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Jia, Y.; Feng, H.; Wang, X.; Alvarado, M. Cross-Platform User-Generated Content. Encyclopedia. Available online: https://encyclopedia.pub/entry/47997 (accessed on 26 December 2024).
Jia Y, Feng H, Wang X, Alvarado M. Cross-Platform User-Generated Content. Encyclopedia. Available at: https://encyclopedia.pub/entry/47997. Accessed December 26, 2024.
Jia, Yiwu, Haolin Feng, Xin Wang, Michelle Alvarado. "Cross-Platform User-Generated Content" Encyclopedia, https://encyclopedia.pub/entry/47997 (accessed December 26, 2024).
Jia, Y., Feng, H., Wang, X., & Alvarado, M. (2023, August 13). Cross-Platform User-Generated Content. In Encyclopedia. https://encyclopedia.pub/entry/47997
Jia, Yiwu, et al. "Cross-Platform User-Generated Content." Encyclopedia. Web. 13 August, 2023.
Cross-Platform User-Generated Content
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This entry is adapted from the peer-reviewed paper 10.3390/jtaer18030064

User-generated content (UGC) from e-commerce platforms and third-party platforms can impact customer-perceived risk and influence product sales in online stores. However, the understanding of UGC from which platform type yields a stronger effect on product sales and how the effects interact across the platforms remains limited, especially from a cross-platform UGC perspective. 

cross-platform UGC sentiment analysis elaboration likelihood model

1. Introduction

Online shopping offers consumers the convenience of shopping from anywhere at any time without the need to visit physical stores. However, it also poses challenges for consumers who cannot physically inspect products before buying, leading to greater pre-purchase uncertainties and risks, particularly for experiential products. Experiential products are products like cosmetics, skincare, and clothes, which often lack clear and specific quality evaluation standards, making it difficult to compare their intrinsic product characteristics [1]. Experiential products have high information acquisition costs [2][3][4], and shoppers often rely on subjective or personal experiences to determine perceived quality [5]. To mitigate such perceived risks, online shoppers seek additional information [6], with user-generated content (UGC) being an important source of such information. UGC, which refers to any content created by users and primarily distributed on the Internet [7], is becoming increasingly prevalent [6][8][9] and can help reduce pre-purchase uncertainties and risks associated with experiential products.
UGC, in the form of product evaluations, can be classified into two types based on their sources. The first type is online reviews generated by other buyers that can be found on the seller’s e-commerce platform. This type of review is a relatively passive source of information that online shoppers can easily obtain. The second type of UGC is product evaluations that are hosted on third-party platforms [10][11][12][13], such as blogs, vlogs (video-blogs), which need to be actively sought out by consumers. Bilibili, TikTok, Consumer Reports, and TechRadar are examples of popular third-party platforms that provide consumers with the second type of UGC to aid in making online purchase decisions.
While existing literature has explored the impact of UGC from both e-commerce and third-party platforms (i.e., cross-platform) on product sales [14][15][16], there is a discrepancy in the research findings regarding the influence of UGC on product sales between these platforms. There is still no consensus on which platform’s UGC has a stronger impact. On the one hand, some studies suggest that product reviews posted on non-commercially affiliated platforms (i.e., third-party platforms) are perceived as more credible than those on seller-affiliated platforms (i.e., e-commerce platforms), consequently having a greater impact on consumer decision-making [15][17]. In particular, some studies have indicated that, compared to their counterparts on e-commerce platforms, third-party platform UGC has a higher impact on the sales of high-involvement products [18]. For example, Gu et al. [15] compared UGC from Amazon (e-commerce platform) to that from three third-party platforms (CNET, DpReview, and Epinions) and found that third-party UGC had a significant impact on the sales of digital cameras, while UGC on the e-commerce platform did not exhibit a similar effect. On the other hand, some scholars have pointed out that the accessibility of information can affect consumers’ judgments of its usefulness, where information received earlier or easier is perceived to be more useful [19][20]. For example, Song et al. [16] confirmed that the enterprise microblogging UGC has stronger predictive power for movie box office revenue than the UGC on Douban! Movies, which is a third-party platform, as it is easier for customers to receive the former information earlier.
However, despite these divergent insights, the existing literature has not thoroughly examined the underlying mechanism that influences the impact of cross-platform UGC, encompassing UGC from both e-commerce platforms and third-party platforms, on product sales. Specifically, the reasons for the varying effects of UGC across platforms have yet to be fully elucidated, making it challenging for businesses to directly apply the findings of relevant research in their marketing practices.

