A Study on the Impact of Chinese Online Customer Reviews on Consumer Purchase Behavior in Online Education Platforms

Abstract

팬데믹 이후 온라인 교육 플랫폼에 대한 수요가 급증하면서 소비자들이 의사 결정을 위해 온라인 리뷰에 더욱 의존하게 되었습니다. 본 연구는 중국 온라인 고객 리뷰가 온라인 교육에서 소비자 구매 행동에 미치는 영향을 조사합니다. 신뢰, 리뷰 감정, 리뷰의 양과 시의성을 분석하여 이러한 요인들이 소비자 결정에 어떻게 영향을 미치는지 이해하고자 합니다. 회귀 모델을 사용한 결과, 부정적인 리뷰, 시기적절한 피드백, 많은 양의 리뷰가 소비자 구매 결정에 긍정적인 영향을 미치며, 코스 가격은 반비례 관계를 나타냅니다. 또한, 인지적 신뢰와 감정적 신뢰는 리뷰와 구매행동 간의 관계를 매개하며, 소비자 결정 성향에 역 U자형 효과를 나타냅니다. 이러한 통찰은 온라인 교육 제공자에게 온라인 리뷰를 관리하고 활용하여 소비자 신뢰를 증진시키고 판매 성과를 향상시킬 필요성을 강조하는 유용한 시사점을 제공합니다.

In the post-pandemic era, the demand for online education platforms has surged, leading to increased consumer reliance on online reviews for decision-making. This study investigates the impact of Chinese online customer reviews on consumer purchase behavior in online education. By examining the role of trust, review sentiment, and the quantity and timeliness of reviews, the research aims to understand how these factors influence consumer decisions. By using regression model, findings reveal that negative reviews, timely feedback, and a higher volume of reviews positively affect consumer purchase decisions, while course pricing demonstrates an inverse relationship. Furthermore, cognitive and affective trust mediate the relationship between reviews and purchase behavior, highlighting a reverse U-shaped effect on consumer decision inclination. These insights provide valuable implications for online education providers, emphasizing the need to manage and leverage online reviews to foster consumer trust and improve sales performance.

I. Introduction

As China's economy has rapidly progressed and material needs have been met, people have begun to pursue spiritual enrichment. The rapid development of information technology has also brought great convenience, leading to a major reform in learning methods. The ways to acquire knowledge and improve skills have become increasingly diversified, such as remote teaching through mobile devices or personal computers, enabling people to access educational courses online. With the advent of the post-pandemic era, online education courses as an emerging learning model have become popular, attracting more and more consumers.

At the same time, the anxiety of acquiring knowledge has driven people to accelerate their self-improvement. However, the massive amount of information has further exacerbated the cognitive burden on users when screening content. Paying for quality courses has gradually become an expectation of learners, and the knowledge payment model has also gained consumer recognition[1]. According to data released by iResearch Consulting Group, about 30% of Tencent Classroom users are willing to pay for video courses, and in 2019 alone, the cumulative payment for IT, Internet, and e-commerce marketing courses exceeded 3,000 yuan. Users' attention to paid course content has steadily increased, with about 60% of users listing course quality as the most important decision factor[2]. The increase in willingness and behavior to pay further drives the development of the paid online course market.

However, the expansion of paid online courses has also exposed some deficiencies, such as uneven content quality and fees that do not match the value of the courses[3]. Especially after the government introduced relevant regulatory policies, consumers have become more cautious in their knowledge payment decisions. Therefore, improving consumer trust and increasing course sales have become urgent tasks [4].

