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Record W7116640908

Western Sport Apparel Brands in a Wanghong Economy: A Critical Discourse Analysis of Lululemon's Influencer Branding

2025· dissertation· en· W7116640908 on OpenAlexaboutno aff

Bibliographic record

VenueDigiNole (Florida State University) · 2025
Typedissertation
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsnot available
Fundersnot available
KeywordsClothingInfluencer marketingSocial mediaCritical discourse analysisNetnographyBrand communityPosition (finance)Discourse analysisDigital ecosystemContent analysis
DOInot available

Abstract

fetched live from OpenAlex

As Western sporting brands navigate China's complex digital consumer economy, they face unique challenges amid rising economic nationalism and state support/subsidization for domestic brands. In this context, understanding platform-specific influencer (wanghong) economic relations become crucial for analyzing market penetration, particularly as China's digital ecosystem operates distinctly from Western social media environments. While sport management researchers have examined consumer culture and brand communities in Western contexts (Coakley & Pike, 2021; Funk et al., 2022), and during the period of opening up (kai fang) there was considerable research on Western brands' penetrating into an increasing open Chinese market (Dong & Tian, 2009; Yu et al., 2017), little attention has been paid to how global sporting brands today must adapt to China's highly regulated digital spaces—where influencer-brand relationships are more explicitly commercialized and state-monitored than their Western counterparts. To address this gap, I employed critical discourse analysis (CDA) to examine how the Canadian sport apparel brand Lululemon navigates Chinese social media platforms. And I used wanghong influencers as 'brand embodiments' (Filo, Lock, & Karg, 2015; Skliar, & Cherrier, 2020), which localize identities of a global brand community (Mastromartino et al., 2020; Yoshida, Gordon, Heere, & James, 2015), to explore how the brand seeks to position itself as woven into the fabric of an increasingly insular everyday Chinese consumer culture. Focusing on its strategic positioning across the platform RedNote, I conducted a content analysis of over 500 videos, texts, and social media posts across the RedNote Platform. I also analyzed nearly 10,000 of related responses and user comments. My analysis of Lululemon's platform presence revealed four distinct strategies shaping brand community formation within Chinese digital spaces. First, the brand has developed a 'fitness with Chinese characteristics' marketing approach, adapting Western fitness concepts to align with Chinese cultural values. Second, Lululemon specifically targets 'super girls'—affluent, health-conscious, urban-dwelling women seeking premium athletic wear. Third, the brand promotes a new cosmopolitanism, defined by specialized knowledge of body aesthetics and exercise techniques that distinguish its community members as globally aware yet locally grounded. Fourth, Lululemon employs interactive and personalized salesmanship through the wanghong economy. The implementation of these strategies specifically in RedNote helps to foster distinctive approaches to body presentation, user interactivity, and aesthetic cultivation. This platform-specific variation in content creation highlights how the wanghong economy requires nuanced approaches that align with RedNote platform's endogenous characteristics. This research contributes to sport management literature by illuminating how Western sporting brands must navigate China's unique digital marketing landscape amid growing economic nationalism and state intervention in consumer markets. The findings have important implications for sport marketing practitioners and scholars: they demonstrate how success in the Chinese market requires understanding platform-specific community-building strategies, the distinctive nature of the wanghong economy, and the increasing challenge of competing with state-backed domestic brands. These insights are particularly valuable for sport organizations seeking to develop effective cross-cultural digital marketing strategies in an increasingly complex Chinese market environment characterized by technological sovereignty and consumer nationalism.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.306
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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