2. Theoretical Model

Here focuses on the impact of cross-platform UGC on experiential product sales, specifically examining the differential effects between UGC on e-commerce platforms and UGC on third-party platforms. The underlying mechanism behind these differences is explored. The focus is on cosmetic products, which represent a typical experiential product. When consumers select cosmetic products on e-commerce platforms, they primarily encounter two different types of UGC (i.e., cross-platform UGC):
  • E-commerce platform UGC: online reviews on mainstream e-commerce platforms (such as Tmall, JD, and Amazon), primarily comprise detailed textual product reviews shared by users who have previously made purchases. These reviews are accompanied by high-quality evidence directly linked to the transactions.
  • Third-party platform UGC: product evaluations on third-party platforms (such as Bilibili, TikTok, and TechRadar), which provides users with peripheral clues about products and is considered a more reliable source [15][17], encompassing various formats such as video blogs and images.
In the given scenario, which type of UGC would have a greater impact on consumers’ purchase decisions? Furthermore, why do different platforms show variations in the influence of UGC on consumers’ purchase decisions? These questions are the focal point since consumers’ purchase decisions ultimately manifest as sales on e-commerce platforms. The elaboration likelihood model (ELM) is a dual-process theory, which is often used to explain people’s cognitive processes and decision-making mechanisms when accepting and processing information [21][22]. ELM theory suggests that external information (such as, but not limited to UGC) is a significant factor in driving attitude change and subsequent behavior change [23][24]. The core idea of ELM is that individuals employ two different processing paths, namely the central path and the peripheral path when making decisions. The central path refers to the process of carefully considering the argument quality and evaluating it. Argument quality refers to an individual’s perception of the strength and soundness of the arguments presented in a message, as opposed to weak and deceptive ones. On the other hand, the peripheral path involves drawing conclusions based on heuristics or relying on cues such as source credibility (i.e., peripheral cues), without critically evaluating the actual merits of the argument [21][25]. Based on the principles of the ELM and the characteristics of cross-platform UGC in e-commerce platforms, it is suggested that UGC on the e-commerce platform, which is associated with argument quality, should be processed through the central path. On the other hand, third-party platform UGC, which is primarily related to peripheral cues, should be processed through the peripheral path. Furthermore, individuals who choose the peripheral path typically either lack the desire or are unable to invest the cognitive effort required for elaboration [26].
The ELM offers a conceptual basis for investigating attitude and persuasion [26]. According to the ELM, recipients of information vary in their ability and motivation to engage in elaboration, which influences the path they use to process information, subsequently affecting the formation or change of their attitudes. The ELM captures this variation in ability and motivation through the construct of elaboration likelihood [24].
It allows for a comparison of different types of UGC and a clearer determination of the role (i.e., argument quality or peripheral cues) each type plays in persuasive information processing. Ultimately, this approach will uncover the mechanisms through which different types of UGC influence product sales. Specifically, researchers utilize ELM theory as The theoretical framework for the following reasons: Firstly, ELM is widely recognized and extensively used in the field of persuasion and information processing [23][27][28]. It provides a comprehensive understanding of how individuals process and evaluate persuasive messages, considering both central and peripheral paths of information processing. Secondly, ELM is a quintessential dual-process model [21][22][25], and it is particularly suitable for The research focus on electronic commerce and the influence of cross-platform UGC on product sales. ELM helps people analyze the impact of UGC on consumer decision-making in different scenarios, such as e-commerce platforms and third-party platforms. By employing ELM, researchers can compare and contrast the effects of different types of UGC and gain insights into the underlying mechanisms behind their influence on product sales. Lastly, ELM offers a systematic framework to examine the role of factors such as motivation, cognitive abilities, and message characteristics in information processing.
In The research, according to the ELM, when faced with cross-platform UGC, customers may employ different processing paths, namely the central path and the peripheral path, based on their motivation and elaboration ability to process information. These differential processing strategies are expected to influence customers’ attitudes, which in turn will impact their purchase decisions. The conceptual model of the research, which is based on the cross-platform UGC perspective and ELM theory [21][24], is illustrated in Figure 1.
Jtaer 18 00064 g001 550
Figure 1. Conceptual model.
Although online reviews on e-commerce platforms and product evaluations on third-party platforms both belong to UGC, they come from platforms of different natures and have different impact paths on consumers under the ELM framework. As an important form of UGC, online reviews significantly impact consumer purchase decisions and product sales [29]. When judging the usefulness of online reviews, consumers usually consider the extremity and depth of the reviews [30], which can be measured by review inconsistency [14] and review length [31], respectively. In addition to online reviews on e-commerce platforms, consumers can also obtain product evaluation information from third-party platforms to guide their consumption decisions. However, it is difficult for consumers to directly use the length and inconsistency of online reviews on e-commerce platforms as a reference for their decisions. The length and inconsistency of online reviews on e-commerce platforms can only be processed when consumers have sufficient motivation and sophisticated information processing capabilities, during which the central path assumes a dominant persuasive role. Therefore, the length and inconsistency of online reviews, which belong to the e-commerce platform UGC, tend to be processed through the central path. On the other hand, third-party platforms are relatively more objective and neutral. User-generated product evaluations on third-party platforms are mainly presented in the form of videos, which contain richer and more intuitive information. Consumers do not need a high level of information processing capability and are more likely to resonate emotionally with the content creators, which can lead to purchase decisions. Moreover, the more evaluation videos on the product, the easier it is for consumers to obtain its experiential information. Therefore, the number of product evaluation videos, which belong to the third-party platform UGC, tends to be processed through the peripheral path.
To clarify how cross-platform UGC affects consumer purchase decisions and sales for experiential products, this builds a research model based on the conceptual model in Figure 1, and the research model is illustrated in Figure 2. The central path focuses on the impact of online review length and online review inconsistency on product sales on e-commerce platforms. The peripheral path investigates the impact of the number of product evaluation videos on third-party platforms on product sales. Additionally, cross-platform UGC may influence sales by affecting consumers’ purchase intentions [27], which are highly responsive to pricing [32][33]. For instance, Monroe [34] demonstrated that customers have absolute thresholds for prices, and when a price surpasses these upper or lower thresholds, customers will decline the purchase due to the price. Therefore the model explores the mediating effect of purchase intention and the moderating effect of the product price on the relationship between cross-platform UGC and product sales. Moreover, store rating is included as a control variable to eliminate the influence of store dimensions on product sales, as consumers often use store rating as an important reference for consumption decisions [35][36].
Jtaer 18 00064 g002 550
Figure 2. Research model.

