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Record W4404414855 · doi:10.1080/10447318.2024.2426048

The Role of Service Robots in Restaurant Settings: A Meta-Analysis Study on Consumer Behavior and Intentions

2024· article· en· W4404414855 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

VenueInternational Journal of Human-Computer Interaction · 2024
Typearticle
Languageen
FieldComputer Science
TopicAI in Service Interactions
Canadian institutionsImpact
Fundersnot available
KeywordsService (business)RobotConsumer behaviourService robotAdvertisingMeta-analysisBusinessPsychologyMarketingComputer scienceArtificial intelligenceMedicine

Abstract

fetched live from OpenAlex

The employment of service robots in restaurants has become increasingly common. Previous studies have explored the factors related to the impact of service robots on consumers from multiple perspectives, but this topic still lacks an integrated empirical study to organize and analyze the conclusions of previous studies. This study obtained 46 empirical studies through the WoS and Scopus databases. Based on the conclusions and data of these studies and guided by the SOR theory, a holistic conceptual framework was constructed to describe how service robots affect restaurant consumers. This study tested the conceptual framework of the construct through meta-analysis and verified the moderating role of macro variables such as time and culture. This study not only has theoretical significance for future research but can also provide practical guidance for restaurant managers in the application and deployment of service robots.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.727

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.056
GPT teacher head0.376
Teacher spread0.320 · 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