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Research Journal Questionnaire Impact OF Product Reviews TO THE Online Buying Behavior Towards Clothing OF LSPU
Survey Research
University of the Philippines System
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EFFECTS OF PRODUCT REVIEWS TO THE ONLINE BUYING
BEHAVIOR OF SENIOR HIGH SCHOOL STUDENTS
Abstract: Today, the new generation is very exposed with social media thus; it is part of their everyday use. Online marketing is common among those people who are inclined with using internet. Marketers now are tending to predict the factors that affect the consumers to buy online. This study aims to determine the relationship of review-related platforms, qualitative reviews, quantitative reviews and peers’ influence in online behavior of the respondents. The respondents were the senior high school students in Laguna State Polytechnic University who buy products online. This study used survey questionnaire as the tool for data collection. There are two parts that the respondents answered. The first part consists of the profile of the respondents and the second part corresponds to the review- related platforms: qualitative reviews, quantitative reviews and peers’ influence. The finding shows that review-related platforms have a significant relationship with online behaviour of the respondents. Therefore, the online behaviour of most of the respondents was affected by review-related platforms. Researchers recommend to the future researchers to expand the number of the respondents and the location of the study to get highly credible results.
1. Introduction
The Internet, as it has revolutionized, became a part of people’s daily lives to the extent that it became the preferred medium for everyday tasks and routines. Most of the time, people rely on online means to do their everyday errands. The Internet and the online world gave an opportunity to have an easier way of completing tasks on different means such as education, communication, free expression, and even marketing.
The progress of technology opened the gates for faster transfer of information. This paved the way for marketing to enter and operate through online means. The Internet became a channel for distribution of goods and services across the world for it offer a wide diversity of goods that the consumers can choose from (Dentzel, 2013).
Online shopping is a process whereby consumers directly buy goods, services and others from a seller through the use of the Internet (Gnanadhas, 2014). Buying through online means gives a huge advantage for consumers. Buying online is advantageous for consumers due to its convenience, wide range of prices, more open variety of products, and the ability to have a discreet purchase. It allows no pressure in buying compared to physical stores that use their selling skills to make a person purchase their item and also, this gives way to avoidance to shopping through the crowd (Jain, 2018).
Currently, product reviews have become popular and have been directly linked with online shopping. Product reviews are commonly used on businesses as well as in shopping sites to give the rights for customers to rate and share their comments or feedback on products they have purchased. Thus, other customers will be able to read these to help them in making their purchase decision (Beal, 2019).
In the past, consumers relied on expert reviews such as consumer reports to guide their purchasing decisions. But now, consumers from today’s market rely on online user reviews (Hankin, 2007). According to a study conducted by Podium (2017), online reviews take a vital role when it comes to shopping. Their findings led them to a conclusion that 58% look at online reviews at least weekly and 93% of the consumers say that online reviews have an impact to their purchase decision.
Another study conducted by PowerReviews (2018) showed that the top 5 factors that affect the purchase decisions of the consumers are price, ratings and reviews, recommendation from friends and family, brand, and free shipping. Today’s shopping platforms gives the consumers an access to the information and reviews (in qualitative and quantitative form) of other people to a certain product. With the access to product comparisons, ranking, user reviews and comments, allow a creation of a new page for consumer behavior towards buying on online means.
There are other studies related to consumer purchasing decision and how different factors affect it. A study conducted in more than 400 Taobo shops in China determined the influence of online reviews of experience goods on consumer purchase behavior. The study concluded that positive reviews had a direct impact on purchasing decision. This includes the describing rating, picture reviews, appended reviews and cumulative reviews. On the other hand, negative reviews, logistics ratings and service rating had no significant effect on consumer’s purchasing decision (Peng, et. al., 2015).
Likewise, the results conducted in German online stores as a practical environment have revealed that consumer reviews may influence overall product sales and help a consumer in purchasing decision.
The purpose of this study is to find the correlation between consumer reviews and consumer purchasing behavior. The focus of the study will be the consumer stories mainly about product reviews and ratings.
Thus, the researchers will conduct this study to convey that review-related factors such as qualitative (comments) and quantitative reviews (ratings), and peers’ influence that have an effect on buying behavior of the consumer.
In the Philippines, online buyers range to 33 million on average from 2016- 2018 according to Statista, e-commerce Philippines (2018). It implies that Filipinos rely on online means to purchase a product. In line with this, marketers should have knowledge on the potential factors that can affect their business as they market on online means. According to Statistica Global Consumer Survey (2018) online shoppers who are 18-24 years old covers 23% in the year of 2017. It means that knowing the factors that can affect on having an online market can be a huge step for it covers a large population of young consumers online.
