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Record W4401600115 · doi:10.4018/jgim.352039

How Streamers Enhance Consumer Engagement and Brand Equity in Live Commerce

2024· article· en· W4401600115 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Global Information Management · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsMcGill University
FundersNational Office for Philosophy and Social Sciences
KeywordsBrand equityEquity (law)BusinessMarketingAdvertisingPolitical science

Abstract

fetched live from OpenAlex

Live steamers play key roles in enhancing brand equity in live commerce. Understanding the mechanism of how streamers impact brand equity in live commerce is of great significance for firms to launch live streaming, influencer, and engagement marketing campaigns. Building on social support, consumer engagement and brand equity theories, this study investigates the impact of perceived streamer support on consumer engagement, which in turn affects brand equity in live commerce settings. Based upon analysis of the data from 264 questionnaires with SmartPLS3.0 software, the results demonstrate that 1) perceived emotional, informational and financial support positively impact brand engagement, streamer engagement and live studio engagement separately; 2) brand engagement and streamer engagement positively impact brand equity respectively; and 3) streamer engagement positively impacts brand engagement and live studio engagement respectively. The findings provide conducive guidance for firms to develop live streaming, influencer, and engagement marketing campaigns.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.885
Threshold uncertainty score0.751

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
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 head0.025
GPT teacher head0.350
Teacher spread0.325 · 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