An Analysis on The Effect of Online Reviews on Student Shopping Behavior

IJSART - Volume 11 Issue 9 – SEPTEMBER 2025 ISSN [ONLINE]: 2395-1052 Page | 177 www.ijsart.com An Analysis on The Effect of Online Reviews on Student Shopping Behavior Ms. S. Subhitcha1, Ms. C. Keerthana2 1Dept of B.Com. with Professional Accounting 2Assist.Professor, Dept of Commerce with Retail Marketing (ACCA) 1, 2 Sri Ramakrishna College of Arts & Science (Autonomous), Coimbatore – 641006. AbstractThis study investigates the influence of online reviews on students’ shopping behavior, focusing on how digital feedback shapes purchasing decisions. By examining patterns in student engagement with product ratings, comments, and recommendations, the research identifies key factors that guide their trust and choice in online marketplaces. Findings reveal that students are significantly impacted by both the perceived credibility and the volume of online reviews, suggesting that digital word-of-mouth plays a pivotal role in shaping consumer behavior within this demographic. The study offers insights for marketers and ecommerce platforms aiming to enhance engagement and tailor strategies for student consumers. KeywordsOnline reviews, student consumer behavior, digital word-of-mouth, e-commerce, purchasing decisions, consumer trust I. INTRODUCTION In today’s digital era, online reviews have become a significant factor influencing consumer purchase decisions. With the rapid growth of E-Commerce platforms and social media, customers can easily share their experiences and opinions about products and services. Among these consumers, students represent a unique segment whose purchasing decisions are often shaped by limited budgets, peer influence, and a strong reliance on digital platforms for information. In an age where students are highly active on digital platforms and comfortable navigating online marketplaces, online reviews often serve as their primary guide to understanding product quality and value. Whether it is purchasing academic supplies, electronic gadgets, fashion apparel, or even choosing restaurants and service providers, students increasingly rely on the shared experiences of others to reduce uncertainty and ensure value of money. Online reviews act as a virtual form of word-ofmouth communication, providing potential buyers with insights into the quality, usability, and value of a product or service before making a purchase. For students, such reviews not only reduce the risk of making poor buying decisions but also serve as a trusted source of guidance, especially when they lack prior experience with a particular brand or product category. Furthermore, platforms like Amazon, Flipkart, Meesho, and social media pages provide structured review systems-including star ratings, photos, and verified purchase tags-which enhance the credibility and usefulness of the reviews. This study aims to analyze the effect of online reviews on student shopping behavior, examining the extent to which they influence purchase intentions, brand perception, and overall satisfaction. By understanding these dynamics, businesses, marketers, and e-commerce platforms can developstrategies to better cater to student consumers, while students themselves can make more informed purchasing decisions. II. LITERATURE REVIEW The impact of online reviews on consumer behavior has been widely documented, with early research by Chevalier and Mayzlin (2006) establishing that the valence of reviews significantly influences purchasing decisions. Their study demonstrated that positive reviews contribute to increased sales, whereas negative evaluations reduce the likelihood of purchase. This foundational work highlighted the persuasive power of peer-generated content in shaping consumer preferences and set the stage for subsequent investigations into the mechanisms of online influence. Subsequent research has explored the cognitive and behavioral responses of consumers to online reviews. Hu et al. (2022), using eye-tracking methodologies, found that consumers, including university students, tend to devote more attention to negative reviews compared to positive ones, often overlooking cues indicative of fake or misleading content. This selective attention to negative information underscores the heightened sensitivity of consumers to potential risks in online transactions. Zhu et al. (2024) further examined the effects of review volume and inconsistency, coining the term “online review confusion” to describe the phenomenon in which excessive or contradictory reviews increase perceived IJSART - Volume 11 Issue 9 – SEPTEMBER 2025 ISSN [ONLINE]: 2395-1052 Page | 178 www.ijsart.com purchase risk and frequently result in shopping cart abandonment. Their findings also suggested that mindfulness can serve as a moderating factor, reducing the adverse effects of review overload on decision-making. Meta-analytic evidence reinforces the significance of review characteristics in predicting consumer behavior. Zhang et al. (2023) identified review valence, credibility, and quality as the strongest predictors of purchase intention, with valence exerting the most pronounced effect. Complementing