Consumers pay for online courses out of an intrinsic need for knowledge expansion and self-development. Online courses further enhance the learning experience through visual support [5]. Unlike paid video-on-demand or video game entertainment products, consumers usually have more specific goals when choosing online courses. In order to make wise decisions, they need to obtain additional information before confirming the value of a course. Paid online courses are typical experience products with significant quality uncertainty, and can only be evaluated through reviews from existing consumers [6]. Therefore, in the decision-making process, one of the key goals for consumers is to review online course information to predict quality, reduce uncertainty, and mitigate pre-purchase risk. This study explores how online reviews, as the main text information, affect consumers' trust in the quality of such educational products. Unlike previous research that broadly examines online reviews across various industries, this study focuses on the educational sector, particularly in the Chinese market. The study also uniquely investigates the dual role of cognitive and emotional trust in mediating the relationship between online reviews and purchase behavior, offering nuanced insights into the psychological mechanisms behind consumer trust and its impact on purchase decisions in online education. Based on the research findings, this paper aims to provide effective management suggestions for relevant platforms, institutions, and content creators, which constitutes an important research significance.

II. Literature Review

1. Online Reviews

Online reviews are information provided by consumers that describe the quality experience and characteristics of a product, including the reviewer's identity, review content, and posting time. Scholars have explored the role of online reviews in various application areas. For example, Zhu Jing analyzed online reviews for fresh fruits on JD.com and extracted text topics such as "product quality", "logistics service", and "packaging", discussing their impact on consumer purchasing behavior [7]. Peng (2020) investigated the influence of online reviews on consumer booking behavior on the Xiaozhu short-rental platform, extending the research scope to the shared accommodation field in the tourism service industry [8]. Yang et al. (2018) analyzed factors such as the number of reviews and ratings, concluding that online word-of-mouth has a positive impact on movie box office revenue. From a research perspective, scholars mainly focus on the impact of online reviews on user satisfaction and purchasing decision factors. Chang and Yang (2020) discussed the impact of sentiment polarity in online education product reviews on consumer usage intention, suggesting that review sentiment may differ for different online education products [9]. Wang (2020) proposed a consumer psychological attachment purchase decision model through a questionnaire survey [10]. Sun et al. (2019) conducted a questionnaire survey of college students and used factor analysis to explore factors influencing their purchase of online courses [11].

Through online reviews, consumers can learn about others' usage experiences and emotional attitudes towards purchased products, thereby reducing uncertainty and enhancing trust. The text quality of online reviews, the conveyed sentiment orientation, or structured attributes may all influence consumers' purchasing decisions.

2. Trust Theory

Trust has long been a research hotspot across disciplines. Currently, the academic focus is on consumer trust in online sellers. Previous research has emphasized the importance of online trust for consumption and purchase decisions, with most scholars believing that trust helps promote transactions and reduce consumers' perceived risks [12][13][14]. Trust transfer refers to an entity's trust in a third party being transferred to others, causing them to also trust that third party. Some scholars have pointed out that in the three-party transaction process involving Taobao sellers, existing consumers, and potential consumers, consumers are more likely to trust sellers when existing consumers act as adjacent nodes. Therefore, when consumers face products with high uncertainty factors, they tend to seek product information from existing buyers to reduce purchase risks and enhance trust [15]. Li (2016) research on consumers' willingness to pay for courses on online education platforms verified the positive impact of perceived trust on users' payment intention, indicating that user trust effectively influenced their willingness to pay [16]. When analyzing the relationship between review information characteristics and impulsive buying, Wang (2020) proposed that trust played a mediating role in the influence of online reviews on customers' impulsive buying behavior [17]. In exploring the mediating role of trust and perceived usefulness, Jorge Matute et al. (2016) ve proposed that if consumers perceive online reviews as trustworthy, reviews will help their purchase decisions, making them more inclined to use this information to make decisions, thus forming trust transfer [18][19].

Online reviews play a key role in eliminating consumer information uncertainty, conveying quality information, and gaining consumer trust. Compared to other industries, the quality of online course content is highly opaque, and knowledge-based products often do not provide refund services. Combining the characteristics of knowledge payment and educational significance, consumers will be more cautious in the decision-making process. Potential consumers with purchase intentions will browse course information on the platform, and existing reviews convey quality information, which is an important basis for establishing consumer trust. Previous research on the purchase of online education courses has focused on consumer purchase intention and satisfaction, but there is limited analysis of the trust pathway between online reviews and consumer decision-making. Additionally, review text, which is an important reference for consumer decisions, also has an impact on their decisions, but these aspects have not been thoroughly researched and analyzed. Therefore, this paper draws on trust transfer theory, analyzes online reviews, and attempts to summarize the attributes of online reviews and the effect of trust on influencing consumer purchase decisions.

