The Impact of UGC on Consumer Decision Paths

Mengya Yue

School of Management, Guangdong University of Technology, Guangzhou, China

Keywords: User-Generated Content (UGC), Consumer Decision Journey, Dynamic Influence Mechanisms.

Abstract: In the digital era, user-generated content (UGC) is pivotal to consumer decisions, with over 70% of buyers

referencing UGC pre-purchase. While prior research emphasizes static impacts, this study dynamically

examines UGC’s role across decision stages (awareness, interest, consideration, purchase, after-sale) via

literature review. Findings reveal UGC reshapes decision paths through “information-emotion-social identity”

mechanisms: capturing attention via authentic visuals (awareness), fostering emotional engagement (interest),

reducing risk through comparisons (consideration), leveraging social proof (purchase), and amplifying loyalty

via post-purchase sharing (after-sale). Key contributions include a dynamic UGC model and critiques of

fragmented cross-platform analyses, sample biases, and overlooked negative feedback. Future research should

integrate cross-cultural comparisons and AI-driven sentiment analysis. Practically, brands must adopt an

“incentive-audit-analysis” framework to balance authenticity and engagement, optimizing decision journeys.

This study advances UGC theory with a dynamic, holistic lens, offering insights for Web3.0-era multi-

scenario marketing strategies. Future research directions are proposed to guide subsequent investigations in

this evolving field.

1 INTRODUCTION

In the digital era, where technological advancements

are continuously transforming consumer ecosystems,

user-generated content (UGC) has become a pivotal

source of information, profoundly shaping brand

perception and purchase decisions. UGC

encompasses a wide range of content formats,

including reviews, videos, images, and social media

challenges, contributed by ordinary consumers, key

opinion leaders (KOLs), and celebrities. According to

Statista (2023), global social media users surpassed

4.8 billion in 2023, with over 70% of consumers

referencing UGC before purchases. For example, on

Xiaohongshu, more than 80% of beauty product

consumers reviewed UGC prior to purchases in 2023.

Sharing product recommendations and authentic

experiences not only boosted sales but also enhanced

brand-consumer interactions, underscoring UGC’s

pivotal role in modern marketing(Qin et al., 2024).

Despite its recognized importance, existing studies

predominantly focus on UGC’s static impacts within

isolated stages, leaving its dynamic mechanisms

across the entire consumer decision journey

underexplored. This study addresses the core question:

How does UGC continuously influence consumer

behavior across decision stages?

By systematically examining UGC’s mechanisms

throughout the consumer decision journey, this study

investigates its role in the key stages of awareness,

interest, consideration, purchase, and post-purchase

behavior. Through a comprehensive literature review,

it synthesizes current findings on UGC’s impact and

provides an in-depth analysis of its mechanisms in

shaping consumer decision-making. The study’s

findings offer theoretical insights for brands to refine

UGC strategies, enhance consumer engagement, and

strengthen brand loyalty.

2 MOTIVATION FOR UGC

GENERATION

2.1 Social Demand Drives Content

Creation

According to Tajfel and Turner (1979), individuals

derive self-esteem from group membership, which

aligns with users' motivations to share UGC on

platforms like Xiaohongshu to reinforce social

Yue, M.

The Impact of UGC on Consumer Decision Paths.

DOI: 10.5220/0013841900004719

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 2nd International Conference on E-commerce and Modern Logistics (ICEML 2025), pages 219-225

ISBN: 978-989-758-775-7

219

identity. The core driving force behind UGC

generation stems from users' deep needs for social

identity and self-expression(Ferreira et al., 2022).

Consumers build their personal identity and

cultivate a sense of community by sharing product

experiences and lifestyle narratives on social media.

Xiaohongshu, with its "marking life" community

culture, exemplifies how platform design can

stimulate UGC production. Its interactive

mechanisms, such as likes, comments, and follower-

based social engagement-create a positive feedback

loop, reinforcing content creation and sustaining

continuous UGC generation and interaction.

2.2 The Double-Edged Sword Effect of

Economic Incentive Strategies

Economic incentives are an important guarantee to

promote the continuous output of quality UGC. With

the development of the content creator economy,

platforms and brands have greatly boosted creators'

motivation through the establishment of diversified

economic incentives such as creator funds, business

share, and incentive programs for quality creators.