these findings, Wang and Li (2024) emphasized the role of social influence in shaping consumer trust, showing that reviews from peers or relatable social groups have a disproportionately strong effect on students’ confidence in products. Collectively, these studies illustrate the complex interplay between review content, credibility, social context, and individual cognitive factors, highlighting the critical role of online reviews in shaping student shopping behavior in e-commerce environments. III. STATEMENT OF THE PROBLEM The rapid growth of e-commerce and digital platforms has transformed the way consumers, particularly students, shop for products and services. Among the many online tools available, online reviews have emerged as one of the most influential factors affecting purchase decisions. Students increasingly rely on online reviews when making purchase decisions. However, the credibility and authenticity of these reviews are often uncertain, leading to possible biased or misguided choices. Limited research exists on how such reviews specifically influence student shopping behavior in terms of trust, product preference, and purchase decisions. This aims to examine the extent and nature of that influence. IV. RESEARCH OBJECTIVES  To know how reviews on e-commerce platforms influence product choice  To study student mentality on e-commerce reviews  To understand whether positive or negative reviews influence students more in their product choices  To find out if students read reviews on e-commerce platforms before buying products  To understand if review help students decide what to buy V. RESEARCH METHODOLOGY 5.1. Research Design The present study adopted a descriptive research design to examine the impact of online reviews on students’ shopping behavior. This design was deemed appropriate as it enables the systematic collection and analysis of data to describe prevailing patterns, preferences, and attitudes without manipulating variables. 5.2. Population and Sample The population for the study comprised university students, reflecting a demographic that frequently engages with e-commerce platforms. A sample of 33 respondents was selected using convenience sampling. This approach was chosen due to its suitability for exploratory research and accessibility to the target group. While the sample size is modest, it offers useful insights into the perceptions and behaviors of students regarding online reviews. 5.3. Data Collection Method Primary data were collected through a structured questionnaire designed to capture demographic information, shopping habits, and the role of online reviews in purchase decisions. The questionnaire included both closed-ended and multiple-choice questions to ensure clarity, standardization, and comparability of responses. The instrument was distributed electronically to ensure wider reach and ease of participation. 5.4. Data Analysis Technique The collected responses were compiled, tabulated, and analyzed using descriptive statistical methods such as frequencies and percentages. These techniques were selected to present a clear picture of respondent characteristics and behavioral trends. The findings were organized into tables, and interpretations were drawn to highlight patterns and insights relevant to the research objectives. 5.5. Scope and Limitations The study focuses exclusively on student respondents, primarily undergraduates within the age group of 18–21 years. Consequently, the results are most representative of this demographic and may not fully capture the perspectives of older or working professionals. In addition, the reliance on convenience sampling limits the generalizability of the findings. Despite these constraints, the study provides valuable insights into the ways in which online reviews influence student consumer behavior in digital marketplaces. VI. ANALYSIS AND INTERPRETATION IJSART - Volume 11 Issue 9 – SEPTEMBER 2025 ISSN [ONLINE]: 2395-1052 Page | 179 www.ijsart.com Age of Respondents Age Group No. of respondents Percentage (%) 18–21 years 30 90.91 22–25 years 1 3.03 Above 25 years 2 6.06 Interpretation: The findings show that the vast majority of respondents (90.91%) belong to the 18–21 age category, confirming that the study primarily reflects the perspectives of young undergraduate students. Only a small fraction (9.09%) represents older age groups, making the results particularly relevant to a youth-oriented demographic. Gender of Respondents Gender No. of respondents Percentage (%) Male 14 42.42 Female 19 57.58 Interpretation: A slightly higher proportion of respondents were female (57.58%) compared to male (42.42%). This balanced distribution ensures representation from both genders, allowing for more inclusive insights. Level of Study Level No. of respondents Percentage (%) UG 31 93.94 PG 1 3.03 Others 1 3.03 Interpretation: The data indicate that 93.94% of participants were undergraduates. This reinforces the earlier observation that the study largely reflects the opinions of younger, entrylevel university students. Year of Study Year No. of respondents Percentage (%) 1st Year 2 6.06 2nd Year 6 18.18 3rd Year 22 66.67 Others 3 9.09 