The study that will be conducted is guided by the theory of Adams (2010) that was known as Consumer Behaviour Theory in internet marketing. It is stated that there is a relationship between consumer participating on online marketing and their behavioural perspective. For instance, the behavioural perspective of consumers towards e-shopping varies depending on several factors. First, it is based on the media system dependent theory which explains dependency relationships between individuals and the medium of communication. It is also based on the perceived usefulness of e-shopping in meeting and understanding ones society or self, orientation meaning actions or interactions of consumers and finally it depends on play that deals with e-shopping and interactive goals.
To determine the relationship between the review-related factors and online buying behavior, figure 1 shows its representation.
Independent Variable Dependent Variable1. Profile
- Age
- Sex
- Types of product reviews
- Qualitative reviews
- Quantitative reviews 2.3’ Influence
information is collected without making any changes to the subject of the study. This study used a descriptive-correlational research design to determine the online buying behavior and to relate it to types of product reviews.
- Respondents of the Study
The purposive sampling technique is a type of non-probability sampling that is most effective when one needs to study a certain cultural domain with knowledgeable experts within (Tongco, n.). This study used a purposive sampling method of Senior High School students who use online as a platform for buying products.
- Data Gathering Instrument and Procedures
This study used a survey questionnaire consisting of two parts. The first part describes the profile of the respondents which consists of their name (optional), age, sex, and strand. The second part is correspondent to the types of product reviews: qualitative reviews, quantitative reviews, and peers’ influence. Each of the platform function under the types of product reviews consists of ten (10) questions each for a total of thirty (30) questions. The questionnaire used a four-point Likert scale ranging from: (1) never, (2) sometimes, (3) often and (4) always.
- Statistical Treatment
The data obtained from the results of the survey questionnaire was tabulated and coded for analysis. The scores obtained in this part were computed to mean scores and the highest accumulated mean score confirms the types of product reviews that affect the online buying decision the most. Moreover, to answer the problem of the study, the data gathered was subjected to the following statistical tools:
Frequency distribution is defined as an overview of all distinct values in some variable and the number of times they occur. It was used in this study to show a clear tabular form of the profile of the students in terms of their sex and strand. The mean is equal to the sum of all the values in the data set divided by the number of values. In this study, it is used to determine the average scores in profile and review-related platform of the respondents. The standard deviation is a measure of the spread of scores within a set of data. In this study, it is used to show the scores of respondents in which reviews they were affected, qualitative and quantitative reviews. Pearson R coefficient was used to determine the relationship of profile of the respondents and types of product reviews to online buying behavior of the participants. The data that has been collected was submitted to statistician who derived the analysis of the study.
3. Findings
This part presents the findings with the corresponding interpretation derive from the statistical treatment of data for the present study entitled “Effects of Product Reviews to the Online Buying Behavior of the Senior High School Students
- Profile of the Respondents
Figure 2. Distribution of the Respondent according to Age.
Figure 2 shows the distribution of the respondents in terms of age. As shown in the figure, out of eighty (80) respondents, 17 years old- 18 years old got the highest frequency of fourteen (14) respondents which is seventy six (76) percent. On the other hand, 19 years old and above got the lowest frequency of five (5) respondents which is six (6) percent. This shows that the majority of the respondents were 17 years old- 18 years old.
22%
77%
Male Female
Figure 3. Distribution of the Respondent according to Sex
AG
E
SEX
17%
76%
6%
16 and Below 17 years old - 18 years old 19 years old above
Table 1 Perception of the Respondent’s Online Buying Behavior in Terms of Quantitative Reviews.
Indicators Mean SD Interpretation
- I check quantitative reviews (scales, star-ratings, likes) of a product.
3 0 Always
- I base my buying decision on quantitative reviews.
3 0 Often
- Seeing high quantitative feedback leads me to purchase a product.
3 0 Often
- Every positive quantitative review account to my decision in purchasing the product.
3 0 Often
- Seeing high quantitative feedback on a product makes me conclude that the claims of a product are credible.
3 0 Always
- Seeing high quantitative feedback makes me conclude that a product is worthy for purchase.
3 0 Often
- I disregard products whenever I see a lot of low rating on them.
3 0 Often
- I consider the number of buyers who rated the product low.
3 0 Often
- I compare the number of negative and positive quantitative reviews.
3 0 Often
- Quantitative reviews affects my buying decision compared to other forms of reviews such as qualitative reviews and peer influence.
3 0 Often
Overall Mean 3 1. 1
Often
Legend:. 3.26-4 (Always); 2.51-3 (Often); 1.76-2 (Sometimes); 1.00-1 (Never)
Table 1 shows the perception of the respondents’ online buying behaviour in terms of quantitative reviews. Indicator one (1) “I check quantitative reviews (scales, star-ratings, likes) of a product.” obtained the highest mean of 3 and standard deviation of .706 with verbal interpretation of “always.” However, indicator eight (8) “I consider the number of buyers who rated the product low.” got the lowest mean of 3 with verbal interpretation of ”often.” The overall mean of 3. and standard deviation of 1 was indicated as “often.” This implies that the respondents often check the quantitative reviews of a certain product in purchasing decision. Having positive quantitative feedback from customers may affect their potential sales.