Business-led economic incentives can boost the

number of UGC in the short term, but may weaken

the authenticity and credibility of the content, or even

false content. Studies have shown that monetary

incentives may negatively affect the contribution of

user-generated content (Liu & Feng, 2021). For

instance, e-commerce platforms such as Xiaohongshu

and Taobao encourage users to post positive reviews

through cash incentives (e.g., "Xiaohongshu Creator

Fund") and points-based rewards (e.g., Taobao’s

cashback for positive reviews). However, such

incentives often lead to homogenized, superficial

content (e.g., "swipe reviews"), diminishing the

diversity and depth of user insights.The phenomenon

of false comments triggered by economic incentives

has systematic characteristics. Luca and Zervas (2016)

pointed out that businesses are more likely to post

fake reviews when their reputation is damaged or

competition intensifies, and the extreme nature of

such reviews (such as a high proportion of 1-star or

5-star ratings) is significantly higher than the real

content. For example, on the Yelp platform,

independent restaurants have more than three times

the proportion of false reviews compared to chain

restaurants due to a lack of brand endorsement. This

phenomenon reveals the deep contradiction between

economic incentives and content authenticity, that is,

incentive strategies may distort user motivation,

leading to the 'bad money driving out good money'

effect of the information ecology.

3 REFINING THE FIVE STAGES

OF CONSUMER DECISION

PATH

3.1 Cognitive Stage: Attracting

Attention and Establishing

Preliminary Cognition

The cognitive stage is the stage when consumers first

come into contact with a brand or product, and its

main task is to obtain information and form a

preliminary impression of the brand or product.

Consumers obtain information through multiple

touchpoints during the cognitive stage, which

emphasizes their importance (Lemon & Verhoef,

2016). Modern consumers in the digital age

increasingly rely on peer-generated information, with

82% of shoppers considering UGC crucial during

initial brand discovery phases (Bazaarvoice, 2022).

At this stage, UGC plays a pivotal role in three key

areas: sharing authentic experiences, providing

entertaining content, and utilizing engaging visual

formats (Pop et al., 2022). Research demonstrates

that graphic-textual UGC enhances information

retention through dual-coding mechanisms (Houts et

al., 2006), while short videos leverage dynamic

stimuli to capture attention (Cheng et al., 2010).For

instance, unboxing videos allow consumers to

quickly grasp product functionality and key features,

while humorous, creative, or emotionally engaging

content, such as TikTok’s challenge videos and real-

life scenarios. It further enhances brand visibility.

Additionally, high-quality visuals, compelling

animations, and attention-grabbing headlines amplify

the impact of UGC, distinguishing it from traditional

advertising and fostering a more personalized

consumer-brand connection.

3.2 Interest Stage: Emotional

Resonance and Enhanced Sense of

Participation

The cognitive stage is the stage when consumers first

come into contact with a brand or product, and its

main task is to obtain information and form a

preliminary impression of the brand or product.

Lemon and Verhoef (2016) emphasized the

importance of consumers obtaining information

through multiple touchpoints during the cognitive

stage. UGC, as one of the key touchpoints, plays a

role in this stage through three main ways: sharing

real experiences, entertaining content, and visual

presentation, quickly capturing consumers' attention

ICEML 2025 - International Conference on E-commerce and Modern Logistics

220

(Pop et al., 2022). For example, ordinary users can

help other consumers quickly understand the basic

functions and features of the product by sharing

unboxing videos or pictures of their first use

experience through short videos. Meanwhile, the

humor, creativity, or emotional content of UGC, such

as "challenge videos" or "real-life scenarios" on

TikTok, can effectively attract consumers' attention.

In addition, high-quality graphics, dynamic effects,

and attractive titles also add visual impact to UGC.

These contents break the stereotypes of traditional

advertising and promote consumers to establish a

preliminary understanding of the brand or product

through personalized and life like forms.

At this stage, UGC plays an important role

through emotional content, interactive content, and

entertaining content. Users resonate emotionally with

consumers by telling personal stories and showcasing

how products can improve their lives. For example,

Barta et al. (2023) analyzed TikTok influencer

campaigns and found that humorous and relatable

UGC content (e.g., comedic skits about daily

struggles with skincare routines) generated higher

emotional engagement, with viewers reporting 32%

stronger brand affinity compared to non-humorous

content. Similarly, De Veirman et al. (2017) observed

that Instagram influencers with substantial followings

could stimulate brand interest effectively by sharing

lifestyle-related content, particularly when

incorporating high levels of interactivity.