Interpretation: A significant majority (66.67%) were in their third year of undergraduate study, suggesting that academically experienced students form the core of the dataset. Frequency of Online Shopping Frequency No. of respondents Percentage (%) Rarely 19 57.58 Monthly 11 33.33 Weekly 1 3.03 Very frequently 2 6.06 Interpretation: The results reveal that most respondents engage in online shopping infrequently, with 57.58% shopping rarely and 33.33% shopping monthly. Very frequent and weekly shoppers account for only a small proportion, suggesting that online purchasing is not yet a regular habit for the majority. Preferred E-commerce Platforms Platform No. of respondents Percentage (%) Amazon 17 51.52 Flipkart 7 21.21 Meesho 8 24.24 Myntra 1 3.03 Others 0 0 Interpretation: Amazon dominates as the most used platform (51.52%), followed by Meesho (24.24%) and Flipkart (21.21%). Myntra’s presence is minimal (3.03%), and no respondents reported using other platforms. This highlights Amazon’s established market leadership among students. Types of Reviews Considered Most Influential Review Type No. of respondents Percentage (%) Text reviews 4 12.12 Star ratings 9 27.27 Image/video reviews 15 45.45 Verified buyer reviews 5 15.15 Interpretation: Visual reviews (images/videos) emerged as the most influential (45.45%), followed by star ratings (27.27%). Text reviews and verified buyer tags had less impact, suggesting that students value demonstrable evidence over purely textual descriptions. IJSART - Volume 11 Issue 9 – SEPTEMBER 2025 ISSN [ONLINE]: 2395-1052 Page | 180 www.ijsart.com Review-Reading Behavior Before Purchase Response No. of respondents Percentage (%) Always 27 81.82 Sometimes 6 18.18 Rarely 0 0 Never 0 0 Interpretation: An overwhelming 81.82% of respondents reported always reading reviews before purchase, while the remaining 18.18% did so occasionally. None indicated indifference, confirming that review-checking is a critical step in the buying journey. Importance of Reviews vs. Price Response No. of respondents Percentage (%) Reviews more important 5 15.15 Price more important 3 9.09 Both equally important 25 75.76 Neither matters 0 0 Interpretation: Most respondents (75.76%) view both reviews and price as equally important, indicating that students balance quality perception with affordability in their decisions. Product Categories Most Influenced by Reviews Product Type No. of respondents Percentage (%) Electronics 6 18.18 Fashion 17 51.52 Academic materials 1 3.03 Skincare/beauty 4 12.12 Others 5 15.15 Interpretation: Fashion items (51.52%) are most influenced by reviews, followed by electronics (18.18%). Academic materials rank lowest (3.03%), suggesting that students rely more on peer feedback for lifestyle purchases than academicrelated ones. Do Reviews Help in Product Choice? Response No. of respondents Percentage (%) Yes 22 66.67 No 2 6.06 Sometimes 9 27.27 Interpretation: The majority of respondents (66.67%) confirmed that reviews directly influence their product choices, while 27.27% considered them occasionally useful. Only a small proportion (6.06%) reported that reviews did not affect their decision-making. Most Trusted App for Reviews Platform No. of respondents Percentage (%) Amazon 15 45.45 Flipkart 9 27.27 Meesho 5 15.15 Myntra 2 6.06 Others 2 6.06 Interpretation: Amazon is perceived as the most trustworthy platform for reviews (45.45%), followed by Flipkart (27.27%). Other platforms received comparatively lower trust, aligning with Amazon’s strong reputation among students. Use of Reviews for Product Comparison Response No. of respondents Percentage (%) Yes, always 20 60.61 Sometimes 11 33.33 No 2 6.06 Interpretation: A large proportion (60.61%) consistently compare products using reviews, while 33.33% do so occasionally. Only a minority (6.06%) do not engage in this practice, indicating that review-based comparison is a widespread behavior. Effect of Negative Reviews with High Ratings Response No. of respondents Percentage (%) Yes, star rating matters more 6 18.18 No, I read the negative reviews 5 15.15 Maybe, depends on the product 19 57.58 Not sure 3 9.09 Interpretation: The majority (57.58%) reported that their decision would depend on the specific product, suggesting a contextual approach. While 18.18% prioritize star ratings, 15.15% are more cautious, giving weight to negative feedback. IJSART - Volume 11 Issue 9 – SEPTEMBER 2025 ISSN [ONLINE]: 2395-1052 Page | 181 www.ijsart.com Motivations for Writing Reviews Factor No. of respondents Percentage (%) Product quality 27 81.82 Delivery experience 4 12.12 Customer service 2 6.06 Interpretation: Product quality is the strongest motivator for writing reviews (81.82%), while delivery and customer service have relatively minor influence. This suggests that consumers prioritize product performance in their feedback. Perceptions of Reviews in Decision-Making Response No. of respondents Percentage (%) Strongly agree 11 33.33 Agree 14 42.42 Neutral 8 24.24 Disagree 0 0 Strongly disagree 0 0 Interpretation: A total of 75.75% either strongly agreed or agreed that reviews improve purchasing decisions. The remaining 24.24% were neutral, while no respondents disagreed, suggesting broad consensus on the usefulness of reviews. Most Convincing Review Types Review No. of respondents Percentage (%) Product is amazing! 