Research progress in service automation: a critical review of consumer behavior in tourism and hospitality
Bibliographic record
Abstract
Purpose This study aims to address the conceptual ambiguity and fragmented understanding of service automation consumer behaviors in the tourism and hospitality industry. It synthesizes existing definitions, categorizes research domains and identifies emerging themes to provide a comprehensive framework for understanding consumer behavior in service automation. Design/methodology/approach A systematic literature review was conducted on 70 peer-reviewed articles related to service automation in tourism and hospitality. The study used thematic analysis to identify conceptual patterns, developed concept maps to illustrate interrelationships among constructs and performed citation analysis to uncover methodological trends and research gaps. Findings This review identifies three foundational characteristics of service automation: technology dependence, system autonomy and service delivery. Three major research themes were extracted, including consumer acceptance, humanoid and anthropomorphic design features and the impacts of service automation. The analysis also highlights prevalent application areas and methodological approaches and points to underexplored research opportunities. Originality/value This study offers the first structured synthesis of service automation consumer behavior literature. By developing a comprehensive conceptual framework and visualizing key research interconnections, it advances scholarly understanding of consumer behavior in the context of automated services and sets a clear agenda for future research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".