Engagement mechanisms such as interactive

comments, user challenges, and brand-driven UGC

campaigns further strengthen consumer participation.

Barta et al. (2023) also highlighted the effectiveness

of combining humor with interactivity in TikTok

marketing campaigns, citing L’Oréal’s

#WorthSaying challenge as an example—where

humorous self-affirmation videos led to significantly

higher click-through rates than traditional advertising.

Collectively, these engagement strategies not only

deepen consumer interest but also foster a stronger

emotional connection between brands and their

audiences.

3.3 Consideration Stage: Evaluating

Value and Reducing Decision Risk

As consumers transition from initial interest to a more

evaluative stage, they critically assess product

attributes, comparing alternatives to determine the

best fit for their needs. This stage is characterized by

in-depth analysis of product benefits, trade-offs, and

potential risks (Zhang and Benyoucef, 2016). During

this phase, consumers exhibit a preference for

detailed reviews and image-based content to inform

their decisions (Zhang and Luo, 2023).UGC helps

consumers make more informed choices at this stage

through product evaluation videos, comparative

content, and authentic feedback. Detailed product

evaluations showcase the actual performance of the

product, such as analysis of advantages and

disadvantages, functional demonstrations, etc. For

example, unboxing videos (e.g., unpacking and

testing new products) provide consumers with visual

and experiential insights, reducing uncertainty about

product quality. Research indicates that consumers

who watch unboxing videos for information-seeking

purposes show higher purchase intent, as these videos

offer tangible evidence of product features and

usability (Kim, 2020). Comparative reviews (e.g.,

side-by-side analysis of competing brands) enhance

decision-making by highlighting differences in

performance, price, and user experience. While not

explicitly mentioned in the current literature, the

"consumerism" motive identified in influencer

marketing studies supports this behavior: consumers

actively seek brand comparisons through SMIs to

discover new products and evaluate value

propositions (Lee et al., 2022). Authentic feedback

from ordinary users (e.g., positive and negative

reviews) provides reliable references. The

authenticity of UGC, such as unfiltered user

testimonials or candid experiences shared on social

media, significantly enhances trust in product

information. Studies on social media influencers

emphasize that perceived authenticity directly

correlates with trust in brand-related posts, which in

turn reduces purchasing uncertainty (Lou & Yuan,

2019; Lee et al., 2022).

3.4 Purchase Stage: Inspire Purchasing

Motivation and Enhance

Confidence

The purchasing stage is the stage where consumers

make the final purchasing decision after completing

information evaluation. At this stage, consumers need

sufficient motivation and confidence to complete

their purchasing behavior. UGC drives purchasing

decisions through seeding effects and social proof,

yet their mechanisms vary across platforms like

Instagram and TikTok.

On Instagram, the platform’s emphasis on visual

aesthetics—curated product photography and

aspirational lifestyle posts. It allows influencers to

reinforce social proof via engagement metrics such as

likes, comments, and shares. For instance, skincare

The Impact of UGC on Consumer Decision Paths

221

influencers utilizing swipe-up links to showcase

product applications simultaneously highlight

product functionality and leverage peer validation

(De Veirman et al., 2017; Lee et al., 2022).

Furthermore, authenticity plays a pivotal role: micro-

influencers who provide unfiltered, behind-the-

scenes reviews are perceived as more relatable,

enhancing trust and credibility (Casaló et al., 2020).In

contrast, TikTok leverages algorithm-driven virality

and short-form video dynamics to reshape social

proof mechanisms. The platform’s "For You Page"

algorithm prioritizes discoverability, allowing UGC

like unboxing videos or #TikTokMadeMeBuyIt

challenges to rapidly gain traction. Unlike

Instagram’s polished aesthetics, TikTok’s unfiltered

style (e.g., spontaneous makeup tutorials filmed in

natural lighting) reduces perceived

commercialization, making UGC appear more

organic. This authenticity is further amplified by the

platform’s trend-centric culture, such as the

#GetReadyWithMe trend, where creators integrate

products into daily routines, offering practical

insights that static ads cannot replicate (Ki and Kim,

2019).