III. Research Hypotheses and Theoretical Model

Based on the online review features proposed by previous scholars and the characteristics of online education reviews, this paper will analyze the impact of online review attributes on consumer trust and purchase decisions. The model is illustrated in Figure 1.

Fig. 1. Model of Factors Influencing Online Course Payment Behavior

1. Poor Reviews

Liao Junyun and other scholars propose that if the distribution of online review information tends to be uniform, it indicates that users have also collected product-related information uniformly, and thus they are more likely to trust such review information. In other words, negative reviews may affect product sales. Some scholars also refer to negative reviews as "one-sided reviews", referring to whether consumers' reviews are one-sided (containing only one aspect) or two-sided (including both positive and negative aspects). Many studies have shown that reviews containing both positive and negative information are considered highly persuasive and credible. When review information includes the pros and cons of a product, it can enhance the completeness of the review. This effect can be explained by attribution theory, because two-sided information can reduce consumer uncertainty, thereby increasing the credibility of the information. Therefore, negative reviews may affect consumers' perceived trust in reviews, which in turn affects their purchase decisions.

H1: Poor reviews will affect the sales of online courses.

2. Number of Reviews

The prevalence of online comments has given rise to the concept of "comment count," which represents the sum of numerical feedback typically displayed at the top of comment pages. This metric to some extent reflects the commercial performance of specific goods. According to the persuasion effect theory, when an article receives a large number of comments, customers perceive it as a sign that the product is widely purchased. Furthermore, buyers are willing to allocate time and cognitive resources for evaluation, demonstrating their recognition of product quality. Thus, as the number of reviews increases, consumers' confidence in the product and their willingness to purchase it also correspondingly increase.

H2: The quantity of online course evaluations will impact their sales.

3. Timeliness of Reviews

Previous research has indicated that scholars generally believe that reviews significantly influence consumers' decisions. Due to its specificity, the timeliness of reviews in online education can be measured by the total duration of learning the course by learners. An important feature of course products is their lifecycle. Timeliness has profound effects on the sales of online content products, as the accumulated value of feedback received for a course is crucial to consumers' purchasing decisions. Therefore, we propose H3.

H3: The timeliness of reviews for online courses affects their sales.

4. Course Price

Compared to other knowledge-based paid products, online paid courses tend to have relatively higher prices, thus exacerbating the issue of information asymmetry. Existing research has explored both the negative and positive impacts of prices. From a positive perspective, price is positively correlated with quality, which fosters consumer trust in the product. However, from a negative standpoint, price is associated with costs, and consumers weigh trust signals conveyed through online reviews when considering purchases. When consumers perceive prices as exceeding the benefits they expect, they may abandon their purchases. Scholars generally believe that the negative impact of price is more significant, although some have noted that for different types of products, the net benefits may be positive. For knowledge-based paid products like online courses, price may be a more critical factor as it relates to costs and expenses.

H4: Course price affects the sales of online courses.