3. Impact of Cross-Platform UGC on Product Sales

3.1. Impact of Central Path UGC on Product Sales

Online review length can impact product sales in two ways. Firstly, the length of online reviews can be measured by the total number of words or characters in the review [37][38]. The longer the average review length, the more detailed information about the product or service it contains, and the more useful consumers perceive it [39]. This can help consumers better understand the product or service, positively impacting product sales. Secondly, experiential products have significant individual differences in user experience and effects. Consumers tend to pay more attention to online reviews rich in content and detail. Longer reviews convey more information, which makes it easier for consumers to reduce the risk of purchasing errors due to a lack of product user experiences. Consumers are more likely to uncover omitted details in longer reviews [38]. This notion is supported by Bosman et al. [40], who confirmed that the length of reviews is a dependable gauge of their credibility.
Review inconsistency refers to the extent of sentiment consensus among reviewers on product evaluation, with lower consensus leading to higher review inconsistency [41]. In particular, when consumers are extremely satisfied or dissatisfied, they are more likely to post reviews online, resulting in a bimodal distribution of user ratings [42]. When faced with reviews with high levels of inconsistency, most consumers attribute it to unstable product quality, particularly for experiential products. Consumers tend to be more cautious in purchase decisions. In addition, the inconsistency of online review information can also exacerbate the uncertainty of online shopping environments, leading to a reduced likelihood of product purchasing behavior [43]. For experiential products, the inconsistency of consumer evaluations expressed in reviews can have a negative impact on product sales [44].