Seeding effects also diverge: Instagram relies on

sustained partnerships with niche influencers to build

long-term trust (e.g., fashion bloggers sharing

seasonal wardrobe staples), while TikTok thrives on

ephemeral, user-initiated content. This contrast

highlights how Instagram’s visual curation and

TikTok’s algorithmic spontaneity cater to different

consumer psychographics. Instagram appeals to users

seeking aspirational validation, whereas TikTok

attracts those valuing affordability and relatability.

By tailoring UGC strategies to these platform-

specific dynamics, brands can effectively harness

social proof to reduce perceived risks. Whether

through Instagram’s envy-inducing luxury narratives

or TikTok’s democratized "dupe" culture, the goal

remains consistent: transforming social validation

into purchasing confidence.

3.5 After Sales Behavior and Word-of-

Mouth Communication: Enhancing

Brand Loyalty and Expanding

Influence

The after-sales behavior and word-of-mouth

communication stage is the stage where consumers

influence other consumers by sharing their usage

experience or feedback after purchasing a product.

This stage not only affects the brand's reputation, but

may also lead to secondary dissemination of UGC.

UGC forms a virtuous cycle through user experience

sharing, community interaction, and secondary

dissemination at this stage.

UGC fosters brand loyalty by transforming

passive consumers into active community

participants. Brands leverage platform-specific

features to encourage user-generated content creation.

For example, Instagram’s branded hashtag challenges

(e.g., #ShareYourCoke) invite consumers to

personalize products and share their stories, fostering

a sense of co-creation. Research shows that

participation in such campaigns strengthens

emotional bonds with the brand, as users perceive

their contributions as valued by the community

(Vrontis et al., 2021). Additionally, reciprocal

interactions in comment sections, such as brands or

influencers replying to questions or reposting fan

content—mimic interpersonal relationships. A study

on Instagram influencers found that followers who

received replies to their comments reported higher

trust and loyalty, as these interactions mimic

interpersonal relationships (Lee et al., 2022).

The amplification effect of UGC extends beyond

initial interactions through secondary dissemination.

When consumers voluntarily share reviews, unboxing

experiences, or product recommendations, they

provide implicit social endorsements that enhance

credibility. On Instagram, re-sharing influencer

testimonials with personalized commentary (e.g.,

"This serum transformed my skin!") reinforces word-

of-mouth marketing (Qin et al., 2024).Finally,

authentic UGC that mirrors everyday experiences

builds sustained emotional connections and

relatability. Instagram’s "authenticity motive"

research suggests that users trust such content more

than polished ads, leading to sustained loyalty (Lee et

al., 2022). Similarly, TikTok's trend-driven culture

(e.g., #MomHacks) turns practical UGC into

community-driven knowledge hubs, where ongoing

interaction (e.g., tips in comments) keeps users

engaged long-term.

4 LIMITATIONS OF THE

RESEARCH

Current research on user-generated content (UGC)

exhibits three critical limitations.

First, cross-platform studies remain fragmented,

with most research focusing on isolated platforms

rather than multi-channel interactions. For example,

the divergent effects of short-form videos on Douyin

(TikTok) and long-form textual content on Zhihu

remain underexamined. Existing research (Jia et al.,

ICEML 2025 - International Conference on E-commerce and Modern Logistics

222

2023) highlights significant challenges in processing

multimodal data, such as textual reviews from Tmall

and video content from Bilibili. While the original

study employed text sentiment analysis using the

SnowNLP library, its framework struggled to capture

non-verbal cues in video content (e.g., vloggers’

facial expressions and product demonstration

scenarios), which accounted for only 41.2% of

detectable sentiment information. Furthermore,

platform API heterogeneity—such as mismatches

between Tmall’s product IDs and Bilibili’s AV

numbering system. It resulted in a 23.7% cross-

platform data alignment error rate, potentially

undermining the validity of findings.

Second, methodological biases persist, as existing

research disproportionately samples younger,

digitally active cohorts while neglecting older

demographics. Moreover, the rapid evolution of

platform algorithms, such as TikTok’s 2023 AI-

driven content ranking system, outpaces academic

research cycles, rendering some findings temporally

constrained (Wang et al., 2025).

Finally, insufficient attention is directed toward

longitudinal UGC effects and adverse feedback

mechanisms. Prevailing research prioritizes short-

term conversion metrics while neglecting nonlinear

relationships between UGC exposure and brand

loyalty. Critical phenomena, such as marketing

fatigue induced by overexposure ("oversaturation

fatigue") or the long-tail effects of negative UGC on

brand equity, which remain underintegrated into

theoretical frameworks (Zhu et al., 2024).