15 45.45 Got it on time. Works perfectly. 15 45.45 Five stars just for fast delivery 0 0 Haven’t used it yet, but looks good 3 9.09 Interpretation: Both positive-expressive and performanceoriented reviews were equally persuasive (45.45% each). Reviews focused only on delivery or unverified product use were less convincing. Reviews as a Tool to Avoid Bad Products Response No. of respondents Percentage (%) Yes 27 81.82 No 6 18.18 Interpretation: A significant majority (81.82%) reported that reviews helped them avoid poor products, indicating their preventive role in online shopping. First Impressions of Review Sections Factor No. of respondents Percentage (%) Overall star rating 12 36.36 Top positive review 10 30.3 Top negative review 2 6.06 Total number of reviews 9 27.27 Interpretation: Overall star ratings (36.36%) had the greatest influence on first impressions, followed by top positive reviews (30.3%) and total review count (27.27%). Negative reviews were least impactful initially (6.06%). VII. FINDINGS The study reveals several key insights into the influence of online reviews on student shopping behavior. Demographic analysis shows that the sample is predominantly composed of undergraduate students aged 18–21, with a slight majority of female participants. In terms of online shopping habits, most respondents reported shopping rarely or on a monthly basis, indicating that online purchasing is not yet a highly frequent activity among the group. Amazon emerged as the most preferred and trusted platform for both purchases and reviews, followed by Meesho and Flipkart, while Myntra and other platforms played a minor role. Visual reviews (images and videos) were found to be the most persuasive, surpassing star ratings, textual feedback, and verified buyer tags. A large majority of participants reported that they consistently read reviews before making a purchase, underlining the central role of peer feedback in decisionmaking. When weighing reviews against price, most students considered both equally important, reflecting a balanced approach to value and trust. Product categories such as fashion and electronics were most reliant on reviews, while academic materials attracted minimal dependence. Reviews were also reported to help students avoid poor-quality products, with 81.82% confirming their usefulness in this regard. Furthermore, the majority indicated that reviews aid in making IJSART - Volume 11 Issue 9 – SEPTEMBER 2025 ISSN [ONLINE]: 2395-1052 Page | 182 www.ijsart.com better purchasing decisions, with star ratings and top positive reviews shaping initial impressions of review sections. VIII. SUGGESTIONS 1. Enhancing Review Transparency: E-commerce platforms should prioritize the visibility of authentic and detailed reviews, particularly those including images or videos, as these formats exert the strongest influence on student buyers. 2. Balanced Review Display: Displaying a mix of positive and negative reviews can help reduce confusion and foster trust. Since students often focus on negative comments, platforms should emphasize verified reviews to counterbalance skepticism. 3. Engagement Strategies for Students: Marketers targeting student consumers should recognize that both reviews and price shape decision-making. Promotional campaigns that combine competitive pricing with credible customer feedback are likely to be more effective. 4. Awareness of Review Usefulness: Students should be encouraged to contribute reviews, particularly regarding product quality, as peer-generated content plays a crucial role in shaping informed consumer choices. 5. Platform Trust Building: Given that Amazon was viewed as the most reliable platform for honest reviews, competing platforms like Flipkart, Meesho, and Myntra may benefit from strengthening review verification processes to increase student trust. IX. CONCLUSION The research highlights the pivotal role of online reviews in shaping the shopping behavior of students. While online shopping remains relatively infrequent for most respondents, reviews—particularly visual ones—are consistently consulted and heavily influence decision-making. Students tend to strike a balance between price considerations and the credibility of reviews, with fashion and electronic products being most affected by peer evaluations. The findings affirm that online reviews not only assist in product comparisons but also serve as a safeguard against unsatisfactory purchases. Trust in platforms, review authenticity, and the quality of review content are central to shaping consumer confidence among students. Despite limitations such as the small, student-focused sample size, this study provides meaningful insights into the dynamics of digital word-of-mouth in the student demographic. Future research could broaden the scope by incorporating larger and more diverse samples to validate and expand upon these observations. REFERENCES [1] Chevalier, J. A., &Mayzlin, D. (2006). 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