020; Dewi & Zakaria, 2020). Younger demographics, particularly

university students aged 20–30, dominate this segment (Milo, 2019; Simon & Sarah, 2019).

Given this context, this study aims to examine the factors influencing online purchase intention among urban

university students in Malaysia, focusing on social influence, eWOM, website content, and attitude, guided by

the Theory of Planned Behavior (TPB) (Ajzen, 1991).

LITERATURE REVIEW

Theory of Planned Behavior (TPB)

The Theory of Planned Behavior (Ajzen, 1991) posits that an individual’s behavioral intention is influenced by

attitude, subjective norms (social influence), and perceived behavioral control. Attitude reflects an individual’s

overall evaluation of the behavior, subjective norms capture social pressures, and perceived behavioral control

denotes confidence in performing the behavior. TPB has been extensively applied in consumer behavior

studies, including online shopping, making it an appropriate framework for this research.

Online Purchase Intention

Online purchase intention refers to a consumer’s willingness or likelihood to buy products or services via the

internet. It is often influenced by perceived usefulness, trust, eWOM, and website quality (Suparno, 2020;

Zhang & Jiang, 2021). In Malaysia, Dewi and Zakaria (2020) found that social influence, system security, and

perceived pricing significantly shape online purchase intention. Additionally, external cues such as website

content and online reviews play vital roles in reducing uncertainty and enhancing trust (Ariff et al., 2014;

Nuseir, 2019).

Social Influence

Social influence refers to the impact that individuals or groups have on a person’s attitudes, beliefs, or

behaviors. In online contexts, it includes the influence of family, friends, peers, and online communities.

Studies show that social norms and peer opinions significantly affect consumers’ confidence and purchase

decisions (Doan, 2020; Ratih et al., 2020).

Hypothesis H1: Social influence has a significant relationship with students’ online purchase intention in

urban universities.

Electronic Word-of-Mouth (eWOM)

Electronic word-of-mouth (eWOM) refers to the sharing of product or service experiences through digital

channels such as social media and review platforms. Credible and persuasive eWOM positively influences

trust and purchase intention (Nuseir, 2019; Suparno, 2020; Saleem & Yaseen, 2022).

Hypothesis H2: eWOM has a significant relationship with students’ online purchase intention in urban

universities.

Website Content

Website content encompasses textual and visual elements such as images, descriptions, and navigation. Well-

structured, accurate, and interactive websites enhance user experience and confidence, which positively

influence online purchase intention (Chen & Lin, 2020; Athapaththu & Kulathunga, 2018).

Hypothesis H3: Website content has a significant relationship with students’ online purchase intention in

urban universities.

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

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

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Attitude

Attitude represents an individual’s overall evaluation (favorable or unfavorable) toward performing a specific

behavior (Fazio, 1995). Within TPB, attitude is a strong predictor of behavioral intention. Local evidence

supports that Malaysian students’ trust, perceived usefulness, and positive online experiences foster favorable

attitudes that, in turn, enhance online purchase intention (Suparno, 2020; Dewi & Zakaria, 2020).

Hypothesis H4: Attitude has a significant relationship with students’ online purchase intention in urban

universities.

CONCEPTUAL FRAMEWORK

Based on the Theory of Planned Behavior (Ajzen, 1991), this study proposes that social influence, electronic

word-of-mouth (eWOM), and website content affect students’ attitude toward online shopping, which in turn

influences their online purchase intention.

Figure 1 below illustrates the conceptual framework of the study.

Figure 1: Conceptual framework illustrating the relationship between Social Influence, eWOM, and Website

Content as independent variables influencing Attitude Toward Online Shopping, which subsequently affects

Online Purchase Intention.

RESEARCH METHODOLOGY

Research Design

This study employs a quantitative, descriptive–correlational research design to examine the relationships

between the independent variables (social influence, electronic word of mouth (eWOM), website content, and

attitude) and the dependent variable (online purchase intention). The quantitative approach allows statistical

testing of hypotheses and supports generalization of findings to a broader population. The design is grounded

Attitude

Online Purchase

Intention

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in the Theory of Planned Behavior (TPB), which emphasizes that attitudes, social influence, and perceived

behavioral control shape behavioral intentions.