Collectively, these gaps obstruct both scholarly

comprehension and practical optimization of the

UGC ecosystem, necessitating interdisciplinary

approaches to address platform heterogeneity,

demographic inclusivity, and temporal-technological

interdependencies.

5 FUTURE RESEARCH

DIRECTIONS

Future research should enhance the exploration of the

mechanisms through which user-generated content

(UGC) operates in cross-cultural contexts.

Consumers from different cultural backgrounds

exhibit significant differences in their information

reception, processing, and decision-making strategies.

For instance, in collectivist cultures, digital

endorsements tend to prioritize emotional appeal,

whereas individualistic cultures emphasize rational

communication. Studies have shown that endorsers in

individualistic societies are more focused on self-

promotion, while those in collectivist societies

emphasize interaction and connection(Silva et al.,

2023). Therefore, a deeper investigation into the

moderating role of cultural factors on the influence of

UGC will assist brands in formulating more targeted

global marketing strategies.

Moreover, advancements in technology-driven

UGC analysis represent a critical avenue for future

research. The emergence of artificial intelligence,

particularly deep learning and natural language

processing, has introduced innovative methodologies

for analyzing UGC content (Jia et al., 2023). These

AI-powered techniques enable researchers to more

accurately identify emotional sentiment, thematic

structures, and influence patterns within UGC,

thereby offering a deeper understanding of its

underlying mechanisms and consumer impact.

6 CONCLUSIONS

6.1 Core Summary of Research

Findings

UGC fundamentally transforms consumer decision-

making processes through a threefold mechanism

comprising information dissemination, emotional

engagement, and social identity formation. This

influence extends beyond mere information

transmission, as UGC fosters deeper consumer-brand

connections through social interaction and emotional

resonance. The role of UGC evolves dynamically

across different decision-making stages: in the early

stages, content authenticity is paramount, while at

later stages, social interaction becomes increasingly

influential. From initial attention capture via short-

form unboxing videos to the organic spread of user-

initiated post-purchase content, UGC facilitates a

multidimensional consumer engagement experience.

6.2 Practical Inspirations for Brand

Strategy

For brands, building a healthy UGC ecosystem is

crucial. Brands need to establish a three in one UGC

management framework of "motivation review

analysis", which encourages consumers to

continuously produce high-quality UGC through

designing reasonable incentive mechanisms,

providing high-quality product experiences, and

establishing effective interactive platforms. At the

same time, brands need to attach importance to the

The Impact of UGC on Consumer Decision Paths

223

authenticity management of UGC, establish a

scientific content review mechanism, and maintain a

good reputation environment. Specific suggestions

include: designing a hierarchical incentive system

(such as reward rules that distinguish between

ordinary users and KOCs), integrating AI false

content filtering systems, and establishing a cross

platform UGC sentiment database to predict

consumer behavior inflection points.

6.3 Academic and Social Value

Outlook

Future research needs to integrate communication

studies, psychology, and data science to decipher the

evolutionary patterns of UGC in the Web3.0

environment. Especially in virtual reality (such as

metaverse product reviews) and generative AI (such

as AIGC's impact on UGC authenticity) scenarios,

reconstructing consumer decision theory models is of

urgent significance.

REFERENCES

Bazaarvoice, 2022. Consumer-generated content 2022:

The new shopping reality [Research

report]. https://www.bazaarvoice.com/research/

Cheng, X., Lai, K., Wang, D., Liu, J., 2010. UGC Video

Sharing: Measurement and Analysis. In: Chen, C.W.,

Casaló, L. V., Flavián, C., Ibáñez-Sánchez, S., 2020.

Influencers on instagram: Antecedents and

consequences of opinion leadership. Journal of

Business Research, 117, 510–519.

https://doi.org/10.1016/j.jbusres.2018.07.005

De Veirman, M., Cauberghe, V., Hudders, L., 2017.