3.2. Impact of Peripheral Path UGC on Product Sales

User-generated content often expresses users’ attitudes toward a product. It can help shape other consumers’ perceptions of product quality, which influences their purchase intentions and decisions, known as the recommendation effect [45]. For consumers, third-party UGC platforms can provide more important information about products or brands that cannot be directly observed. Consumers tend to purchase products that attract numerous reviews [46]. For example, marketers can use YouTube beauty channels to provide alternative experiences (i.e., product evaluations) for cosmetic consumers, thereby reducing consumers’ perceived risks and enhancing their purchase intentions [47]. On the other hand, the products with many reviews on third-party platforms indicate their popularity among consumers or a large user base. This suggests that the product is reliable and of good quality, which can stimulate potential buyers’ demand [48]. In addition, vloggers on third-party platforms are more willing to show their pleasant usage experiences and high-quality products to audiences to gain more collections, follows, and shares. Therefore, the number of third-party platform product evaluations also represents consumers’ affirmation of the quality and usage experience of the product to some extent, and products with more third-party platform product evaluations are more likely to be purchased by consumers.

3.3. Mediating Effect of Purchase Intention

The consumption behavior of individuals is a series of reactions in which individuals, influenced by external stimuli, including information, undergo a series of difficult-to-measure psychological changes, resulting in a willingness to purchase and a series of corresponding purchase behaviors. Consumer purchase intention represents the likelihood of an individual purchasing a particular product, with high purchase intention indicating a high likelihood of purchase and low purchase intention indicating a low likelihood of purchase. UGC for experiential products serves as sensory cues that can be used as external stimuli to induce audience engagement, increase their purchase intention [49][50], and increase the likelihood of consumers making purchase decisions when their purchase intention is high enough.
Specifically, informative and commendable online reviews, typically characterized by lengthier reviews, serve to mitigate shopping uncertainty and bolster consumer purchase intention, thereby playing a crucial role in increasing market demand or product sales [51]. In addition, the sentiments expressed in product evaluations, which mainly affect consumers’ purchase intention, significantly impact the future sales performance of the product [52][53][54]. Hence, review inconsistency can potentially escalate consumers’ perceived risk, impede their purchase intention, and subsequently lower product sales. On the other hand, the greater the number of UGC on third-party platforms for a product, the more consumers trust the quality of the product, and the increased trust leads to a stronger intention to purchase, which in turn increases the likelihood of making a purchase decision [46][48].

3.4. Moderating Effect of Product Price

Previous research suggests that product price positively moderates the relationship between online reviews and product sales, primarily through its promotional function and use as a signal of quality [55][56]. Generally, prices can act as a promotion tool, with low prices stimulating consumer willingness to purchase and high prices suppressing it [57][58]. However, prices can also convey a product’s quality signal. Higher prices potentially indicate that the product has better quality compared to similar products, thereby enhancing consumer willingness to purchase. The quality signaling function of price contributes to reinforcing the impact of UGC on sales to a certain extent. For example, the longer online reviews of high-priced products may lead consumers to perceive the product as popular and of high quality, thereby positively influencing product sales.
Compared to purchasing low-priced products, consumers who purchase high-priced experiential products tend to have a higher perception of product risk, which may result in a greater perceived loss. Campbell and Goodstein [59] found that as perceived risk increases, consumers tend to become more cautious and pay greater attention to risk avoidance strategies. Therefore, when it comes to higher-priced products, consumers tend to be more cautious in their purchase decisions and are more sensitive to inconsistent online reviews. As a result, sellers can mitigate the negative impact of inconsistent reviews on sales by offering price reductions. The promotional effect is expected to offset the adverse effects of unfavorable reviews [56].
Perceived product risk, which comes from the decision to purchase high-priced products, can promote risk-avoidance behavior in online consumers. This may result in them spending more time referring to the product information provided by information retrieval systems or third-party platforms [60]. Therefore, when consumers are faced with high-priced products, they are more motivated to refer to product evaluations on third-party platforms, in addition to online reviews on e-commerce platforms, and to synthesize cross-platform UGC generated from central and peripheral paths in order to facilitate the formation of purchase decisions and strengthen the impact of third-party platform UGC on sales. Moreover, a higher quantity of UGC on third-party platforms for a product indicates that additional information about the product is more easily accessible to consumers. As price serves as a signal of quality, consumers are more likely to trust the quality of high-priced products. Hence, the impact of the quantity of third-party platform UGC on the sales of high-priced products is more significant.

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Yiwu Jia
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Haolin Feng
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Xin Wang
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Michelle Alvarado
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