In previous studies, scholars have generally believed that consumer trust is closely related to their purchasing decisions. Consumers are more willing to make purchases when they trust a product, especially in situations where quality is difficult to assess, and services are non-refundable; more purchases indicate a higher level of trust in the merchant. Trust can be measured along two dimensions: cognitive trust and affective trust. Cognitive trust is based on consumers' rational perceptions of a merchant's capabilities, while affective trust stems from consumers' perceived benevolent feelings. Previous research has confirmed that both cognitive trust and affective trust influence consumer decisions. Some scholars have proposed that longer reviews, containing more information, are more conducive to building trust, but excessive length increases consumers' cognitive costs. Conversely, overly concise reviews contain less cognitive information and fail to adequately convey the reviewer's understanding of the course. In a study on an experiential product (hotels), Shi Xu found that reviews that allow consumers to quickly understand the core content are more conducive to decision-making. Therefore, the information consumers gather from online reviews should not only support their decisions but also match their cognitive abilities to avoid information overload. Some scholars classify online reviews based on emotional polarity and analyze the relationship between reviews with different emotional tendencies and consumer decisions. Some studies indicate that people tend to purchase online courses that have received long-term positive reviews. On the other hand, for experiential courses, some research suggests that negative reviews are more important and credible, especially in educational online courses, where over 90% of reviews are positive and approximately 50% of courses achieve 100% satisfaction. However, some scholars believe that negative reviews from users of experiential online education products may be influenced by personal bias and have a lower impact. Therefore, the influence of emotional sentiment in reviews on consumer decisions regarding educational online courses requires further analysis. This study will explore this issue from an inverted "U-shaped" perspective.

Thus, we propose the following hypotheses:

H5: Cognitive trust has an inverted "U-shaped" effect on consumer purchasing decisions.

H6: Affective trust has an inverted "U-shaped" effect on consumer purchasing decisions.

IV. Empirical Study

1. Data Source

The data used in this study is sourced from the Tencent Classroom online course platform. According to a report by iResearch, as of 2021, Tencent Classroom has partnered with over 300,000 institutions, and the peak number of students attending classes during the epidemic period can exceed 23 million, with over 30% of paying consumers enrolled in IT, design, and language study courses. Therefore, this study utilized web scraping techniques (such as Octopus and Python) to collect basic information and textual comments for seven major categories of courses on the Tencent Classroom platform up to June 2021. After data cleaning and preprocessing, we obtained a total of 274 course information records and over 30,000 comments for hypothesis testing in this study. Following reliability checks, the reliability coefficient of the obtained data exceeded 0.7, indicating its suitability for further analysis in this study.

2. Variable Introduction

2.1. Dependent Variable

The dependent variable in this study is the actual sales volume of online courses displayed on Tencent Classroom. For ease of subsequent processing, we standardized the sales volume by taking the logarithm of sales.

2.2. Independent Variables

Comment Dispersion: Comment dispersion indicates the degree of variability in course evaluations. In this study, it is measured by the standard deviation of star ratings in each course's reviews. Since the platform does not display star ratings for courses, we manually annotated them and calculated the overall star rating for each course, from which we derived the comment dispersion.

Comment Timeliness: Comment timeliness refers to the time span covered by each comment. The comments displayed on the platform include timestamp information. We converted the time of students attending classes into minutes and calculated the mean to measure the comment timeliness for each course.

Comment Quantity: The Tencent course platform intuitively displays the real-time number of comments for each course. During data scraping, we collected this information to represent the quantity of comments for each course.

Cognitive Trust: Cognitive trust refers to the extent of users' trust in the professionalism of the course. By analyzing the topics covered in online reviews, including evaluations of teachers, course content, learning experiences, etc., we established a dictionary of words to measure cognitive trust. We measured the coverage of key words in each course's reviews to gauge the professional information reflected in online comments and included it in the model for validation.

Affective Trust: Affective trust represents users' emotional perceptions of the course. By analyzing sentiment words in online review texts, we calculated the positivity and negativity of each comment and normalized them. Finally, we used the average sentiment trust value for each course to represent affective trust and included it in the model for validation.

For detailed variable definitions and descriptions, please refer to Table 1.

Table 1. Variable Definitions and Descriptions

3. Data Analysis Conclusion

3.1. Correlation Analysis

Hypothesis testing was conducted using SPSS20 software, and the results are shown in the table below. According to the correlation test results, online comment dispersion, online comment timeliness, online comment quantity, and course price all have a significant impact on online sales volume. Therefore, hypotheses H1, H2, H3, and H4 are all validated. For specific test results, please refer to Table 2.