Table 1 Perception of the Respondent’s Online Buying Behavior in Terms of Peer’s Influence.
Indicators Mean SD Interpretation
- I ask for my friends’ comments on a certain product.
2 0 Often
- I base my buying decision on my peers’ comments and insights.
2 0 Often
- Hearing positive feedbacks from friends lead me to purchase a product.
3 0 Often
- Every positive review from my peers’ accounts to my decision in purchasing the product.
3 0 Often
- Hearing a lot of positive feedback from friends makes me conclude that the claims of a product are credible.
3 0 Often
- Hearing positive peer feedback makes me conclude that a product is worthy for purchase.
3 0 Often
- I refuse to purchase a product whenever I hear a lot of negative feedback from my peers.
3 0 Often
- I consider the number of my peers that do not recommend a product.
3 0 Often
- I compare the number of negative and positive feedback from my peers.
2 0 Often
- My peers influence my buying decision compared to other forms of reviews such as qualitative reviews and quantitative reviews.
3 0 Often
Overall Mean 3 1 Often
Legend: 3.26-4 (Always); 2.51-3 (Often); 1.76-2 (Sometimes); 1.00-1 (Never)
Table 1 presents the perception of the respondents’ online buying behaviour in terms of peers’ influence. Indicator six (6) “Hearing positive peer feedback makes me conclude that a product is worthy for purchase.” obtained the highest mean of 3 and standard deviation of 0 with verbal interpretation of “often.” However, indicator two (2) “I base my buying decision on my peers’ comments and insights.” got the lowest mean of 2 with verbal interpretation of ”often.” The overall mean of 2 and standard deviation of 1 was indicated as “sometimes.” This implies that sometimes, the respondents’ online buying behavior is influenced by peers.
Table 2. Perception of the Respondents Towards Their Online Buying Behavior.
Indicators Mean SD Interpretation
Legend. **. Correlation is significant at the 0 level (2-tailed).
Table 4 shows the correlation between respondent’s online buying behaviour and the review platform factors. Based on the table, the qualitative reviews got the highest r-value having 0. It means that qualitative reviews are highly correlated to respondent’s online buying behaviour. All of the review platform factors have a significant relationship to the respondent’s online buying behaviour. This indicates that the qualitative reviews, quantitative reviews and peer-influence were correlated to the purchasing decision of the respondents.
This can be parallel to the study conducted by Ahsan (2017) about the consumer ratings-reviews and its impact on consumer purchasing behaviour. The study concluded that the reviews and ratings appear to act as a consumer- generated marketing content and seems to influence consumers’ online and offline purchases behavior. Another study conducted by Johnson (2015) about influence of parents, peers, internet product search and visual social media on college students’ purchase behaviour. Based on the results and findings, individuals tend to go to their peers to find the idea for a product and then consult online resources and family members to further gain advice.
Since buying a product online does not involve physical contact with the product, consumers resort on to analyzing the qualitative and quantitative reviews to have an idea about the product.
4. Conclusion
This section presents the result concluded in this study.
- Age has no significant relationship to the respondents’ online buying behavior. The respondents who are 16 years old and below; 17 and 18 years old; and 19 years old and above do not influence the consumers on their online buying behavior. Sex has no significant relationship to the respondents’ online buying behavior.
Therefore, the hypothesis stating that there is no significant relationship between the profile of the respondents and their online buying behavior is sustained.
- Qualitative reviews have significant relationship to the respondents’ online buying behavior. The comments, video reviews, posts, images, etc. do not make different online buying behavior. Quantitative reviews have significant relationship to the respondents’ online buying behavior. The scale, star-ratings, likes, etc. do not influence the online buying behavior. Peers’ influence has significant relationship to the respondents’ online buying behavior. Friends, family and people surrounding the respondents personally do not make difference to the online buying behavior. In general, according to the result, it can be summarized that the types of product reviews (qualitative reviews, quantitative reviews and peers’ influence) have a significant relationship with the online buying behavior.
Therefore, the hypothesis stating that there is no significant relationship between the types of product reviews and the respondents’ online buying behavior is not sustained.
Recommendations
Based on the findings and conclusion of the study, researchers deliberated on to some recommendations in the following persona;
Future Researchers – Since this study had only focused on senior high school students , it is recommended that further studies be carried out on students from other colleges and faculties. Other than that, this study was only conducted on students. Thus, a larger scope must be considered involving professionals or simply online market users. Adding the variable allowance is recommended to see its relation to the buying behavior. Furthermore, future research could also explore the difference between online buying and non-online buying behavior of the respondents.