Quantitative Research

Quantitative research focuses on collecting and analyzing numerical data through structured instruments such

as questionnaires. This approach is suitable for identifying correlations, testing hypotheses, and making data-

driven decisions. It provides an objective method to assess how social influence, eWOM, website content, and

attitude affect students’ online purchase intentions.

Data Collection Method

Both primary and secondary data collection methods were employed to ensure comprehensive and reliable

results.

Primary Data

Primary data was obtained through a structured online questionnaire distributed to urban university students in

Malaysia. The questionnaire consisted of closed-ended questions using a 5-point Likert scale (1 = Strongly

Disagree to 5 = Strongly Agree) to measure perceptions of each variable:

 Social Influence

 Electronic Word of Mouth (eWOM)

 Website Content

 Attitude

 Online Purchase Intention

The questionnaire was designed based on validated measurement items adapted from previous studies. Google

Forms was used to distribute and collect responses due to its accessibility and ease of use.

Secondary Data

Secondary data was gathered from academic journals, scholarly articles, books, and reputable online sources

relevant to the study’s variables. This information provided theoretical support for the conceptual framework

and guided the development of hypotheses based on TPB.

Sampling

Sampling Frame

The sampling frame consists of students currently enrolled in public and private universities located in urban

areas of Malaysia. This group was chosen because they are active users of digital platforms and represent a

demographic with high online purchasing behavior.

Sampling Technique

A convenience sampling technique was employed, which is a type of non-probability sampling where

respondents are selected based on their availability and willingness to participate. This method was chosen due

to its practicality, cost-effectiveness, and suitability for collecting data within a limited timeframe.

Sample Size

A total of 150–200 respondents was targeted to ensure sufficient representation for statistical analysis. This

range aligns with recommendations for correlational studies involving multiple variables. The sample size is

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

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expected to provide reliable results for testing relationships among the constructs using statistical tools such as

SPSS or SmartPLS.

Data Analysis Techniques

Data collected from the questionnaires will be analyzed using Statistical Package for the Social Sciences

(SPSS). The following techniques will be applied:

 Descriptive analysis to summarize respondents’ demographic profiles.

 Reliability analysis (Cronbach’s Alpha) to ensure internal consistency of the measurement items.

 Correlation analysis to determine relationships among variables.

 Multiple regression analysis to test the hypotheses and identify the influence of independent variables on

online purchase intention.

Summary

This methodology provides a structured approach to examine the relationships among social influence,

eWOM, website content, and attitude toward online purchase intention among urban university students in

Malaysia. By adopting a quantitative correlational design underpinned by the Theory of Planned Behavior, the

study ensures both theoretical grounding and empirical rigor.

ACKNOWLEDGEMENT

All authors would like to thank the Unitar University College Kuala Lumpur (UUCKL) for providing support

for this paper.

REFERENCES

1. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision

Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T

2. Almousa, M. (2011). Perceived risk in apparel online shopping: A multi-dimensional perspective.

Canadian Social Science, 7(2), 23–31. https://doi.org/10.3968/j.css.1923669720110702.002

3. Ariff, M. S. M., Sylvester, M., Zakuan, N., Ismail, K., & Ali, K. M. (2014). Consumer perceived risk,

attitude and online shopping behaviour: Empirical evidence from Malaysia. IOP Conference Series:

Materials Science and Engineering, 58(1), 012007. https://doi.org/10.1088/1757-899X/58/1/012007

4. Athapaththu, J. C., & Kulathunga, D. K. (2018). Factors affecting online purchase intention: Effects of

technology and social commerce. International Business Research, 11(10), 111–128.

https://doi.org/10.5539/ibr.v11n10p111

5. Chen, Y.-C., & Lin, H.-H. (2020). The effects of website content and trust on online purchase intention.

Advances in Economics, Business and Management Research, 145, 1–7.