Table 2. Correlation Coefficients of Latent Variables

3.2. Mediation Effects of Trust

This study employed the method used by Mozan scholars in verifying the mediation effects of comment credibility and conducted regression analysis using SPSS20. The results of the model regression analysis are shown in Table 3. [34].

Table 3. Model Regression Results

In the models 1 to 4, the variable factors and intermediate factors were respectively put in, while model 5 was the complete model obtained by adding all explanatory variables. The results show that all models are significant, and the indicators are at reasonable levels. Comparing the indicators in models 1 to 4 with those in model 5, it is found that cognitive trust and affective trust have significant mediation effects (significance level is 0.05) in the relationship between comment dispersion, comment timeliness, comment quantity, course price, and consumer payment decisions, and the regression coefficients of the variables are slightly reduced. This indicates that cognitive trust and affective trust partially mediate the relationship between comment dispersion, comment timeliness, comment quantity, course price, and consumer payment decisions. Therefore, hypotheses H5 and H6 are validated.

V. Discussions

1. Research Conclusion

Online courses, as typical experiential products, have utilities that are relatively difficult to measure. Consumers' judgments of course quality rely more on the accumulated online reviews. This study validates the impact of online reviews and prices on potential consumer decisions. In addition to analyzing structured data from online reviews, this study also analyzes the textual content of online reviews and calculates cognitive and affective levels of the content, further expanding the application of trust theory.

Online reviews play a significant role in influencing sales volume by increasing consumer trust levels. The quantity of online reviews has a significant positive impact on the sales volume of online course products. The more reviews there are, the better consumers can be persuaded to believe that the course quality meets their needs. The relationship between the dispersion of course ratings and online sales volume also shows a significant positive impact. This reflects the characteristics of experiential products, where multifaceted reviews can provide consumers with richer information, making them more inclined to trust the course product and thus make a purchase decision. In addition, there is also a significant positive relationship between comment timeliness and online course sales volume. The longer the reviewer learns the course, the more authentic and complete the experience reflected in the comment, which plays a greater role in enhancing consumer trust and purchase intention.

However, price has a negative impact on sales volume as it represents the transaction cost borne by consumers. Higher prices may have a negative impact on consumers, leading to a decrease in purchase intention. Therefore, course platforms should pay attention to formulating reasonable pricing strategies to meet the needs and expectations of consumers, thereby increasing sales volume.

Furthermore, cognitive trust and affective trust have a U-shaped effect on sales volume, indicating that overly complex or extreme emotional comments can affect consumer trust and purchase intention. Therefore, platforms should encourage users to post genuine and neutral reviews, avoid artificially manipulating review distribution, and enhance consumer trust.

In conclusion, this study has important theoretical and practical significance for understanding the factors affecting online course sales volume and the trust mechanism in consumer purchase decisions. For managers, they should pay attention to the diversification of review ratings, the importance of review quantity, reducing user cognitive costs, and the rationality of pricing to improve the quality of course content and user experience, and promote the increase in sales volume.

2. Limitations

This study has several limitations:

Limitation of single-platform selection: This study selected a single online course platform - Tencent Classroom - as the research object. Although Tencent Classroom is one of the platforms providing the richest courses in the field of online education, its user base, course institutions, and course information may differ from other platforms (such as NetEase Cloud Classroom). Therefore, whether the research conclusions of this study are applicable to other platforms needs further verification.

Cross-sectional data limitation: This study analyzed cross-sectional data, while users' commenting behavior and payment decisions are dynamic processes. The historical information of the course may affect consumers' purchasing decisions when they choose to pay. Therefore, there are certain limitations in reflecting this dynamic process in this study.

Limitation of courses with sales but no comments: On the Tencent Classroom platform, there are also some courses that have sales but no comments. For these types of courses, this study did not further explore the factors affecting their sales. Future research can further explore the characteristics of these courses and their influencing factors.

In summary, although this study has achieved certain research results, there are still limitations in platform selection, data collection, and research methods. Future research can consider expanding the research sample, using more diverse data collection methods, and combining richer research designs to comprehensively understand the factors influencing the sales volume of online courses.