Marketing through instagram influencers: The impact

of number of followers and product divergence on

brand attitude. International Journal of Advertising,

36(5), 798–828.

https://doi.org/10.1080/02650487.2017.1348035

Ferreira, C., Robertson, J., Reyneke, M., 2022. How many

likes are good enough? An evaluation of social media

performance. Journal of Internet Commerce, 21(3),

341–363.

https://doi.org/10.1080/15332861.2021.1966724

Houts, P., Doak, C., Doak, L., Loscalzo, M., 2006. The role

of pictures in improving health communication: A

review of research on attention, comprehension, recall,

and adherence. Patient Education and Counseling,

61(2), 173–190.

https://doi.org/10.1016/j.pec.2005.05.004

Jia, Y., Feng, H., Wang, X., Alvarado, M., 2023.

“Customer reviews or vlogger reviews?” the impact of

cross-platform UGC on the sales of experiential

products on E-commerce platforms. Journal of

Theoretical and Applied Electronic Commerce

Research, 18(3).

https://doi.org/10.3390/jtaer18030064

Ki, C., Kim, Y., 2019. The mechanism by which social

media influencers persuade consumers: The role of

consumers’ desire to mimic. Psychology & Marketing,

36(10), 905–922. https://doi.org/10.1002/mar.21244

Lee, J., Sudarshan, Sabitha, Sussman, Kristen L., Bright,

Laura F., Eastin, M., 2022. Why are consumers

following social media influencers on instagram?

Exploration of consumers’ motives for following

influencers and the role of materialism. International

Journal of Advertising, 41(1), 78–100.

https://doi.org/10.1080/02650487.2021.1964226

Lemon, K., Verhoef, P., 2016. Understanding customer

experience throughout the customer journey. Journal of

Marketing, 80(6), 69–96.

https://doi.org/10.1509/jm.15.0420

Li, Z., Lian, S. (eds) Intelligent Multimedia

Communication: Techniques and Applications. Studies

in Computational Intelligence, vol 280. Springer,

Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-

11686-5_12.

Liu, Y., Feng, J., 2021. Does money talk? The impact of

monetary incentives on user-generated content

contributions. Information Systems Research, 32(2),

394–409. https://doi.org/10.1287/isre.2020.0971

Lou, C., Yuan, S., 2019. Influencer marketing: How

message value and credibility affect consumer trust of

branded content on social media. Journal of Interactive

Advertising, 19(1), 58–73.

https://doi.org/10.1080/15252019.2018.1533501

Pop, R., Săplăcan, Z., Dabija, D., Alt, M., 2022. The impact

of social media influencers on travel decisions: The

role of trust in consumer decision journey. Current

Issues in Tourism, 25(5), 823–843.

https://doi.org/10.1080/13683500.2021.1895729

Qin, M., Qiu, S., Zhao, Y., Zhu, W., Li, S., 2024. Graphic

or short video? The influence mechanism of UGC types

on consumers’ purchase intention—Take Xiaohongshu

as an example. Electronic Commerce Research and

Applications, 65, 101402.

https://doi.org/10.1016/j.elerap.2024.101402

Silva, M., Farias, S., Silva, C., 2023. Endorsement on

instagram and cultural dimensions: An analysis of

digital influencers. The Bottom Line, 36(1), 1–28.

https://doi.org/10.1108/BL-12-2021-0127

Vrontis, D., Makrides, A., Christofi, M., Thrassou, A.,

2021. Social media influencer marketing: A systematic

review, integrative framework and future research

agenda. International Journal of Consumer Studies,

45(4), 617–644. https://doi.org/10.1111/ijcs.12647

Wang, Y., Eshghi, A., Ding, Y., Gopal, R., 2025. Echoes of

authenticity: Reclaiming human sentiment in the large

language model era. PNAS Nexus, 4(2), pgaf034.

https://doi.org/10.1093/pnasnexus/pgaf034

Zhang K., Benyoucef M., 2016. Consumer behavior in

social commerce: A literature review Decision Support

Systems, 86, 95–108.

https://doi.org/10.1016/j.dss.2016.04.001

ICEML 2025 - International Conference on E-commerce and Modern Logistics

224

Zhang, M., Luo, L., 2023. Can consumer-posted photos

serve as a leading indicator of restaurant survival?

Evidence from yelp. Management Science, 69(1), 25–

50. https://doi.org/10.1287/mnsc.2022.4359

Zhu, K., Khern-am-nuai, W., Yu, Y., 2024. Negative peer

feedback and user content generation: Evidence from a

restaurant review platform. Production and Operations

Management.

https://doi.org/10.1177/10591478231224941

The Impact of UGC on Consumer Decision Paths

225