https://doi.org/10.2991/aebmr.k.200626.001

6. Dewi, C. K., & Zakaria, M. (2020). Determinants of online purchase intention. Journal of Asia Business

Studies, 14(3), 281–306. https://doi.org/10.1108/JABS-10-2018-0299

7. Doan, T.-T. T. (2020). Factors affecting online purchase intention: A study of Vietnam online customers.

Management Science Letters, 10(6), 2337–2342. https://doi.org/10.5267/j.msl.2020.3.033

8. East, F. M. (2020, August 3). Are we witnessing the awakening of a new world order? Forbes Middle

East. https://www.forbesmiddleeast.com/leadership/opinion/are-we-witnessing-the-awakening-of-a-new-

world-order

9. Fazio, R. H. (2014). Attitudes as object-evaluation associations: Determinants, consequences, and

correlates of attitude accessibility. In R. E. Petty & J. A. Krosnick (Eds.), Attitude strength (pp. 247–

282). Psychology Press.

10. Lim, L. P., Ong, C. H., Teo, P. C., & Theresa, H. C.-F. (2024). Online purchase intention of digital

products among university students: The roles of social influence, product preference, system security,

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

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

Page 2515

www.rsisinternational.org

and perceived pricing. Business Management and Strategy, 15(1), 241–255.

https://doi.org/10.5296/bms.v15i1.21869

11. Malaysian Communications and Multimedia Commission. (2022, December 19). Malaysian

Communications and Multimedia Commission (MCMC). https://www.mcmc.gov.my/en/home

12. Market Business News. (2021). Online shopping – Definition and meaning.

https://marketbusinessnews.com/financial-glossary/online-shopping-definition-meaning/

13. Milo, E. (2019, March 22). Malaysia’s online shopping behaviour in infographic. ecInsider.

https://www.ecinsider.my/2019/03/malaysia-online-shopping-behaviour-infographic.html

14. Nuseir, M. T. (2019). The impact of electronic word of mouth (e-WOM) on the online purchase intention

of consumers in Islamic countries: A case of UAE. Journal of Islamic Marketing, 10(3), 759–767.

https://doi.org/10.1108/JIMA-03-2018-0059

15. Ratih, H., Ana, A., Asnul, D. M., & Thompson, S. (2020). Model of purchase impulsive behaviour of

online consumers: Case in Indonesia. International Journal of Advanced Science and Technology, 29(7),

290–298.

16. Saleem, U., & Yaseen, S. (2022). The impact of website quality on customer satisfaction and eWOM in

online purchase intention: The moderating role of gender in risk-taking. Frontiers in Psychology, 13,

860014. https://doi.org/10.3389/fpsyg.2022.860014.

17. Simon, & Sarah. (2019, September 18). Ecommerce in Malaysia in 2019. DataReportal – Global Digital

Insights. https://datareportal.com/reports/digital-2019-ecommerce-in-malaysia

18. Statista. (2021). Global digital population as of January 2021. Statista.

https://www.statista.com/statistics/617136/digital-population-worldwide/

19. Suparno, C. (2020). Online purchase intention of halal cosmetics: S-O-R framework application. Journal

of Islamic Marketing, 12(9), 1665–1681. https://doi.org/10.1108/JIMA-09-2019-0192

20. Tian, Y., Chan, T. J., Haris Fadzilah, A., Ng, M. L., Syed Zainudin, S. S., & Mohd Jalis, F. (2024).

Factors influencing Malaysian university students’ intention to use online payment systems: An

application of the extended perceived value theory. Journal of Logistics, Informatics and Service

Science, 11(9), 19–36.

21. Zehran, S. Z., Che Musa, N., & Tajudin, M. M. (2024). Evaluating online purchase intentions among

Malaysian private university students: The role of perceived risk and trust in online vendors.

International Journal of Academic Research in Business and Social Sciences, 14(9), 889–899.

https://doi.org/10.6007/IJARBSS/v14-i9/22127

22. Zhang, Y., & Jiang, Z. (2021). TAM model evidence for online social commerce purchase intention.

Information Resources Management Journal, 34(2), 86–108. https://doi.org/10.4018/IRMJ.2021040105