Marketers – It is recommended to use this study as a basis on creating their marketing plans. Based on the findings, marketers can formulate marketing strategies to obtain positive feedbacks by thinking on how the customer will criticize the product.
References
Ahsan. A. (2017). Consumer ratings-reviews and its impact on consumer purchasing beha-vior. Retrieved on February 25, 2018 from pdfs.semanticscholar/9813/d5657943e bf15372379a6d7e291776feda2? fbclid=IwAR2lEIqP9JU2vRBsDLaD8u0Mbj9sCs53JJS4yTtgNZVB0BHNIhLUB6- Ty0M
Beal (2019). Product Review. Retrieved on February 17, 2019 from webopedia/TERM/P/product_review.html
Constantinides, E. (2016). Impact of Online Product Reviews on Purchasing Decisions. Retrieved on February 20, 2019 from researchgate/publication/ 24_Impact_of_Online_Product_Reviews_on_Purchasing_Decisions? fbclid=IwAR0RJx7nBYbmRPnwiwXxR6wE4b4ZTnJMmytUtZnCNoyqYmw_0aMgxa HC6ro
Dentzel, Z. (2013). How the Internet Has Changed Everyday Life. Retrieved on February 2, 2019 from bbvaopenmind/en/articles/internet- changed-everyday-life/
Gnanadhas (2014). Online Shopping. Retrieved on February 17, 2019 from resear- chgate/publication/264556861_Online_Shopping___An_Overview
Hankin, L. (2007). The Effects of User Reviews on Online Purchasing Behavior across Multiple Product Categories. Retrieved on February 25, 2019 from ischool.berkeley du/sites/default/files/lhankin_report?fbclid=IwAR1S4R8t7keX1Q9bPxg_- HCBlcNxfJr3_8r94yxnll2NMIGSujsgD_ZoK1k
Effects of Product Reviews to the Online Buying Behavior of LSPU-SPCC Senior
High School Students
Survey Questionnaire
To the respondents,
Good day!
This questionnaire is the instrumental tool to be used by the researchers in conducting their
study which aims to determine the effects of product reviews to the online buying behavior of the
consumers. This survey questionnaire will ask about your personal information and questions regarding
to your buying behavior. Answer the following questions based on your experiences. Your responses will
be anonymous and will never be linked to you personally. Thank you for your cooperation.
Sincerely,
The Researchers
Name(Optional): ____________________________ Age:
Sex:
I. Online Buying Behavior - type of behaviour which is exhibited by customers while browsing
websites of an e-tailer in order to search, select and purchase goods and services, in order to fulfill their
needs and wants
Direction: Indicate your answer by putting a check mark () on the corresponding item.
4 – Always 3 – Often 2 – Sometimes 1 – Never
16 and below
17 y/o - 18 y/o
19 y/o and above
Male Female
II.
Qualitative Review-Related Factors – a general term for comments, video reviews, posts,
images, etc.
Direction: Indicate your answer by putting a check mark () on the corresponding item.
4 – Always 3 – Often 2 – Sometimes 1 – Never
III.
Quantitative Review-Related Factors – a general term for scale, star-ratings, likes and etc.
Direction: Indicate your answer by putting a check mark on the corresponding item.
4 – Always 3 – Often 2 – Sometimes 1 – Never
4 3 2 1
The internet always comes first in my mind when I need a certain product.
I often purchase products online.
Buying online saves my time.
Shopping online is convenient for me.
Being able to shop any time online is a great advantage for me.
I prefer to buy from online resellers than on websites.
7. I feel comfortable buying products online.
8. I feel relieved when I purchase products online.
9. I feel satisfied after an online purchase.
10. Online shopping is not just buying products but is
entertainment for me.
4 3 2 1
- I check qualitative reviews (comments, video reviews, posts, images, etc.) ofa product.
- I base my buying decision on qualitative reviews.
- Seeing a lot of positive qualitative feedback leads me to purchase a product.
- Every positive qualitative review accounts to my decision in purchasing the product.
- Seeing a lot of qualitative feedback on a product makes me conclude that the claims of a product are credible.
- Seeing a lot of positive qualitative feedback makes me conclude that a product is worthy for purchase.
- I disregard products whenever there are a lot of negative comments on them.
- I consider the number of buyers who posted negative comments on a product.
- I compare the number of negative and positive qualitative reviews.
- Qualitative reviews affect my buying decision compared to other forms of reviews such as quantitative reviews and peer influence.
from my peers. 10. My peers influence my buying decision compared to other forms of reviews such as qualitative reviews and quantitative reviews.
(Adapted and modified questionnaire from Constantinides, E. (2016). Impact of Online Product Reviews on Purchasing Decisions.)
Signature
Research Journal Questionnaire Impact OF Product Reviews TO THE Online Buying Behavior Towards Clothing OF LSPU
Course: Survey Research
University: University of the Philippines System
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